Mathematics of Public Health

Diverse local epidemics reveal the distinct effects of population density, demographics, climate, depletion of susceptibles, and intervention in the first wave of COVID-19 in the United States (N. Ashfordi, B. Holder, M. Bahrami, D. Lichtblau).- Describing, modelling and forecasting the spatial and temporal spread of COVID-19 (J. Arino).- A logistic growth model with logistically varying carrying capacity for Covid-19 deaths using data from Ontario, Canada (G. Bucyibaruta, C.B. Dean, E.M. Renouf).- COVID-19 in Ontario (R. Fields, L Humphrey, E.W. Thommes, M.G. Cojocaru).-  Sub-epidemic model forecasts during the first wave of the COVID-19 pandemic in the USA and European hotspots (G. Chowell, R. Rothenberg, K. Roosa, A. Tariq, J.M. Hyman, R. Luo).- A Model on the Large Scale Use of Convalescent Plasma to Treat Patients with Severe Symptoms (X. Huo).- Don't wait, re-escalate: delayed action results in longer duration of COVID-19 restrictions (A. Hurford, J. Watmough).- Generalized Additive Models to Capture the Death Rates in Canada COVID-19 (F. Izadi).- Real-time prediction of the end of an epidemic wave (Q. Griette, Z. Liu, P. Magal, R.N. Thompson).- The Effect that Heterogeneity in Social Distancing Has on the Infection Peak (C. McCluskey).- Forecasting PPE Demand for Ontario Acute Care Hospitals During COVID-19 (B. Sander).- Learning COVID-19 Mitigation Strategies using Reinforcement Learning (N. Denis, A. El-Hajj, B Drummond, Y. Abiza, K.C. Gopaluni).- Joint Modeling of Hospitalization and Mortality of Ontario Covid-19 cases (D.Z. Xi).- Evaluating the risk of reopening the border: a case study of Ontario (Canada) to New York (USA) using mathematical modeling (P. Yuan, E. Aruffo, Q. Li, J. Li, Y. Tan, T. Zheng, J. David, N. Ogden, E. Gatov, E. Gournis, S. Collier, B. Sander, G. Fan, J. Heffernan, J. Li, J.D. Kong, J. Arino, J. Belair, J. Watmough, H. Zhu).- Optimal staged reopening schedule based on ICU capacity (K. Nah, M. Chen, A.