Is It Safe to Lift COVID-19 Travel Bans? the Newfoundland Story

based on data from July 1, 2020

Is it safe to lift COVID-19 travel bans? The Newfoundland story.

Kevin Linka Proton Rahman Alain Goriely Ellen Kuhl · · ·

Received: August 2, 2020

Abstract A key strategy to prevent a local outbreak during 1 Motivation the COVID-19 pandemic is to restrict incoming travel. Once a region has successfully contained the disease, it becomes On July 3, 2020, the Canadian province of Newfoundland critical to decide when and how to reopen the borders. Here and Labrador enjoyed the rather exceptional and enviable we explore the impact of border reopening for the example position of having the coronavirus pandemic under control of Newfoundland and Labrador, a Canadian province that with the total number of 261 cases, with 258 recovered, has enjoyed no new cases since late April, 2020. We com- 3 deaths, no active cases for 16 consecutive days, and no bine a network epidemiology model with machine learn- new cases for 36 days [2]. On the same day, after a two- ing to infer parameters and predict the COVID-19 dynam- months long local travel ban, the Atlantic Bubble opened to ics upon partial and total airport reopening, with perfect allow air travel between the four Atlantic Provinces, New- and imperfect quarantine conditions. Our study suggests that foundland and Labrador, Nova Scotia, New Brunswick, and upon full reopening, every other day, a new COVID-19 case Prince Edward Island, with no quarantine requirements for would enter the province. Under the current conditions, ban- travelers [37]. Under the increasing pressure to fully reopen, ning air travel from outside Canada is more efficient in man- health officials and political decision makers now seek to un- aging the pandemic than fully reopening and quarantining derstand the risk of gradual and full reopening under perfect 95% of the incoming population. Our study provides quan- quarantine conditions and quarantine violation [24]. titative insights of the efficacy of travel restrictions and can The province of Newfoundland and Labrador is the inform political decision making in the controversy of re- second smallest Canadian province with a population of opening. 519,716. It has two major geographical divisions, the island of Newfoundland that accounts for 92% of the population Keywords COVID-19 epidemiology SEIR model · · · and a continental region of Labrador that is home to the re- reproduction number machine learning · maining 8% [35]. The demographics of its population, the “There is one and only one way to absolutely prevent it and highest rates of obesity and overweight, metabolic disease, that is by establishing absolute isolation. It is necessary to and cancer nationally, and an unhealthy lifestyle with the shut off those who are capable of giving off the virus from highest rate of cigarette smoking among all provinces set those who are capable of being infected, or vice versa.” The Newfoundland and Labrador apart from the rest of Canada Lessons Of The Pandemic, Science 1919. [3]. These factors are critical when developing policies for the management of COVID-19. Kevin Linka Ellen Kuhl Department of· Mechanical Engineering, Stanford University, Stanford, The first reported case of COVID-19 in Newfoundland California, United States E-mail: klinka/[email protected] and Labrador was on March 14, 2020 followed by a rapid es- Proton Rahman calation in the number of cases caused by a super-spreader Department of Medicine Memorial University of Newfoundland, event at a funeral home [37]. Rapid and well-coordinated Cananda E-mail: [email protected] implementation of provincial public health measures re- Alain Goriely sulted in excellent viral epidemic control of the first wave Mathematical Institute, University of Oxford, Oxford, United King- and the province has not had a documented case of com- dom E-mail: [email protected] munity transmission since mid-April 2020 [2]. In the ab- NOTE: This preprint reports new research that has not been certified by peer review and should not be used to guide clinical practice. medRxiv preprint doi: https://doi.org/10.1101/2020.07.16.20155614; this version posted August 2, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license .

2 Kevin Linka et al. sence of any reported COVID-19 cases in the province, the Here (˙) = d( )/dt denotes the time-derivative of the com- ◦ ◦ risk of any future outbreaks will originate from travelers. partment (˙) and N = S + E + I + R is the total population. ◦ On May 4, 2020 the Chief Medical Officer of the province Three parameters govern the transition from one compart- issued a Special Measures Order stating that the only peo- ment to the next: the contact rate β, the latency rate α, and ple allowed to enter the province were residents of New- the infectious rate γ. They are the inverses of the contact foundland and Labrador, asymptomatic workers, and those period B = 1/β, the latent period A = 1/α, and the infec- granted a permit due extenuating circumstances [31]. Since tious C = 1/γ. For simplicity, we assume that the latency 1 1 there is a limited number of entry points into Newfound- rate α = 1/2.5 days− and the infectious rate γ = 6.5 days− land, with three quarters of all travelers entering via air [26], are disease-specific for COVID-19, and constant in space passenger air travel is a good metric to assess the impact and time [19, 20, 33]. To account for societal and political of travel restrictions on the importation risk in Newfound- actions [39], we introduce a behavior specific dynamic con- land [15]. tact rate β = β(t) that varies both in space and time [22]. A relaxation of the travel ban naturally induces anxiety For easier interpretation, we express the contact rate, and fear of a new outbreak. From a public health perspective, the major challenges are (i) to understand the effect of the β(t) = R(t)γ , (2) travel bubble; (ii) to predict the effect of a wider opening to the rest of Canada and the United States; and (iii) to estimate in terms of the dynamic effective reproduction number R(t) the effect of imperfect quarantine assuming that a fraction [9], for which we make an ansatz of Gaussian random walk of travelers would ignore the guidelines for self-isolation. type [30] with a constant time-window of four days, Answering these questions will help to understand the short- R(t) = N(t; µ,τ). (3) and long-term effects of reopening. To explore whether and when it would be safe to lift Here N(t) is the time-varying Gaussian distribution, the travel ban, we model the dynamics of COVID-19 us- r ing a network approach that links a local epidemiological τ N(t) = exp( τ(R(t) µ)2/2), (4) model with air-traffic mobility [21]. Local epidemiological 2π − − modeling [17] is now a well-accepted approach to follow the dynamics of a homogeneous population during an epi- parameterized in terms of the drift µ and the daily stepwidth demic [13]. The extra network layers allow us to capture the τ = τ∗/[1.0 s], where τ∗ is the the step width precision − mobility between different local populations [22]. A unique and s is the associated smoothing parameter [23]. feature of this approach is that we can dynamically infer the parameters of the epidemiology model using reported case data [18,38] and update it in real time during the progression 2.2 Mobility modeling of the disease [23]. In addition, we can easily extract mobility data from passenger air travel statistic between the differ- We model each province, territory, and state of North Amer- ent locations [15]. Here use this approch to study three re- ica as a homogeneous population with its own local SEIR opening scenarios by gradually adding air traffic from (i) the dynamics and connect them to the province of Newfound- Atlantic Provinces; (ii) all of Canada; and (iii) all of North land and Labrador through a global mobility network [4]. America. From this mobility network, we create a weighted graph G in which the i = 1,..,n nodes N represent the individual provinces, territories, and states and the weighted edges E 2 Methods represent the mobility between them [11]. We approximate the weights of the edges using the average daily passenger 2.1 Epidemiology modeling air travel statistics [15], and summarize this information in the adjacency matrix Aij that reflects the travel frequency be- We model the local epidemiology of the COVID-19 out- tween two regions i and j, and in the degree matrix, break using an SEIR model [5, 29, 41, 42] with four com- n partments, the susceptible, exposed, infectious, and recov- Dii = diag∑j=1,j=i Aij , (5) ered populations, governed by the set of ordinary differential 6 equations, that reflects the number of incoming passengers for each region i. The difference between the degree matrix Dij and S˙ = β(t)SI/N the adjacency matrix A defines the weighted graph Lapla- − ij E˙ = +β(t)SI/N α E cian [21], − (1) I˙ = + α E γ I − R˙ = + γ I . Lij = Dij Aij . (6) − medRxiv preprint doi: https://doi.org/10.1101/2020.07.16.20155614; this version posted August 2, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license .

