Google Trends: Opportunities and Limitations in Health and Health

Health Policy 123 (2019) 338–341

Contents lists available at ScienceDirect

Health Policy

j ournal homepage: www.elsevier.com/locate/healthpol

Google Trends: Opportunities and limitations in health and health

policy research

a,∗ b c

Vishal S. Arora , Martin McKee , David Stuckler

Harvard Medical School, 77 Avenue Louis Pasteur, Boston, MA, USA

London School of Hygiene & Tropical Medicine, ECOHOST, 15-17 Tavistock Place, London, WC1H 9SH, United Kingdom

Università Bocconi, Via Sarfatti, 25, Milano, Italy

a r t i c l e i n f o a b s t r a c t

Article history: Web search engines have become pervasive in recent years, obtaining information easily on a variety

Received 1 April 2015

of topics, from customer services and goods to practical information. Beyond these search interests,

Received in revised form 3 January 2019

however, there is growing interest in obtaining health advice or information online. As a result, health

Accepted 6 January 2019

and health policy researchers are starting to take note of potential data sources for surveillance and

research, such as Google Trends , a publicly available repository of information on real-time user search

Keywords: TM

patterns. While research using Google Trends is growing, use of the dataset still remains limited. This

Health policy

paper offers an overview of the use of such data in a variety of contexts, while providing information on

Social media

Internet its strengths, limitations, and recommendations for further improvement.

Health behaviours

1. Introduction a health-related topic online, ranging from mental health, immu-

nizations to sexual health information [4].

Google dominates the market for internet search engines and is Health and health policy researchers are also starting to take

so pervasive that the term “to Google” has entered everyday use note of the potential of these data. A PubMed search for “Google

in a way that none of its competitors has. In Europe it is used in Trends” or “Google Insights” (previous version of Google Trends )

85% of internet searches [1] while in the US, it accounts for 65% revealed an over 20-fold increase in original research articles or

[2]. In 2012, Google handled approximately 1.2 trillion searches research letters using Google Trends from 2009 to 2018 (Fig. 1).

globally, or 3.3 billion searches per day [3]. Although more recent While much of this information is kept secret by online providers,

data are difﬁcult to obtain because of commercial conﬁdentiality, other elements are available to anyone. This paper offers a general

it has been estimated that the total number rose to about 2 tril- guide to how Google collects and shares search engine data, how

lion in 2018. In an era where web searches and transactions are their data has been used in the past, and how health and health

recorded instantaneously, this activity generates a massive volume policy researchers can make greater use of these data in the future.

of data whose uses are often unexpected and virtually limitless.

Every search that is undertaken, and every page that is viewed, is

tracked. Consequently, Google itself, along with many online con- 2. Google Trends : what it is and how it works

tent providers, such as Amazon, make extensive use of these data,

tailoring advertisements and the results of searches to each user’s Google Trends is the principle tool used to study trends

browsing history. and patterns of search engine queries using Google. It is one of

While individuals search for many things online, such as con- a suite of Google tools that track different types of activity, such

sumer goods and services, or practical information (such as opening as Google Scholar , which records citations of papers, and Google

hours or travel timetables), there is also signiﬁcant search activity Analytics , which allows the owner of a website to track where

related to health concerns. According to the Pew Internet and Amer- and when people are viewing that site. As in any epidemiolog-

ican Life Project, 80% of Internet users in the US have searched for ical study, it is important to take account of the denominator

when interpreting counts. Google Trends does this by expressing

the absolute number of searches relative to the total number of

searches in each location and at each time. The number of searches

∗

for each term (e.g. “alcoholism”) relative to total searches is referred

Corresponding author.

E-mail address: vishal [email protected] (V.S. Arora). to as the query share. This query share is then normalised to the

https://doi.org/10.1016/j.healthpol.2019.01.001

V.S. Arora et al. / Health Policy 123 (2019) 338–341 339

2008 ﬁnancial crisis. In contrast, the highest intensity in the USA

was back in 2004.

