According to the smoke detector and functional flexibility principles of human behavioral immune system (BIS), the exposure to COVID-19 cues could motivate vaccine uptake. Using the tool of Google Trends, we tested that coronavirus-related searches—which assessed natural exposure to COVID-19 cues—would positively predict actual vaccination rates. As expected, coronavirus-related searches positively and significantly predicted vaccination rates in the United States (Study 1a) and across the globe (Study 2a) after accounting for a range of covariates. The stationary time series analyses with covariates and autocorrelation structure of the dependent variable confirmed that more coronavirus-related searches compared with last week indicated increases in vaccination rates compared with last week in the United States (Study 1b) and across the globe (Study 2b). With real-time web search data, psychological scientists could test their research questions in real-life settings and at a large scale to expand the ecological validity and generalizability of the findings.
AckermanJ. M.HillS. E.MurrayD. R. (2018). The behavioral immune system: Current concerns and future directions. Social and Personality Psychology Compass, 12(2), Article e12371. https://doi.org/10.1111/spc3.12371
2.
AckermanJ. M.TyburJ. M.BlackwellA. D. (2021). What role does pathogen-avoidance psychology play in pandemics?Trends in Cognitive Sciences, 25(3), 177–186. https://doi.org/10.1016/j.tics.2020.11.008
3.
Adam-TroianJ.ArciszewskiT. (2020). Absolutist words from search volume data predict state-level suicide rates in the United States. Clinical Psychological Science, 8(4), 788–793. https://doi.org/10.1177/2167702620916925
4.
Adam-TroianJ.BagciC. (2021). The pathogen paradox: Evidence that perceived COVID-19 threat is associated with both pro- and anti-immigrant attitudes. International Review of Social Psychology, 34(1), 1–15. https://doi.org/10.5334/irsp.469
5.
Adam-TroianJ.BonettoE.ArciszewskiT. (2021). “We shall overcome”: First-person plural pronouns from search volume data predict protest mobilization across the United States. Social Psychological and Personality Science, 12(8), 1476–1485. https://doi.org/10.1177/1948550620987672
6.
Adam-TroianJ.BonettoE.ArciszewskiT. (2022). Using absolutist word frequency from online searches to measure population mental health dynamics. Scientific Reports, 12(1), 1–10. https://doi.org/10.1038/s41598-022-06392-4
7.
Adam-TroianJ.BonettoE.VaretF.ArciszewskiT.GuillerT. (2020, June7). Pathogen threat increases electoral success for conservative parties: Results from a natural experiment with COVID-19 in France. PsyArXiv. https://doi.org/10.31234/osf.io/aqkpm
8.
AlperS. (2019). Does the association between illness-related and religious searches on the Internet depend on the level of religiosity?Social Psychological and Personality Science, 12(4), 497–505. https://doi.org/10.1177/1948550620923233
9.
AlperS.BayrakF.UsE. Ö.YilmazO. (2020). Do changes in threat salience predict the moral content of sermons? The case of Friday Khutbas in Turkey. European Journal of Social Psychology, 50(3), 662–672. https://doi.org/10.1002/ejsp.2632
ArndtJ.CookA.GoldenbergJ. L.CoxC. R. (2007). Cancer and the threat of death: The cognitive dynamics of death-thought suppression and its impact on behavioral health intentions. Journal of Personality and Social Psychology, 92(1), 12–29. https://doi.org/10.1037/0022-3514.92.1.12
12.
AroraV. S.McKeeM.StucklerD. (2019). Google Trends: Opportunities and limitations in health and health policy research. Health Policy, 123(3), 338–341. https://doi.org/10.1016/j.healthpol.2019.01.001
13.
BeallA. T.HoferM. K.SchallerM. (2016). Infections and elections: Did an Ebola outbreak influence the 2014 US federal elections (and if so, how)?Psychological Science, 27(5), 595–605. https://doi.org/10.1177/0956797616628861
14.
ChanE. Y.SaqibN. U. (2021). Privacy concerns can explain unwillingness to download and use contact tracing apps when COVID-19 concerns are high. Computers in Human Behavior, 119, Article 106718. https://doi.org/10.1016/j.chb.2021.106718
15.
