COOPERATION IN THE PANDEMIC (working paper) 1

How is the COVID-19 pandemic affecting cooperation?

Jessica D. Ayers1,2✝, Diego Guevara Beltran1,2✝, Joe Alcock2,3, Cristina Baciu1,2,4, Scott Claessens2,5, Lee Cronk2,6, Nicole M. Hudson1, 2, Geoffrey Miller2,7, Keith Tidball2,8, Pamela Winfrey2,4, Emily Zarka2,9 Peter M. Todd2,10 ⁐& Athena Aktipis1,2,4 ⁐ 1Department of Psychology, Arizona State University 2Zombie Apocalypse Medicine Alliance 3Department of Emergency Medicine, University of New Mexico 4Biodesign Center for Biocomputing, Security and Society, Arizona State University 5School of Psychology, University of Auckland, New Zealand 6Department of Anthropology, Rutgers University - New Brunswick 7Psychology Department, University of New Mexico 8Department of Natural Resources, Cornell University 9Department of English, Arizona State University 10Cognitive Science Program and Department of Psychological and Brain Sciences, Indiana University Bloomington

This working paper has not yet been peer reviewed.

✝ These authors share first authorship on this work ⁐ These authors share senior authorship on this work COOPERATION IN THE PANDEMIC (working paper) 2

Abstract Do crises bring people together or pull them apart? Here we examine how people’s willingness to help others and their perceived interdependence with others changed during the COVID-19 pandemic, and assess what factors are associated with any change. We collected data at 4 time points from the same cohort of 497 paid participants, starting on March 6th, before the pandemic was declared, through April 2. We found that perceived interdependence with neighbors and with humanity increased over time on multiple measures. However, regarding cooperation, agreement with the statement that helping someone in need “is the right thing to do” decreased over time (towards both a neighbor and a citizen of another country). Although the changes per time period were small for some of these effects, cumulatively they were non- trivial (ranging from a .33 to a .75 change on a 7-point likert scale). There was no change over time in participants' reported willingness to help somebody in their neighborhood (cooperation) or their feelings that when “All of humanity succeeds” they feel good (interdependence). We found reliable associations of change in cooperation and interdependence with sex, age, and pre-existing medical condition. We are collecting data on an ongoing basis which will allow us to investigate how these variables continue to change or not as the pandemic unfolds. COOPERATION IN THE PANDEMIC (working paper) 3

How is the COVID-19 pandemic affecting cooperation and perceived interdependence?

INTRODUCTION During times of disaster and uncertainty, we see both the best and worst sides of human nature. People sometimes become fearful and aggressive, hurting others, stealing resources, and committing crimes (Drury et al., 2013). Other times they become more cooperative with their communities, providing help to the needy and protection to the vulnerable (Bauer et al., 2016; Páez et al., 2007), showing what Zaki (2020) calls “catastrophe compassion”. The current COVID-19 pandemic offers an opportunity to examine how cooperation and perceived interdependence change over time as a global crisis unfolds. In this study we asked participants about their willingness to cooperate and their perceptions of interdependence with those in their neighborhoods and with all of humanity. We collected data from 4 time points from the same cohort of 497 paid international participants, starting on March 6th, before the pandemic was declared, and ending on April 2.

Throughout this pandemic there have been countless examples of people helping others within communities. Volunteers distributed food to families in need, lab workers volunteered to work in COVID-19 testing facilities, and doctors volunteered to work in facilities for treating COVID-19 patients. In the US, many federal and state military personnel volunteered to assist with the COVID-19 response to run mortuaries, deliver food, and build hospitals in some of the hardest- hit areas. More than 16,00 healthy people have volunteered to become infected with COVID-19 for a potential human-challenge trial (Kuznia, 2020), which could speed up vaccine development (Eyal et al., 2020). Even more people have helped others in less dramatic, costly, and risky ways, such as hosting extended family in their homes during lockdowns, working extra shifts to keep the food supply chain running, or checking in on neighbors who may be vulnerable during the pandemic (Booth, 2020; Samuel, 2020). In fact, mutual aid networks that are spontaneously appearing in communities across the United States (Tolentino, 2020) -- Colorado librarians are making supply kits for the elerdly and children (COVID-19 Mutual Aid - It’s Going Down, 2020), a collective in Seattle, WA has set up a mutual aid network specifically geared at helping underrepresented and vulnerable populations (Covid19 Mutual Aid - Seattle, 2020), disabled people have created an aid network where they can ask their community for help when they are in need, and all New York boroughs have come together to provide child care, pet care, deliver medicine and groceries, and raise money for rent and food for those who are in need (Tolentino, 2020). Mutual aid networks such as these are appearing across the United States to help those who are in need (see https://itsgoingdown.org/c19-mutual-aid/ for a list of mutual aid networks across the US).

During crises and other times of need, people often help one another without expecting to be paid back for their help. This pattern of need-based transfers is common across small scale societies (Cronk et al., 2019). The primary goal of need-based transfers is to meet the need of the recipient (not to create debt or increase the status of the giver). Networks of need-based helping allow individuals and communities to better manage the risks of uncertain and unpredictable events such as natural disasters, droughts, and disease outbreaks. For example, when needs result from unexpected and uncontrollable events, ranchers in the American Southwest report that they do not expect to be paid back for helping other ranchers (Cronk et al., under revision), and, similarly, Danish and American participants are more supportive of welfare for people who are in need because of unexpected and uncontrollable events than for people who are in need due to their own decisions (Petersen et al., 2011). Mutual aid networks have also been shown to track positive group-level outcomes, such as increased social connectedness, shared group identity, solidarity with one’s group, and resilience (Drury, 2018; Drury et al., 2009). Computational models show that need-based transfers provide survival COOPERATION IN THE PANDEMIC (working paper) 4 advantages over alternative resource transfer rules including debt-based transactions (Aktipis et al., 2011, 2016). The reason that need-based systems can outperform debt-based systems is simple: agents that follow a debt-based rule end relationships with other agents that fail to repay gifts within a fixed period of time, making those other agents unavailable to help them later when they are in need. In contrast, agents that follow a need-based strategy do not end relationships and so have others they can call upon for help when they are in need. Free-riding can be a problem in need-based transfer systems, especially when wealth can be hidden (Claessens et al., in review), though this problem of free-riding exists across all cooperative systems and is not unique to need-based transfers (Aktipis, 2016).

Networks of helping can buffer individuals and communities from risk, but in some cases the very act of helping can be costly and involve exposure to risk. This is the case during pandemics, where helping in places where there is need can increase the risk of becoming infected. Nevertheless, many people do volunteer to help despite these risks. For example, during the Ebola crisis in Liberia, community responders helped with difficult and risky tasks including quarantining areas containing dead bodies, assisting with mortuary affairs, and helping to relocate afflicted families (Abramowitz et al., 2015). People can also engage in less risky forms of helping during disasters, such as using mobile phone applications to provide live updates on the spread of infectious diseases, as some did during the 2009 H1N1 pandemic (Freifeld et al., 2010), and responding to erroneous content in social media to dispel hoaxes or misinformation (Carter, 2014). In the current pandemic, people are more likely to follow social distancing guidelines when social distancing is framed as a prosocial behavior that helps others in the community compared to a self-serving behavior that protects one’s self from contracting the disease (Jordan et al., 2020). Additionally, people are most likely to engage in protective behaviors when they feel efficacy about their behaviors, especially when individual susceptibility of contracting the disease is low (Jørgensen et al., 2020). Humans are more likely to cooperate when we believe that others around us are cooperating (Fischbacher et al., 2001), suggesting that a way to increase global cooperation in the face of the pandemic is to make instances of cooperative behavior more publicly observable (Van Bavel et al., 2020).

The worst sides of human nature can also be seen during times of disaster, as cooperation and interdependence can break down, as observed in historical responses to widespread disease and famine. For example, during several European plagues, including the Black Death (caused by the bacterium Yersinia pestis), there was a breakdown of many informal and formal institutions and a surge of exploitation of a fearful populace for individual gain (Defoe, 1722). Diseases are often managed through cooperative efforts, but these efforts can sometimes increase pre-existing societal problems like poverty, religious prejudice, and racial inequalities (Carmichael, 1998; Farmer, 2001; Risse, 2015). Perceived vulnerability to disease can make people less welcoming of outgroups (e.g., immigrants) (Duncan et al., 2009), and disease prevalence can also increase people’s ties to their own religious groups (Fincher & Thornhill, 2012), potentially at a cost of increased antagonism towards religious outgroups. In the case of the COVID-19 pandemic, preexisting islamophobic sentiments have been excacerbated in India, with some Muslims fearing a surge in scape-goating (Perrigo, 2020). Similarly, Asian people, erroneously thought by some to be vectors of COVID-19, became targets of discrimination in the United States and abroad (Chung & Li, 2020; He et al., 2020; Kelley, 2020).

A recent study in the UK suggests that people may have a pessimistic view of human nature during epidemics in general, and during the COVID-19 pandemic in particular (Nettle, 2020) because people are more likely to behave selfishly when they expect others to behave selfishly (Frank et al., 1993; 2020). Hoarding and price gouging of sanitizer and personal protective equipment have also been ongoing problems (The White House, 2020; U.S. Attorney’s Office COOPERATION IN THE PANDEMIC (working paper) 5

District of Alaska, 2020). Hoarding and panic buying can undermine the benefits of cooperation and shared identity by creating fear that others are only looking out for themselves and, therefore, makes people feel like they need to do the same (Van Bavel et al., 2020). Even more severe are costly and potentially dangerous scams preying on the uncertainty and fear many people are feeling during the pandemic, including false tests and cures (Heilweil, 2020), scams offering Medicare benefits and relief payments (Miranda, 2020), and phishing text messages telling people they have come in contact with somebody infected with COVID-19 (Barone, 2020). Disasters can create new opportunities for scammers to take advantage of uncertainty, but overall crime rates do not necessarily increase during disasters and in their aftermath (Varano et al., 2010; Zahnow, 2015; Zahran et al., 2009; Zaki, 2020). On the other hand, overall crime rates have decreased around the world since the beginning of the COVID-19 pandemic, partly due to reduced movement and public activity (Stefanie Dazio et al., 2020), but perhaps partly due to an increased sense of cooperation and interdependence.

Given the range of behaviors brought out during times of adversity like these, from positive to negative, it is important that we do not simply assume that selflessness or selfishness will be the general outcome, but rather seek to measure if and how individuals’ willingness to cooperate and feelings of interdependence change over time as a crisis like the COVID-19 pandemic plays out.

We set out to assess general trends in people’s reports of cooperation and perceived interdependence over the initial stages of the COVID-19 pandemic. We also investigated factors that could drive differences in cooperation, including perceived interdependence, geographic region, sex, age, socioeconomic status, having children, having a pre-existing health condition, and perceived risk of contracting COVID-19. Fitness interdependence -- the reliance that people have on one another for their survival, reproduction and general wellbeing -- is an important foundation for cooperation (Aktipis et al., 2018; Roberts, 2005). Recent tools to formalize and measure fitness interdependence include the situational interdependence scale (Gerpott et al., 2018) which measures more external aspects of interdependence, and the perceived fitness interdependence scale (Sznycer et al., 2020)1, which measures something more internal: the extent to which individuals feel their outcomes are tied to the outcomes for a specific category of other individual (e.g., using items such as “ [target] and I rise and fall together”). We focus on perceived fitness interdependence with neighbors and with all of humanity, both because crises can increase people’s awareness of their reliance on one another and also because the very nature of the disease threat is rooted in interdependence: if one’s neighborhood is more affected by the pandemic, this translates to greater individual risk. And likewise, if humanity is more affected by the pandemic, this also can lead to greater individual risk.

During crises, people often come together both literally and figuratively to help one another, sharing resources, advice, and protection. But during a pandemic, the best way to help is for people to stay physically apart, while still trying to help from a distance, so that they do not contribute to transmission of the disease. This makes predicting changes in cooperation more challenging because some acts of helping might also be seen as uncooperative if they could contribute to disease transmission. Thus as a group, we did not have specific predictions about how our measures of cooperation would change, though we predicted that perceived fitness interdependence would increase over the course of the pandemic.

1 This paper is currently in revision and will be updated on PsyArXiv as additional analyses are conducted. COOPERATION IN THE PANDEMIC (working paper) 6

METHODS

Figure 1. Geographic regions represented in the study. Circle size represents the number of respondents as a continuous variable. Participants had to be fluent in English to participate in the study.

A total of 522 English-speaking participants from around the world were recruited through Prolific (prolific.co), an online participant recruitment system. A total of 25 participants were removed (7 who were missing participant IDs and were therefore unidentifiable across time points, 7 who indicated they were not fluent in English, 10 who did not report current country of residence, and one participant who reported “other” for sex2), yielding a total of 497 participants who were included in the analyses (Mage = 28.31, SDage = 9.87, 53.1% female) - living in 35 countries (Figure 1 and Table 1). Most participants lived in Europe (47%), UK/Ireland (28%), or US/Canada (14%)3. Almost all participants (99.2%) recruited completed the survey at time point 1 (March 6th, 2020), and most returned to complete follow-up surveys at time points 2 through 4. Most participants had no children (76.9%), followed by those who had one (9.7%), two (10.3%), and three or more children (4.2%). Of the 115 participants who had at least one child, most (69%) had children under the age of 12. In terms of education, 22.2% had a high school degree, 19.4% completed some college, 7.1% had a 2-year degree, 30.2% had a Bachelor’s degree, 14.9 had a Master’s degree and 4% had a Doctoral or professional degree. On the MacArthur scale of subjective social status (Adler et al., 1994), participants on average rated themselves slightly above the midpoint (M = 5.58, SD = 1.49 on the 1-10 scale) (Adler et al., 1994). Most participants were White/Caucasian (79.4%). Most participants lived either with their parents (31.1%) or with their spouse and their children (24.5%). Most reported no pre-existing health condition (88.1%). A majority of participants identified as White or Caucasian (79.3%), followed by Hispanic or Latino/a (9.1%), Asian/Pacific Islander (6.6%), “Other” (2.6%), and Black or African American (1.8%).