Is it safe to lift COVID-19 travel bans? The Newfoundland story. 3

For the province of Newfoundland and Labrador, the incom- 4n unknowns, ing and outgoing passenger air travel from and to other re- Is it safe to lift COVID-19 travel bans? The Newfoundland story.S˙ = ∑n L S β S I /N 3 gions is relatively similar and we can simply average the i − j=1 ij j − i i ˙ n two whichFor the results province in an of undirected Newfoundland graph andG Labrador,and symmetric the incom- 4n unknowns,Ei = ∑j=1 Lij Ej + β Si Ii/N α Ei − − (7) adjacencying and and outgoing Laplacian passenger matrices, airA travelij = fromAji and andL toij = otherLji. re- nn I˙S˙=i = ∑∑ LLij ISj β Si Ii/N + α E γ I Since wegions focus is relatively on the early similar phase and of we a resurgence, can simply average we only the i −− j=j=11 ij j − i − i ˙ nn simulatetwo the which mobility results into in an and undirected out of graph NewfoundlandG and symmetric and R˙iE=i = ∑∑j=1LLijijREjj + β Si Ii/N α Ei + γ Ii . −− j=1 − (7) Labradoradjacency and neglect and Laplacian the intraregional matrices, mobilityAij = Aji betweenand Lij = allLji. ˙ n Ii = ∑j=1 Lij Ij + α Ei γ Ii other regions.Since we This focus implies on the earlythat only phase a of single a resurgence, row and we col- only We discretize− the system of equations (7)− in time using n simulate the mobility into and out of Newfoundland and an explicitR˙i = Euler∑ forwardLij Rj time integration scheme+ γ Ii . and ap- umn of the adjacency matrix are populated, Ai1 = A1j = 0, − j=1 Labrador and neglect the intraregional mobility between6 all proximate the time derivatives as (˙)=[( ) (˙) ]/∆t, while all other entries are zero, Aij = 0 for all i,j = 1. Sim- We discretize the system of equations (7)n in+1 time usingn other regions. This implies that only a single6 row and col- ◦ ◦ − ◦ ilarly, only one entry of the degree matrix is populated, wherean explicit∆t denotes Euler that forward discrete time time integration step size. scheme and ap- umn of the adjacency matrix are populated, Ai1 = A1j = 0, D11 = 0, while all other entries are zero, Dii = 0 for all i = 1.6 proximate the time derivatives as (˙) = [( )n+1 (˙)n ]/∆t, 6 while all other entries are zero, Aij = 0 for all i,j = 1.6 Sim- ◦ ◦ − ◦ 6 where ∆t denotes that discrete time step size. ilarly, only one entry of the degree matrix is populated, 2.3 COVID-19 epidemiology and mobility data D = 0, while all other entries are zero, D = 0 for all i = 1. 11 6 ii 6 For2.3 the COVID-19 COVID-19 epidemiology epidemiology and data, mobility we draw data the COVID- 19 history of all 13 Canadian provinces and territories [2] andFor all the 51 COVID-19 United States epidemiology [34] from data, the we beginning draw the of COVID- the out- break19 history until July of all 1, 13 2020. Canadian From provinces these data, and weterritories extract [2] the and all 51 United States [34] from the beginning of the out- newly confirmed cases Iˆ(t) as the difference between today’s break until July 1, 2020. From these data, we extract the and yesterday’s reported cases and the cumulative confirmed newly confirmed cases Iˆ(t) as the difference between today’s ˆ ( ) casesandD yesterday’st as the reported sum of allcases reported and the cases cumulative to date. confirmed casesForD theˆ (t) mobilityas the sum data, of all we reported sample cases all North to date. American air trafficFor data the to mobility and from data, the we province sample all of North Newfoundland American air and Labradortraffic data and to use and a from 15-month the province period of before Newfoundland the COVID-19 and outbreak,Labrador from and use January a 15-month 1, 2019 period to March before 31, the 2020, COVID-19 to esti- mateoutbreak, the daily from air January traffic 1, [15]. 2019 Figure to March 2 illustrates 31, 2020, the to esti- aver- agemate daily the air daily traffic air to traffic and from[15]. FigureNewfoundland 2 illustrates and the Labrador average daily air traffic to and from Newfoundland and Labrador

Fig. 1 Mobility modeling. Discrete graphs GAP of the Atlantic Provinces (green), GCA of Canada (green and red), and GNA of North AmericaFig. (green, 1 Mobility red, and modeling. blue) withDiscrete n = 4, n graphs= 13, andGAP nof= 64 the nodes Atlantic Provinces (green), G of Canada (green and red), and G of North and e = n 1 edges that representCA the main travel routes to Newfound-NA America− (green, red, and blue) with n = 4, n = 13, and n = 64 nodes land andand Labrador. e = n 1 Dark edges blue that edges represent represent the main the travel connections routes to from Newfound- the Atlanticland Provinces, and Labrador.− light blue Dark edges blue edges from representthe other theCanadian connections provinces from the and territories,Atlantic and Provinces, red edges light from blue the edges United from States.the other Canadian provinces and territories, and red edges from the United States.

FigureFigure 1 illustrates 1 illustrates three three discrete discrete graphs graphs of the of the Atlantic Atlantic Provinces,Provinces, Canada, Canada, and North and North America. America. The The graph graph of ofthe the AtlanticAtlantic Provinces ProvincesGAP consistsGAP consists of n of= n4= nodes4 nodes and and e = e 3= 3 edges,edges, shown shown in dark in blue;dark blue; the graph the graph of Canada of CanadaGCAGCAcon-consists ofsists n = of13 n nodes= 13 nodes and e and= 12 e = edges12 edges shown shown in dark in dark and and average air traffic [people/day] light blue,light and blue, the and graph the graph of North of North America AmericaGNAGconsistsNA consists of of n = 64n nodes= 64 nodes and e and= 63 e = edges63 edges shown shown in dark in dark and and light light blue blue 0 100 and red.and We red. discretize We discretize our SEIR our SEIR model model on these on these weighted weighted Fig.Fig. 2 2 Average Average daily daily air air traffic traffic to and from from Newfoundland Newfoundland and and Labrador. Number of daily incoming and outgoing air passengers graphsgraphsG andG introduceand introduce the susceptible, the susceptible, exposed, exposed, infectious, infectious, Labrador. Number of daily incoming and outgoing air passengers fromfrom the the Canadian Canadian Provinces Provinces and and Territories Territories and and the the United United States States for for and recovered populations Si, Ei, Ii, and Ri as global depen- a 15-months period before the COVID-19 outbreak, from January 1, and recovered populations Si, Ei, Ii, and Ri as global depen- a 15-months period before the COVID-19 outbreak, from January 1, dent variables at the i = 1,...,n nodes of the graph. This re- 2019 to March 31, 2020, as reported by the International Air Transport dent variables at the i = 1,...,n nodes of the graph. This re- 2019 to March 31, 2020, as reported by the International Air Transport sults in a spatial discretization of the set of equations with Association [15]. sults in a spatial discretization of the set of equations with Association [15]. medRxiv preprint doi: https://doi.org/10.1101/2020.07.16.20155614; this version posted August 2, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license .

