Kraemer, M. U. G., Hill, V., Ruis, C., Dellicour, S., Bajaj, S., McCrone, J. T., Baele, G., Parag, K. V., Battle, A. L., Gutierrez, B., Jackson, B., Colquhoun, R., O’Toole, Á., Klein, B., Vespignani, A., COVID-19 Genomics UK (COG-UK) Consortium‡, Volz, E., Faria, N. R., Aanensen, D. M., … Pybus, O. G. (2021). Spatiotemporal invasion dynamics of SARS-CoV-2 lineage B.1.1.7 emergence. Science, 373(6557), 889–895. https://doi.org/10.1126/science.abj0113

Parsons, J. E., Newby, K. V., & French, D. P. (2018). Do interventions containing risk messages increase risk appraisal and the subsequent vaccination intentions and uptake? – A systematic review and meta‐analysis. British Journal of Health Psychology, 23(4), 1084–1106. https://doi.org/10.1111/bjhp.12340

Brewer, N. T., DeFrank, J. T., & Gilkey, M. B. (2016). Anticipated Regret and Health Behavior: A Meta-Analysis. Health Psychology : Official Journal of the Division of Health Psychology, American Psychological Association, 35(11), 1264–1275. https://doi.org/10.1037/hea0000294

Rothmund, T., Farkhari, F., Azevedo, F., & Ziemer, C.-T. (2020). Scientific Trust, Risk Assessment, and Conspiracy Beliefs about COVID-19—Four Patterns of Consensus and Disagreement between Scientific Experts and the German Public. PsyArXiv. https://doi.org/10.31234/osf.io/4nzuy

Elgar, F. J., Stefaniak, A., & Wohl, M. J. A. (2020). The trouble with trust: Time-series analysis of social capital, income inequality, and COVID-19 deaths in 84 countries. Social Science & Medicine, 263, 113365. https://doi.org/10.1016/j.socscimed.2020.113365

Brodeur, Abel, Leonardo Baccini, and Stephen Weymouth. ‘The COVID-19 Pandemic and US Presidential Elections’. MetaArXiv, 10 November 2020. https://doi.org/10.31222/osf.io/sxajv.

Hyland, P., Vallières, F., Shevlin, M., Bentall, R. P., McKay, R., Hartman, T. K., McBride, O., & Murphy, J. (2021). Resistance to COVID-19 vaccination has increased in Ireland and the UK during the pandemic. PsyArXiv. https://doi.org/10.31234/osf.io/ry6n4

ReconfigBehSci on Twitter: ‘RT @PsyArXivBot: Resistance to COVID-19 vaccination has increased in Ireland and the UK during the pandemic https://t.co/AgKErDr7Yj’ / Twitter. (n.d.). Retrieved 2 March 2021, from https://twitter.com/SciBeh/status/1366707710151053312

McCarrick, D., Prestwich, A., Prudenzi, A., & O’Connor, D. (2021). Health Effects of Psychological Interventions for Worry and Rumination: A Meta-analysis. PsyArXiv. https://doi.org/10.31234/osf.io/bsf9e

Brewer NT, Chapman GB, Gibbons FX, Gerrard M, McCaul KD, Weinstein ND. Meta-analysis of the relationship between risk perception and health behavior: the example of vaccination. Health Psychol. 2007;26(2):136–45. doi:10.1037/0278-6133.26.2.136

Weingarten. E., Chen. Q., McAdams., Yi. J., (2016). From Primed Concepts to Action: A Meta-Analysis of the BehavioralEffects of Incidentally Presented Words. Psychological Bulletin 2016 (142) pp 472-497.

Fischer, R., & Karl, J. (2020). Predicting behavioral intentions to prevent or mitigate COVID-19: A meta-analysis. PsyArXiv. https://doi.org/10.31234/osf.io/ek69g

Behrens. F., Kret. M. (2020) Under the Umbrella of Prosocial Behavior – A Critical Comparison of Paradigms. PsyArXiv Preprints. Retrieved from: https://psyarxiv.com/9uebc/

Whitney R. Robinson on Twitter: “1/ An #EpiTwitter 🧵 about theory... https://t.co/rSjfkHG21r” / Twitter. (n.d.). Twitter. Retrieved August 18, 2020, from https://twitter.com/WhitneyEpi/status/1295522551892971520

