Who Is Most Susceptible To COVID Misinformation? (2021, August 11). News. https://www.wgbh.org/news/science-and-technology/2021/08/11/who-is-most-susceptible-to-covid-misinformation

Mizutaka, S., Mori, K., & Hasegawa, T. (2021). Synergistic epidemic spreading in correlated networks. ArXiv:2105.08992 [Physics, q-Bio]. http://arxiv.org/abs/2105.08992

Holme, P. (2021). Fast and principled simulations of the SIR model on temporal networks. PLOS ONE, 16(2), e0246961. https://doi.org/10.1371/journal.pone.0246961

Humphries, R., Mulchrone, K., Tratalos, J., More, S., & Hövel, P. (2020). A Systematic Framework of Modelling Epidemics on Temporal Networks. ArXiv:2009.11965 [Nlin, Physics:Physics]. http://arxiv.org/abs/2009.11965

Krapivsky, P. L. ‘An Infection Process near Criticality: Influence of the Initial Condition’. ArXiv:2009.08940 [Cond-Mat, Physics:Physics, q-Bio], 18 September 2020. http://arxiv.org/abs/2009.08940.

Moser, Christian A, and Pierre Yared. ‘Pandemic Lockdown: The Role of Government Commitment’. Working Paper. Working Paper Series. National Bureau of Economic Research, April 2020. https://doi.org/10.3386/w27062.

Stock, James H. ‘Data Gaps and the Policy Response to the Novel Coronavirus’. Working Paper. Working Paper Series. National Bureau of Economic Research, March 2020. https://doi.org/10.3386/w26902.

Holme, P. (2020). Fast and principled simulations of the SIR model on temporal networks. ArXiv:2007.14386 [Physics, q-Bio]. http://arxiv.org/abs/2007.14386

Koerth, M. (2020, March 31). Why It’s So Freaking Hard To Make A Good COVID-19 Model. FiveThirtyEight. https://fivethirtyeight.com/features/why-its-so-freaking-hard-to-make-a-good-covid-19-model/

Wise, J. (2020). Covid-19: Surveys indicate low infection level in community. BMJ, m1992. https://doi.org/10.1136/bmj.m1992

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

Zhang, J., Litvinova, M., Liang, Y., Wang, Y., Wang, W., Zhao, S., Wu, Q., Merler, S., Viboud, C., Vespignani, A., Ajelli, M., & Yu, H. (2020). Changes in contact patterns shape the dynamics of the COVID-19 outbreak in China. Science, eabb8001. https://doi.org/10.1126/science.abb8001

Banerjee, D. (2020). The Impact of Covid‐19 Pandemic on Elderly Mental Health. International Journal of Geriatric Psychiatry, gps.5320. https://doi.org/10.1002/gps.5320

Jordan, R. E., & Adab, P. (2020). Who is most likely to be infected with SARS-CoV-2? The Lancet Infectious Diseases, S1473309920303959. https://doi.org/10.1016/S1473-3099(20)30395-9

Delvin, H. (2020, May 13). Are children less susceptible to coronavirus? The Guardian. https://www.theguardian.com/world/2020/may/13/are-children-less-susceptible-to-coronavirus

Masuda, N., & Holme, P. (2020). Small inter-event times govern epidemic spreading on networks. Physical Review Research, 2(2), 023163. https://doi.org/10.1103/PhysRevResearch.2.023163

Inglesby, T. V. (2020). Public Health Measures and the Reproduction Number of SARS-CoV-2. JAMA. https://doi.org/10.1001/jama.2020.7878