2 Because we used sex as a categorical covariate in our analyses, a third group of sex would have had an n = 1. We were thus not able to include this participant in the analyses. We acknowledge this limitation and are exploring alternative ways of analyzing this data that allow us to include this participant. 3 We included UK/Ireland in the same geographic region because of spatial proximity and we grouped European countries together for the same reason. COOPERATION IN THE PANDEMIC (working paper) 7

Region Country Number of participants %

Europe 235 47.2 Portugal 76 15.3 Poland 49 9.9 Spain 26 5.2 Greece 18 3.6 France 8 1.6 Hungary 8 1.6 Italy 6 1.2 Belgium 5 1 Czech Republic 5 1 Germany 5 1 Netherlands 5 1 Norway 5 1 Estonia 4 0.8 Slovenia 3 0.6 Finland 2 0.4 Latvia 2 0.4 Luxembourg 2 0.4 Sweden 2 0.4 Switzerland 2 0.4 Austria 1 0.2 Denmark 1 0.2 UK/Ireland 140 28.2 United Kingdom 137 27.6 Ireland 3 0.6 US/Canada 71 14.3 United States 45 9.1 Canada 26 5.2 Other 51 10.2 Mexico 27 5.4 Australia 13 2.6 Chile 4 0.8 New Zealand 3 0.6 Israel 2 0.4 South Africa 1 0.2 Turkey 1 0.2 Table 1. Number of participants from each country represented in the sample

Data was collected over 4 time periods, starting on March 6, 2020, before COVID-19 was officially declared a pandemic on March 11, and continuing for several weeks as countries around the world were going into lockdowns (figure 2). Participants first viewed the consent form informing them of the purpose, risks, benefits, compensation, and were informed that they had the right to refuse to answer questions. At the end of the page, participants read that by continuing on in the survey there were acknowledging that they were at least 18 years old, consented to be in the study, and consented to be contracted through Prolific for the follow-up studies. Participants then answered standard demographic questions (e.g., Prolific ID, age, sex, number of children, education level, subjective socioeconomic status, ethnicity, zip code, COOPERATION IN THE PANDEMIC (working paper) 8 country of residence), followed by the items in our surveys. After completing the survey, participants were debriefed and thanked for their time.

Figure 2. Timeline of COVID-19 pandemic (Taylor, 2020; World Health Organization, 2020a, 2020b, 2020c, 2020d, 2020e, 2020f, 2020g, 2020h, 2020i; World Health Organization Regional Office for Europe, 2020) and data collection time points (green).

After the first data collection period, data were subsequently collected approximately every 10 days for a 72 hour time period (table 2) and the same participants were invited to participate each time. This study is part of a broader project designed to investigate whether there were changes in perceived interdependence, cooperation/willingness to help, risk perception, risk management and attitudes about the future over the progression of the COVID-19 pandemic. Not all dependent variables that we measured fit within the scope of this paper and so not all are included here. For a complete list of all questionnaire items for each time period, see https:// osf.io/gtsbr/. Because some items were added and removed from time period to time period, the total time it took for participants to take the study was not the same across all time periods. COOPERATION IN THE PANDEMIC (working paper) 9

Time 1 Time 2 Time 3 Time 4 Dates March March March April 6 - 7 14 - 17 24 - 27 3 - 6 Number of participants 497 404 394 377 Drop out rate from time 1 N/A 18.71% 20.72% 24.14% Compensation (USD) $1.75 $1.75 $1.25 $1.25 Approximate survey length 10 - 15 10 - 15 3 - 7 3 - 7 (minutes) Table 2. Survey characteristics for each time period.

As a measure of local cooperation, we used the following item regarding willingness to help a neighbor: Someone from your neighborhood is having their residence fixed, so it isn't livable. How willing would you be to let them move into your residence for a week? (1 = not at all willing, 7 = very willing). To measure global cooperation, we used the following item regarding willingness to help humanity: A person who is not a citizen of your own country is having their residence fixed, so it isn't livable. How willing would you be to let them move into your residence for a week? (1 = not at all willing, 7 = very willing). To measure attitudes and motivations toward local cooperation, we asked participants to rate their agreement with the statement: Helping someone from my neighborhood when they are in need is the right thing to do (1 = strongly disagree, 7 = strongly agree). To measure attitudes and motivations toward global cooperation, we asked participants to rate their agreement with the statement: Helping a person who is not a citizen of your own country when they are in need is the right thing to do (1 = strongly disagree, 7 = strongly agree). Our local measures of interdependence included feeling mutual success with one’s neighborhood: When my neighborhood succeeds, I feel good (1 = do not agree at all, 7 = strongly agree); and shared fate with one’s neighborhood: My neighborhood and I rise and fall together (1 = do not agree at all, 7 = strongly agree). Our global measures of interdependence included mutual success with humanity: When all of humanity succeeds, I feel good (1 = do not agree at all, 7 = strongly agree); and shared fate with humanity: All of humanity and I rise and fall together (1 = do not agree at all, 7 = strongly agree). Lastly, to measure perceived risk of contracting COVID-19, we asked participants to report on the following item: How likely do you think it is that you will contract/become infected with COVID- 19? (1 = not at all, 7 = extremely).

We used multilevel growth modeling (see detailed methods in Appendix 1) to identify variables that significantly changed over time. This approach allows us to identify marginal changes over time (i.e., whether average responses changed over time), as well as individual rates of change over time (i.e., variability around the average rate of change over time). We also explored whether geographic region, sex, age, subjective socioeconomic status, having children, having a pre-existing health condition, and perceived risk of contracting COVID-19 affected the initial starting point or the rate of change across time for these variables. The gap between each successive time point of data collection is treated as one unit of time. Participants were nested by their IDs and geographic regions (Table 1). COOPERATION IN THE PANDEMIC (working paper) 10

RESULTS

We first test whether ther are changes in cooperation, as measured by participants reponses to questions about thier willingness to help a neighbor or a person from a different country, as well as thier agreement with the statement that helping a neighbor or someone from a different country is the right thing to do; we also assess whether these rates of cooperation varied by geographic region or demographic factors including age and sex. We then explore whether measures of perceived interdependence towards a neighbor or all of humanity show changes over time, whether these vary by geographic region, and whether they are influenced by demographics. We also explore whether perceived interdependence influenced rates of cooperation at time 1 or over time. Lastly, we report changes over time on perceived risk of contracting COVID-19, whether demographic variables influenced this perceived risk, and whether perceived risk affected cooperation or perceived interdependence. Analyses reported reflect predicted responses at time 1, and predicted linear changes over time based on multilevel growth modeling. However, in the figures, we present the raw mean scores and standard errors. Thus, these figures reflect the actual changes over time but do not visually represent the multilevel growth modeling (which is reported in detail in Appendix 1). We focus here on the significant results, summarized in Table 3; the full results including all non- significant findings are in Appendix 1. In these analyses we did not adjust for multiple comparisons because multi-level models as used here create more reliable estimates due to partial pooling of error variances (i.e., variances are pooled by between and within individual level error variances) (Gelman et al., 2012; Rothman, 1990). We also did not use Bonferroni corrections, which would be overly conservative, and because our analyses are mostly exploratory4 (Rothman, 1990).

Some measures of cooperation increased, some decreased, and others did not change

Willingness to help someone representing all of humanity was measured by asking about allowing “a displaced person who is not a citizen of your own country” to move in for a week. This measure increased over time (b = 0.11, t(359) = 4.26 [0.06, 0.16]), while willingness to help a neighbor in this same way did not change over time (b = 0.03, t(852) = 1.25 [-0.02, 0.08]) (Figure 1a). Endorsement of the need-based helping towards “someone from my neighborhood” (b = -0.14, t(359) = 1.83 [-0.19, -0.08]) and “someone who is not a citizen of your own country” decreased over time (b = -0.12, t(377) = -4.34 [-0.18, -0.07]) (Figure 1b). We did not see significant differences among regions in the rate of change in responses to these items, but people from Europe (b = 0.80, t(819) = 3.38 [0.34, 1.27]), and US/Canada (b = 0.81, t(536) = 2.49 [0.17, 1.44]) reported greater endorsement of need-based helping towards “someone from my neighborhood” at time 1 compared to people from the UK/Ireland region and “Other” region. Women (b = 0.39, t(368) = 2.21 [0.04, 0.74]) and older people (b = 0.019, t(334) = 2.09, p = 0.04 [0.001, 0.04]) reported greater endorsement with the statement that helping “someone from your neighborhood” is the right thing to do at time 1. No other measure of cooperation differed by age, sex, or any other individual measure collected in our sample.

4 There is no current scientific consensus about the question of whether (and if so, how) multilevel models need to be corrected for multiple testing. We are continuing to investigate the most appropriate methods for analyzing our data given this lack of scientific consensus. COOPERATION IN THE PANDEMIC (working paper) 11

Figure 1. (a) Willingness to allow a neighbor to live in one’s house did not change over time, but willingness to let somebody who is not a citizen of one’s country live in one's house increased over time during the course of the pandemic. (b) Endorsement of the statement that helping someone in need “is the right thing to do” decreased over time towards both neighbors and citizens of other countries.

Some measures of perceived interdependence increased while some did not change

Perceived interdependence with neighbors increased over time as measured by both mutual success, “When my neighborhood succeeds, I feel good” (b = 0.12, t(295) = 4.58 [0.07, 0.17]) (figure 2a), and shared fate, “My neighborhood and I rise and fall together,” (b = 0.25, t(356) = 8.52 [0.19, 0.31]) (figure 2b). Perceived interdependence with all of humanity increased only for the “rise and fall together” item (b = 0.12, t(918) = 4.34 [0.01, 0.18]) (figure 2b). Perceived interdependence with humanity as measured by the item “When all of humanity succeeds, I feel good” did not change over time (figure 2a), though it should be noted that it was already rather high at the start of our data collection (intercept = 5.67 [5.52, 5.82]). Ratings were higher for perceived interdependence with humanity than with neighbors for both the mutual success item (“When all of humanity/my neighborhood succeeds, I feel good”) and for the “rise and fall together” in all time points. COOPERATION IN THE PANDEMIC (working paper) 12

Figure 2. (a) Perceived interdependence as measured by feelings of mutual success increased toward “my neighborhood,” but not toward “all of humanity.” (b) Perceived interdependence as measured by shared fate increased for both all of humanity and neighborhood.

Changes in perceived interdependence varied across some geographic regions

We used multilevel growth modeling to determine whether there were differences across regions in perceived interdependence at time 1 and in the rate of change over time. Feelings of mutual success with neighbors did not vary by region at time 1 (Table 7), and increases over time in mutual success with neighbors were observed for participants from UK/Ireland, US/Canada and Europe, but not “Other” regions (Table 7, Figure 3a). In contrast, mutual success with all of humanity did not increase over time in any geographic region, although all regions reported similarly high levels of mutual success with humanity at time 1 (Table 9, Figure 3c). Participants from the United States/Canada reported higher levels of shared fate with their neighbors at time 1 compared to all other regions. Whereas increases over time in shared fate with neighbors were smaller in Europe relative to UK/Ireland and US/Canada; participants in “Other” regions showed no statistically significant increases over time (Table 8, Figure 3b). Perceived interdependence as measured by the item “All of humanity and I rise and fall together” was higher in US/Canada at time 1 compared to all other regions, and US/Canada participants' rating of this item did not increase over time. All other regions increased over time in their rating of this interdependence item (Table 10, Figure 3d). COOPERATION IN THE PANDEMIC (working paper) 13

Figure 3. (a) Interdependence with one’s neighborhood as measured by the mutual success item increased in the US/Canada, UK/Ireland and Europe regions. (b) Perceived interdependence with neighborhood increased across all regions as measured by the “rise and fall together” item. (c) Perceived interdependence with humanity as measured by mutual success did not change over time for any regions. (d) Perceived interdependence with humanity as measured by the “rise and fall together” item increased over time for all regions except the US/Canada region, though the US/Canada region started higher at time 1.

Perceived Interdependence was associated with greater cooperation at time 1, but did not affect rate of change

Although neither of our measures of interdependence influenced the rate of change over time for our measures of cooperation, we found that people who reported greater interdependence with neighbors and all of humanity at time 1 simultaneously reported higher levels of cooperation. Specifically, greater willingness to help a neighbor by allowing them to move in for a week was associated higher ratings of mutual success as measured by the item “When my neighborhood succeeds, I feel good” (b = 0.18, t(951) = 3.51 [0.08, 0.28]), and shared fate as measured by “My neighborhood and I rise and fall together” (b = 0.18, t(896) = 3.63 [0.08, 0.28]) at time 1. Similarly, greater willingness to help a person from a different country by allowing them to move in for a week was associated with both higher scores on “When all of humanity succeeds, I feel good” (b = 0.12, t(556) = 2.08 [0.01, 0.23]), and “All of humanity and I rise and fall together” (b = 0.12, t(541) = 2.86 [0.04, 0.21]) at time 1. Only mutual success with neighbors, but not shared fate with neighbors, was associated at time 1 with greater endorsement of the statement that helping a neighbor who is in need is the right thing to do (b = 0.25, t(947) = 9.20 [0.19, 0.30]). Similarly, mutual success with humanity, but not shared fated COOPERATION IN THE PANDEMIC (working paper) 14 with humanity, was associated at time 1 with greater endorsement of the statement that helping a “person who is not a citizen of your own country” when they are in need is the right thing to do (b = 0.24, t(1029) = 7.60 [0.18, 0.31]).

Age, sex, and health have some influences on perceived interdependence

Older participants rated the items “When my neighborhood succeeds, I feel good” (figure 4a) (t(367) = 2.61 [0.01, 0.04]) and “My neighborhood and I rise and fall together” (t(344) = 2.43 [0.004, 0.04]) higher than younger participants, with a ten-year increase in age corresponding to an increase of 0.20 at time 1 for both of these items. In contrast, younger participants rated the items “When all of humanity succeeds, I feel good” higher at time 1 than older participants did, such that, on average, a 10-year increase in age corresponded to a -0.25 lower initial rating for this item (b = -0.025, t(987) = -3.16 [-0.04, -0.009]). However, older peoples’ ratings of this mutual success with humanity item increased at a slightly higher rate over time relative to younger peoples’ ratings (b = 0.006, t(674) = 2.77 [0.002, 0.01]), which were more stable (figure 4b). Some of these effects are not entirely apparent in Figure 4 due to the fact that we included the entire range of ages in the multilevel models upon which the analyses are based, while the figures show the data only broken down by two age categories.

Figure 4. (a) Older people (blue lines) initially rated the item “When my neighborhood succeeds, I feel good” slightly higher than younger people (red lines). (b)Younger people initially rated the item “When all of humanity succeeds, I feel good” higher than older people. These figures are broken down by age categories and so some of the effects which we detected in multilevel models are not as apparent in this data presentation.

