Managing COVID-19 Pandemic across Geography and Demography

This page provides resources, original research, and tools that could help individuals and policy makers with a scientific, balanced, and evidence-based approach to manage and navigate the COVID-19 Pandemic across the globe.

Watch my colloquium at Perimeter Institute (July 29, 2020) about this work (slides in keynote and PDF)

Read our paper: 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

From our paper: This figure shows the phase portrait of COVID-19 epidemic in NYC, plotting Daily vs Total Mortality per population. The green disc shows the “herd immunity threshold” which is the fixed point of the epidemic, at normal social mobility. The red curves are predicted trajectories at normal mobility, while the blue curves are for -42% mobility. The black curve shows the 7-day rolling average of the reported mortality.

Read my blog post: Diverse Drivers of a Pandemic: A Physical Model for COVID-19

United States COVID Immunity Maps (as of July 7th, 2020)

These maps show the immunity, and/or rate of relative growth of COVID mortality in different US counties, should social mobility returns to its normal (pre-Pandemic) level. As of July 7th, 2020, the best-fit model predicts that 12% ± 3% of US population live in counties that have passed herd immunity threshold, i.e. the COVID-19 daily mortality should not grow at resumption of normal social activity.

Counties in cyan have passed the immunity threshold, while those in blue are within 1-sigma threshold of immunity
Predicted relative mortality growth rate (in units of 1/day) for US counties, in lieu of social distancing or other interventions
Significance (growth rate divided by its error), or confidence in positive COVID growth across the US, at normal social mobility