4 Kevin Linka et al. from all of North America. The locations with the largest To model the effect of perfect and imperfect quarantine, we mobility to and from the province are Ontario with 188/day, assume that a fraction νq of all incoming travelers fully sat- Quebec with 146/day, Alberta with 143/day, and Florida isﬁes a 14-day quarantine period, whereas [1 ν ] violate − q with 102/day, followed by New Jersey and British Columbia the quarantine conditions. We modulate the graph Lapla- both with 67/day, Nova Scotia with 41/day, Manitoba and cian, L = [1 ν ]L , by the fraction of travelers [1 ν ] ij∗ − q ij − q Texas both with 20/day. that violates the quarantine requirements and select different quarantine levels, νq = [0%,25%,50%,75%,95%]. For νq = 0%, none of the incoming travelers satisfy the quaran- 2.4 Bayesian inference tine requirements and all incoming exposed and infectious individuals mix instantaneously with the local population, Our dynamic SEIR model [22] introduces three parameters Lij∗ = Lij. For νq = 100%, all incoming travelers satisfy the for each territory, province, or state to characterize the indi- mandatory quarantine requirements, there is no quarantine vidual time-dependent effective reproduction numbers R(t), violation, and none of the incoming exposed and infectious individuals mix with the local population until they have ϑ = µ, τ∗, s , (8) { } fully recovered, Lij∗ = 0ij. We estimate the effects of both re- the drift µ, the stepwidth precision τ∗, and the smoothing opening scenarios on the COVID-19 outbreak dynamics in parameter s of our Gaussian random walk type ansatz (4). Newfoundland and Labrador for a 150-day period starting We estimate these model parameters using Bayesian infer- July 1, 2020. ence [1, 16, 27] with Markov Chain Monte Carlo sampling [21, 29]. Speciﬁcally, we adopt a Student’s t-distribution for the likelihood between the reported cumulative case 3 Results numbers Dˆ (t) and the simulated cumulative case numbers Outbreak dynamics of COVID-19 in North America. D(t,ϑ) = I(t) + R(t) with a case-number-dependent width, Figure 3 illustrates the outbreak dynamics of COVID-19 in

p(Dˆ (t) ϑ) StudentTν=4( mean = D(t,ϑ), the Atlantic Provinces, the other Canadian provinces and ter- | ∼ p (9) width = σ D(t,ϑ)). ritories, and the United States from the beginning of the outbreak until July 1, 2020. The top of each graph shows the Here σ represents the width of the likelihood p(Dˆ (t) ϑ) be- time-dependent effective reproduction number R(t) of our | tween the reported and simulated case numbers, Dˆ (t) and dynamic SEIR model according to equation (4) as red curve, D(t,ϑ). We apply Bayes’ rule the bottom shows the confirmed cases Dˆ (t) as dots and the model fit D(t) = I(t)+R(t) according to equations (1.3) and pDˆ (t) D(t,ϑ) p(ϑ) p(ϑ Dˆ (t)) = | . (10) (1.4) as orange curve. The solid lines represent the median | p Dˆ (t) values, the shaded areas highlight the 95% the confidence in- to obtain the posterior distribution of the parameters using tervals. Table 1 summarizes the outbreak dynamics on July the reported case numbers and selected prior distributions 1, 2020, the susceptible, exposed, infectious, and recovered using the NO-U-Turn sampler (NUTS) [14] implemented in populations S, E, I, R and the effective reproduction number the Python package PyMC3 [32]. For the prior distributions, Rt for all 64 locations. we select the drift µ Normal(0,2), the stepwidth precision Of most interest are the regional exposed and infectious ∼ τ Exponential (1/2), the smoothing parameter s Uni- populations E and I on the day of reopening, columns 4 and ∗ ∼ ∼ form(0,1), and the likelihood width σ HalfCauchy(β = 5 of Table 1, as they determine how rapidly the outbreak will ∼ 1). We report the resulting effective reproduction number travel into Newfoundland and Labrador. The exposed pop- R(t) and the reported cases Dˆ (t) and and simulated cases ulation on July 1, 2020 was largest in Florida with 0.134%, D(t) = I(t)+R(t) for each territory, province, and state from Arizona with 0.115%, South Carolina with 0.091%, Nevada the early outbreak on March 15 until July 1, 2020. with 0.088%, and Texas with 0.065%. The infectious population on July 1, 2020 was largest in Arizona with 0.252%, Florida with 0.187%, South Carolina with 0.158%, Nevada 2.5 Reopening forecast with 0.124%, and Texas with 0.118%. For comparison, no Canadian province or territory had an exposed or infectious We explore two reopening scenarios, partial and total air- population larger than 0.011%. port reopening, with perfect and imperfect quarantine con- Another important variable to estimate the effect of the ditions. To model the effect of partial and total reopen- incoming exposed and infectious individuals is the effective ing, we allow travel within the Atlantic Provinces using reproduction number R(t) on the day of reopening, column 7 the graph GAP, within Canada using the graph GCA, and of Table 1, since this number determines how fast the virus within North America using the graph GNA from Figure 1. will replicate locally within Newfoundland and Labrador. medRxiv preprint doi: https://doi.org/10.1101/2020.07.16.20155614; this version posted August 2, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license .

Is it safe to lift COVID-19 travel bans? The Newfoundland story. 5

Atlantic Provinces

Other Canadian Provinces

United States

Fig. 3 Outbreak dynamics of COVID-19 in the Atlantic Provinces, all other Canadian provinces, and the United States. Effective reproduction number (red), confirmed cases (dots) [2,34], and model fit (orange) from the beginning of the outbreak until July 1, 2020. Solid lines represent the median values, shaded areas highlight the 95% confidence intervals. medRxiv preprint doi: https://doi.org/10.1101/2020.07.16.20155614; this version posted August 2, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license .

6 Kevin Linka et al.

Table 1 Outbreak dynamics of COVID-19 in the Atlantic Provinces, all other Canadian provinces, and the United States. Susceptible, exposed, infectious, and recovered populations S, E, I and R, and effective reproduction number Rt on July 1, 2020 inferred from reported case numbers [2, 34], and air passengers before the COVID-19 outbreak, from January 1, 2019 to March 31, 2020 [15]; n.d. indicates Rt not deﬁned.