Men and women did not differ in their ratings of the item “My neighborhood and I rise and fall together” at time 1 (t(365) = -1.12, [-0.58, 0.16]); but women’s ratings increased more quickly relative to men’s (b = 0.13, t(352) = 2.23 [0.01, 0.25]); a one unit increase in time corresponded to a 0.19 increase for men (t(344) = 4.35 [0.10, 0.27]), and a 0.32 increase for women (t(346) = 7.76, [0.24, 0.40]) (Figure 5). COOPERATION IN THE PANDEMIC (working paper) 15

Figure 5. There was no difference between males and females initial ratings of how much they “rise and fall together” with their neighborhoods, but women’s ratings increased over time more quickly than men’s.

Participants reported whether they had any pre-existing medical condition that would require extra precautions to avoid being sick3. We find that people with a pre-existing medical condition reported lower mutual success with all of humanity at time 1 than people with no medical condition (b = 0.55, t(1066) = 2.35 [0.09, 1.02]) (Figure 6a). However, this effect does not hold when accounting for other demographic variables (b = 0.12, t(460) = 0.75 [-0.19, 0.43]). Compared to people with no medical condition, those with a pre-existing medical condition reported lower shared fate with humanity at time 1 (b = 0.78, t(1120) = 2.55 [0.18, 1.38]), but increased at a faster rate over time (b = -0.35, t(781) = -4.07 [-0.52, 0.18]) (Figure 6b).

______

3Having a pre-existing medical condition was recorded on a binary choice scale (1 = yes, 2 = no). COOPERATION IN THE PANDEMIC (working paper) 16

Figure 6. (a) People with a pre-existing medical condition reported lower mutual success with humanity at time 1, though this effect disappears when controlling for age. (b) People with a pre-existing medical condition reported lower shared fate with humanity at time 1, but increased at a faster rate over time than people with no pre-existing medical condition.

Perceived risk of contracting COVID-19 increased over time and varied by age

On average, people’s perception of the risk of contracting COVID-19 at the beginning of the study was 3.19 ([2.7, 3.48]), increasing at an average rate of 0.23 points per time period (t(380) = 7.55 [0.21, 0.34]) for a total increase of .69. Relative to younger people, older participants reported a lower perceived risk of becoming infected at time 1 (b = -0.02, t(351) = -2.53 [-0.04, - 0.01]), but their perceived risk of infection increased more quickly (b = 0.02, t(316) = 4.1 [0.01, 0.02]); on average, a 10-year increase in age corresponded with a -0.20 lower initial perceived risk of contracting COVID-19, and a 0.20 increase in perceived risk per unit of time (figure 7). Perceived risk of becoming infected with COVID-19 did not influence any of the dependent measures at time 1 or their rate of change over time. Perceived risk of becoming infected also did not influence responses for people with a pre-existing medical condition relative to people with no pre-existing medical condition for any of our dependent measures. COOPERATION IN THE PANDEMIC (working paper) 17

Figure 7. Perceived risk of contracting COVID-19 increased over the course of the pandemic.

Some rates of change in cooperation and interdependence were stable across individuals; some show substantial variability

The results above present patterns in mean values of responses, which may obscure meaningful differences between individuals. Here we briefly discuss the observed variability in rate of change over time across individuals (summarized in Table 3 and reported in detail in Appendix 1). The ratings of willingness to help a neighbor and of perceived mutual success with humanity, which did not change over time on average, also did not change for most individuals (i.e. variability in both rates of change was low). Two measures of perceived interdependence-- mutual success with neighbors, and shared fate with humanity-- showed mean increases over time, and these increases were also consistent between individuals. Willingness to help non- citizens and shared fate with neighbors also increased on average, but these ratings actually decreased over time for an appreciable proportion of participants, as indicated by the substantial variability in these rates of change over time. Endorsement of helping a neighbor or citizen of another country when they are in need decreased on average, but again substantial variability in these rates of change indicated that some participants increased in their endorsement over time. COOPERATION IN THE PANDEMIC (working paper) 18

Individual Geographic Region Demographics Variability

Mean Change Change Change Cumulative Time 1 Time 1 Time 1 over time over time over time Change

Cooperation

Someone from your neighborhood is having their housed fixed, so it isn't Europe and No change No No No Yes No livable. How willing would US/Canada (+) you be to let them move into your house for a week?

A person who is not a citizen of your own country is having their house fixed, so it isn't 0.33 No No No No Yes Yes livable. How willing would you be to let them move into your house for a week?

Helping someone from your neighborhood when they are Women and -0.42 No No No Yes Yes in need is the right thing to Age (+) do

Helping a person who is not a citizen of your own country -0.36 No No No No Yes Yes when they are in need is the right thing to do

Interdependence

When my neighborhood 0.36 No "Other" (-) Age (+) No Yes No succeeds, I feel good

When all of humanity No change No No Age (-) No Yes No succeeds, I feel good

My neighborhood and I rise Europe and 0.75 US/Canada (+) No Women (+) Yes Yes and fall together "Other" (-)

All of humanity and I rise and US/Canada Medical Medical 0.36 US/Canada (-) Yes No fall together and "Other" (+) condition (-) condition (+)

How likely do you think it is that you will contract/become 0.69 US/Canada (-) Europe (-) Age (-) Age (+) Yes Yes infected with COVID19?

Note. “+” indicate positive influence/difference, “-” indicates negative influence/difference.

Table 3. Summary findings for measures of cooperation, interdependence, and risk of infection, indicating amount of mean change over time (on 7-point scale), and whether and how they showed significant differences in initial level at Time 1 or in rate of change over time for different geographic regions, for different demographic groups, or among different individuals. COOPERATION IN THE PANDEMIC (working paper) 19

DISCUSSION Our longitudinal survey during the early development of the COVID-19 pandemic revealed changes in some measures of cooperative intent and feelings of interdependence, and stability in several others. Here we discuss the results and their implications, and some of the directions that need to be explored further.

Cooperation increased by some measures and decreased by others We used two items to assess willingness to help and two items about endorsement of helping others when they need it. Willingness to help a citizen of another country by allowing them to move into your house increased over time, but willingness to help someone from one’s neighborhood in this same way did not change over time. This is somewhat surprising because it is often assumed that individuals become more wary of those who are perceived as outgroup members during stressful times (Rios et al., 2013) and when disease risk is high (Wu & Chang, 2012). Agreement that helping others in need is the right thing to do decreased over time towards both a neighbor and a citizen of another country. These mixed results -- with cooperation increasing by some measures and decreasing by others -- may be because various dimensions of cooperation change differently during pandemics, or because some measures of cooperation might be inappropriate during pandemics (see section on measuring cooperation during pandemics).

Perceived interdependence increased over time and was higher for humanity than neighborhood Most measures of perceived interdependence increased over the course of the pandemic as predicted. Perceived interdependence with neighbors increased across all geographic regions over the course of the pandemic. This was the case for mutual success with neighbors (i.e., “when my neighborhood succeeds I feel good”) and for shared fate with neighbors and all of humanity (i.e., “my neighborhood[all of humanity] and I rise and fall together”) but not for mutual success towards humanity (i.e., “when all of humanity succeeds I feel good”), which was already high to begin with in all regions which may explain why it did not increase over time. Perceived interdependence with all of humanity as measured by the “rise and fall together” item did not change for participants from the United States/Canada region, but they reported higher interdependence on this measure to begin with. Shared fate with one’s neighborhood increased at a slower rate in Europe compared to participants in UK/Ireland, and US/Canada, whereas participants in other regions did not increase in their shared fate with neighbors over time.

Perceived interdependence with all of humanity was consistently higher than perceived interdependence with neighborhood. This is counterintuitive because other work has suggested that people care about others less as they become more distant (Bradner & Mark, 2002; Charness & Gneezy, 2008; Hoffman et al., 1996; Majolo et al., 2006) and the number of individuals in those groups become larger (Isaac & Walker, 1988; Kerr, 1989; Nosenzo et al., 2015). This effect appeared most strongly for younger people. To our knowledge, this is the first study to find that people perceived greater interdependence with humanity than with their neighborhoods and the first study to find an effect of age.

Changes in cooperation were not driven by perceived COVID-19 risk or interdependence While we observe increases over time in perceived risk of contracting COVID-19 and in perceived interdependence, changes in cooperation were not affected by either of these factors. The fact that we see an increase in perceived risk of infection but no corresponding increase or decrease in cooperation could suggest that people’s cooperative tendencies may be stable even in the face of increased threat of disease. Alternatively, people who feel more COOPERATION IN THE PANDEMIC (working paper) 20 interdependent with their neighbors and all of humanity may be more willing to incur the increased risk of infection (initially higher levels of cooperation did associate with higher initial perceived interdependence, older age, and being a woman). To the extent that changes in cooperation occurred during the current pandemic, the pathways through which these changes are happening are more complex than either perceived risk of infection, perceived interdependence, or basic demographics such as age and sex. In future work alternative causal pathways that extend beyond risk of infection (e.g., disruptions to social support, feelings of isolation) should be explored.

Most demographic variables did not affect cooperation or interdependence We tested for effects of age, sex, socioeconomic status, having children and having a pre- existing health condition for all dependent variables. We also tested whether perceived risk of infection interacts with having a pre-existing health condition to influence cooperative intent or ratings of interdependence. Only age, sex and pre-existing health condition had significant effects on some interdependent meaures. Age and sex affected one of our measures of cooperation at time 1, but no demographic variable influenced change over time in rates of cooperation.

Some measures of cooperation might not be appropriate for a pandemic During a pandemic, acts of cooperation might take on different meanings because of the altered context of constant potential risk of contagion during social contact. This means that some measures that have to do with closeness or ask about people’s willingness to interact with another person might not be capturing cooperation, but rather people’s willingness to take the risk of interacting with one another. It is possible that some of our cooperation and interdependence items took on different meanings because of the situation created by the pandemic.

For example, a drop in participants’ willingness to let someone move into their home for a week as the pandemic progressed should not necessarily be interpreted as a decrease in cooperation, because it could arise from greater contagion fears. In our data we did not actually see such a drop. This could have been because the desire to cooperate balanced or outweighed the fear of contagion. Another possibility is that people might have been more lonely as a result of social distancing orders, making them more open to having somebody live in their house for a week. It thus remains difficult to disentangle how much changes in this measure reflect cooperation versus other factors. Moreover, we cannot yet explain why people’s willingness to let a citizen of another country stay in their home increased over time, while their willingness to let somebody from their neighborhood stay in their home remained the same.

Our other cooperation item, asking about people’s agreement that helping someone in need is the right thing to do, decreased over time. This may be because people became more focused on their own and their families immediate needs as the pandemic progressed and social distancing measures were put in place. But it might also be that people inferred that helping those in need entailed in-person interaction or other activities that might increase their risk of infection. Further work is needed to distinguish between these possibilities and more generally to understand how people interpret questions about cooperation and helping during pandemics where contagion risk may influence the meaning of these questions.

Given that the threat of communicable disease can make cooperation itself risky, the changes we found in some of the measures of cooperative attitudes and perceived interdependence in the face of this pandemic may seem surprisingly small, especially when thinking about societal collapse associated with other pandemics. This could be an instance of environmental COOPERATION IN THE PANDEMIC (working paper) 21 mismatch, in which our behavioral immune systems (Miller & Maner, 2012; Schaller & Park, 2011; van Leeuwen & Petersen, 2018) that evolved to keep us away from sources of infection are not being triggered in a situation where the visual (and visceral) cues of someone being ill in one’s immediate vicinity are mostly absent for many people--simply being told (repeatedly) that infection is around and we must stay away from it may not have the same degree of motivational impact (and could even lead to a desire to venture out to see if the verbal reports are accurate). If so, this mismatch may have the positive outcome of not seriously decreasing our cooperative behavior during this pandemic. (It could also be the case that the societal impact of previous pandemics has been overestimated--see Mordechai et al. (2019)--which might suggest that our cooperative tendencies are stable even under more extreme conditions.) It is also important not to generalize these results to possible effects on cooperation in other types of disasters or crises--for instance, in shocks where the harm does not spread from person to person through contact, such as damage from earthquakes or famine from crop failures, cooperative interaction between individuals is both beneficial and safe, and the psychology involved may operate differently.

Future research: Cooperation can sometimes lead to negative outcomes for the sick In our study we did not explore the question of how people might behave differently towards those who are sick (or suspected to be sick) and those who are not. Historically, cooperation during pandemics has sometimes taken the form of attempts to protect the healthy at the expense of the sick. This is clear from both historical records as well as folklore and literature. For example, a story from Ancient Greece recalls how Apollonius encouraged an entire city to stone an old beggar to death because they believed him to be the personification of the plague (Philostratus, 1912), which mirrors the real practice of stoning individuals believed to be contaminated (Steiner, 1995). Scandinavian folkloric traditions around the Black Death describe using fire, smoke, and live burial, all of which had real world counterparts (Tangherlini, 1988; Tillhagen, 1967). The collective cooperation required to create institutions such as pesthouses -- quarantine and isolation facilities where promised care more often resulted in poor living conditions including overcrowding, deficient resources, and pest infestation -- shows that cooperation during pandemics is not simply a positive influence, but rather that it can often have negative consequences for the sick (Carmichael, 1998; Dobson, 2015; Risse, 2015). In future work we plan to look at cooperation towards both healthy and sick (or suspected to be sick) individuals.

Future research: People’s survey responses may not be consistent with their behavior The current analyses did not include behavioral measures, but focused on participants' self- reported attitudes and beliefs. This limits our ability to draw conclusions about changes in people’s behavior over the course of the pandemic. In our ongoing work we are incorporating measures that allow us to capture real-world behavior and forms of cooperation that are appropriate to the current pandemic.

