Campos-Mercade, Pol, Armando Meier, Florian Schneider, and Erik Wengström. “Prosociality Predicts Health Behaviors during the COVID-19 Pandemic.” Department of Economics - University of Zurich, May 2020. https://EconPapers.repec.org/RePEc:zur:econwp:346.

Ledford, H. (2020). How Facebook, Twitter and other data troves are revolutionizing social science. Nature, 582(7812), 328–330. https://doi.org/10.1038/d41586-020-01747-1

Pettifor, A. (2020). Rebuild the ramshackle global financial system. Nature. https://doi.org/10.1038/d41586-020-01507-1

The Lancet Gastroenterology & Hepatology. (2020). Drinking alone: COVID-19, lockdown, and alcohol-related harm. The Lancet Gastroenterology & Hepatology, 5(7), 625. https://doi.org/10.1016/S2468-1253(20)30159-X

Peer review should be an honest, but collegial, conversation. (2020). Nature, 582(7812), 314–314. https://doi.org/10.1038/d41586-020-01622-z

Tsolaki, Vasiliki, George E. Zakynthinos, and Dimosthenis Makris. ‘The ARDSnet Protocol May Be Detrimental in COVID-19’. Critical Care 24, no. 1 (December 2020): 351. https://doi.org/10.1186/s13054-020-03081-4.

Boosting research without supporting universities is wrong-headed. (2020). Nature, 582(7812), 313–314. https://doi.org/10.1038/d41586-020-01788-6

Sorokowska, A., Sorokowski, P., Hilpert, P., Cantarero, K., Frackowiak, T., Ahmadi, K., Alghraibeh, A. M., Aryeetey, R., Bertoni, A., Bettache, K., Blumen, S., Błażejewska, M., Bortolini, T., Butovskaya, M., Castro, F. N., Cetinkaya, H., Cunha, D., David, D., David, O. A., … Pierce, J. D. (2017). Preferred Interpersonal Distances: A Global Comparison. Journal of Cross-Cultural Psychology, 48(4), 577–592. https://doi.org/10.1177/0022022117698039

Kucharski, A. J., Klepac, P., Conlan, A. J. K., Kissler, S. M., Tang, M. L., Fry, H., Gog, J. R., Edmunds, W. J., Emery, J. C., Medley, G., Munday, J. D., Russell, T. W., Leclerc, Q. J., Diamond, C., Procter, S. R., Gimma, A., Sun, F. Y., Gibbs, H. P., Rosello, A., … Simons, D. (2020). Effectiveness of isolation, testing, contact tracing, and physical distancing on reducing transmission of SARS-CoV-2 in different settings: A mathematical modelling study. The Lancet Infectious Diseases, 0(0). https://doi.org/10.1016/S1473-3099(20)30457-6

Bettinger, E. P., Fox, L., Loeb, S., & Taylor, E. S. (2017). Virtual classrooms: How online college courses affect student success. American Economic Review, 107(9), 2855-75.

Clark, A., Jit, M., Warren-Gash, C., Guthrie, B., Wang, H. H. X., Mercer, S. W., Sanderson, C., McKee, M., Troeger, C., Ong, K. L., Checchi, F., Perel, P., Joseph, S., Gibbs, H. P., Banerjee, A., Eggo, R. M., Nightingale, E. S., O’Reilly, K., Jombart, T., … Jarvis, C. I. (2020). Global, regional, and national estimates of the population at increased risk of severe COVID-19 due to underlying health conditions in 2020: A modelling study. The Lancet Global Health, S2214109X20302643. https://doi.org/10.1016/S2214-109X(20)30264-3

Htun, M. (2020). Tenure and promotion after the pandemic. Science, 368(6495), 1075–1075. https://doi.org/10.1126/science.abc7469

Marshall, J. C., Murthy, S., Diaz, J., Adhikari, N., Angus, D. C., Arabi, Y. M., Baillie, K., Bauer, M., Berry, S., Blackwood, B., Bonten, M., Bozza, F., Brunkhorst, F., Cheng, A., Clarke, M., Dat, V. Q., de Jong, M., Denholm, J., Derde, L., … Zhang, J. (2020). A minimal common outcome measure set for COVID-19 clinical research. The Lancet Infectious Diseases, S1473309920304837. https://doi.org/10.1016/S1473-3099(20)30483-7

Ooi, E. E., & Low, J. G. (2020). Asymptomatic SARS-CoV-2 infection. The Lancet Infectious Diseases, S1473309920304606. https://doi.org/10.1016/S1473-3099(20)30460-6