Atlantic Provinces Population S E I R Rt Air Passengers Newfoundland and Labrador 519716 0.99948 0.00000 0.00000 0.00052 n.d. – New Brunswick 747101 0.99979 0.00000 0.00000 0.00021 n.d. 30621 Nova Scotia 923598 0.99880 0.00000 0.00001 0.00119 n.d. 18523 Prince Edward Island 142907 0.99980 0.00000 0.00000 0.00020 n.d. 6509

Other Canadian Provinces Population S E I R Rt Air Passengers Alberta 4067175 0.99797 0.00004 0.00007 0.00192 1.31198 65048 British Columbia 4648055 0.99937 0.00001 0.00002 0.00061 1.08524 30608 Manitoba 1278365 0.99975 0.00000 0.00000 0.00025 n.d. 9098 Northwest Territories 41786 0.99987 0.00000 0.00000 0.00013 n.d. 2277 Nunavut 35944 1.00000 0.00000 0.00000 0.00000 n.d. 1020 Ontario 13448494 0.99725 0.00003 0.00008 0.00264 0.32863 85504 Quebec 8164361 0.99308 0.00003 0.00011 0.00678 n.d. 66545 Saskatchewan 1098352 0.99927 0.00001 0.00004 0.00068 0.43724 6180 Yukon 35874 0.99968 0.00000 0.00000 0.00032 n.d. 406

United States Population S E I R Rt Air Passengers Alabama 4903185 0.99164 0.00059 0.00116 0.00660 1.26937 98 Alaska 731545 0.99833 0.00013 0.00025 0.00129 1.27325 252 Arizona 7278717 0.98796 0.00115 0.00252 0.00836 1.08640 1753 Arkansas 3017825 0.99273 0.00038 0.00115 0.00574 0.57118 12 California 39512223 0.99366 0.00049 0.00089 0.00496 1.44335 4441 Colorado 5758736 0.99418 0.00014 0.00028 0.00541 1.22445 634 Connecticut 3565287 0.98688 0.00005 0.00017 0.01289 0.11798 195 Delaware 973764 0.98790 0.00035 0.00055 0.01121 1.80054 0 District of Columbia 705749 0.98531 0.00010 0.00030 0.01429 0.10039 1592 Florida 21477737 0.99145 0.00134 0.00187 0.00534 2.15466 46656 Georgia 10617423 0.99214 0.00060 0.00099 0.00627 1.63627 1347 Hawaii 1415872 0.99934 0.00003 0.00005 0.00058 1.33847 1073 Idaho 1792065 0.99611 0.00048 0.00074 0.00267 1.81372 37 Illinois 12671821 0.98848 0.00013 0.00035 0.01104 0.79747 1374 Indiana 6732219 0.99290 0.00016 0.00036 0.00659 1.03362 354 Iowa 3155070 0.99048 0.00027 0.00071 0.00854 0.79137 60 Kansas 2913314 0.99462 0.00033 0.00055 0.00450 1.68635 83 Kentucky 4467673 0.99629 0.00015 0.00031 0.00325 1.15865 510 Louisiana 4648794 0.98688 0.00061 0.00116 0.01136 1.33347 1790 Maine 1344212 0.99750 0.00008 0.00016 0.00226 1.29048 72 Maryland 6045680 0.98859 0.00014 0.00040 0.01086 0.76133 427 Massachusetts 6949503 0.98420 0.00007 0.00023 0.01550 n.d. 5534 Michigan 9986857 0.99290 0.00005 0.00017 0.00688 n.d. 946 Minnesota 5639632 0.99338 0.00019 0.00044 0.00599 0.96952 725 Mississippi 2976149 0.99033 0.00052 0.00117 0.00797 1.01498 87 Missouri 6137428 0.99614 0.00023 0.00043 0.00320 1.43212 726 Montana 1068778 0.99900 0.00011 0.00016 0.00073 1.87814 60 Nebraska 1934408 0.98986 0.00021 0.00052 0.00940 0.92765 61 Nevada 3080156 0.99304 0.00088 0.00124 0.00484 2.10005 5779 New Hampshire 1359711 0.99573 0.00004 0.00012 0.00411 0.62427 6 New Jersey 8882190 0.98026 0.00017 0.00035 0.01922 1.20830 1989 New Mexico 2096829 0.99391 0.00028 0.00054 0.00527 1.31363 71 New York 19453561 0.97946 0.00007 0.00021 0.02026 0.78300 7562 North Carolina 10488084 0.99340 0.00040 0.00085 0.00535 1.12729 1515 North Dakota 762062 0.99515 0.00015 0.00029 0.00441 1.30264 88 Ohio 11689100 0.99536 0.00020 0.00041 0.00403 1.20717 548 Oklahoma 3956971 0.99628 0.00026 0.00057 0.00290 1.06800 282 Oregon 4217737 0.99779 0.00014 0.00030 0.00177 1.17868 327 Pennsylvania 12801989 0.99276 0.00013 0.00027 0.00685 1.19329 1814 Rhode Island 1059361 0.98407 0.00009 0.00027 0.01557 0.10155 145 South Carolina 5148714 0.99202 0.00091 0.00158 0.00548 1.55259 920 South Dakota 884659 0.99219 0.00015 0.00042 0.00724 0.80479 65 Tennessee 6833174 0.99344 0.00036 0.00078 0.00542 1.06544 2807 Texas 28995881 0.99362 0.00065 0.00118 0.00455 1.41288 8915 Utah 3205958 0.99250 0.00052 0.00106 0.00592 1.21308 260 Vermont 623989 0.99810 0.00001 0.00003 0.00186 n.d. 10 Virginia 8535519 0.99250 0.00016 0.00041 0.00694 0.85318 483 Washington 7614893 0.99557 0.00011 0.00030 0.00401 0.90306 767 West Virginia 1787147 0.99831 0.00006 0.00015 0.00148 1.03586 10 Wisconsin 5822434 0.99428 0.00027 0.00052 0.00493 1.31016 353 Wyoming 578759 0.99727 0.00016 0.00033 0.00224 1.17731 3 medRxiv preprint doi: https://doi.org/10.1101/2020.07.16.20155614; this version posted August 2, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license .

IsIs it safeit safeIs to it to safe lift lift COVID-19 to COVID-19 lift COVID-19 travel travel travel bans? bans? The The Newfoundland NewfoundlandThe Newfoundland story. story. story. 7 7 7

estimatedestimated incoming incoming exposed exposed travelers travelers [people/day] [people/day] [-] [-] estimatedestimated incoming incoming infectious infectious travelers travelers [people/day] [people/day] 0.000.00 0.14 0.14 0.000.00 0.19 0.19 Fig.Fig. 4 4Fig. Estimated Estimated 4 Estimated COVID-19 COVID-19 COVID-19 exposed exposed exposed travelers travelers to to Newfoundland Newfoundland to NewfoundlandFig.Fig. 5Fig. Estimated5 5 Estimated Estimated COVID-19 COVID-19 COVID-19 infectious infectious travelers travelers travelers to Newfoundland to to Newfoundland Newfoundland and Labrador. Number of daily incoming air passengers from Canada and Labrador. Number of daily incoming air passengers from the andand Labrador. Labrador.NumberNumber of of daily daily incoming air air passengers passengers from from Canada Canada andand Labrador. Labrador.NumberNumber of daily of daily incoming incoming air passengers air passengers from the from the and theand United the United States States that have that havebeen been exposed exposed to COVID-19. to COVID-19. The es- The es-CanadianCanadianCanadian provinces provinces provinces and andterritories and territories territories and the and United the the United United States States States that are that that in- are are in- in- and thetimate United assumes States averagethat have daily been travel exposed from to Figure COVID-19. 2 and the The outbreak es- fectious with COVID-19 assuming average daily travel from Figure 2 timatetimate assumes assumes average average daily daily travel travel from from Figure Figure 2 2 and and the the outbreak outbreak fectiousfectious with with COVID-19 COVID-19 assuming assuming average average daily traveldaily travelfrom Figure from Figure 2 2 dynamicsdynamics from fromFigure Figure 3 as of 3 asJuly of 1, July 2020. 1, 2020. and theand outbreak the outbreak dynamics dynamics from from Figure Figure 3 as of 3 as July of 1, July 2020. 1, 2020. dynamics from Figure 3 as of July 1, 2020. and the outbreak dynamics from Figure 3 as of July 1, 2020.