In addition to measuring cooperation through survey and behavioral measures, there may be important opportunities to study the spontaneous outpourings of cooperation and examples of interdependence that have arisen through the internet. For example, some platforms like Nextdoor and Facebook have helped to connect people in need to those who can help them (Piñon, 2020). There has also been a flood of artistic projects involving cooperation, collaboration, and gifting on social media and fundraising platforms. The fundraising site, Kickstarter, whose mission is bringing creative projects to life, stated “We’re seeing our community elevating creators' projects, reaching out with kind words in the comments section, being understanding about potential production delays, and coming together (digitally) to see COOPERATION IN THE PANDEMIC (working paper) 22 these projects through” (Kickstarter, 2020). Artists have also been generously sharing their work during the pandemic, for example in Italy many musicians performed on their balconies, porches or through their open windows. One of these musicians spoke about the power of music and the arts to bring people together: “The beauty of art makes us united, and part of something that is bigger than us...It feels like we are a team, going forward together” (UN News, 2020). These kinds of artistic outpourings are not limited to professional artists. The public have also taken part in spontaneous music performances and dance parties on balconies (Italians sing, dance on balconies during coronavirus lockdown: VIDEO, 2020) as a way of coming together through music while they were physically distancing. These expressions of collective exuberance may play an important role in intentions to cooperate and perceptions of interdependence. Our survey did not assess aspects of cooperation and influences on interdependence such as these, and they should be explored in further work.

CONCLUSION In terms of cooperation and interdependence, the first weeks of the COVID-19 pandemic appears to have neither consistently brought people together nor driven them apart. We did find an increase in perceived interdependence for most measures, but people’s responses to our measures of cooperation did not change in a consistent manner over the course of the pandemic. Moreover, cooperation and interdependence did not rise and fall together -- some measures of perceived interdependence increased, while some measures of cooperation decreased -- suggesting they are not tightly causally linked. The relatively small changes in some of the measures over time may indicate that other more appropriate approaches may be needed to capture attitudes and motivations during pandemics. But it could also point to resilience in people’s tendency to cooperate even as the world changes in major ways.

Acknowledgements We are grateful to the members of The Human Generosity Project for their feedback and suggestions on this project and to Daniel McNeish for sharing his expertise regarding multiple testing and multilevel models.

Funding statement This study was funded by the Interdisciplinary Cooperation Initiative, a Strategic Initiative of the President's Office at Arizona State University and by the Indiana University College of Arts & Sciences.

Authors contributions Aktipis co-conceived the study, co-funded the study, and wrote the first draft of the main text of the paper. Ayers created the surveys, conducted data collection, conducted the preliminary analyses for the studies, and wrote parts of the method section, several of the appendices and supplementary materials. Baciu assisted with project management, helped draft Appendix 2, and contributed to the editing of the manuscript. Claessens created the figures for the paper and consulted on the data analysis. Cronk helped design the survey and helped write the paper. Guevara Beltran conducted the longitudinal analyses and wrote up the detailed results in Appendix 1. Hudson created the timeline figure, worked on formatting demographic tables, and assisted with formatting references and citations. Miller helped with survey design as well as writing and editing the paper. Tidball contributed to the survey items and also helped with the writing and editing of the paper. Todd co-conceived and co-funded the study and helped with survey design and writing. Winfrey and Zarka contributed to the writing and editing of the paper. COOPERATION IN THE PANDEMIC (working paper) 23

APPENDIX 1 DETAILED MULTILEVEL MODEL ANALYSIS AND RESULTS

Here we present detailed analyses and results for the questions covered in the main text. We test whether there were changes across time in the perceived risk of contracting COVID-19, in interdependence towards people’s neighborhood and towards all of humanity, in willingness to let a neighbor or someone from a different country spend the week in one’s home, and whether people agreed that helping someone from their neighborhood or someone from a different country was the right thing to do. We also test whether each of these responses at time 1 (i.e., on March 6-7) or the marginal rate of change across time (i.e., from March 6-7 to April 3- 6) were different by geographic region (United Kingdom/Ireland, US/Canada, Europe excluding UK/Ireland, and “Other”; Table 1). To test whether responses at time 1 or over time varied by region, geographic region and its interaction with time were entered as fixed predictors where the United Kingdom/Ireland was the reference group. The largest represented country was the UK (26% of total sample), so the UK/Ireland region was chosen as the reference group. Lastly, we explore whether demographic variables such as age (grand mean centered), sex, subjective socio-economic status (grand mean centered), having children (0 = no, 1 = at least one child), having a preexisting medical condition (1 = yes, 2 = no), and perceived risk of contracting COVID-19 influence responses at time 1 or the marginal rate of change across time. To explore these possibilities, we transformed the data such that there were up to 4 observations per participant (one per time point), yielding 1988 observations (N = 497). Seven participants were removed from analyses because they indicated they were not fluent in English, 7 were missig participant ID and were unidentifiale across time points, 10 were removed due to missing data on current country of residence (which was used to determine geographic region), and 1 participant who indicated “other” for sex were removed. Participants were nested by ID and geographic region. Variables were modeled by estimating random intercepts and slopes for participant ID (i.e., each participant received their own unique intercept and slope), allowing the random intercepts and slopes to correlate. Correlations between time- points were constrained to be equal, but variances at each time point were uniquely estimated by region (i.e., the variability around the mean at each time point for each region) employing maximum-likelihood estimation. Random slopes for participant ID were excluded from models in cases where there was no significant variation in how people changed over time. Variances, and tests of model fit for variance and covariance components are reported in supplemental materials. Analyses were conducted in SAS software, version 9.4, using the MIXED procedure.

Willingness to help and endorsement of need-based helping

Willingness to help a neighbor by allowing them to move in for a week did not change, but varied by geographic region at time 1; demographics did not influence responses

The marginal willingness to help a neighbor was 3.12 [2.92, 3.32] at time 1, with significant variation around the random intercept = 2.27 (Z = 13.07, p < .001). There were no changes over time in willingness to help a neighbor (b = 0.03, t(852) = 1.25, p = 0.21 [-0.02, 0.08]), and no significant variation around the random slope (훥휒2(2) = 6.8, p > .05). At time 1, willingness to help a neighbor was 2.60 [2.23, 2.98] in UK/Ireland, and willingness to help a neighbor did not change over time in UK/Ireland (b = 0.06, t(191) = 1.21, p = 0.23 [-0.04, 0.16]). Willingness to help a neighbor at time 1 was higher in Europe (b = 0.80, t(819) = 3.38, p = 0.001 [0.34, 1.27]), and US/Canada (b = 0.81, t(536) = 2.49, p = 0.01 [0.17, 1.44]) than in UK/Ireland, but not in Other regions (b = 0.20, t(354) = 0.56, p = 0.59 [-0.52, 0.93]). The rate of change over time in willingness to help a neighbor was not different from UK/Ireland in Europe (b = -0.05, COOPERATION IN THE PANDEMIC (working paper) 24 t(388) = -0.80, p =0.43 [-0.17, 0.07]), US/Canada (b = -0.11, t(203) = -1.21, p = 0.23 [-0.28, 0.07]), or Other regions (b = 0.08, t(162) = 0.82, p = 0.41 [-0.11, 0.27]).

Table 4. Region specific intercepts and slopes for willingness to help a neighbor. Obs. = 1326 B SE df t p 95 CI

UK/Ireland Intercept 2.602 0.19 505 13.6 < .001 2.227 2.98

UK/Ireland Time 0.061 0.05 191 1.21 0.229 -0.04 0.16

US/Canada Intercept 3.409 0.26 306 13.0 < .001 2.895 3.92

US/Canada Time -0.045 0.07 103 -0.63 0.532 -0.19 0.1

Europe Intercept 3.408 0.14 815 23.9 < .001 3.128 3.69

Europe Time 0.012 0.04 475 0.33 0.738 -0.06 0.08

Other Intercept 2.803 0.32 215 8.86 < .001 2.179 3.43

Other Time 0.140 0.08 90.2 1.71 0.091 -0.02 0.3

In a model where we include time, having a pre-existing medical condition and their interaction, we find that having a pre-existing medical condition did not influence willingness to help a neighbor at time 1(b = 0.50, t(1041) = 1.64, p = 0.10 [-0.10, 1.10]), or rate of change over time (b = 0.02, t(742) = 0.32, p = 0.74 [-0.13, 0.18]). In a model where we include level of perceived risk of contracting COVID-19, time, and their interaction we find that perceived risk of contracting COVID-19 did not influence willingness to help a neighbor at time 1 (b = -0.10, t(699) = -1.55, p = 0.12 [-0.23, 0.03]), or the rate of change over time (b = 0.01, t(721) = 0.62, p = 0.53 [-0.03, 0.06]). We probe for a three-way interaction between time, risk of contracting COVID-19, and having a pre-existing medical condition. We find no evidence for an interaction between pre-existing medical condition and perceived risk of contracting COVID-19 (b = -0.49, t(412) = -1.81, p = 0.07 [-1.03, 0.04]), suggesting perceived risk of contracting COVID-19 did not influence willingness to help a neighbor at time 1 differently for people with or without a medical condition. We also find no evidence for a three-way interaction between time, medical condition, and perceived risk (b = 0.15, t(412) = 1.83, p = 0.07 [-0.01, 0.30]), suggesting willingness to help a neighbor did not change differently over time for people with a medical condition compared to people without a medical condition depending on the level of perceived risk of contracting COVID-19. Neither age, sex, subjective SES, or having children influenced responses at time 1 or change over time.

Endorsement of need-based helping towards a neighbor decreased over time, did not vary by region; women and older people reported greater endorsement at time 1 COOPERATION IN THE PANDEMIC (working paper) 25

The marginal need-based endorsement towards a neighbor (NBT-neighbor) was 5.86 [5.68, 6.04], with significant variation around the random intercept = 1.84 (Z = 6.79, p < .001). A one unit increase in time corresponded with a -0.14 decrease in NBT-neighbor (t(359) = 1.83, p < 0.001 [-0.19, -0.08]), with significant variation around the random slope = 0.11 (Z = 4.25, p < .001). Assuming normality, the variance in the random slope indicates that a one standard deviation from the marginal slope is equal to 0.33, meaning that 68% of individual slopes fell between -0.47 and 0.19, and 95% between -0.80 and 0.52. The random slope and intercept were negatively correlated (r = -0.63, p < .001). In UK/Ireland, the average NBT-neighbor was 5.89 [5.55, 6.24] at time 1. NBT-neighbor was not different in Europe (b = -0.16, t(342) = -0.75, p = 0.45 [-0.59, 0.26]), US/Canada (b = 0.36, t(262) = 1.31, p = 0.19 [-0.18, 0.90]), or in Other regions (b = -0.19, t(209) = -0.59, p = 0.55 [-0.84, 0.45]) than in UK/Ireland at time 1. Changes over time in NBT-neighbor were not statistically significantly different from UK/Ireland in Europe (b = -0.05, t(335) = -0.77, p = 0.44 [-0.18, 0.08]), US/Canada (b = -0.08, t(209) = -0.88, p = 0.38 [-0.25, 0.09]), or in Other regions (b = -0.09, t(191) = -0.93, p = 0.35 [-0.29, 0.10]).

Table 5. Region specific intercepts and slopes for need-based helping towards a neighbor. Obs. = 1328 B SE df t p 95 CI

UK/Ireland Intercept 5.898 0.18 277 33.7 < .001 5.553 6.243

UK/Ireland Time -0.084 0.05 247 -1.54 0.125 -0.193 0.024

US/Canada Intercept 6.259 0.21 169 29.3 < .001 5.838 6.680

US/Canada Time -0.162 0.07 118 -2.35 0.02 -0.299 -0.026

Europe Intercept 5.734 0.13 323 44.3 < .001 5.480 5.989

Europe Time -0.137 0.04 286 -3.51 < .001 -0.213 -0.060

Other Intercept 5.704 0.28 138 20.7 < .001 5.160 6.248

Other Time -0.180 0.09 117 -2.09 0.039 -0.350 -0.010

We explore whether demographics or perceived risk of contracting COVID-19 influence responses at time 1 or change over time by running separate models with each variable as a covariate and its interaction with time. We find that women report higher NBT-neighbor at time 1 than men (b = 0.39, t(368) = 2.21, p = 0.03 [0.04, 0.74]), but the rate of change over time was not different for men and women (b = 0.01, t(356) = 0.14, p = 0.89 [-0.10, 0.11]). Similarly, we find that a 10-year increase in age corresponded with a 0.19 increase in NBT-neighbor at time 1 (t(334) = 2.09, p = 0.04 [0.001, 0.04]), but age had no influence on the rate of change over time (b = -0.001, t(306) = -0.34, p = 0.73 [-0.006, 0.004]). Having a pre-existing medical condition did not influence NBT-neighbor at time 1 (b = -0.11, t(360) = -0.41, p = 0.68 [-0.64, 0.42]), or the rate of change over time (b = 0.02, t(322) = 0.24, p = 0.81 [-0.14, 0.18]). Perceived risk of contracting COVID-19 also did not influence NBT-neighbor at time 1 (b = -0.01, t(376) = -0.23, p COOPERATION IN THE PANDEMIC (working paper) 26

= 0.82 [-0.13, 0.11]), or change over time (b = 0.02, t(446) = 0.99, p = 0.32 [-0.02, 0.06]). Probing for a three-way interaction between time, perceived risk of contracting COVID-19, and pre-existing medical condition, we find no evidence for a two-way interaction between perceived level of risk and medical condition (b = -0.05, t(234) = -0.24, p = 0.81 [-0.50, 0.39]), suggesting perceived level of risk did not influence NBT-neighbor differently at time 1 for people with a pre- existing medical condition compared to people with no medical condition. We also find no evidence for a three-way interaction (b = 0.08, t(239) = 1.22, p = 0.22 [-0.05, 0.21]), suggesting perceived risk of contracting COVID-19 did not influence change over time in NBT-neighbor differently for people with a pre-existing medical condition compared to people with no pre- existing condition. Subjective SES, and having children did not influence responses at time 1 or rate of change over time.