Oran, D. P., & Topol, E. J. (2020). Prevalence of Asymptomatic SARS-CoV-2 Infection: A Narrative Review. Annals of Internal Medicine, M20-3012. https://doi.org/10.7326/M20-3012

Brodeur, A., Cook, N., & Heyes, A. (2020). A Proposed Specification Check for p-Hacking. AEA Papers and Proceedings, 110, 66–69. https://doi.org/10.1257/pandp.20201078

Ofosu, G. K., & Posner, D. N. (2020). Do Pre-analysis Plans Hamper Publication? AEA Papers and Proceedings, 110, 70–74. https://doi.org/10.1257/pandp.20201079

Raleigh, V. S. (2020). Tackling UK’s mortality problem: Covid-19 and other causes. BMJ, 369. https://doi.org/10.1136/bmj.m2295

Bertoncello, C., Ferro, A., Fonzo, M., Zanovello, S., Napoletano, G., Russo, F., Baldo, V., & Cocchio, S. (2020). Socioeconomic Determinants in Vaccine Hesitancy and Vaccine Refusal in Italy. Vaccines, 8(2). https://doi.org/10.3390/vaccines8020276

Friston KJ, Parr T, Zeidman P et al. Dynamic causal modelling of COVID-19 [version 1; peer review: awaiting peer review]. Wellcome Open Res 2020, 5:89 (https://doi.org/10.12688/wellcomeopenres.15881.1)

Evans, M. C., & Cvitanovic, C. (2018). An introduction to achieving policy impact for early career researchers. Palgrave Communications, 4(1), 1–12. https://doi.org/10.1057/s41599-018-0144-2

Abbott, A., Askelson, N., Scherer, A. M., & Afifi, R. A. (2020). Critical Reflections on COVID-19 Communication Efforts Targeting Adolescents and Young Adults. Journal of Adolescent Health, 0(0). https://doi.org/10.1016/j.jadohealth.2020.05.013

Camacho, D., Panizo-LLedot, Á., Bello-Orgaz, G., Gonzalez-Pardo, A., & Cambria, E. (2020). The Four Dimensions of Social Network Analysis: An Overview of Research Methods, Applications, and Software Tools. Information Fusion. https://doi.org/10.1016/j.inffus.2020.05.009

Gencoglu, O., & Gruber, M. (2020). Causal Modeling of Twitter Activity During COVID-19. ArXiv:2005.07952 [Cs]. http://arxiv.org/abs/2005.07952

Ziems, C., He, B., Soni, S., & Kumar, S. (2020). Racism is a Virus: Anti-Asian Hate and Counterhate in Social Media during the COVID-19 Crisis. ArXiv:2005.12423 [Physics]. http://arxiv.org/abs/2005.12423

Gozzi, N., Tizzani, M., Starnini, M., Ciulla, F., Paolotti, D., Panisson, A., & Perra, N. (2020). Collective response to the media coverage of COVID-19 Pandemic on Reddit and Wikipedia. ArXiv:2006.06446 [Physics]. http://arxiv.org/abs/2006.06446

Okell, L. C., Verity, R., Watson, O. J., Mishra, S., Walker, P., Whittaker, C., Katzourakis, A., Donnelly, C. A., Riley, S., Ghani, A. C., Gandy, A., Flaxman, S., Ferguson, N. M., & Bhatt, S. (2020). Have deaths from COVID-19 in Europe plateaued due to herd immunity? The Lancet, 0(0). https://doi.org/10.1016/S0140-6736(20)31357-X

Li, Z., Chen, Q., Feng, L., Rodewald, L., Xia, Y., Yu, H., Zhang, R., An, Z., Yin, W., Chen, W., Qin, Y., Peng, Z., Zhang, T., Ni, D., Cui, J., Wang, Q., Yang, X., Zhang, M., Ren, X., … Li, S. (2020). Active case finding with case management: The key to tackling the COVID-19 pandemic. The Lancet, 0(0). https://doi.org/10.1016/S0140-6736(20)31278-2

Li, Z., Phillips, J., & Durgin, F. H. (2011). The underestimation of egocentric distance: Evidence from frontal matching tasks. Attention, Perception, & Psychophysics, 73(7), 2205. https://doi.org/10.3758/s13414-011-0170-2

Chu, D. K., Akl, E. A., Duda, S., Solo, K., Yaacoub, S., Schünemann, H. J., Chu, D. K., Akl, E. A., El-harakeh, A., Bognanni, A., Lotfi, T., Loeb, M., Hajizadeh, A., Bak, A., Izcovich, A., Cuello-Garcia, C. A., Chen, C., Harris, D. J., Borowiack, E., … Schünemann, H. J. (2020). Physical distancing, face masks, and eye protection to prevent person-to-person transmission of SARS-CoV-2 and COVID-19: A systematic review and meta-analysis. The Lancet, 0(0). https://doi.org/10.1016/S0140-6736(20)31142-9