ChengL.ZhouX.WangF.XiaoL. (2020). A state-level analysis of mortality and Google searches for pornography: Insight from life history theory. Archives of Sexual Behavior, 49(8), 3005–3011. https://doi.org/10.1007/s10508-020-01765-0
16.
CheungH. K.HeblM.KingE. B.MarkellH.MorenoC.NittrouerC. (2017). Back to the future: Methodologies that capture real people in the real world. Social Psychological and Personality Science, 8(5), 564–572. https://doi.org/10.1177/1948550617709113
17.
ClayR. (2017). The behavioral immune system and attitudes about vaccines: Contamination aversion predicts more negative vaccine attitudes. Social Psychological and Personality Science, 8(2), 162–172.
18.
ConnorP.SarafidisV.ZyphurM. J.KeltnerD.ChenS. (2019). Income inequality and White-on-Black racial bias in the United States: Evidence from project implicit and Google trends. Psychological Science, 30(2), 205–222. https://doi.org/10.1177/0956797618815441
19.
CulpepperP. D.HavlíčekJ.LeongómezJ. D.RobertsS. C. (2018). Visually activating pathogen disgust: A new instrument for studying the behavioral immune system. Frontiers in Psychology, 9, Article 1397. https://doi.org/10.3389/fpsyg.2018.01397
20.
DiMuccioS. H.KnowlesE. D. (2021). Precarious manhood predicts support for aggressive policies and politicians. Personality and Social Psychology Bulletin, 47(7), 1169–1187. https://doi.org/10.1177/0146167220963577
21.
DrorA. A.EisenbachN.TaiberS.MorozovN. G.MizrachiM.ZigronA.SroujiS.SelaE. (2020). Vaccine hesitancy: The next challenge in the fight against COVID-19. European Journal of Epidemiology, 35(8), 775–779. https://doi.org/10.1007/s10654-020-00671-y
22.
DuH.YangJ.KingR. B.YangL.ChiP. (2020). COVID-19 increases online searches for emotional and health-related terms. Applied Psychology, 12(4), 1039–1053. https://doi.org/10.1111/aphw.12237
23.
EysenbachG. (2009). Infodemiology and infoveillance: Framework for an emerging set of public health informatics methods to analyze search, communication and publication behavior on the Internet. Journal of Medical Internet Research, 11(1), Article e11. https://doi.org/10.2196/jmir.1157
24.
FincherC. L.ThornhillR. (2008). Assortative sociality, limited dispersal, infectious disease and the genesis of the global pattern of religion diversity. Proceedings of the Royal Society B, 275(1651), 2587–2594. https://doi.org/10.1098/rspb.2008.0688
25.
FincherC. L.ThornhillR. (2012). Parasite-stress promotes in-group assortative sociality: The cases of strong family ties and heightened religiosity. Behavioral and Brain Sciences, 35(2), 61–79. https://doi.org/10.1017/s0140525x11000021
26.
GanasegeranK.Ch’ngA. S. H.AzizZ. A.LooiI. (2020). Population’s health information-seeking behaviors and geographic variations of stroke in Malaysia: An ecological correlation and time series study. Scientific Reports, 10, Article 11353. https://doi.org/10.1038/s41598-020-68335-1
27.
GelfandM. J.JacksonJ. C.PanX.NauD.PieperD.DenisonE.DagherM.Van LangeP. A.ChiuC.-Y.WangM. (2021). The relationship between cultural tightness–looseness and COVID-19 cases and deaths: A global analysis. The Lancet Planetary Health, 5(3), e135–e144. https://doi.org/10.1016/S2542-5196(20)30301-6
28.
GötzF. M.GoslingS. D.RentfrowP. J. (2022). Small effects: The indispensable foundation for a cumulative psychological science. Perspectives on Psychological Science, 17(1), 205–215.
GrömpingU. (2007). Relative importance for linear regression in R: The package relaimpo. Journal of Statistical Software, 17(1), 1–27. https://doi.org/10.18637/jss.v017.i01
31.
GrossmannI.VarnumM. E. (2015). Social structure, infectious diseases, disasters, secularism, and cultural change in America. Psychological Science, 26(3), 311–324. https://doi.org/10.1177/0956797614563765
32.