resume with the outbreak dynamics of July 1, 2020, the es- TheThe effective effective reproduction reproduction number number on July on July 1, 2020 1, 2020 was wasresume with the outbreak dynamics of July 1, 2020, the es- timatedtimated number number of of incoming incoming exposed and and infectious infectious traveltravel- Thelargest effectivelargest in Florida in reproduction Florida with with 2.15, number 2.15, Nevada Nevada on with July with 2.10, 1, 2.10, Montana2020 Montana was timated number of incoming exposed and infectious travel- ersers would would be be 0.203/day 0.203/day and and 0.329/day, suggesting suggesting that that every every largestwithwith 1.88, in Florida1.88, Idaho Idaho with with with 1.81, 2.15, 1.81, and Nevada Delawareand Delaware with with 2.10, with 1.80.1.80. Montana Of the Of theers would be 0.203/day and 0.329/day, suggesting that every fivefive days, days, an an exposed exposed traveler, traveler, and every every three three days, days, an an in- in- withCanadian 1.88,Canadian Idaho provinces provinces with and 1.81, territories, and and territories, Delaware it was it onlywas with only defined 1.80. defined in Of Al- inthe Al-five days, an exposed traveler, and every three days, an in- fectiousfectious traveler traveler would would enter enter the province province of of Newfoundland Newfoundland Canadianbertaberta with provinces with 1.31, 1.31, British and British territories, Columbia Columbia with it was with 1.09, only 1.09, Saskatchewan defined Saskatchewan in Al- fectious traveler would enter the province of Newfoundland andand Labrador Labrador via via air air travel. travel. bertawith withwith 0.44, 1.31,0.44, and Ontario and British Ontario with Columbia with 0.33. 0.33. The with Thenumber 1.09, number Saskatchewanof new of new cases casesand Labrador via air travel. was zero, or too low to calculate a meaningful effective re- withwas 0.44, zero, and or too Ontario low to with calculate 0.33. a The meaningful number effective of new cases re- OutbreakOutbreakOutbreak dynamics dynamics dynamics of COVID-19 of of COVID-19 COVID-19 in Newfoundland in in Newfoundland Newfoundland and and and production number, in Newfoundland and Labrador, New wasproduction zero, or number,too low toin calculateNewfoundland a meaningful and Labrador, effective New re- Labrador.Labrador.Labrador.FiguresFiguresFigures 6 and 6 6 and and 7 highlight 7 highlight the timelinethe the timeline timeline of the of of the the Brunswick, Nova Scotia, Prince Edward Island, Manitoba, productionBrunswick, number, Nova Scotia, in Newfoundland Prince Edward and Island, Labrador, Manitoba, New COVID-19COVID-19COVID-19 outbreak outbreak outbreak in Newfoundland in in Newfoundland and and Labrador. and Labrador. Labrador. The The The the Northwest Territories, Nunavut, Quebec, and Yukon. Brunswick,the Northwest Nova Territories, Scotia, Prince Nunavut, Edward Quebec, Island, and Manitoba, Yukon. graphsgraphsgraphs distinguish distinguish distinguish between between between three three time time time intervals: intervals: intervals: the first the the first pe- first pe- pe- This is why we use the population weighted mean effec- theThis Northwest is why we Territories, use the population Nunavut, weighted Quebec, mean andeffec- Yukon. riodriodriod without without without travel travel travel restrictions restrictions restrictions from from from March March March 15 until 15 15 until May until May 4, May 4, 4, tive reproductiontive reproduction number number for Canada, for Canada, 1.16 1.160.17,0.17, and forand for 2020, the second period with travel restrictions from May This is why we use the population weighted± ± mean effec- 2020,2020, the the second second period period with with travel travel restrictions restrictions from fromMay May NorthNorth America, America, 1.35 1.350.330.33 for the for reopening the reopening forecast forecast in in 4 until July 1, 2020, and the third period upon gradual re- tive reproduction number± for± Canada, 1.16 0.17, and for 4 until4 until July July 1, 2020, 1, 2020, and and the thirdthe third period period upon upon gradual gradual re- re- NewfoundlandNewfoundland and Labrador. and Labrador. ± opening from July 1, 2020 forward. The graphs report the North America, 1.35 0.33 for the reopening forecast in opening from July 1, 2020 forward. The graphs report the ± openingdaily new from cases July and 1, total 2020 cases forward. as dots, The compared graphs toreport the fit the NewfoundlandEstimatedEstimated COVID-19 and COVID-19 Labrador. exposed exposed and and infectious infectious travelers. travelers.daily new cases and total cases as dots, compared to the fit dailyof the new SEIR cases model and totalas solid cases orange as dots, curves, compared from the to early the fit FiguresFigures 4 and 4 and5 illustrate 5 illustrate the daily the daily number number of incoming of incomingof the SEIR model as solid orange curves, from the early ofoutbreak the SEIR on model from March as solid 15 orangeuntil July curves, 1, 2020. from From the then early Estimatedexposedexposed and COVID-19 andinfectious infectious exposed travelers travelers and to the to infectious province the province oftravelers. New- of New-outbreak on from March 15 until July 1, 2020. From then outbreakon, the dashed on from lines March highlight 15 until the reopeningJuly 1, 2020. forecast From for then a Figuresfoundlandfoundland 4 and and5and Labrador. illustrate Labrador. The the The number daily number number of exposed of exposed of incoming and and in- in-on, the dashed lines highlight the reopening forecast for a on,60-day the dashed period. lines The solid highlight and dashed the reopening lines represent forecast the me- for a exposedfectiousfectious and air passengers infectious air passengers from travelers from Canada Canada to theand provincetheand United the United of States New- States60-day period. The solid and dashed lines represent the me- 60-daydian values, period. the The shaded solid areas and highlight dashed lines their represent 95% confidence the me- foundlandis a reflectionis a reflection and of Labrador. both of both the The frequency the frequency number of air of of travel exposed air travel from and from Fig- in- Fig-dian values, the shaded areas highlight their 95% confidence dianintervals. values, the shaded areas highlight their 95% confidence fectiousure 2ure and air 2theand passengers local the local outbreak from outbreak Canada dynamics dynamics and from the from Figure United Figure 3 States and 3 andintervals. isTable a reflectionTable 1. Figure 1. ofFigure4 both shows 4 the shows that frequency thatmost most exposed of exposed air travel travelers travelers from come Fig- come intervals.FigureFigure 6 explores 6 explores the effect the effect of quarantine of quarantine upon upon reopen- reopen- urefrom 2from and Florida the Florida with local with 0.137/day, outbreak 0.137/day, Texas dynamics Texas with with 0.013/day, from 0.013/day, Figure Nevada 3 Nevada and ing:ing: allFigure incoming all incoming 6 explores travelers travelers the quarantining effect quarantining of quarantine to 100% to 100% upon in dark in reopen- dark Tablewithwith 1. 0.011/day, Figure 0.011/day, 4 Alberta shows Alberta andthat andOntario most Ontario exposed both both with travelers with 0.005/day. 0.005/day. come blue,ing:blue, to all 50% to incoming 50% in light in light blue,travelers blue, andand quarantining0% in0% red. in red. While to While 100% a 100% a 100%in dark Figure 5 shows that most infectious travelers come from quarantine does not result in any new cases, 50% quarantine fromFigure Florida 5 shows with that 0.137/day, most infectious Texas with travelers 0.013/day, come Nevada from quarantineblue, to does 50% not in result light in blue, any andnew cases,0% in 50% red. quarantine While a 100% Florida with 0.192/day, Texas with 0.023/day, Nevada, Que- results in a mild but notable increase of new cases, and 0% withFlorida 0.011/day, with 0.192/day, Alberta Texas and Ontariowith 0.023/day, both with Nevada, 0.005/day. Que- resultsquarantine in a mild does but not notable result increase in any new of new cases, cases, 50% and quarantine 0% bec, and Ontario all with 0.016/day. If air traffic would fully quarantine triggers a rapid exponential outbreak. Figure 7 Figurebec, and 5 shows Ontario that all with most 0.016/day. infectious If air travelers traffic would come fully from quarantineresults in triggers a mild a but rapid notable exponential increase outbreak. of new cases,Figure and 7 0% Florida with 0.192/day, Texas with 0.023/day, Nevada, Que- quarantine triggers a rapid exponential outbreak. Figure 7 bec, and Ontario all with 0.016/day. If air traffic would fully explores the effect of restricted travel under the assump- resume with the outbreak dynamics of July 1, 2020, the es- tion of no quarantine: air traffic only between the Atlantic 600600