Google Trends offers a high level of geographical precision

in developed countries, allowing for searches to be stratiﬁed at a

national, regional, and city level. Trends in searches for different

terms can be compared and multiple search terms can be combined,

with a “+” sign, to identify those searching for terms in combination

(e.g. “alcoholism + treatment”).

Lastly, Google uses natural language processing methods and

indexes web pages collected to classify search queries into one of 25

speciﬁc categories (including health) and over 300 sub-categories.

Unlike other public health datasets, what makes Google Trends

data so novel is that it is collected and reported in real time and is

publicly available.

Fig. 1. Research using Google Trends/ Insights, 2009 to 2018.

Source: PubMed search for records with “Google Trends” or “Google Insights” in title

or abstract. TM

3. Applications of Google Trends in population health

research

highest volume of searches for that term over the time period being

studied. This index ranges from 0 to 100, with 100 recorded on Initially, one of the best known applications of Google search

the date that saw the highest relative search volume activity for engine query data in population health research was early detec-

that term. Thus, a Google Trends search index of 25 indicates tion of inﬂuenza epidemics. In 2009, collaborators at Google and

that search activity for a particular term was 25% of that seen at the US Centers for Disease Control found that the relative frequency

the time when search activity was most intense. Fig. 2 illustrates of searches for inﬂuenza-like illness correlated well with the per-

this, and also how patterns can vary across countries. Thus, using centage of physician visits for inﬂuenza in the United States, with

searches for the term “antidepressants” (and equivalent in relevant a 1-day reporting lag (traditional CDC estimates have a 1–2 week

languages) over the period 2004 to 2018, the highest intensities in reporting lag) [5]. Since then, however, the uses of Google search

three of the countries, Australia, France, and the United Kingdom, engine data in population health research have grown substan-

have been in 2017/18, with levels around 20 until the onset of the tially. Many examples involve early detection of other infectious

Fig. 2. Search activity for anti-depressants in France, Australia, United Kingdom, and USA January 2004 to December 2018.

Note: Search terms – France, antidepressants + antidépresseur; UK/ Australia – antidepressants; USA - antidepressants + antidepresivo (Spanish).

Source: Google Trends searched 31st December 2018.

340 V.S. Arora et al. / Health Policy 123 (2019) 338–341

Box 1: Tracking interest in electronic cigarettes: Evi- Box 3: Uncovering racism.

dence from Australia, Canada, United Kingdom, and the Social desirability bias exists where people answer questions

United States. in ways that they expect will be viewed favourably by others.

In the past few years electronic cigarettes (e-cigarettes) have This makes research on issues such as racism difﬁcult. One

been marketed intensively [16]. Although the clinical evidence study measured the proportion of Google searches for the “N-

that they aid quitting is weak, social media abounds with word” in 196 locations covering the USA [26]. They found a

claims that they are effective in this respect. To determine signiﬁcant association with mortality among African Ameri-

how consumer interest in these products has evolved, Ayers cans, even after adjusting for white mortality rates. As the

et al. [36] examined Google Trends search activity for e- authors noted, these ﬁndings are consistent with other liter-

cigarettes against traditional smoking cessation products (e.g. ature on the adverse associations between racism and health.

nicotine replacement therapy) from July 2008 to February 2010.

Their results showed that search activity for e-cigarettes rapidly

surpassed that of any of the traditional smoking cessation

products. For example, search volume for e-cigarettes was The ability to combine search terms unlocks the potential for

® ®

some especially imaginative approaches. For example, White et al.

300% and 160% higher than Chantix or Champix (vareni-

cline) in the US and UK, respectively. Furthermore, search [27] demonstrated the ability to identify interactions between

activity for e-cigarettes within the US was signiﬁcantly higher drugs from searches for their names in combination, something

for those states that had stronger tobacco control measures, that would easily be missed using routine post-marketing surveil-

as determined by the American Lung Association. lance.