HelzerE. G.PizarroD. A. (2011). Dirty liberals! Reminders of physical cleanliness influence moral and political attitudes. Psychological Science, 22(4), 517–522. https://doi.org/10.1177/0956797611402514
33.
HerrenC. M.BrownwrightT. K.LiuE. Y.El AmiriN.MajumderM. S. (2020). Democracy and mobility: A preliminary analysis of global adherence to non-pharmaceutical interventions for COVID-19. Social Science Research Network. Advance online publication. https://doi.org/10.2139/ssrn.3570206
HongJ.XuX-w.YangJ.ZhengJ.DaiS-m.ZhouJ.ZhangQ-m.RuanY.LingC.-q. (2021). Knowledge about, attitude and acceptance towards, and predictors of intention to receive the COVID-19 vaccine among cancer patients in Eastern China: A cross-sectional survey. Journal of Integrative Medicine, 20(1), 34–44. https://doi.org/10.1016/j.joim.2021.10.004
36.
HromatkoI.GrusA.KolđerajG. (2021). Do islanders have a more reactive behavioral immune system? Social cognitions and preferred interpersonal distances during the COVID-19 pandemic. Frontiers in Psychology, 12, Article 64756. https://doi.org/10.3389/fpsyg.2021.647586
37.
HusnayainA.FuadA.SuE. C.-Y. (2020). Applications of google search trends for risk communication in infectious disease management: A case study of COVID-19 outbreak in Taiwan. International Journal of Infectious Diseases, 95, 221–223. https://doi.org/10.1016/j.ijid.2020.03.021
38.
HuynhA. C.GrossmannI. (2021). Rising ethnic diversity in the United States accompanies shifts toward an individualistic culture. Social Psychological and Personality Science, 12(7), 1316–1325. https://doi.org/10.1177/1948550620967230
39.
JebbA. T.TayL. (2017). Introduction to time series analysis for organizational research: Methods for longitudinal analyses. Organizational Research Methods, 20(1), 61–94. https://doi.org/10.1177/1094428116668035
40.
JunS.-P.YooH. S.ChoiS. (2018). Ten years of research change using Google Trends: From the perspective of big data utilizations and applications. Technological Forecasting and Social Change, 130, 69–87. https://doi.org/10.1016/j.techfore.2017.11.009
KarlssonL. C.SoveriA.LewandowskyS.KarlssonL.KarlssonH.NolviS.KarukiviM.LindfeltM.AntfolkJ. (2022). The behavioral immune system and vaccination intentions during the coronavirus pandemic. Personality and Individual Differences, 185, Article 111295. https://doi.org/10.1016/j.paid.2021.111295
43.
KarwowskiM.KowalM.GroyeckaA.BiałekM.LebudaI.SorokowskaA.SorokowskiP. (2020). When in danger, turn right: Does covid-19 threat promote social conservatism and right-wing presidential candidates. Human Ethology, 35, 37–48. https://doi.org/10.31234/osf.io/pjfhs
44.
KhubchandaniJ.SharmaS.PriceJ. H.WiblishauserM. J.SharmaM.WebbF. J. (2021). COVID-19 vaccination hesitancy in the United States: A rapid national assessment. Journal of Community Health, 46(2), 270–277. https://doi.org/10.1007/s10900-020-00958-x
45.
KimJ.LeeJ.JhangJ.ParkJ.LeeJ. C. (2021). The impact of the COVID-19 threat on the preference for high versus low quality/price options. Journal of Hospitality Marketing & Management, 30(6), 699–716. https://doi.org/10.1080/19368623.2021.1884163
46.
KusanoK.KemmelmeierM. (2020). Multi-level modelling of time-series cross-sectional data reveals the dynamic interaction between ecological threats and democratic development. Royal Society Open Science, 7(3), Article 191804. https://doi.org/10.1098/rsos.191804
47.
LaiK.LeeY. X.ChenH.YuR. (2017). Research on web search behavior: How online query data inform social psychology. Cyberpsychology, Behavior, and Social Networking, 20(10), 596–602. https://doi.org/10.1089/cyber.2017.0261
48.
