Authors: Vineet Desai; Jessie Duggan; Jakub Glowala; Manav Gupta; Kiryung Kim; Gina Liu; Katherine McDaniel, MSc; Katherine Nabel; Himaja Nagireddy; Deborah Plana; Emily Rencsok; Connor Verheyen; Lily Zhong
Editor: Himaja Nagireddy
Reviewers: Wolfram Goessling, MD, PhD; Andrea Wershof Schwartz, MD, MPH; William Hanage, PhD; Rebecca Kahn, MS; James Hay, PhD
Highlight of Updates (1/03/21): Pending faculty review
Glossary: Added definition of presymptomatic vs. asymptomatic
Added section on differential disease and mortality burden by race
Included information on super spreading events in nursing homes
Updated South Korea Case Study
Created the Re-opening Section
Added section on Mental Health Concerns
Added section on Equitable Vaccine Distribution
In this module, we move from the biology and pathophysiology of SARS-CoV-2 to its implications at a population level. We start with an introduction to epidemiological terms. To understand where the epidemic is now, we link a curated set of continuously updating resources. Current estimates for the U.S. indicate a caseload 10-50x of what is currently recognized, with asymptomatic, presymptomatic, and mildly symptomatic people as a major contributor to transmission. Next, we give an overview of the factors used to predict where the epidemic is going in the U.S., focusing on the concept of exponential growth. Mathematically and empirically, small modifications to the parameters of this growth can “flatten the curve," which lengthens the time over which severely ill people present, providing the healthcare system more time to prepare to treat patients and scientists time to test and optimize new treatment strategies to reduce mortality. At this phase, the U.S. is primarily attempting to flatten the curve by “social distancing.” Modeling from the UK indicates social distancing may be required for months.
We end with three case studies to contextualize these epidemiology principles. The influenza pandemic of 1918 prompted different responses from three U.S. cities, with three dramatically different outcomes for morbidity and mortality. The 2009 H1N1 pandemic, a frequent foil to COVID-19, required less disruption to control due to a lower R0 and case fatality rate, as well as faster testing, prior population immunity and pre-existing antiviral treatments. In confronting COVID-19, South Korea presents a contemporary example of a country that rapidly scaled up testing, contact tracing, and social distancing without nationwide lockdown, and has brought new cases to a minimum.
By the end of this module, medical students should be able to:
Define R0, Re, incubation period, serial interval, epidemic curve, community transmission, social distancing, and flattening the curve as they pertain to COVID-19
Access a reliable source of the latest epidemiologic information about COVID-19
Describe how changing epidemiological parameters changes disease dynamics
Contrast three cases that illustrate how nonpharmaceutical interventions save lives in a pandemic
Sanderson, G. Exponential Growth and Epidemics. Youtube, 3.8.20
Stevens, H. Why outbreaks like coronavirus spread exponentially, and how to “flatten the curve”. Washington Post, 3.14.20.
Scott, D. Flattening the Curve Worked- Until It Didn't. Vox, 12.31.20
Bitton, A. Social Distancing: This Is Not a Snow Day. Ariadne Labs, 3.20.20
Pueyo, T. Coronavirus: The Hammer and the Dance. Medium, 3.19.2020.
Scudellari, M. How the Pandemic May Play Out in 2021 and Beyond. Nature, 8.5.2020
Baird, R. What Went Wrong with Coronavirus Testing in the U.S. New Yorker, 3.16.20
Barry, J. The Single Most Important Lesson From the 1918 Influenza. New York Times, 3.17.20.