4. Where we go from here with Google Trends

Box 2: Association of abortion-related searches with TM

While Google Trends has been able to provide valuable

abortion policies and availability: A global perspective.

insights into population health surveillance and behaviours, the

There are few, if any, medical procedures that provoke as much

intense political debate as aborting a foetus. Moreover, as abor- data are subject to certain caveats. Among these limitations, the

tions remain illegal or heavily restricted in many jurisdictions, most obvious one is that all of the search data available through

leading women to obtain them illegally or in other countries, Google Trends is anonymised and reﬂects those with internet

accurate data on abortion provision is often unreliable and

access, potentially excluding vulnerable groups (e.g. elderly) or

outdated. Because information identifying those undertaking

regions where internet uptake could be low (e.g. some parts of

internet searches is not in the public domain, data on volume

low- and middle-income countries). Researchers will not be able

of searches may provide a proxy for interest in obtaining an

to know who is searching for health terms and what their inten-

abortion. Based on this assumption, Reis and Brownstein [17]

TM tions might be. While Google does use natural language processing

explored the relationships between Google Trends search

methods to code health-related searches, this is not available for all

activity, local abortion rates, and local abortion policies. Both

countries and languages. Third, it is still not quite clear what search

in the US and internationally, the study found search volume

for abortions was inversely related to local abortion rates. terms one should use when exploring a particular health behaviour

However, search volume was also signiﬁcantly higher in those (e.g. depression, alcoholism, etc.). Fourth, studies should be based

regions of the US where barriers to an abortion were more on a clear conceptual model of behaviour, where appropriate, in

stringent (e.g. mandatory parental notiﬁcation for minors).

which the searches can plausibly be linked to ideas and ultimately

behaviour. This is not always the case [28]. Finally, it is important to

be aware of the risk of reporting bias, with only those studies ﬁnd-

outbreaks, such as Lyme disease [6], a selection of tropical diseases ing positive correlations being published, as has been suggested

in India [7], syphilis [8], HIV [9], and Zika virus infections [10]. recently [29].

Over time, Google search engine data has increasingly been uti- Research using search engine activity is still in its infancy and

lized to understand health behaviours. For example, it has been there are some things that population health researchers and

shown that changes in the volume of suicide-related searches may Google might do to maximise the value of this method.

provide an early warning of changing mental health risk [11–13], The ﬁrst relates to consistency of reporting. As Nuti et al. [30]

although the association is strongest for suicides among younger note in their systematic review on Google Trends , there is no

people and middle-aged women, both groups more likely to take deﬁned consensus on how to document Google search engine

overdoses (and thus require information on how to do it) than queries in academic papers. For example, only 19% of the publi-

among older men, among whom hanging is more common [14]. A cations they identiﬁed had deﬁned the search category used (e.g.

related study examined the commonly held view that media cov- health) and only 39% of papers provided an explicit search strategy.

erage of celebrity suicides can either increase or decrease suicidal As a minimum, research utilising Google Trends data should doc-

ideation, ﬁnding limited evidence for both, but only with the most ument the exact search terms inputted, the translations used when

prominent celebrities [15]. searching in other than English, category used, a downloadable

Some other novel uses of Google Trends have included mon- spreadsheet of extracted search indices, and the date the analysis

itoring interest in electronic cigarettes [16], abortions [17], and was performed.

bariatric surgery [18], assessing the relationship between health- The second relates to how health-related searches are collected

related searches and economic conditions (e.g. unemployment and categorised, especially if a search term might be misconstrued

rates) [19–21], and tracking pharmaceutical utilisation and rev- as non-health related (e.g. “smoking” when juxtaposed with “chim-

enues [22] (Boxes 1 and 2 ). Several studies have also examined ney” or “gun”). This is an area where there is considerable scope for

seasonality of events not easily identiﬁable from existing data dialogue between population health researchers and Google, tak-

sources [23,24]. A related application was seen in a study that quan- ing advantage of advances in artiﬁcial intelligence. Without any

tiﬁed the number of days during that increased interest in smoking transparency on how algorithms for search terms are calculated, it

cessation lasted after a tax rise [25]. Information on what people will be difﬁcult for researchers to know just how accurately search

search has even provided insights on societal attitudes, such as activity can model trends in search activity within a population

racism, which is less easily discernible in survey data (Box 3) [26]. [31].

V.S. Arora et al. / Health Policy 123 (2019) 338–341 341

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