LakeJ.GerransP.SneddonJ.AttwellK.BotterillL. C.LeeJ. A. (2021). We’re all in this together, but for different reasons: Social values and social actions that affect COVID-19 preventative behaviors. Personality and Individual Differences, 178, Article 110868. https://doi.org/10.1016/j.paid.2021.110868
49.
LazarusJ. V.RatzanS. C.PalayewA.GostinL. O.LarsonH. J.RabinK.KimballS.El-MohandesA. (2021). A global survey of potential acceptance of a COVID-19 vaccine. Nature Medicine, 27(2), 225–228. https://doi.org/10.1038/s41591-020-1124-9
50.
LiuK.HeM.ZhuangZ.HeD.LiH. (2020). Unexpected positive correlation between human development index and risk of infections and deaths of COVID-19 in Italy. One Health, 10, Article 100174. https://doi.org/10.1016/j.onehlt.2020.100174
51.
LiuX.HuangJ.LiC.ZhaoY.WangD.HuangZ.YangK. (2021). The role of seasonality in the spread of COVID-19 pandemic. Environmental Research, 195, Article 110874. https://doi.org/10.1016/j.envres.2021.110874
52.
LiuY.PengG.HuL.DongJ.ZhangQ. (2019). Using Google trends and Baidu index to analyze the impacts of disaster events on company stock prices. Industrial Management & Data Systems, 120(2), 350–365. https://doi.org/10.1108/imds-03-2019-0190
53.
LuJ. G.JinP.EnglishA. S. (2021). Collectivism predicts mask use during COVID-19. Proceedings of the National Academy of Sciences, 118(23), 1–8. https://doi.org/10.1073/pnas.2021793118
54.
MaM. Z. (2021a). COVID-19 concerns in cyberspace predict human reduced dispersal in the real world: Meta-regression analysis of time series relationships across American states and 115 countries/territories. Computers in Human Behavior, 127, Article 107059. https://doi.org/10.1016/j.chb.2021.107059
55.
MaM. Z. (2021b). Group-level human values estimated with web search data and archival data explain the geographic variation in COVID-19 severity in the United States. Psychology & Health. Advance online publication. https://doi.org/10.1080/08870446.2021.1952582
56.
MaM. Z.YeS. (2021a). The COVID-19 pandemic and seeking information about condoms online: An infodemiology approach. Psychology & Health. Advance online publication. https://doi.org/10.1080/08870446.2021.2005794
57.
MaM. Z.YeS. (2021b). The role of ingroup assortative sociality in the COVID-19 pandemic: A multilevel analysis of google trends data in the United States. International Journal of Intercultural Relations, 84, 168–180. https://doi.org/10.1016/j.ijintrel.2021.07.010
58.
MacInnisC. C.HodsonG. (2015). Do American states with more religious or conservative populations search more for sexual content on Google?Archives of Sexual Behavior, 44(1), 137–147. https://doi.org/10.1007/s10508-014-0361-8
59.
MakhanovaA.ShepherdM. A. (2020). Behavioral immune system linked to responses to the threat of COVID-19. Personality and Individual Differences, 167, Article 110221. https://doi.org/10.1016/j.paid.2020.110221
60.
MalikA. A.McFaddenS. M.ElharakeJ.OmerS. B. (2020). Determinants of COVID-19 vaccine acceptance in the US. EClinicalMedicine, 26, Article 100495. https://doi.org/10.1016/j.eclinm.2020.100495
61.
MarzialiM. E.HoggR. S.OduwoleO. A.CardK. G. (2021). Predictors of COVID-19 testing rates: A cross-country comparison. International Journal of Infectious Diseases, 104, 370–372. https://doi.org/10.1016/j.ijid.2020.12.083
62.
MatzS. C.GladstoneJ. J.StillwellD. (2017). In a world of big data, small effects can still matter: A reply to Boyce, Daly, Hounkpatin, and Wood (2017). Psychological Science, 28(4), 547–550. https://doi.org/10.1177/0956797617697445
63.
MavraganiA.OchoaG. (2019). Google Trends in infodemiology and infoveillance: Methodology framework. JMIR Public Health and Surveillance, 5(2), Article e13439. https://doi.org/10.2196/13439
64.