medRxiv preprint doi: https://doi.org/10.1101/2020.07.16.20155614; this version posted August 2, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license . no travel restrictions travel restrictions reopening forecast predicted new cases predicted predicted new cases predicted NorthNorth America America no travel restrictions travel restrictions reopening forecast no travel restrictions travel restrictions reopeningCanadaCanada forecast 8 Kevin Linka et al. no travel restrictions travel restrictions reopening forecast 8 0 KevinAtlanticAtlantic Linka Provinces Provinces et al. 500 0 July Aug Sept Oct Nov 25July Aug Sept Oct Nov no travel restrictions travel restrictions reopening forecast no travel restrictions travel restrictions reopening forecast 600600 0.1%0.1% of of population population 500 25 reported cases SEIR model reported cases

total cases total 0% quarantine SEIR model new cases 50% quarantine reportedNorth Americacases 100%0%0% quarantine quarantine quarantine SEIRCanada model 25%25% quarantine quarantine reported cases Atlantic Provinces

predicted new cases predicted 50% quarantine

total cases total 0% quarantine SEIR model 0 0 75%75% quarantine quarantine

daily new cases 50% quarantine North America Apr May June July 100% quarantineAug Apr May June July 95%95% quarantine quarantineAug Canada 00 Atlantic Provinces JulyJuly AugAug SeptSept OctOct NovNov 0 0 no travel restrictions travel restrictions reopening forecast Apr May June July Aug Apr May June July Aug Fig.Fig. 8 8 Effect Effect of of quarantine quarantine on on COVID-19 COVID-19 in in Newfoundland Newfoundland and and Labrador.Labrador.ReopeningReopening forecast forecast for for 150-day 150-day period period with with incoming incoming trav- trav- no travel restrictions travel restrictions reopening forecast no travel restrictions travel restrictions reopening forecast elerselers quarantining quarantining from from 95% 95% (blue) (blue) to to 0% 0% (red). (red). Predictions Predictions are are based based 500 onon a a local local SEIR SEIR model model with with incoming incoming air air trafﬁc trafﬁc from from all all of of North North AmericaAmerica using using the the mean mean effective effective reproduction reproduction number number of ofRRt t==11.35.35 no travel restrictions travel restrictions reopening forecast forfor all all of of North North America America (solid (solid lines) lines) and andRRtt==11.16.16 for for Canada Canada (dashed (dashed 500 lines).lines). The The black black horizontal horizontal line line marks marks 0.1% 0.1% of of the the population population of of New- New- foundlandfoundland and and Labrador. Labrador.

reported cases total cases total SEIR model tions, an opening to all of North America would trigger a 0% quarantine Effects of quarantine and restricted travel. Figures 8 and 50% quarantine rapid exponential outbreak. reported cases 9 summarize the effects of quarantine and restricted travel total cases total 100% quarantine SEIR model 0 Effectson the numberof quarantine of COVID-19 and restricted cases in travel. NewfoundlandFigures 8 and and 0% quarantine Apr May June July Aug 50% quarantine 9Labrador summarize for thea 150-day effects periodof quarantine as predicted and restricted by our reopen- travel 100% quarantine ing forecast. The solid and dashed lines show the reopening 0 Fig. 6 Outbreak dynamics of COVID-19 in Newfoundland and and on the number of COVID-19 cases in Newfoundland and Labrador and the effect of quarantine. Daily new cases and total Apr May June July Aug Labrador and the effect of quarantine. Daily new cases and total Labradorforecast with for aincoming 150-day travelers period as quarantining predicted by at our varying reopen- per- cases with model ﬁt for periods without travel travel restrictions restrictions and and with with ingcentages forecast. and The with solid travel and restricted dashed linesto the show Atlantic the reopening Provinces, travel restrictions. Reopening forecast for 60-day period with all in- travel restrictions. Reopening forecast for 60-day period with all in- Canada, and all of North America. The predictions use the coming travelers quarantining to 100% (dark blue), blue), 50% 50% (light (light blue), blue), forecast with incoming travelers quarantining at varying per- and 0% (red). Solid and dashed lines represent the the median median values, values, centagesmean effective and with reproduction travel restricted numbers to the of AtlanticRt = 1.35 Provinces, for all of shadedno areas travel highlight restrictions the 95%traveltravel conﬁdence restrictionsrestrictions intervals. intervals.reopeningreopening forecastforecast Canada,North America and all ofand NorthRt = America.1.16 for Canada. The predictions The black use hori- the meanzontal effective lines mark reproduction 520 predicted numbers cases ofcorrespondingRt = 1.35 for to all 0.1% of no travel restrictions travel restrictionsrestrictions reopeningreopening forecastforecast Northof the America populationnono travel travel restrictions restrictions and ofR Newfoundlandt = 1travel.travel16 forrestrictions restrictions Canada. and Labrador. Thereopeningreopening black Tableforecast forecast hori- 2 500 zontalsummarizes lines mark the 520 dates predicted and number cases corresponding of days by which to 0.1% the ofcurves the2525 population cross this lineof Newfoundland and the number and of Labrador. COVID-19 Table cases 2 summarizesreaches 0.1% the of the dates population. and number Our ofsimulation days by predicts which thethat curvesthis will cross occur this after line only andthe 37 or number 38 days of COVID-19without travel cases re- reported cases reachesstrictions 0.1% and of no the quarantine. population. Quarantining Our simulation onlyreported predicts half cases of that the SEIRSEIR model model reportedreported casescases