Maltby, J., Hunt, S. A., Ohinata, A., Palmer, E., & Conroy, S. (2020). Frailty and Social Isolation: Comparing the Relationship between Frailty and Unidimensional and Multifactorial Models of Social Isolation: Journal of Aging and Health. https://doi.org/10.1177/0898264320923245

Tuite, A. R., Greer, A. L., De Keninck, S., & Fisman, D. N. (2020). Risk for COVID-19 Resurgence Related to Duration and Effectiveness of Physical Distancing in Ontario, Canada. Annals of Internal Medicine. https://doi.org/10.7326/M20-2945

DellaVigna, S & Linos E. (2020). RCTs to scale: Comprehensive evidence from two nudge units. UC Berkeley. https://eml.berkeley.edu/~sdellavi/wp/NudgeToScale2020-03-20.pdf

Scally, G., Jacobson, B., & Abbasi, K. (2020). The UK’s public health response to covid-19. BMJ, m1932. https://doi.org/10.1136/bmj.m1932

Glasziou, P. P., Sanders, S., & Hoffmann, T. (2020). Waste in covid-19 research. BMJ 2020;369. doi: https://doi.org/10.1136/bmj.m1847

Boustan, L. P., Kahn, M. E., Rhode, P. W., & Yanguas, M. L. (2020). The Effect of Natural Disasters on Economic Activity in US Counties: A Century of Data. Journal of Urban Economics, 103257. https://doi.org/10.1016/j.jue.2020.103257

Dewa, L. H., Lawrence‐Jones, A., Crandell, C., Jaques, J., Pickles, K., Lavelle, M., Pappa, S., & Aylin, P. (n.d.). Reflections, impact and recommendations of a co-produced qualitative study with young people who have experience of mental health difficulties. Health Expectations, n/a(n/a). https://doi.org/10.1111/hex.13088

McAvoy, A., Allen, B., & Nowak, M. A. (2020). Social goods dilemmas in heterogeneous societies. Nature Human Behaviour, 1–13. https://doi.org/10.1038/s41562-020-0881-2

Lancet, T. (2020). The plight of essential workers during the COVID-19 pandemic. The Lancet, 395(10237), 1587. https://doi.org/10.1016/S0140-6736(20)31200-9

Brashier, N. M., & Schacter, D. L. (2020). Aging in an Era of Fake News. Current Directions in Psychological Science, 0963721420915872. https://doi.org/10.1177/0963721420915872

Yaqub, W., Kakhidze, O., Brockman, M. L., Memon, N., & Patil, S. (2020). Effects of Credibility Indicators on Social Media News Sharing Intent. Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems, 1–14. https://doi.org/10.1145/3313831.3376213

Mitze, T., Kosfeld, R., Rode, J., & Wälde, K. (2020). Face Masks Considerably Reduce COVID-19 Cases in Germany: A Synthetic Control Method Approach (No. 13319). Institute of Labor Economics (IZA).

Arslan, G., Yildirim, M., & Wong, p. T. P. (2020, June 10). Meaningful Living, Resilience, Affective Balance, and Psychological Health Problems during COVID-19. https://doi.org/10.31234/osf.io/wsr3e

Murphy, C., Laurence, E., & Allard, A. (2020). Deep learning of stochastic contagion dynamics on complex networks. ArXiv:2006.05410 [Cond-Mat, Physics:Physics, Stat]. http://arxiv.org/abs/2006.05410

Sturniolo, S., Waites, W., Colbourn, T., Manheim, D., & Panovska-Griffiths, J. (2020). Testing, tracing and isolation in compartmental models. MedRxiv, 2020.05.14.20101808. https://doi.org/10.1101/2020.05.14.20101808

Science in the time of COVID-19. Nat Hum Behav 4, 327–328 (2020). https://doi.org/10.1038/s41562-020-0879-9

Altay, S., de Araujo, E., & Mercier, H. (2020, June 4). “If this account is true, it is most enormously wonderful”: Interestingness-if-true and the sharing of true and false news.