MoranJ. B.GohJ. X.KerryN.MurrayD. R. (2021). Outbreaks and outgroups: Three tests of the relationship between disease avoidance motives and xenophobia during an emerging pandemic. Evolutionary Psychological Science, 7, 419–429. https://doi.org/10.1007/s40806-021-00283-z
65.
MoranJ. B.KerryN.GohJ. X.MurrayD. R. (2021). Parasites and promiscuity: Acute disease salience leads to more restricted sexual attitudes. Journal of Social and Personal Relationships, 38(11), 3333–3349. https://doi.org/10.1177/02654075211030999
66.
Nazif-MuñozJ. I.PeñaS.OulhoteY. (2021). The global viralization of policies to contain the spreading of the COVID-19 pandemic: Analyses of school closures and first reported cases. PLOS ONE, 16(4), Article e0248828. https://doi.org/10.1371/journal.pone.0248828
67.
NesseR. M. (2005). Natural selection and the regulation of defenses: A signal detection analysis of the smoke detector principle. Evolution and Human Behavior, 26(1), 88–105. https://doi.org/10.1016/j.evolhumbehav.2004.08.002
68.
NeubergS. L.KenrickD. T.SchallerM. (2011). Human threat management systems: Self-protection and disease avoidance. Neuroscience & Biobehavioral Reviews, 35(4), 1042–1051. https://doi.org/10.1016/j.neubiorev.2010.08.011
OronceC. I. A.ScannellC. A.KawachiI.TsugawaY. (2020). Association between state-level income inequality and COVID-19 cases and mortality in the USA. Journal of General Internal Medicine, 35(9), 2791–2793. https://doi.org/10.1007/s11606-020-05971-3
71.
O’SheaB. A.WatsonD. G.BrownG. D.FincherC. L. (2020). Infectious disease prevalence, not race exposure, predicts both implicit and explicit racial prejudice across the United States. Social Psychological and Personality Science, 11(3), 345–355. https://doi.org/10.1177/1948550619862319
72.
PelhamB. W.ShimizuM.ArndtJ.CarvalloM.SolomonS.GreenbergJ. (2018). Searching for God: Illness-related mortality threats and religious search volume in Google in 16 nations. Personality and Social Psychology Bulletin, 44(3), 290–303. https://doi.org/10.1177/0146167217736047
73.
PolitiE.Van AsscheJ.CapraraG. V.PhaletK. (2021). No man is an island: Psychological underpinnings of prosociality in the midst of the COVID-19 outbreak. Personality and Individual Differences, 171, Article 110534. https://doi.org/10.1016/j.paid.2020.110534
74.
PolletT. V.SaxtonT. K. (2019). How diverse are the samples used in the journals “evolution & human behavior” and “evolutionary psychology”?Evolutionary Psychological Science, 5, 357–368. https://doi.org/10.1007/s40806-019-00192-2
75.
PyszczynskiT.GreenbergJ.SolomonS. (1999). A dual-process model of defense against conscious and unconscious death-related thoughts: An extension of terror management theory. Psychological Review, 106(4), 835–845. https://doi.org/10.1037/0033-295X.106.4.835
76.
PyszczynskiT.LockettM.GreenbergJ.SolomonS. (2021). Terror management theory and the COVID-19 pandemic. Journal of Humanistic Psychology, 61(2), 173–189. https://doi.org/10.1177/0022167820959488
77.
ReiterP. L.PennellM. L.KatzM. L. (2020). Acceptability of a COVID-19 vaccine among adults in the United States: How many people would get vaccinated?Vaccine, 38(42), 6500–6507. https://doi.org/10.1016/j.vaccine.2020.08.043
78.
RotellaA.VarnumM. E.SngO.GrossmannI. (2021). Increasing population densities predict decreasing fertility rates over time: A 174-nation investigation. American Psychologist, 76(6), 933–946. https://doi.org/10.1037/amp0000862
79.
SalaliG. D.UysalM. S. (2020). COVID-19 vaccine hesitancy is associated with beliefs on the origin of the novel coronavirus in the UK and Turkey. Psychological Medicine. Advance online publication. https://doi.org/10.1017/S0033291720004067
80.