total cases total 0% quarantine thisincoming willnew cases occur population after only increases 38 or this 39 days time periodwithout to travel 44 or re- 46 total cases total 0% quarantine SEIRSEIR modelmodel new cases 50% quarantine North America 50% quarantine North America 100%100% quarantine quarantine CanadaCanada AtlanticAtlantic ProvincesProvinces 0 TableTable00 2 2 Effects Effects of of quarantine quarantine and and restricted restricted travel travel on on COVID-19 COVID-19 dynamics in Newfoundland and Labrador. The dates and days mark Apr May JuneJune JulyJuly AugAug dynamics in NewfoundlandAprApr MayMay and Labrador.JuneJune TheJulyJuly dates andAug daysAug mark thethe time time point point at at which which the the number number of of cases cases reaches reaches 0.1% 0.1% of of the the pop- pop- Fig. 7 Outbreak dynamics of COVID-19 in Newfoundland and ulation. Simulations use the mean effective reproduction numbers of Fig. 7no Outbreak travel restrictions dynamicstraveltravel of restrictions COVID-19restrictions in Newfoundlandreopeningreopening forecastforecast and ulation. Simulations use the mean effective reproduction numbers of Labrador and the effect of restricted travel. Total cases with model North America and Canada of R = 1.35 and R = 1.16 for the predici- Labrador and the effect of restricted travel. Total cases with model North America and Canada of Rtt = 1.35 and Rt t = 1.16 for the predici- fit for periods without travel restrictions and with travel travel restrictions. restrictions. ton.ton. Reopeningno travel forecast restrictions for 60-daytravel period restrictionsrestrictions with mobilityreopeningreopening only only forecastforecast within within the the Atlantic Provinces (dark blue), all of Canadian (light blue), and all of traveltravel from from RtRt = = 1.35 1.35 RtRt = = 1.16 1.16 Atlantic500 Provinces (dark blue), all of Canadian (light blue), and all of North America date days date days North America (red). Solid and dashed lines represent the the median median val- val- North America date days date days 0% quarantine 08/07/2020 37 08/08/2020 38 ues, shaded areas highlight the 95% confidence intervals. intervals. 0% quarantine 08/07/2020 37 08/08/2020 38 25%25% quarantine quarantine 08/10/202008/10/2020 4040 08/11/202008/11/2020 4141 50%50% quarantine quarantine 08/14/202008/14/2020 4444 08/16/202008/16/2020 4646 75% quarantine 08/22/2020 52 08/25/2020 55 explores the effect of restricted travel under the assump- 75% quarantine 08/22/2020 52 08/25/2020 55 Provinces in dark blue, between all of Canadareported in light cases blue, 95%95% quarantine quarantine 09/16/202009/16/2020 7777 09/28/202009/28/2020 8989 total cases total reported cases andtion cases total between of no quarantine: all of North air America traffic only in red. between WhileSEIR the anmodel Atlantic opening SEIR model traveltravel at at RtRt = = 1.35 1.35 RtRt = = 1.16 1.16 0% quarantine Provinces in dark blue, between all of Canada in0% lightquarantine blue, 0% quarantine date days date days to the Atlantic Provinces and to all of Canada does50% quarantine not result 0% quarantine date days date days and between all of North America in red. While50% an quarantine opening in a notable number of new cases, under the100% current quarantine condi- NorthNorth America America 08/07/202008/07/2020 3737 08/08/202008/08/2020 3838 0 100% quarantine tions,to0 the Atlantic an opening Provinces to all ofand North to all Americaof Canada would does not trigger result a CanadaCanada 10/04/202010/04/2020 9595 11/01/202011/01/2020 123123 Apr May June July Aug Atlantic Provinces 10/08/2020 99 11/06/2020 128 rapidin a notable exponentialApr number outbreak.May of newJune cases, underJuly the currentAug condi- Atlantic Provinces 10/08/2020 99 11/06/2020 128 medRxiv preprint doi: https://doi.org/10.1101/2020.07.16.20155614; this version posted August 2, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license .

Is it safe to lift COVID-19 travel bans? The Newfoundland story. 9

600 pandemic and it is critical to dynamically adjust the reopening strategy. Before the travel restrictions were announced on May 4, 2020, the seven-day average of new cases was 1717.0 for Canada with 1091.6 and 438.1 cases originat- ing from the two largest provinces, Quebec and Ontario. By July 1, 2020, these seven-day averages had fallen to 311.1

predicted new cases predicted North America for Canada, 83.9 for Quebec, and 171.6 for Ontario [6]. In Canada the Atlantic Provinces, the infection rate has remained low Atlantic Provinces 0 throughout the entire period, except for Nova Scotia that had July Aug Sept Oct Nov a seven-day average of 12.1 on May 4, 2020 which dropped Fig.600 9 Effect of restricted travel on COVID-19 in Newfoundland 0.1% of population to 0.3 by July 1, 2020 [6]. Figure 3 provides a side-by-side and Labrador. Reopening forecast for 150-day period with incoming travelers from Atlantic Provinces, Canada, and all of North Amer- comparison of these individual case trajectories. Unlike the ica with no quarantine requirements. Predictions are based on a local United States, the Canadian provinces and territories display SEIR model with incoming air trafﬁc from all of North America using a clear trend towards slowing the spread of new cases [2]. the mean effective reproduction numbers of R = 1.35 for all of North t 0% quarantine Notably, all Atlantic Provinces have managed to maintain America (solid lines) and Rt = 1.16 for Canada (dashed25% quarantine lines). The black horizontal line marks 0.1% of the population of Newfoundland community transmission at a minimum.