How Many Lives Are Lost Due to the Precautionary Principle? (n.d.). Human Progress. Retrieved June 10, 2020, from humanprogress.org/article.php

Wallis, P., & Nerlich, B. (2005). Disease metaphors in new epidemics: The UK media framing of the 2003 SARS epidemic. Social Science & Medicine, 60(11), 2629–2639. https://doi.org/10.1016/j.socscimed.2004.11.031

Chong, D., & Druckman, J. N. (2007). Framing Theory. Annual Review of Political Science, 10(1), 103–126. https://doi.org/10.1146/annurev.polisci.10.072805.103054

Marshall, B. D. L., & Galea, S. (2015). Formalizing the Role of Agent-Based Modeling in Causal Inference and Epidemiology. American Journal of Epidemiology, 181(2), 92–99. https://doi.org/10.1093/aje/kwu274

Ferguson, N., Laydon, D., Nedjati Gilani, G., Imai, N., Ainslie, K., Baguelin, M., Bhatia, S., Boonyasiri, A., Cucunuba Perez, Z., Cuomo-Dannenburg, G., Dighe, A., Dorigatti, I., Fu, H., Gaythorpe, K., Green, W., Hamlet, A., Hinsley, W., Okell, L., Van Elsland, S., … Ghani, A. (2020). Report 9: Impact of non-pharmaceutical interventions (NPIs) to reduce COVID19 mortality and healthcare demand. In 20 [Report]. https://doi.org/10.25561/77482

Layer, R. M., Fosdick, B., Larremore, D. B., Bradshaw, M., & Doherty, P. (2020). Case Study: Using Facebook Data to Monitor Adherence to Stay-at-home Orders in Colorado and Utah. MedRxiv, 2020.06.04.20122093. https://doi.org/10.1101/2020.06.04.20122093

Research, B. and S. S. at N. (2020, May 23). Standards for evidence in policy decision-making. Behavioural and Social Sciences at Nature Research. http://socialsciences.nature.com/users/399005-kai-ruggeri/posts/standards-for-evidence-in-policy-decision-making

Liu, Andrew, and Mason A. Porter. ‘Spatial Strength Centrality and the Effect of Spatial Embeddings on Network Architecture’. Physical Review E 101, no. 6 (9 June 2020): 062305. https://doi.org/10.1103/PhysRevE.101.062305.

Infurna, F. J., & Luthar, S. S. (2018). Re-evaluating the notion that resilience is commonplace: A review and distillation of directions for future research, practice, and policy. Clinical Psychology Review, 65, 43–56. https://doi.org/10.1016/j.cpr.2018.07.003

Infurna, F. J., & Jayawickreme, E. (2019). Fixing the Growth Illusion: New Directions for Research in Resilience and Posttraumatic Growth. Current Directions in Psychological Science, 28(2), 152–158. https://doi.org/10.1177/0963721419827017

Yi, Eunhee S., Matthew J. Cecchini, and Melanie C. Bois. ‘Pathologists in Pursuit of the COVID-19 Culprit’. The Lancet Infectious Diseases 0, no. 0 (8 June 2020). https://doi.org/10.1016/S1473-3099(20)30449-7.

Cinus, F., Bonchi, F., Monti, C., & Panisson, A. (2020). Generating Realistic Interest-Driven Information Cascades. Proceedings of the International AAAI Conference on Web and Social Media, 14, 107–118.

Shew, A. (2020). Let COVID-19 expand awareness of disability tech. Nature, 581(7806), 9–9. https://doi.org/10.1038/d41586-020-01312-w

Hsiang, S., Allen, D., Annan-Phan, S., Bell, K., Bolliger, I., Chong, T., Druckenmiller, H., Huang, L. Y., Hultgren, A., Krasovich, E., Lau, P., Lee, J., Rolf, E., Tseng, J., & Wu, T. (2020). The effect of large-scale anti-contagion policies on the COVID-19 pandemic. Nature, 1–9. https://doi.org/10.1038/s41586-020-2404-8

Tann, W. J.-W., Chang, E.-C., & Hooi, B. (2020). SHADOWCAST: Controlling Network Properties to Explain Graph Generation. ArXiv:2006.03774 [Cs, Stat]. http://arxiv.org/abs/2006.03774

Bravo-Hermsdorff, G., Felso, V., Ray, E., Gunderson, L. M., Helander, M. E., Maria, J., & Niv, Y. (2019). Gender and collaboration patterns in a temporal scientific authorship network. Applied Network Science, 4(1), 112. https://doi.org/10.1007/s41109-019-0214-4

Parisi, F., Squartini, T., & Garlaschelli, D. (2020). A faster horse on a safer trail: Generalized inference for the efficient reconstruction of weighted networks. New Journal of Physics, 22(5), 053053. https://doi.org/10.1088/1367-2630/ab74a7