SchaalN. K.ZöllkauJ.HeppP.FehmT.HagenbeckC. (2021). Pregnant and breastfeeding women’s attitudes and fears regarding the COVID-19 vaccination. Archives of Gynecology and Obstetrics. Advance online publication. https://doi.org/10.1007/s00404-021-06297-z
81.
SchallerM. (2011). The behavioural immune system and the psychology of human sociality. Philosophical Transactions of the Royal Society B, 366(1583), 3418–3426. https://doi.org/10.1098/rstb.2011.0029
82.
SchallerM.MurrayD. R.BangerterA. (2015). Implications of the behavioural immune system for social behaviour and human health in the modern world. Philosophical Transactions of the Royal Society B, 370(1669), Article 20140105. https://doi.org/10.1098/rstb.2014.0105
83.
SchallerM.MurrayD. R.HoferM. K. (2021). The behavioural immune system and pandemic psychology: The evolved psychology of disease-avoidance and its implications for attitudes, behaviour, and public health during epidemic outbreaks. European Review of Social Psychology. Advance online publication. https://doi.org/10.1080/10463283.2021.1988404
SchernhammerE.WeitzerJ.LaubichlerM. D.BirmannB. M.BertauM.ZenkL.CanigliaG.JägerC. C.SteinerG. (2021). Correlates of COVID-19 vaccine hesitancy in Austria: Trust and the government. Journal of Public Health (Oxford, England), 44(1), e106–e116. https://doi.org/10.1093/pubmed/fdab122
86.
SchwartzS. H. (2012). An overview of the Schwartz theory of basic values. Online Readings in Psychology and Culture, 2(1). https://doi.org/10.9707/2307-0919.1116
87.
ScrimaF.MiceliS.CaciB.CardaciM. (2022). The relationship between fear of COVID-19 and intention to get vaccinated. The serial mediation roles of existential anxiety and conspiracy beliefs. Personality and Individual Differences, 184, Article 111188. https://doi.org/10.1016/j.paid.2021.111188
88.
SenecalC.GulatiR.LermanA. (2020). Google Trends insights into reduced acute coronary syndrome admissions during the COVID-19 pandemic: Infodemiology study. JMIR Cardio, 4(1), Article e20426. https://doi.org/10.2196/20426
89.
ShookN. J.SeviB.LeeJ.OosterhoffB.FitzgeraldH. N. (2020). Disease avoidance in the time of COVID-19: The behavioral immune system is associated with concern and preventative health behaviors. PLOS ONE, 15(8), Article e0238015. https://doi.org/10.1371/journal.pone.0238015
SorokowskiP.GroyeckaA.KowalM.SorokowskaA.BiałekM.LebudaI.DobrowolskaM.ZdybekP.KarwowskiM. (2020). Can information about pandemics increase negative attitudes toward foreign groups? A case of COVID-19 outbreak. Sustainability, 12(12), Article 4912. https://doi.org/10.3390/su12124912
92.
SpringerS.MenzelL. M.ZiegerM. (2020). Google Trends provides a tool to monitor population concerns and information needs during COVID-19 pandemic. Brain, Behavior, and Immunity, 87, 109–110. https://doi.org/10.1016/j.bbi.2020.04.073
93.
Stephens-DavidowitzS. (2014). The cost of racial animus on a black candidate: Evidence using Google search data. Journal of Public Economics, 118, 26–40. https://doi.org/10.1016/j.jpubeco.2014.04.010
94.
Stephens-DavidowitzS. (2017). Everybody lies: Big data, new data, and what the Internet can tell us about who we really are. HarperCollins.
95.
TaberneroC.Castillo-MayénR.LuqueB.CuadradoE. (2020). Social values, self-and collective efficacy explaining behaviours in coping with Covid-19: Self-interested consumption and physical distancing in the first 10 days of confinement in Spain. PLOS ONE, 15(9), Article e0238682. https://doi.org/10.1371/journal.pone.0238682
96.
TiokhinL.HruschkaD. (2017). No evidence that an Ebola outbreak influenced voting preferences in the 2014 elections after controlling for time-series autocorrelation: A commentary on Beall, Hofer, and Schaller (2016). Psychological Science, 28(9), 1358–1360. https://doi.org/10.1177/0956797616680396
97.