Willingness to help a “displaced person who is not a citizen of your own country” by allowing them to move in for a week increased over time, did not vary by region, and was not influenced by demographics

The marginal willingness to help “a person who is not a citizen of your own country” was 2.38 [2.19, 2.56] at time 1, with significant variation around the random intercept = 2.28 (Z = 8.34, p < .001). A one unit increase in time was associated with a 0.11 increase in willingness to help (t(359) = 4.26, p < 0.001 [0.06, 0.16]), with significant variation around the random slope = 0.09 (Z = 3.90, p < .001). The random slope variance indicates that a one standard deviation from the marginal slope is equal to 0.3, meaning that we can expect 68% of individual slopes to fall between -0.19 and 0.41, and 95% between -0.49 and 0.71. The random slope and intercept were negatively correlated (r = -0.39, p < .001). Change over time in willingness to help was not different in Europe (b = 0.02, t(275) = 0.29, p = 0.77 [-0.10, 0.14]), US/Canada (b = -0.10, t(185) = -1.14, p = 0.26 [-0.27, 0.07]), or in Other regions (b = 0.02, t(162) = 0.15, p = 0.88 [- 0.19, 0.23]) from change over time in UK/Ireland. Willingness to help at time 1 was not different from UK/Ireland in Europe (b = 0.34, t(349) = 1.59, p = 0.11 [-0.08, 0.77]), or in Other regions (b = 0.35, t(218) = 0.97, p = 0.33 [-0.36, 1.07]), but willingness to help was higher in US/Canada than UK/Ireland at time 1 (b = 0.86, t(304) = 2.85, p = 0.005 [0.27, 1.45]). However, including geographic region as a categorical fixed predictor and its interaction with time did not improve model fit (훥휒2(6) = 11.5, p > .05), implying there were no meaningful differences by region.

Table 6. Willingness to help a person who is not a citizen of your own country by region. Obs. = 1326 B SE df t p 95 CI

UK/Ireland Intercept 2.059 0.17 273 12.09 < .001 1.724 2.394

UK/Ireland Slope 0.114 0.048 183 2.36 0.020 0.018 0.209

US/Canada Intercept 2.915 0.247 240 11.8 < .001 2.429 3.402

US/Canada Slope 0.013 0.074 126 0.18 0.855 -0.132 0.159

Europe Intercept 2.404 0.134 394 17.97 < .001 2.141 2.667

Europe Slope 0.131 0.037 324 3.55 < .01 0.058 0.204 COOPERATION IN THE PANDEMIC (working paper) 27

Other Intercept 2.413 0.323 165 7.47 < .001 1.775 3.052

Other Slope 0.130 0.097 120 1.34 0.184 -0.063 0.323

Having a pre-existing medical condition did not influence willingness to help at time 1 (b = 0.46 t(402) = 1.64, p = 0.10 [-0.09, 1.02]), or the rate of change over time (b = 0.02, t(327) = 0.26, p = 0.79 [-0.14, 0.18]). Perceived risk of contracting COVID-19 also did not influence willingness to help at time 1 (b = -0.11, t(404) = -1.70, p = 0.09 [-0.23, 0.02]), or change over time (b = 0.04, t(506) = 1.77, p = 0.08 [-0.004, 0.08]). We again explore whether risk of contracting COVID-19 influenced responses depending on pre-existing medical condition. We find no evidence for a two way interaction between perceived risk of contracting COVID-19 and pre-existing condition (b = -0.42, t(267) = -1.78, p = 0.07 [-0.88, 0.04]), or a three-way interaction between time, perceived risk, and pre-existing medical condition (b = 0.13, t(290) = 1.88, p = 0.06 [-0.01, 0.27]), suggesting perceived risk of contracting COVID-19 did not influence willingness to help humanity differently for people with a medical condition at time 1 or change over time relative to people with no medical condition. We did not observe any differences by age, sex, subjective SES, or having children on responses at time 1 or change over time.

Endorsement of need-based helping towards a “displaced person who is not a citizen of your own country” decreased over time, did not vary by region, and was not influenced by demographics

The marginal need-based helping towards a “displaced person who is not a citizen of your own country” (NBT-humanity) was 5.61 [5.44, 5.78] at time 1, with significant variation around the random intercept = 1.55 (Z = 6.34, p < .001). A one unit increase in time corresponded with a -0.12 decrease in NBT-humanity (t(377) = -4.34, p < 0.001 [-0.18, -0.07]), with significant variation around the random slope = 0.14 (Z = 5.14, p < .001). The variance around the random slope indicates that a one SD from the marginal slope is equal to 0.37, meaning that 68% of individual slopes are predicted to fall between -0.49 and 0.25, 95% fall between -0.86 and 0.62. The random intercept and slope were negatively correlated (r = -0.47, p < .001). Neither Europe (b = -0.36, t(329) = -1.70, p = 0.09 [-0.77, 0.05]), US/Canada (b = 0.16, t(258) = 0.54, p = 0.59 [-0.42, 0.74]), or Other regions (b = -0.14, t(200) = -0.46, p = 0.65 [- 0.75, 0.47]) reported a different NBT-humanity than UK/Ireland at time 1. Similarly, change over time in NBT-humanity was not different in Europe (b = -0.02, t(322) = -0.28, p = 0.78 [-0.16, 0.12]), US/Canada (b = -0.01, t(259) = -0.14, p = 0.89 [-0.22, 0.19]), or in Other regions (b = - 0.11, t(197) = -1.08, p = 0.28 [-0.32, 0.09]) than change over time in UK/Ireland.

Table 7. Need-based helping for a person who is not a citizen of your own country by region. Obs. = 1326 B SE df t p 95 CI

UK/Ireland Intercept 5.778 0.17 263 33.4 < .001 5.438 6.119

UK/Ireland Slope -0.098 0.06 250 -1.65 0.101 -0.216 0.019 COOPERATION IN THE PANDEMIC (working paper) 28

US/Canada Intercept 5.939 0.24 166 24.5 < .001 5.461 6.418

US/Canada Slope -0.113 0.09 163 -1.31 0.193 -0.284 0.058

Europe Intercept 5.420 0.12 303 45.1 < .001 5.183 5.656

Europe Slope -0.119 0.04 299 -3.02 0.003 -0.196 -0.041

Other Intercept 5.637 0.26 130 22 < .001 5.131 6.143

Other Slope -0.212 0.09 124 -2.45 0.016 -0.383 -0.040

In a model where we include pre-existing medical condition and its interaction with time, we find that people with a pre-existing medical condition did not report a different NBT-humanity at time 1 than people with no medical condition (b = 0.08, t(382) = 0.29, p = 0.77 [-0.45, 0.60]), and the rate of change over time in NBT-humanity was also not different for people with a medical condition compared to people with no medical condition (b = 0.02, t(373) = 0.28, p = 0.78 [-0.15, 0.20]). Perceived risk of contracting COVID-19 also did not influence NBT-humanity at time 1 (b = 0.04, t(354) = 0.60, p = 0.54 [-0.08, 0.16]), or change over time (b = -0.01, t(471) = -0.36, p = 0.72 [-0.05, 0.03]). We probe for a three-way interaction between time, perceived risk of contracting COVID-19, and pre-existing medical condition. We find no evidence for a two-way interaction between perceived risk and medical condition (b = 0.08, t(331) = 0.32, p = 0.75 [- 0.41, 0.57]), or a three-way interaction between time, perceived risk of contracting COVID-19, and pre-existing medical condition (b = 0.07, t(385) = 0.95, p = 0.34 [-0.07, 0.22]), suggesting perceived risk of contracting COVID-19 did not influence NBT-humanity differently for people with a medical condition at time 1 or change over time relative to people with no medical condition. No demographic factor (i.e., age, sex, subjective SES, having children) was found to influence responses at time 1 or change over time.

Interdependence with neighborhood and all of humanity Interdependence “When my neighborhood succeeds, I feel good” increased over time, changes over time varied by region, and older people reported higher responses at time 1

At time 1, the marginal interdependence (mutual success) towards one’s neighborhood was 4.21, with significant variation around the random intercept = 1.65 (Z = 12.43, p < .001). A one unit increase in time was associated with a 0.12 increase (t(295) = 4.58, p < .001 [0.07, 0.17]), with no significant variation around the random slope (훥휒2(2) = 3.4, p > .05), suggesting interdependence (mutual success) towards one’s neighborhood increased at a similar rate for people across time. At time 1, interdependence (mutual success) towards a neighborhood in UK/Ireland was 4.21 [3.84, 4.58], and a one unit increase in time was associated with an increase of 0.17 (t(228) = 3.08, p = .002 [0.06, 0.28]). Interdependence (mutual success) towards one’s neighborhood was not different from UK/Ireland at time 1 in Europe (b = -0.17, t(351) = -0.76, p = 0.45 [-0.62, 0.27]), US/Canada (b = 0.34, t(303) = 1.11, p = 0.27 [-0.26, 0.94], or in Other regions (b = 0.24, t(209) = 0.70, p = 0.48 [-0.44, 0.93]). Increases over time were also not different from UK/Ireland in Europe (b = -0.06, t(298) = -0.92, p = 0.36 [-0.19, 0.07]), or US/Canada (b = 0.04, t(184) = 0.49, p = 0.62 [-0.13, 0.22]), but changes in interdependence COOPERATION IN THE PANDEMIC (working paper) 29

(mutual success) towards one’s neighborhood over time were smaller in Other regions than in UK/Ireland (b = -0.22, t(161) = -2.14, p = 0.03 [-0.42, -0.02]), such that Other regions did not increase over time (Table 8).

Table 8. Intercepts and slopes by region for interdependence (mutual success) neighborhood. Obs. = 1327 B SE df t p 95 CI

UK/Ireland Intercept 4.217 0.185 443 22.80 < .001 3.853 4.581

UK/Ireland Time 0.174 0.055 231 3.16 0.002 0.065 0.282

US/Canada Intercept 4.562 0.236 234 19.33 < .001 4.097 5.027

US/Canada Time 0.214 0.069 93 3.12 0.002 0.078 0.351

Europe Intercept 4.038 0.126 788 32.04 <.001 3.791 4.285

Europe Time 0.114 0.032 459 3.54 < .001 0.051 0.177

Other Intercept 4.468 0.284 156 15.75 < .001 3.908 5.028

Other Time -0.047 0.080 90 -0.58 0.563 -0.206 0.113

We explore whether demographics or perceived risk of contracting COVID-19 influence responses at time 1 or change over time by running separate models for each covariate and their interaction with time. Having a pre-existing medical condition did not influence interdependence (mutual success) towards one’s neighborhood at time 1 (b = -0.26, t(371) = - 0.92, p = 0.36 [-0.82, 0.29]), or change over time (b = 0.07, t(298) = 0.87, p = 0.39 [-0.09, 0.23]). Perceived risk of contracting COVID-19 also did not influence responses at time 1 (b = -0.05, t(333) = -0.80, p = 0.42 [-0.17, 0.07]), or change over time (b = 0.02, t(422) = 0.94, p = 0.35 [- 0.02, 0.06]). When we test for independent effects, people who reported having at least one child reported higher interdependence (mutual success) towards one’s neighborhood at time 1 than people with no children (b = 0.50, t(1042) = 2.33, p = 0.02 [0.08, 0.92]), although this effect does not hold when controlling for age. Having children did not influence the rate of change over time (b = -0.07, t(808) = -1.18, p = 0.24 [-0.19, 0.05]). Men and women did not differ at time 1 (b = -0.04, t(1125) = -0.24, p = 0.81 [-0.40, 0.31]), but interdependence (mutual success) towards one’s neighborhood increased at a slightly higher rate over time for women compared to men (b = 0.01, t(853) = 2.02, p = 0.04 [0.002, 0.19]). Again, this effect does not hold when controlling for age. A one-year increase in age was associated with a 0.02 increase in interdependence (mutual success) towards one’s neighborhood at time 1 (t(367) = 2.61, p = 0.01 [0.01, 0.04]), but age did not influence rate of change over time (b = -0.001, t(301) = -0.42, p = 0.67 [-0.01, 0.004]). In a model where we enter time, children, sex, age, and the interaction between time and sex as predictors, we find that having children no longer influences interdependence (mutual success) towards one’s neighborhood at time 1 (b = 0.07, t(470) = 0.40, p = 0.69 [-0.28, 0.42]), and the rate of change over time between men and women is only marginally significantly different (b = 0.09, t(291) = 1.90, p = 0.06 [-0.003, 0.20]. Only age remained a COOPERATION IN THE PANDEMIC (working paper) 30 significant predictor (b = 0.02, t(469) = 2.45, p = 0.01 [0.004, 0.03]). If we transform the effect of age such that a one unit increase in age corresponds to a 10-year increase in age, we can see that a 10-year increase in age (for someone who was 28 years old) was associated with a 0.70 increase in empathy towards one’s neighborhood at time 1. Lastly, we explore whether perceived risk of contracting COVID-19 affects people with a pre-existing medical condition differently than those with no medical condition. To test this possibility we ran a model with perceived risk of contracting COVID-19, having a pre-existing medical condition, time and their interaction as predictors. We find no evidence for an interaction between perceived risk and pre- existing condition (b = -0.35, t(247) = -1.47, p = 0.14 [-0.81, 0.11], suggesting that perceived risk of contracting COVID-19 does not influence interdependence (mutual success) towards one’s neighborhood at time 1 differently for people with or with no medical condition. We also find no evidence for a three-way interaction between time, perceived risk, and pre-existing condition (b = 0.11, t(278) = 1.54, p = 0.12 [-0.03, 0.25]), suggesting that people’s interdependence (mutual success) towards one’s neighborhood did not change differently over time for people with or with no medical condition depending on their level of perceived risk of contracting COVID-19. Subjective SES also had no influence on responses.

Interdependence “My neighborhood and I rise and fall together” increased over time, varied by region; older people report higher responses at time 1, and women increased more than men

The marginal interdependence (shared fate) with one’s neighborhood was 2.61 [2.42, 2.79] at time 1, with significant variation around the random intercept = 1.60 (Z = 5.35, p < .001). A one unit increase in time was associated with a 0.25 increase in shared fate with one’s neighborhood (t(356) = 8.52, p < .001 [0.19, 0.31]), with significant variation around the random slope = 0.10 (Z = 3.22, p < .001). Random slope variance translates into a one standard deviation equal to 0.31 from the marginal slope, indicating that 68% of individual slopes fell between -0.06 and 0.56, and 95% between -0.37 and 0.87. The random slope and intercept were not correlated (r = -0.10, p = .21). At time 1, shared fate with one’s neighborhood was 2.46 [2.11, 2.82]] in the UK/Ireland, and a one unit increase in time was associated with a 0.37 increase in shared fate (t(205) = 6.29, p < .001 [0.26, 0.49]). Shared fate with one’s neighborhood was not different from UK/Ireland at time 1 in Europe (b = -0.15, t(296) = -2.0, p = 0.89 [-0.47, 0.41]), or in Other regions (b = .33, t(201) = 0.99, p = .32 [-.33, 0.99]), but shared fate was higher in US/Canada than in UK/Ireland at time 1 (b = 0.92, t(245) = 2.84, p = 0.005 [0.28, 1.56]). Change over time was not different in US/Canada than UK/Ireland (b = -0.13, t(207) = -1.17, p = 0.24 [-0.35, 0.09]), but changes over time in shared fate with one’s neighborhood were smaller in Europe (b = -0.14, t(276) = -2.0, p = 0.047 [-0.29, -0.002]) and Other regions (b = -0.24, t(185) = -2.25, p = 0.02 [-0.45, -0.03]) than in UK/Ireland, such that increases in shared fate were smaller in Europe but did not increase in Other regions (Table 9).