Seetharaman, J. H. and D. (2020, May 26). Facebook Executives Shut Down Efforts to Make the Site Less Divisive. Wall Street Journal. https://www.wsj.com/articles/facebook-knows-it-encourages-division-top-executives-nixed-solutions-11590507499

The quest for a vaccine could restore faith in big pharma. (n.d.). The Economist. Retrieved June 8, 2020, from https://www.economist.com/business/2020/06/04/the-quest-for-a-vaccine-could-restore-faith-in-big-pharma

Van Mieghem, P., & Wang, F. (2020). Time dependence of susceptible-infected-susceptible epidemics on networks with nodal self-infections. Physical Review E, 101(5), 052310. https://doi.org/10.1103/PhysRevE.101.052310

Della Rossa, F., & DeLellis, P. (2020). Stochastic master stability function for noisy complex networks. Physical Review E, 101(5), 052211. https://doi.org/10.1103/PhysRevE.101.052211

The sharing economy will have to change. (n.d.). The Economist. Retrieved June 8, 2020, from https://www.economist.com/business/2020/06/04/the-sharing-economy-will-have-to-change

Ngo, S.-C., Percus, A. G., Burghardt, K., & Lerman, K. (2020). The transsortative structure of networks. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 476(2237), 20190772. https://doi.org/10.1098/rspa.2019.0772

Efron, B. (2020). Prediction, Estimation, and Attribution. Journal of the American Statistical Association, 115(530), 636–655. https://doi.org/10.1080/01621459.2020.1762613

Zhou, B., Lu, X., & Holme, P. (2020). Universal evolution patterns of degree assortativity in social networks. Social Networks, 63, 47–55. https://doi.org/10.1016/j.socnet.2020.04.004

Natera, L., Battiston, F., Iñiguez, G., & Szell, M. (2020). Extracting the multimodal fingerprint of urban transportation networks. ArXiv:2006.03435 [Physics]. http://arxiv.org/abs/2006.03435

Ortiz, E., García-Pérez, G., & Serrano, M. Á. (2020). Geometric detection of hierarchical backbones in real networks. ArXiv:2006.03207 [Physics]. http://arxiv.org/abs/2006.03207

Oliver, N., Lepri, B., Sterly, H., Lambiotte, R., Deletaille, S., Nadai, M. D., Letouzé, E., Salah, A. A., Benjamins, R., Cattuto, C., Colizza, V., Cordes, N. de, Fraiberger, S. P., Koebe, T., Lehmann, S., Murillo, J., Pentland, A., Pham, P. N., Pivetta, F., … Vinck, P. (2020). Mobile phone data for informing public health actions across the COVID-19 pandemic life cycle. Science Advances, 6(23), eabc0764. https://doi.org/10.1126/sciadv.abc0764

Riggare, S., Stecher, B., & Stamford, J. (n.d.). Patient advocates respond to ‘Utilizing Patient Advocates…’ by Feeney et al. Health Expectations, n/a(n/a). https://doi.org/10.1111/hex.13087

Attali, Y., Budescu, D., & Arieli-Attali, M. (2020). An item response approach to calibration of confidence judgments. Decision, 7(1), 1–19. https://doi.org/10.1037/dec0000111

Winman, A., Hansson, P., & Juslin, P. (2004). Subjective Probability Intervals: How to Reduce Overconfidence by Interval Evaluation. Journal of Experimental Psychology: Learning, Memory, and Cognition, 30(6), 1167–1175. https://doi.org/10.1037/0278-7393.30.6.1167

Moore, D. A., & Healy, P. J. (2008). The trouble with overconfidence. Psychological Review, 115(2), 502–517. https://doi.org/10.1037/0033-295X.115.2.502

Erev, I., Wallsten, T. S., & Budescu, D. V. (1994). Simultaneous over- and underconfidence: The role of error in judgment processes. Psychological Review, 101(3), 519–527. https://doi.org/10.1037/0033-295X.101.3.519

Steinmetz, H., Batzdorfer, V., & Bosnjak, M. (2020). The ZPID lockdown measures dataset for Germany [Report]. ZPID (Leibniz Institute for Psychology Information). http://dx.doi.org/10.23668/psycharchives.3019

Could the next generation of researchers be lost in the aftermath of Covid-19? – INGSA. (n.d.). Retrieved June 6, 2020, from https://www.ingsa.org/covidtag/covid-19-featured/ecr-future/

Gollust, Sarah E., Rebekah H. Nagler, and Erika Franklin Fowler. ‘The Emergence of COVID-19 in the U.S.: A Public Health and Political Communication Crisis’. Journal of Health Politics, Policy and Law. Accessed 5 June 2020. https://doi.org/10.1215/03616878-8641506.