Journal
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
Volume 117, Issue 51, Pages 32764-32771Publisher
NATL ACAD SCIENCES
DOI: 10.1073/pnas.2009911117
Keywords
epidemics; epidemiology; nonlinear dynamics; control; public health
Categories
Funding
- Simons Foundation [329108]
- Army Research Office [W911NF1910384]
- NIH [1R01AI46592-01]
- NSF [1806606, 1829636, 2008855, 1953694]
- Canadian Institutes of Health Research
- Natural Sciences and Engineering Research Council of Canada
- Direct For Mathematical & Physical Scien
- Division Of Physics [1806606] Funding Source: National Science Foundation
- Division of Computing and Communication Foundations
- Direct For Computer & Info Scie & Enginr [2008855] Funding Source: National Science Foundation
- Division Of Ocean Sciences
- Directorate For Geosciences [1829636] Funding Source: National Science Foundation
- Div Of Electrical, Commun & Cyber Sys
- Directorate For Engineering [1953694] Funding Source: National Science Foundation
- U.S. Department of Defense (DOD) [W911NF1910384] Funding Source: U.S. Department of Defense (DOD)
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The COVID-19 pandemic has caused more than 1,000,000 reported deaths globally, of which more than 200,000 have been reported in the United States as of October 1, 2020. Public health interventions have had significant impacts in reducing transmission and in averting even more deaths. Nonetheless, in many jurisdictions, the decline of cases and fatalities after apparent epidemic peaks has not been rapid. Instead, the asymmetric decline in cases appears, in most cases, to be consistent with plateau- or shoulder-like phenomena-a qualitative observation reinforced by a symmetry analysis of US state-level fatality data. Here we explore a model of fatality-driven awareness in which individual protective measures increase with death rates. In this model, fast increases to the peak are often followed by plateaus, shoulders, and lag-driven oscillations. The asymmetric shape of model-predicted incidence and fatality curves is consistent with observations from many jurisdictions. Yet, in contrast to model predictions, we find that population-level mobility metrics usually increased from low levels before fatalities reached an initial peak. We show that incorporating fatigue and long-term behavior change can reconcile the apparent premature relaxation of mobility reductions and help understand when post-peak dynamics are likely to lead to a resurgence of cases.
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