Bhattacharya, C., Chowdhury, D., Ahmed, N., Ozgur, S., Bhattacharya, B., Mridha, S. K., & Bhattacharyya, M. (2020). The Nature, Cause and Consequence of COVID-19 Panic among Social Media Users in India. https://doi.org/10.31234/osf.io/dgr45

Litman. L,. Hartman. R., Jaffe. S., Robinson. J. (2020) County-level recruitment in online samples: Applications to COVID-19 and beyond. PsyArXiv Preprints. Retrieved from: https://psyarxiv.com/g3xw7/

COVID-19 Social Science Tracker - Google Sheets

Brooks, H. Z., Kanjanasaratool, U., Kureh, Y. H., & Porter, M. A. (2020). Disease Detectives: Using Mathematics to Forecast the Spread of Infectious Diseases [Preprint]. SocArXiv. https://doi.org/10.31235/osf.io/mvn9z

Crystal, J. (2020, May 18). Mobilizing behavioral scientists to respond to COVID-19. Psychonomic Society Featured Content. https://featuredcontent.psychonomic.org/mobilizing-behavioral-scientists-to-respond-to-covid-19/

Mancastroppa, M., Burioni, R., Colizza, V., & Vezzani, A. (2020). Active and inactive quarantine in epidemic spreading on adaptive activity-driven networks. ArXiv:2004.07902 [Cond-Mat, Physics:Physics]. http://arxiv.org/abs/2004.07902

Lanovaz, M., & Turgeon, S. (2020). Tutorial: Applying Machine Learning in Behavioral Research [Preprint]. PsyArXiv. https://doi.org/10.31234/osf.io/9w6a3

Toxvaerd, F. M. O. (2020). Equilibrium Social Distancing [Working Paper]. Faculty of Economics, University of Cambridge. https://doi.org/10.17863/CAM.52489

Zoder-Martell, K., Markelz, A., Floress, M. T., Skriba, H. A., & Sayyah, L. E. N. (2020, May 6). Technology to Facilitate Telehealth in Applied Behavior Analysis. https://doi.org/10.31234/osf.io/nz5s7

Du, H., Yang, J., King, R. B., Yang, L., & Chi, P. (2020). COVID-19 Increases Online Emotional and Health-Related Searches [Preprint]. PsyArXiv. https://doi.org/10.31234/osf.io/5gskw

Vilella, S., Paolotti, D., Ruffo, G. et al. News and the city: understanding online press consumption patterns through mobile data. EPJ Data Sci. 9, 10 (2020). https://doi.org/10.1140/epjds/s13688-020-00228-9

Horstmann, K. T., Rauthmann, J. F., Sherman, R. A., & Ziegler, M. (2020, April 30). Unveiling an Exclusive Link: Predicting Behavior with Personality, Situation Perception, and Affect in a Pre-Registered Experience Sampling Study. Retrieved from psyarxiv.com/ztw2n

Tarbox, C., Silverman, E. A., Chastain, A. N., Little, A., Bermudez, T. L., & Tarbox, J. (2020, April 30). Taking ACTion: 18 Simple Strategies for Supporting Children with Autism During the COVID-19 Pandemic. Retrieved from psyarxiv.com/96whj

Moyers, S. A., & Hagger, M. S. (2020, April 20). Physical activity and sense of coherence: A meta-analysis. https://doi.org/10.31234/osf.io/d9e3k

Dai, B., Fu, D., Meng, G., Qi, L., & Liu, X. (2020, April 25). The effects of governmental and individual predictors on COVID-19 protective behaviors in China: a path analysis model. https://doi.org/10.31234/osf.io/hgzj9

Wang, T., Chen, X., Zhang, Q., & Jin, X. (2020, April 26). Use of Internet data to track Chinese behavior and interest in COVID-19. https://doi.org/10.31234/osf.io/j6m8q

Colombo, R., Wallace, M., & Taylor, R. S. (2020, April 11). An Essential Service Decision Model for Applied Behavior Analytic Providers During Crisis. https://doi.org/10.31234/osf.io/te8ha

Giangreco, G. (n.d.). Case fatality rate analysis of Italian COVID-19 outbreak. Journal of Medical Virology, n/a(n/a). https://doi.org/10.1002/jmv.25894