Table 9. Region specific interdependence (shared fate) with one’s neighborhood. Obs. = 1325 B SE df t p 95 CI

UK/Ireland Intercept 2.464 0.18 231 13.6 < .001 2.107 2.82

UK/Ireland Time 0.373 0.06 205 6.29 < .001 0.256 0.49

US/Canada Intercept 3.387 0.27 163 12.6 < .001 2.855 3.92

US/Canada Time 0.244 0.09 133 2.62 0.01 0.06 0.43 COOPERATION IN THE PANDEMIC (working paper) 31

Europe Intercept 2.431 0.13 290 18.6 < .001 2.174 2.69

Europe Time 0.230 0.04 255 5.71 < .001 0.151 0.31

Other Intercept 2.796 0.28 133 9.89 < .001 2.237 3.36

Other Time 0.132 0.09 114 1.48 0.142 -0.04 0.31

We again explore whether demographics or perceived risk of contracting COVID-19 influence responses at time 1 or change over time by running separate models for each covariate and their interaction with time. Having a pre-existing medical condition does not influence shared fate with one’s neighborhood at time 1 (b = -0.29, t(372) = -1.02, p = 0.31 [- 0.87, 0.27]), or change over time (b = 0.04, t(354) = 0.48, p = 0.63 [-0.14, 0.22]). Perceived risk of contracting COVID-19 also did not influence shared fate at time 1 (b = 0.02, t(389) = 0.39, p = 0.69 [-0.10, 0.15]), or change over time (b = 0.001, t(518) = 0.05, p = 0.96 [-0.04, 0.04]). We also find no sex differences in shared fate with one’s neighborhood at time 1 (t(365) = -1.12, p = 0.26 [-0.58, 0.16]), however, shared fate increased at a higher rate over time for women than for men (b = 0.13, t(352) = 2.23, p = 0.02 [0.01, 0.25]). At time 1, men reported a shared fate of 2.72 [2.44, 2.99], and a one unit increase in time was associated with a 0.19 increase in shared fate for men (t(344) = 4.35, p < 0.001 [0.10, 0.27]). In contrast, women reported a shared fate of 2.51 [2.25, 2.76] at time 1, and a one unit increase in time was associated with a 0.32 increase in shared fate with one’s neighborhood (t(346) = 7.76, p < .001 [0.24, 0.40]). Age did not influence rate of change over time (t(319) = 1.45, p = 0.15 [-0.001, 0.01]), but a one-year increase in age was associated with a 0.02 increase in shared fate with one’s neighborhood at time 1 (t(344) = 2.43, p = 0.01 [0.004, 0.04]). Alternatively, a 10-year increase in age (for someone who was 28 years old) corresponded with a 0.20 increase in shared fate with one’s neighborhood at time 1. We again probe for a three-way interaction between time, perceived risk of contracting COVID-19, and having a pre-existing medical condition. We find no evidence for an interaction between risk of contracting COVID-19 and having a pre-existing medical condition (b = -0.02, t(413) = -0.06, p = 0.95 [-0.64, 0.60]), suggesting that level of perceived risk did not influence shared fate with one’s neighborhood at time 1 for people with or without a medical condition. We also find no evidence for a three-way interaction between time, perceived risk of contracting COVID-19, and pre-existing medical condition (b = 0.04, t(333) = 0.50, p = 0.62 [-0.11, 0.19]), suggesting perceived level of risk did not influence the rate of change over time in shared fate towards one’s neighborhood differently for people with or without a pre- existing medical condition. Again, neither subjective SES nor having children had an influence on responses at time or over time.

Interdependence “When all of humanity succeeds, I feel good” did not change, and did not vary by region; younger people reported higher responses at time 1

The marginal interdependence (mutual success) towards humanity was 5.67 [5.52, 5.82] at time 1, with significant variation around the random intercept = 0.99 (Z = 11.76, p < .001). There were no changes over time in mutual success towards humanity (b = -0.02, t(837) = - 1.01, p = 0.31 [-0.06, 0.02]), and there was no significant variation around the random slope (훥휒2(2) = 4.8, p > .05). Neither Europe (b = 0.37, t(699) = 1.92, p = 0.05 [-0.01, 0.74]), US/Canada (b = 0.13, t(434) = 0.51, p = 0.61 [-0.38, 0.65]), or Other regions (b = 0.43, t(268) = 1.46, p = 0.15 [-0.15, 1.02]) were different than UK/Ireland at time 1. Similarly, rate of change over time was not different in Europe (b = -0.09, t(379) = -1.56, p = 0.12 [-0.19, 0.02]), COOPERATION IN THE PANDEMIC (working paper) 32

US/Canada (b = 0.03, t(232) = 0.42, p = 0.67 [-0.12, 0.19]), or Other regions (b = -0.14, t(167) = -1.66, p = 0.09 [-0.32, 0.03]) from rate of change over time in UK/Ireland.

Table 10. Interdependence (mutual success) towards humanity by region. Obs. = 1327 B SE df t p 95 CI

UK/Ireland Intercept 5.412 0.16 422 33.77 < .001 5.097 5.727

UK/Ireland Time 0.040 0.049 230 0.83 0.408 -0.055 0.136

US/Canada Intercept 5.547 0.209 213 26.52 < .001 5.135 5.959

US/Canada Time 0.074 0.064 109 1.16 0.25 -0.053 0.202

Europe Intercept 5.778 0.104 764 55.52 < .001 5.574 5.983

Europe Time -0.047 0.027 450 -1.71 0.088 -0.101 0.007

Other Intercept 5.845 0.25 146 23.34 < .001 5.349 6.339

Other Time -0.105 0.072 85.6 -1.45 0.151 -0.248 0.039

To explore whether demographics influenced responses at time 1 or rate of change over time, we ran separate models with each variable as a covariate and its interaction with time. Sex had no influence on interdependence (mutual success) towards humanity at time 1 (b = -0.05, t(1166) = -0.31, p = 0.76 [-0.35, 0.25]). However, sex influenced change over time (b = 0.09, t(830) = 2.12, p = 0.03 [0.01, 0.17]), such that men reported a slight decrease in interdependence (mutual success) towards humanity (b = -0.06, t(742) = -2.19, p = 0.03 [-0.13, - 0.01]), whereas women showed no changes over time (b = 0.02, t(853) = 0.80, p = 0.42 [-0.03, 0.08]). A one 10-year increase in age corresponded with a -0.25 decrease in mutual success towards humanity (t(987) = -3.16, p = 0.001 [-0.04, -0.009]) at time 1, and a 10-year increase in age was associated with a 0.06 increase per unit of time in mutual success towards humanity (t(674) = 2.77, p = 0.005 [0.002, 0.01]). When we investigate the independent effects of having a pre-existing medical condition (which do not hold when controlling for other demographics) on responses at time 1, and change over time, we find that people with a pre-existing medical condition reported a lower mutual success towards humanity at time 1 than people with no medical condition (b = 0.55, t(1066) = 2.35, p = 0.02 [0.09, 1.02]). We also find an interaction between having a pre-existing medical condition and time (b = -0.16, t(759) = -2.35, p = 0.02 [- 0.29, 0.03]), suggesting the rate of change over time was different between people with and without a medical condition. However, neither people with no medical condition (b = -0.04, t(813) = -1.71, p = 0.09 [-0.08, 0.006]), or people with a medical condition (b = 0.1, t(726) = 1.89, p = 0.06 [-0.005, 0.24]) showed statistically significant changes over time. Again, effects of medical condition do not hold when controlling for other demographics. Having children did not influence rate of change over time in mutual success towards humanity (b = 0.09, t(821) = 1.61, p = 0.09 [-0.02, 0.19]), but people with children reported a lower mutual success towards humanity than people with no children at time 1 (b = -0.45, t(1113) = -2.48, p = 0.01 [-0.81, - 0.09]). In a model where we simultaneously enter time, sex, age, pre-existing medical condition, having children, the interaction between time and sex, and the interaction between time and age as predictors, we find that neither medical condition (b = 0.12, t(460) = 0.75, p = 0.45 [-0.19, 0.43]), having children (b = -0.18, t(482) = -1.22, p = 0.22 [-0.46, 0.11]), or the interaction COOPERATION IN THE PANDEMIC (working paper) 33 between time and sex (b = -0.07, t(828) = 1.77, p = 0.07 [-0.01, 0.16]) influenced mutual success towards humanity. However, age (b = -0.02, t(944) = -2.38, p = 0.02 [-0.04, -0.003]), and its interaction with time (b = 0.05, t(653) = 2.49, p = 0.01 [0.001, 0.009]) remain significant predictors of mutual success towards humanity. Perceived risk of contracting COVID-19 did not influence mutual success towards humanity at time 1 (b = -0.004, t(655) = -0.07, p = 0.94 [-0.10, -0.09]), or change over time (b = -0.0005, t(682) = -0.03, p = 0.98 [-0.03, 0.03]). We probe for a three-way interaction between time, perceived risk of contracting COVID-19, and having a pre- existing medical condition on mutual success towards humanity. We find no evidence for a two- way interaction between perceived risk and medical condition (b = -0.27, t(245) = -1.38, p = 0.17 [-0.67, 0.12]), suggesting perceived level of risk of contracting COVID-19 did not influence mutual success towards humanity at time 1 differently for people with a medical condition relative to people with no medical condition. We also find no evidence for a three-way interaction between time, perceived risk, and pre-existing condition (b = 0.10, t(276) = 1.76, p = 0.08 [-0.01, 0.22]), suggesting perceived risk of contracting COVID-19 did not influence change over time differently for people with a medical condition relative to people with no medical condition. Subjective SES did not influence responses at time 1 or over time.

Interdependence “All of humanity and I rise and fall together” increased over time, varied by region, and health

The marginal shared fate with humanity at time 1 was 4.23 [4.04, 4.43], with significant variation around the random intercept = 1.78 (Z = 12.09, p < .001). A one unit increase in time was associated with a 0.12 increase in shared fate with humanity (t(918) = 4.34, p < 0.001 [0.01, 0.18]), with no significant variation around the random slope (훥휒2(2) = 2.7, p > .05). Shared fate with humanity was not different in Europe (b = 0.37, t(780) = 1.49, p = 0.14 [-0.12, 0.85]) than UK/Ireland at time 1, but shared fate with humanity was higher in US/Canada (b = 1.39, t(474) = 4.13, p < 0.001 [0.72, 2.05]), and in Other regions (b = 0.74, t(355) = 2.01, p = 0.04 [0.02, 1.46]) than in UK/Ireland at time 1. Change over time in shared fate towards humanity was not different in Europe (b = -0.10, t(432) = -1.46, p = 0.14 [-0.24, 0.03]), or in Other regions (b = -0.14, t(202) = -1.39, p = 0.16 [-0.34, 0.06]) from rate of change in UK/Ireland, but change over time in shared fate with humanity was smaller in US/Canada (b = - 0.35, t(241) = -3.46, p < 0.001 [-0.54, 0.15]) than in UK/Ireland.

Table 11. Region intercepts and slopes for interdependence (shared fate) with humanity. Obs. = 1325 B SE df t p 95 CI

UK/Ireland Intercept 3.785 0.2 458 18.7 < .001 3.388 4.183

UK/Ireland Slope 0.234 0.06 239 3.91 < .001 0.116 0.352

US/Canada Intercept 5.172 0.27 241 19.3 < .001 4.644 5.70

US/Canada Slope -0.11 0.08 115 -1.41 0.161 -0.273 0.046

Europe Intercept 4.151 0.14 800 29.5 < .001 3.875 4.428 COOPERATION IN THE PANDEMIC (working paper) 34

Europe Slope 0.13 0.04 479 3.46 < .001 0.056 0.204

Other Intercept 4.526 0.31 198 14.7 < .001 3.919 5.132

Other Slope 0.092 0.08 96.1 1.12 0.2651 -0.071 0.255

In a model where we include time, pre-existing medical condition, and the interaction between time and pre-existing condition, we find that people with no pre-existing condition reported a higher shared fate with humanity at time 1 than people with a pre-existing medical condition (b = 0.78, t(1120) = 2.55, p = 0.01 [0.18, 1.38]). We also find an interaction between time and pre-existing condition (b = -0.35, t(781) = -4.07, p < 0.001 [-0.52, 0.18]), such that people with a pre-existing medical condition increased in shared fate with humanity at a higher rate per unit of time (b = 0.43, t(741) = 5.31, p < 0.001 [0.27, 0.59]) than people with no medical condition (b = 0.08, t(911) = 2.66, p = 0.01 [0.02, 0.14]). In a separate model in which we include time, perceived risk of contracting COVID-19, and the interaction between time and perceived risk as predictors, we find no evidence that risk of contracting COVID-19 influenced shared fate with humanity at time 1 (b = 0.05, t(463) = 0.82, p = 0.41 [-0.08, 0.19]), or change over time (b = -0.02, t(627) = -0.83, p = 0.40 [-0.06, 0.02]). We then probe for a three-way interaction between time, perceived risk of contracting COVID-19, and medical condition. We find no evidence for a three-way interaction (b = 0.005, t(316) = 0.07, p = 0.94 [-0.15, 0.16]), suggesting perceived risk of contracting COVID-19 did not influence change over time in shared fate with humanity differently for people with a medical condition relative to people with no medical condition. We also find no evidence for a two-way interaction between perceived risk of contracting COVID-19 and medical condition (b = -0.03, t(294) = -0.21, p = 0.84 [-0.34, 0.27]), suggesting perceived risk of contracting COVID-19 did not influence shared fate with humanity at time 1 differently for people with a medical condition compared to people with no medical condition. Age, sex, subjective SES, and having children had no influence on responses at time 1 or over time.