TskhayK. O.WilsonJ. P.RuleN. O. (2016). People use psychological cues to detect physical disease from faces. Personality and Social Psychology Bulletin, 42(10), 1309–1320. https://doi.org/10.1177/0146167216656357
98.
TyburJ. M.BryanA. D.MagnanR. E.HooperA. E. C. (2011). Smells like safe sex: Olfactory pathogen primes increase intentions to use condoms. Psychological Science, 22(4), 478–480. https://doi.org/10.1177/0956797611400096
99.
TyburJ. M.InbarY.AarøeL.BarclayP.BarlowF. K.De BarraM.BeckerD. V.BorovoiL.ChoiI.ChoiJ. A. (2016). Parasite stress and pathogen avoidance relate to distinct dimensions of political ideology across 30 nations. Proceedings of the National Academy of Sciences, 113(44), 12408–12413. https://doi.org/10.1073/pnas.1607398113
100.
UzI. (2015). The index of cultural tightness and looseness among 68 countries. Journal of Cross-Cultural Psychology, 46(3), 319–335. https://doi.org/10.1177/0022022114563611
101.
VailK. E.III.JuhlJ.ArndtJ.VessM.RoutledgeC.RutjensB. T. (2012). When death is good for life: Considering the positive trajectories of terror management. Personality and Social Psychology Review, 16(4), 303–329. https://doi.org/10.1177/1088868312440046
102.
VarnumM. E.GrossmannI. (2016). Pathogen prevalence is associated with cultural changes in gender equality. Nature Human Behaviour, 1(1), Article 0003. https://doi.org/10.1038/s41562-016-0003
103.
VarnumM. E.GrossmannI. (2021). The psychology of cultural change: Introduction to the special issue. American Psychologist, 76(6), 833–837. https://doi.org/10.1037/amp0000898
104.
VarnumM. E.KremsJ. A.MorrisC.WormleyA.GrossmannI. (2021). Why are song lyrics becoming simpler? A time series analysis of lyrical complexity in six decades of American popular music. PLOS ONE, 16(1), Article e0244576. https://doi.org/10.1371/journal.pone.0244576
105.
VarotsosC. A.KrapivinV. F.XueY. (2021). Diagnostic model for the society safety under COVID-19 pandemic conditions. Safety Science, 136, Article 105164. https://doi.org/10.1016/j.ssci.2021.105164
106.
VerelstF.WillemL.BeutelsP. (2016). Behavioural change models for infectious disease transmission: A systematic review (2010–2015). Journal of the Royal Society Interface, 13(125), Article 20160820. https://doi.org/10.1098/rsif.2016.0820
107.
WalkerA.HopkinsC.SurdaP. (2020). Use of Google Trends to investigate loss-of-smell–related searches during the COVID-19 outbreak. International Forum of Allergy & Rhinology, 10(7), 839–847. https://doi.org/10.1002/alr.22580
108.
WillisD. E.AndersenJ. A.Bryant-MooreK.SeligJ. P.LongC. R.FelixH. C.CurranG. M.McElfishP. A. (2021). COVID-19 vaccine hesitancy: Race/ethnicity, trust, and fear. Clinical and Translational Science, 14(6), 2200–2207. https://doi.org/10.1111/cts.13077
109.
WolfL. J.HaddockG.MansteadA. S.MaioG. R. (2020). The importance of (shared) human values for containing the COVID-19 pandemic. British Journal of Social Psychology, 59(3), 618–627. https://doi.org/10.1111/bjso.12401
110.
WuQ.TanC.WangB.ZhouP. (2015). Behavioral immune system and ingroup derogation: The effects of infectious diseases on ingroup derogation attitudes. PLOS ONE, 10(3), Article e0122794. https://doi.org/10.1371/journal.pone.0122794
111.
WuX.NetheryR. C.SabathM.BraunD.DominiciF. (2020). Air pollution and COVID-19 mortality in the United States: Strengths and limitations of an ecological regression analysis. Science Advances, 6(45), 1–6. https://doi.org/10.1126/sciadv.abd4049