predicted new cases predicted 50% quarantine and Labrador. 75% quarantine An important piece of information in predicting the ef- 95% quarantine 0 fects of partial and total reopening is the daily count of July Aug Sept Oct Nov days, quarantining 95% of the incoming population to 77 incoming exposed and infectious travelers. We estimate and 89 days. Limiting travel within Canada increases this these populations using our network epidemiology model time period to 95 and 123 days, limiting it within only the for North America, calibrated with the reported case data Atlantic Provinces to 99 and 128 days. for all Canadian provinces and territories [2] and all United States [34], and multiply these numbers with the daily travel data for each region [15]. Table 1 summarizes this informa- 4 Discussion tion as of July 1, 2020 and Figures 4 and 5 illustrate the estimated number of incoming exposed and infectious trav- Two interacting features determine the outbreak dynamics elers per day. These contour plots allow us to quickly iden- of the COVID-19 pandemic: the local epidemiology of the tify critical regions like Florida, from which 0.137 exposed disease and the global mobility of diseased individuals [22]. and 0.192 infectious individuals would enter Newfoundland Reducing mobility is a controversial but highly effective and Labrador every day. They also suggest that it is safe to measure to manage the outbreak dynamics [40]. Early in open travel within the Atlantic Provinces, New Brunswick, the pandemic, many countries have implemented travel re- Nova Scotia, and Prince Edward Island, and reasonably safe strictions to reduce the number of infectious individuals that to open travel within Canada. While the travel frequency travel into the country from the outside [4]. In parallel, they within the Atlantic Provinces and Canada is high as we can have managed the local epidemiology by reducing contacts see in Figure 2, the current case numbers in these regions are through limiting large gatherings, closing schools, or imple- low enough to keep the risk of opening low. The opposite is menting total lockdowns [10]. Some regions, mostly smaller true for states like California, with a low travel frequency states or provinces, have successfully managed to reduce the but high case numbers, which suggests that opening travel number of current cases to zero. One of those provinces is within all of North America would expose Newfoundland the Canadian province of Newfoundland and Labrador [2]. and Labrador to a disproportionally high risk. Obviously, the most effective way to prevent a future An interesting metric is the estimated number of incom- outbreak would be to keep isolating these healthy regions ing exposed and infectious travelers upon full reopening, from the outside world. The freedom of movement and eco- 0.203/day and 0.329/day. This suggests that every ﬁve days nomic constraints are probably the two strongest arguments and every three days, an exposed and an infectious traveler for reopening [25]. Numerous different reopening strategies would enter the province of Newfoundland and Labrador. In have been proposed, but not all of them seem equally ade- other words every other day, a new COVID-19 case would quate for smaller provinces and states. Here we explore two enter the Newfoundland and Labrador via air travel. Since complementary exit strategies: partial reopening and quar- the exposed and early infectious individuals are still pre- antine. We use the example of Newfoundland and Labrador symptomatic, it is impossible to identify and isolate them to forecast the local outbreak dynamics for a region that has without strict quarantine requirements [12]. To estimate the not seen any new cases for more than two months. precise effects of quarantine and restricted travel, Figures The disease conditions outside Newfoundland and 6 and 7 show our reopening forecast for a 60-day window Labrador change continuously throughout the course of the starting on July 1, 2020. The forecast conﬁrms our intuition medRxiv preprint doi: https://doi.org/10.1101/2020.07.16.20155614; this version posted August 2, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license .

10 Kevin Linka et al. that there are two strategies to prevent a new outbreak, either reproduction number of all states, provinces, and territories mandating strict quarantine requirements or limited travel remains constant at its July 1, 2020 level. Since this num- within the Atlantic Bubble. The increasingly wide 95% con- ber reflects both social behavior and personal interaction [7], fidence intervals for more relaxed conditions suggest that re- this is a strong limitation. Yet, it seems reasonable to antic- liable predictions become difficult beyond this time window ipate that the current North American mean of Rt = 1.36 and case numbers could very well increase beyond control represents an upper limit for our prediction in the sparsely within only a few weeks. populated province of Newfoundland and Labrador. Third, To estimate the time window beyond which the new we have assumed that the fraction of exposed and infectious COVID-19 case numbers would exceed 0.1% of the pop- travelers to Newfoundland and Labrador is similar to the ex- ulation, we perform a forward analysis using the data from posed and infected fractions at the locations of origin. Nat- Table 1 as initial condition and assuming that the exposed urally, we would assume that truly sick individuals are less and infectious groups maintain their current status quo for likely to travel, a behavioral effect, which we could include all regions except for the province of Newfoundland and using agent-based modeling. Fourth, our mobility forecast Labrador. Figures 8 and 9 show the effects of quarantine assumes that air traffic fully resumes at its 150-day mean and restricted travel for two different effective reproduction before the outbreak of the pandemic [15]. With people be- numbers that reflect the population-weighted mean across ing less likely to travel in the wake of a global pandemic, all of North America and across Canada. As such, both Fig- this estimate might rather represent an upper bound than the ures showcase the effects of local epidemiology and global true case scenario upon reopening. Fifth, our current model mobility: The differences between the solid and dashed does not include seasonality, which could play a critical role, curves of the same color are a result of the different re- both in the local disease dynamics and in the global mo- production numbers, Rt = 1.35 for solid and Rt = 1.16 bility pattern. While we can only estimate the seasonality for dashed, associated with new internal cases from within of the disease, we could certainly include the known eco- Newfoundland and Labrador [8]; the differences between all nomical factors of seasonal fishing and tourism to include solid curves and all dashed curves are a result of varying the seasonality of mobility. Sixth, our study uses an SEIR mobility, associated with new external cases traveling into model with fixed latency and infectious rates α and γ. Us- Newfoundland and Labrador [4]. From the intersection of ing a more complex epidemiology model [42] or inferring these curves with the black dashed lines, we can estimate the the rate constants from the reported case data could certainly dates and number of days by which the number of COVID- improve the fit and make the predictions more accurate. 19 cases reaches 0.1% of the population, which we summa- Probable even more importantly, the epidemiology model rize in Table 2. At full reopening, without travel restrictions we have used in this study does not include asymptomatic and no quarantine, this will occur after only 37 or 38 days. individuals. Asymptomatic transmission plays an important Quarantining only half of the incoming population increases role in spreading COVID-19 [30]. Once seroprevalence data this time period to 44 or 46 days, quarantining 95% of the in- become available for the province of Newfoundland and coming population to 77 and 89 days. Limiting travel within Labrador, we could include this information and make more Canada increases this time period to 95 and 123 days, limit- accurate predictions about individuals that travel with mild ing it within only the Atlantic Provinces to 99 and 128 days. or no symptoms but still carry the virus and could infect oth- Strikingly, this simple analysis suggests that, under current ers. conditions, banning air travel from outside Canada is more efficient in managing the pandemic than fully reopening and 5 Conclusion quarantining 95% of the incoming population. Just like any model, our network epidemiology model Relaxing travel restriction is a highly contentious political has several important limitations: First, the current effec- decision. However, from an outbreak dynamics perspective, tive reproduction number in a region with no active cases the picture is quite clear: Without proper control, an influx of is undefined which makes predictions very difficult. Here infected travelers can easily become the seed for a new expo- we approximate the effective reproduction number of New- nential outbreak. In the early phases of exponential growth, foundland and Labrador by the population-weighted mean the new case numbers may appear low and manageable, but across all of North America and across Canada, which we when unaddressed, the case numbers will begin to grow at infer from the reported COVID-19 case data using machine an alarming rate. At this point, it becomes impossible to learning [28]. However, we have no idea how well these manage a new outbreak with soft measures alone. Clearly, estimates represent the true behavior of the population of opening borders is a critical decision, especially towards re- Newfoundland and Labrador upon gradual reopening, since gions with a higher case prevalence. Our study shows that– a population that has not experienced a serious outbreak may especially for smaller provinces or states–tight border con- be more complacent. Second, we assume that the effective trol is often easier and more effective than quarantine. Par- medRxiv preprint doi: https://doi.org/10.1101/2020.07.16.20155614; this version posted August 2, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license .

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