People reported higher interdependence with all of humanity than with their neighborhoods across all time points Perceived interdependence as measured by the item “When all of humanity/my neighborhood succeeds, I feel good” was higher towards all of humanity than with “my neighborhood” at time 1 (paired-samples t(226) = 11.65, p < .001, Mdiff = 1.32 [1.10, 1.55]), time 2 (paired-samples t(225) = 11.14, p < .001, Mdiff = 1.27 [1.04, 1.49]), time 3 (paired-samples t(225) = 11.79, p < .001, Mdiff = 1.09 [0.91, 1.28]), and at time 4 (paired-samples t(226) = 9.46, p < .001, Mdiff = 0.89 [0.79, 1.07]). Participants also reported greater interdependence with all of humanity than with their neighborhood in the “rise and fall together” item at time 1 (paired-samples t(223) = 11.45, p < .001, Mdiff = 1.55 [1.28, 1.82]), time 2 (paired samples t(225) = 11.33, p < .001, Mdiff = 1.43 [1.18, 1.68]), time 3 (paired samples t(225) = 11.71, p < .001, Mdiff = 1.30 [1.08, 1.52]), and at time 4 (paired samples t(223) = 10.05, p < .001, Mdiff = 1.16 [0.93, 1.39]).

Effects of Perceived Interdependence on Cooperation To explore whether perceived interdependence influenced cooperation at time 1, or the rate of change over time we first ran separate models with each measure of interdependence, time, and their interaction with time as fixed predictors. We control for demographics in models where demographic variables were found to influence rates of cooperation at time 1. Measures of interdependence were grand-mean centered for the following analyses. COOPERATION IN THE PANDEMIC (working paper) 35

Shared fate and mutual success increased willingness to allow a neighbor to move in for a week at time 1, but not the rate of change over time

Mutual success with neighbors “When my neighborhood succeeds, I feel good,” did not influence the rate of change over time on willingness to allow a neighbor to move in for a week (b = 0.002, t(849) = 0.15, p = 0.88 [-0.03, 0.03]), but higher mutual success with neighbors was associated with higher willingness to help a neighbor at time 1 (b = 0.18, t(951) = 3.51, p < .001 [0.08, 0.28]). Willingness to help a neighbor was also higher at time 1 for people who reported higher interdependence with their neighbors on the item “My neighborhood and I rise and fall together” (b = 0.18, t(896) = 3.63, p < .001 [0.08, 0.28]), but this item did not influence rate of change over time (b = -0.001, t(790) = -0.07, p = 0.95 [-0.03, 0.03]. We then run a model where we simultaneously enter time, mutual success with neighbors, and shared fate with neighbors as fixed predictors. Both shared fate (b = 0.13, t(1170) = 4.30, p < .001 [0.07, 0.18]), and mutual success (b = 0.12, t(1185) = 3.73, p < .001 [0.06, 0.18]) remain significant predictors.

Mutual success, but not shared fate, increased need-based helping towards a neighbor at time 1, but not the rate of change over time

Neither mutual success “When my neighborhood succeeds, I feel good” (b = 0.01, t(551) = 0.95, p = 0.34 [-0.02, 0.05]), or shared fate “My neighborhood and I rise and fall together” (b = 0.02, t(499) = 1.36, p = 0.17 [-0.01, 0.05]) had an influence on the rate of change over time on people’s endorsement with the statement that helping a neighbor who is in need is the right thing to do. However, mutual success (b = 0.19, t(538) = 3.90, p < .001 [0.09, 0.29]), but not shared fate (b = 0.02, t(373) = 0.36, p = .72 [-0.07, 0.11]) was associated with higher ratings of need-based helping towards a neighbor at time 1. We test whether interdependence increases ratings of need-based helping towards a neighbor at time 1 over and above age and sex, which were found to influence responses at time 1. In a model where we enter time, age, sex, shared fate, and mutual success as fixed predictors, we find that age is no longer a significant predictor of need-based helping towards a neighbor at time 1 (b = 0.01, t(421) = 1.72, p = 0.08 [-0.001, 0.02]), but the effect of sex remains (b = 0.33, t(438) = 3.30, p < .01 [0.13, 0.52]), with women reporting greater need-based helping at time 1. Mutual success remains a significant predictor of need-based helping at time 1 (b = 0.25, t(947) = 9.20, p < .001 [0.19, 0.30]), while shared fate remains a non-statistically significant predictor (b = -0.04, t(687) = -1.50, p = 0.13 [-0.09, 0.01]).

Mutual success and shared fate increased willingness to help a “person who is not a citizen of your own country” by allowing them to move in for a week at time 1, but not the rate of change over time

We find that both mutual success “When all of humanity succeeds, I feel good” (b = 0.12, t(556) = 2.08, p = .04 [0.01, 0.23]), and shared fate “All of humanity and I rise and fall together” (b = 0.12, t(541) = 2.86, p = .004 [0.04, 0.21]) increased willingness to help a person from a different country by allowing them to move in for a week at time 1. Neither mutual success (b = 0.004, t(552) = 0.19, p = 0.85 [-0.03, 0.04]), or shared fate (b = -0.004, t(552) = -0.28, p = 0.78 [-0.03, 0.03]) influenced the rate of change over time. In a model where we enter time, mutual success, and shared fate as fixed predictors, both shared fate (b = 0.09, t(1104) = 3.69, p < 0.001 [0.04, 0.14]), and mutual success (b = 0.08, t(1093) = 2.61, p = 0.01 [0.02, 0.15]) remain significant predictors of willingness to help at time 1. COOPERATION IN THE PANDEMIC (working paper) 36

Mutual success, but not shared fate, increased need-based helping towards a “person who is not a citizen of your own country” at time 1, but not the rate of change over time

Neither mutual success, “When all of humanity succeeds, I feel good,” (b = 0.02, t(543) = 1.0, p = 0.32 [-0.02, 0.06]) or shared fate “All of humanity and I rise and fall together” (b = 0.02, t(601) = 1.28, p = 0.20 [-0.01, 0.05]) influenced the rate of change over time on people’s endorsement with the statement that helping a person from a different country who is in need is the right thing to do. Shared fate also did not influence need-based helping towards humanity at time 1 (b = 0.01, t(545) = 0.13, p = 0.89 [-0.08, 0.09]), but mutual success was associated with higher need- based helping towards humanity at time 1 (b = 0.19, t(516) = 3.37, p < 0.001 [0.08, 0.30]). In a model where we enter time, shared fate, and mutual success as fixed predictors we again find that mutual success (b = 0.24, t(1029) = 7.60, p < 0.001 [0.18, 0.31]), but not shared fate (b = - 0.005, t(1048) = -0.22, p = 0.82 [-0.05, 0.04]) increased ratings of need-based helping towards humanity at time 1.

Perception of COVID-19 risk Perceived risk of contracting/becoming infected with COVID-19 increased over time, varied by region; older people reported lower risk at time 1, but increased more than younger people

At time 1, the marginal perceived risk of contracting COVID-19 was 3.19 [2.7, 3.48] on the scale from 1=”not at all” to 7=”extremely”, with significant variation around the random intercept = 2.16 (Z = 6.54, p < .001), suggesting people began with different levels of perceived risk at time 1. A one unit increase in time was associated with a 0.23 increase in the marginal perceived risk of contracting COVID-19 (t(380) = 7.55, p < .001 [0.21, 0.34]), with significant variation around the random slope = 0.15 (Z = 4.63, < .001), suggesting people differed in how their perceived risk changed over time. Random slope variance translates into a one standard deviation of 0.39 in the marginal slope, indicating that 68% of individual slopes fell between - 0.16 and 0.62, while 95% fell between -0.55 and 1.01. The random slope and intercept were negatively correlated (r = -.663, p < .001), indicating that people who began at a lower perceived risk at time 1, increased faster over time. In UK/Ireland perceived risk was 3.09 [2.71, 3.48] at time 1, and a one unit increase in time (from one time point to the next) was associated with a 0.40 [0.27, 0.52] increase in perceived risk. Perceived risk was lower at time 1 in US/Canada than in UK/Ireland (b = -0.81, t(270) = -2.54, p = .01 [-1.44, -0.18]), but risk in US/Canada did not change differently across time than in UK/Ireland (t(243) = 0.85, p = 0.39 [-0.11, 0.29]. Perceived risk at time 1 for Europe (t(373) = 1.16, p = 0.25 [-0.19, 0.76] was not different than in UK/Ireland, but risk increased at a slower rate in Europe than in UK/Ireland (b = -0.25, t(361) = - 3.27, p = 0.001 [-0.40, -0.10]). Neither risk at time 1 (b = -0.47, t(242) = -1.28, p = 0.20 [-1.19, 0.25]) or rate of change across time (b = -0.06, t(214) = -0.53, p = 0.59 [-0.28, 0.16] were different in “Other” regions than in UK/Ireland.

Table 12. Region-specific intercepts and slopes for perceived risk of contracting COVID-19. Obs. = 1331 B SE df t p 95 CI

UK/Ireland Intercept 3.097 0.199 295 15.58 <.0001 2.706 3.488

UK/Ireland Time 0.401 0.064 262 6.28 <.0001 0.275 0.526

US/Canada Intercept 2.281 0.254 179 8.96 <.0001 1.779 2.783 COOPERATION IN THE PANDEMIC (working paper) 37

US/Canada Time 0.489 0.082 140 5.94 <.0001 0.326 0.652

Europe Intercept 3.379 0.142 338 23.78 <.0001 3.099 3.658

Europe Time 0.149 0.044 299 3.42 0.0007 0.0635 0.235

Other Intercept 2.631 0.311 167 8.47 <.0001 2.017 3.244

Other Time 0.340 0.095 132 3.58 0.0005 0.152 0.528

To explore whether demographics influenced marginal perceived risk of contracting COVID-19 at time 1, or rate of change over time, we ran separate models with age, sex, subjective SES, having children (0 = no, 1 = at least one), and having a pre-existing medical condition (1 = no, 2 = yes) and their interaction with time as covariates. The only demographic variable found to influence perceived risk was age, with older people reporting slightly less risk at time 1 (b = -0.02, t(351) = -2.53, p = .011 [-0.04, -0.01]), but also increasing in perceived risk at a slightly higher rate over time (b = 0.02, t(316) = 4.1, p < .001 [0.01, 0.02]). If we transform the estimates such that they correspond to a 10-year, rather than a one-year increase in age, we can see that, on average, a one 10-year increase in age corresponded with a -0.20 decrease in perceived risk of contracting COVID-19 at time 1, and a 10-year increase in age corresponded with a 0.20 increase in perceived risk per unit of time. Thus older people began at a lower perceived risk, but increased at a higher rate over time. For people who reported having at least one child, their perception of risk of contracting COVID-19 increased at a higher rate over time than for those who did not report having any children (b = 0.18, t(373) = 2.36, p < .02 [0.03, 0.32]). However, in a model where we simultaneously enter time, age, having children, and the interactions between time and age, and time and having children as fixed predictors, we find that having children no longer influenced the rate of change over time in perception of risk (b = 0.02, t(363) = 0.03, p = .97 [-0.53, 0.55]), whereas the effect of age on time remained unchanged (b = 0.01, t(295) < 3.37, p < .001 [0.005, 0.02]). COOPERATION IN THE PANDEMIC (working paper) 38

APPENDIX 2 SURVEY QUESTIONS

The surveys included questions on different aspects of behavior, perceptions, and attitudes in the following order. Not all questions were asked in all surveys-- below is a list of those questions asked across time points and included in our analyses. Covariates were collected at time point 1. A complete list of every question asked in each survey is available on OSF (https:// osf.io/gtsbr/).

TABLE 2A QUESTIONS ASKED AT ALL TIME POINTS Please enter your Prolific ID here What is the zip/ postal code of your current residence? How likely do you think it is that you will contract COVID19?/ How likely do you think it is that you will become infected with COVID19? [1 Not at all to 7 Extremely] I am likely to ask parents or friends for help preparing for the COVID19 epidemic/ pandemic. [1 Do not agree at all to 7 Strongly agree] I have been stocking up on food and supplies so that I am prepared for the COVID19 epidemic/ pandemic. [1 Do not agree at all to 7 Strongly agree] I try to reduce my risk of getting COVID19 by doing things like washing my hands often. [1 Do not agree at all to 7 Strongly agree] I completely avoid situations that could put me at risk of contracting COVID19, for example staying away from large events where there have been cases./ I completely avoid situations that could put me at risk of contracting COVID19, like going to the grocery store when it is crowded. [1 Do not agree at all to 7 Strongly agree] How many days of food do you currently have for your household? Numbers only. How many days of food would you like to have for your household? Numbers only. When my neighborhood succeeds, I feel good. [1 Do not agree at all to 7 Strongly agree] My neighborhood and I rise and fall together. [1 Do not agree at all to 7 Strongly agree] Someone from your neighborhood is having their house fixed, so it isn't livable. How willing would you be to let them move into your house for a week? [1 Not at all willing to 7 Very willing] Helping someone from my neighborhood when they are in need is the right thing to do. [1 Strongly disagree to 7 Strongly agree] When all of humanity succeeds, I feel good. [1 Do not agree at all to 7 Strongly agree] All of humanity and I rise and fall together. [1 Do not agree at all to 7 Strongly agree] A displaced person who is not a citizen of your own country is having their house fixed, so it isn't livable. How willing would you be to let them move into your house for a week? [1 Not at all willing to 7 Very willing] Helping a displaced person who is not a citizen of your own country when they are in need is the right thing to do. [1 Strongly disagree to 7 Strongly agree] COOPERATION IN THE PANDEMIC (working paper) 39

TABLE 2B DEMOGRAPHIC QUESTIONS ASKED AT TIME POINT 1 AND USED AS COVARIATES What is your age? What is your sex? (M/F/Other) How many children do you have? Below, you will see a ladder. At the top of the ladder are the people who are the best off, have the most money, most education, and best jobs. These people are represented by number 10 marked on the ladder. At the bottom are the people who are the worst off, have the least money, least education, worst jobs, or no job. These people are represented by number 1 at the bottom of the ladder.

Please choose the number associated with the rung that best represents where you think you stand on the ladder. [1 to 10] What country do you currently live in? [Open ended]

Do you have any pre-existing health conditions that require you to take extra precautions to avoid being sick? [Yes or No] COOPERATION IN THE PANDEMIC (working paper) 40

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Supplemental Materials

Tables 13-15. Tests of model fit and variance estimates for perceived risk of contracting COVID-19 (Obs. = 1331).

50:50 mixture chi-square test for variance components

No random Random No random Random intercept intercept Slope slope

-2LL 4714.3 4588.2 4721.5 4588.2

Δ - 126.1 - 133.3 2LL

휒2 - 2*** - 2*** (df)

Chi-square test for covariance components

Intercept Time Region Age

-2LL 4698.9 4579.3 4545.9 4561.5

Δ 2LL - 110.7 33.4 17.8

휒2 (df) - 2*** 6** 2**

Note. Model fit for region and its interaction with time, and age and its interaction with time, are compared against the Time model, which included a fixed intercept and slope, and a random intercept and slope for participant ID, allowing the random intercept and slope to correlate.

Region Variance

Intercept 2.139

Slope 0.151

r(intercept, slope) -0.663 COOPERATION IN THE PANDEMIC (working paper) 51

Time 1 Europe 0.871

Time 2 Europe 0.793

Time 3 Europe 0.908

Time 4 Europe 1.019

Time 1 US/Canada 0.787

Time 2 US/Canada 0.631

Time 3 US/Canada 0.561

Time 4 US/Canada 1.087

Time 1 Other 1.136

Time 2 Other 0.668

Time 3 Other 0.533

Time 4 Other 1.446

Time 1 UK/Ireland 1.516

Time 2 UK/Ireland 1.095

Time 3 UK/Ireland 0.548

Time 4 UK/Ireland 1.370

Note. Variances reported were modeled by including a fixed intercept and slope, random intercepts and slopes for participant ID, allowing the random intercepts and slopes to correlate, and geographic region as a fixed categorical predictor.

Tables 16-18. Tests of model fit and variances estimates for interdependence (empathy) neighborhood (Obs. = 1327).

50:50 mixture chi-square test for variance components COOPERATION IN THE PANDEMIC (working paper) 52

No random Random No random Random intercept intercept Slope slope

-2LL 4670.5 4469.2 4472.6 4469.2

Δ - 201.3 - 3.4 2LL

휒2 - 2*** - 2(n.s.) (df)

Chi-square test for covariance components

Intercept Time Region Age

-2LL 4485.5 4463.4 4445.8 4452.1

Δ 2LL - 22.1 17.6 11.3

휒2 (df) - 1*** 6** 2**

Note. Model fit for region and its interaction with time, and age and its interaction with time, are compared against the Time model, which included a fixed intercept and slope, and a random intercept for participant ID.

Region Variance

Intercept 1.574

Time 1 Europe 0.805

Time 2 Europe 0.817

Time 3 Europe 0.603

Time 4 Europe 0.996

Time 1 US/Canada 0.772 COOPERATION IN THE PANDEMIC (working paper) 53

Time 2 US/Canada 0.703

Time 3 US/Canada 1.157

Time 4 US/Canada 0.709

Time 1 Other 0.521

Time 2 Other 0.753

Time 3 Other 1.675

Time 4 Other 1.871

Time 1 UK/Ireland 1.004

Time 2 UK/Ireland 1.074

Time 3 UK/Ireland 1.633

Time 4 UK/Ireland 0.946

Note. Variances reported were modeled by including a fixed intercept and slope, a random intercept for participant ID, and geographic region as a fixed categorical predictor.

Tables 19-21. Tests of model fit and variance estimates for interdependence (shared fate) towards one’s neighborhood (Obs. = 1325).

50:50 mixture chi-square test for variance components

No random Random No random Random intercept intercept Slope slope

-2LL 4766.7 4650.4 4675.5 4650.4

Δ - 116.3 - 25.1 2LL

휒2 - 2*** - 2*** (df) COOPERATION IN THE PANDEMIC (working paper) 54

Chi-square test for covariance components

Intercept Time Region Age

-2LL 4743.0 4641.6 4617.0 4610.5

Δ 2LL - 101.4 24.6 31.1

휒2 (df) - 2*** 6*** 4***

Note. Model fit for region and its interaction with time, and age and its interaction with time, are compared against the Time model, which included a fixed intercept and slope, and a random intercept and slope for participant ID, allowing the random slope and intercept to correlate.

Region Variance

Intercept 1.529

Slope 0.098

r(intercept, slope) -0.111

Time 1 Europe 0.846

Time 2 Europe 0.906

Time 3 Europe 0.785

Time 4 Europe 0.973

Time 1 North America 1.035

Time 2 North America 0.998

Time 3 North America 0.907

Time 4 North America 2.16

Time 1 Other 0.910

Time 2 Other 0.625

Time 3 Other 1.416

Time 4 Other 0.624 COOPERATION IN THE PANDEMIC (working paper) 55

Time 1 UK/Ireland 1.182

Time 2 UK/Ireland 1.094

Time 3 UK/Ireland 0.663

Time 4 UK/Ireland 1.455 Note. Variances reported were modeled by including a fixed intercept and slope, a random intercept and slope for participant ID, allowing the random intercept and slope to correlate, and geographic region as fixed categorical predictor.

Tables 21-23. Tests of model fit and variance estimates for willingness to help a neighbor (Obs. = 1326).

50:50 mixture chi-square test for variance components

No random Random No random Random intercept intercept Slope slope

-2LL 4907.0 4641.8 4648.6 4641.8

Δ - 265.2 - 6.8 2LL

휒2 - 2*** - 2(n.s.) (df)

Chi-square test for covariance components

Intercept Time Region Interdependence

-2LL 4641.3 4639.7 4624.8 4560.9

Δ 2LL - 1.6 18.2 78.8

휒2 (df) - 1(n.s.) 6** 2** Note. Model fit for region and its interaction with time, and interdependence, are compared against the Time model, which included a fixed intercept and slope, and a random intercept for participant ID. COOPERATION IN THE PANDEMIC (working paper) 56

Region Variance

Intercept 2.183

Time 1 Europe 0.777

Time 2 Europe 0.835

Time 3 Europe 1.109

Time 4 Europe 1.102

Time 1 North America 0.768

Time 2 North America 0.536

Time 3 North America 0.937

Time 4 North America 1.496

Time 1 Other 0.943

Time 2 Other 0.487

Time 3 Other 1.929

Time 4 Other 1.128

Time 1 UK/Ireland 0.824

Time 2 UK/Ireland 0.998

Time 3 UK/Ireland 0.712

Time 4 UK/Ireland 2.078

Note. Variances reported were modeled by including a fixed intercept and slope, a random intercept for participant ID, and region as a categorical fixed predictor.

Tables 24-26. Tests of model fit and variance estimates for need based helping towards a neighbor (Obs. = 1328).

50:50 mixture chi-square test COOPERATION IN THE PANDEMIC (working paper) 57

for variance components

No random Random No random Random intercept intercept Slope slope

-2LL 4417.0 4280.3 4303.0 4280.3

Δ - 136.7 - 22.7 2LL

휒2 - 2*** - 2*** (df)

Chi-square test for covariance components

Intercept Time Region Sex Age Interdependence

-2LL 4322.6 4270.9 4256.6 4256.6 4250.6 4137.2

Δ 2LL - 51.7 14.3 14.3 6 113.4

휒2 (df) - 2*** 6* 1*** 1* 2**

Note. Model fit for region and its interaction with time, and Sex, are compared against the Time model, which included a fixed intercept and slope, and a random intercept and slope for participant ID. The random intercept and slope were allowed to correlate. Model fit for age is compared against the Sex model; model fit for interdependence is compared against the Age model.

Region Variance

Intercept 1.796

Slope 0.109

r(intercept, slope) -0.637

Time 1 Europe 0.697

Time 2 Europe 0.821 COOPERATION IN THE PANDEMIC (working paper) 58

Time 3 Europe 0.590

Time 4 Europe 0.764

Time 1 North America 0.911

Time 2 North America 0.909

Time 3 North America 0.329

Time 4 North America 0.028

Time 1 Other 0.388

Time 2 Other 1.033

Time 3 Other 0.734

Time 4 Other 0.909

Time 1 UK/Ireland 1.029

Time 2 UK/Ireland 0.941

Time 3 UK/Ireland 0.433

Time 4 UK/Ireland 0.803 Note. Variances reported were estimated by including a fixed intercept and slope, a random intercept and slope for participant ID, allowing the random intercept and slope to correlate, and region as a categorical fixed predictor.

Tables 27-29. Tests of model fit and variance estimates for interdependence (empathy) towards humanity (Obs. = 1327).

50:50 mixture chi-square test for variance components

No random Random No random Random intercept intercept Slope slope

-2LL 4191.3 4037.9 4042.7 4037.9

Δ - 153.4 - 4.8 2LL

휒2 - 2*** - 2(n.s.) COOPERATION IN THE PANDEMIC (working paper) 59

(df)

Chi-square test for covariance components

Intercept Time Region Age

-2LL 4033.7 4032.8 4025.1 4022.8

Δ 2LL - 1.1 7.7 10

휒2 (df) - 2(n.s.) 6(n.s.) 2** Note. Model fit for region and its interaction with time, and age and its interaction with time, are compared against the Time model which included a fixed intercept and slope, and a random intercept for participant ID.

Region Variance

Intercept 0.996

Time 1 Europe 0.732

Time 2 Europe 0.454

Time 3 Europe 0.659

Time 4 Europe 0.514

Time 1 North America 0.802

Time 2 North America 0.551

Time 3 North America 0.930

Time 4 North America 0.632

Time 1 Other 0.713

Time 2 Other 0.751

Time 3 Other 0.813

Time 4 Other 1.236

Time 1 UK/Ireland 1.043

Time 2 UK/Ireland 1.031 COOPERATION IN THE PANDEMIC (working paper) 60

Time 3 UK/Ireland 0.792

Time 4 UK/Ireland 0.799 Note. Variances reported were estimated by including a fixed intercept, and a random intercept for participantID.

Tables 29-31. Tests of model fit and variance estimates for interdependence (shared fate) towards humanity (Obs. = 1325).

50:50 mixture chi-square test for variance components

No random Random No random Random intercept intercept Slope slope

-2LL 4916.2 4719.6 4722.3 4719.6

Δ - 196.6 - 2.7 2LL

휒2 - 2*** - 2(n.s.) (df)

Chi-square test for covariance components

Medical Intercept Time Region condition

-2LL 4731.1 4713.4 4695.1 4696.9

Δ 2LL - 17.7 18.3 16.5

휒2 (df) - 1*** 6** 2*** Note. Model fit for region and its interaction with time, and medical condition and its interaction with time, are compared against the Time model which included a fixed intercept and slope, and a random intercept for participant ID.

Region Variance

Intercept 1.747

Time 1 Europe 1.043

Time 2 Europe 0.965 COOPERATION IN THE PANDEMIC (working paper) 61

Time 3 Europe 1.130

Time 4 Europe 1.189

Time 1 North America 1.101

Time 2 North America 0.902

Time 3 North America 1.480

Time 4 North America 1.426

Time 1 Other 1.157

Time 2 Other 0.523

Time 3 Other 1.085

Time 4 Other 1.625

Time 1 UK/Ireland 1.245

Time 2 UK/Ireland 1.337

Time 3 UK/Ireland 1.230

Time 4 UK/Ireland 1.953 Note. Variances reported were estimated by including a fixed intercept and slope, a random intercept for participant ID, and region as a fixed categorical predictor.

Tables 32-34. Tests of model fit and variance estimates for willingness to help a person who is not a citizen of your own country (Obs. = 1326).

50:50 mixture chi-square test for variance components

No random Random No random Random intercept intercept Slope slope

-2LL 4695.3 4424.1 4444.8 4424.1

Δ - 271.2 - 20.2 2LL

휒2 - 2*** - 2*** (df) COOPERATION IN THE PANDEMIC (working paper) 62

Chi-square test for covariance components

Intercept Time Region Interdependence

-2LL 4455.9 4415.1 4403.6 4367.5

Δ 2LL - 40.8 11.5 47.6

휒2 (df) - 2*** 6(n.s.) 2** Note. Model fit for region and its interaction with time, and interdependence, are compared against the Time model which included a fixed intercept and slope, and a random intercept and slope for participant ID, allowing the random intercept and slope to correlate.

Region Variance

Intercept 2.273

Slope 0.086

r(intercept, slope) -0.386

Time 1 Europe 0.421

Time 2 Europe 0.739

Time 3 Europe 0.885

Time 4 Europe 0.742

Time 1 North America 0.628

Time 2 North America 0.277

Time 3 North America 0.561

Time 4 North America 1.406

Time 1 Other 0.771

Time 2 Other 1.300

Time 3 Other 1.301

Time 4 Other 1.094 COOPERATION IN THE PANDEMIC (working paper) 63

Time 1 UK/Ireland 0.526

Time 2 UK/Ireland 0.775

Time 3 UK/Ireland 0.361

Time 4 UK/Ireland 0.507

Note. Variances reported were estimated by including a fixed intercept and slope, and a random intercept and slope for participant ID, allowing the random intercept and slope to correlate.

Tables 35-37. Tests of model fit and variance estimates for need-based helping towards a person who is not a citizen of your own country (Obs. = 1326).

50:50 mixture chi-square test for variance components

No random Random No random Random intercept intercept Slope slope

-2LL 4500.1 4392.4 4441.3 4329.4

Δ - 107.7 - 48.9 2LL

휒2 - 2*** - 2*** (df)

Chi-square test for covariance components

Intercept Time Region Interdependence

-2LL 4456.1 4383.3 4367.5 4285.6

Δ 2LL - 72.8 15.8 97.7

휒2 (df) - 2*** 6* 2** Note. Model fit for region and its interaction with time, and interdependence, are compared against the Time model, which included a fixed intercept and slope, and a random intercept and slope for participant ID, allowing the random intercept and slope to correlate.

Region Variance

Intercept 1.495 COOPERATION IN THE PANDEMIC (working paper) 64

Slope 0.137

r(intercept, slope) -0.492

Time 1 Europe 0.646

Time 2 Europe 0.766

Time 3 Europe 0.704

Time 4 Europe 0.464

Time 1 North America 0.751

Time 2 North America 0.889

Time 3 North America 0.426

Time 4 North America 1.539

Time 1 Other 0.596

Time 2 Other 1.542

Time 3 Other 0.324

Time 4 Other 0.615

Time 1 UK/Ireland 1.138

Time 2 UK/Ireland 1.179

Time 3 UK/Ireland 0.588

Time 4 UK/Ireland 0.623 Note. Variances reported were estimated by including a fixed intercept and slope, a random intercept and slope for participant ID, allowing the random intercept and slope to correlate, and region as a fixed categorical predictor.