Oscillations in U.S. COVID-19 Incidence and Mortality Data Reflect Diagnostic and Reporting Factors

ABSTRACT The coronavirus disease 2019 (COVID-19) pandemic currently in process differs from other infectious disease calamities that have previously plagued humanity in the vast amount of information that is produced each day, which includes daily estimates of the disease incidence and mortality dat...

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Autores principales:	Aviv Bergman, Yehonatan Sella, Peter Agre, Arturo Casadevall
Formato:	article
Lenguaje:	EN
Publicado:	American Society for Microbiology 2020
Materias:	COVID-19 coronavirus epidemiology Microbiology QR1-502
Acceso en línea:	https://doaj.org/article/d026d75f016248bcb3eb9aa93f217fc3
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spelling	oai:doaj.org-article:d026d75f016248bcb3eb9aa93f217fc32021-12-02T19:46:20ZOscillations in U.S. COVID-19 Incidence and Mortality Data Reflect Diagnostic and Reporting Factors10.1128/mSystems.00544-202379-5077https://doaj.org/article/d026d75f016248bcb3eb9aa93f217fc32020-08-01T00:00:00Zhttps://journals.asm.org/doi/10.1128/mSystems.00544-20https://doaj.org/toc/2379-5077ABSTRACT The coronavirus disease 2019 (COVID-19) pandemic currently in process differs from other infectious disease calamities that have previously plagued humanity in the vast amount of information that is produced each day, which includes daily estimates of the disease incidence and mortality data. Apart from providing actionable information to public health authorities on the trend of the pandemic, the daily incidence reflects the process of disease in a susceptible population and thus reflects the pathogenesis of COVID-19, the public health response, and diagnosis and reporting. Both new daily cases and daily mortality data in the United States exhibit periodic oscillatory patterns. By analyzing New York City (NYC) and Los Angeles (LA) testing data, we demonstrate that this oscillation in the number of cases can be strongly explained by the daily variation in testing. This seems to rule out alternative hypotheses, such as increased infections on certain days of the week, as driving this oscillation. Similarly, we show that the apparent oscillation in mortality in the U.S. data are mostly an artifact of reporting, which disappears in data sets that record death by episode date, such as the NYC and LA data sets. Periodic oscillations in COVID-19 incidence and mortality data reflect testing and reporting practices and contingencies. Thus, these contingencies should be considered first prior to suggesting biological mechanisms. IMPORTANCE The incidence and mortality data for the COVID-19 data in the United States show periodic oscillations, giving the curve a distinctive serrated pattern. In this study, we show that these periodic highs and lows in incidence and mortality data are due to daily differences in testing for the virus and death reporting, respectively. These findings are important because they provide an explanation based on public health practices and shortcomings rather than biological explanations, such as infection dynamics. In other words, when oscillations occur in epidemiological data, a search for causes should begin with how the public health system produces and reports the information before considering other causes, such as infection cycles and higher incidences of events on certain days. Our results suggest that when oscillations occur in epidemiological data, this may be a signal that there are shortcomings in the public health system generating that information.Aviv BergmanYehonatan SellaPeter AgreArturo CasadevallAmerican Society for MicrobiologyarticleCOVID-19coronavirusepidemiologyMicrobiologyQR1-502ENmSystems, Vol 5, Iss 4 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	COVID-19 coronavirus epidemiology Microbiology QR1-502
spellingShingle	COVID-19 coronavirus epidemiology Microbiology QR1-502 Aviv Bergman Yehonatan Sella Peter Agre Arturo Casadevall Oscillations in U.S. COVID-19 Incidence and Mortality Data Reflect Diagnostic and Reporting Factors
description	ABSTRACT The coronavirus disease 2019 (COVID-19) pandemic currently in process differs from other infectious disease calamities that have previously plagued humanity in the vast amount of information that is produced each day, which includes daily estimates of the disease incidence and mortality data. Apart from providing actionable information to public health authorities on the trend of the pandemic, the daily incidence reflects the process of disease in a susceptible population and thus reflects the pathogenesis of COVID-19, the public health response, and diagnosis and reporting. Both new daily cases and daily mortality data in the United States exhibit periodic oscillatory patterns. By analyzing New York City (NYC) and Los Angeles (LA) testing data, we demonstrate that this oscillation in the number of cases can be strongly explained by the daily variation in testing. This seems to rule out alternative hypotheses, such as increased infections on certain days of the week, as driving this oscillation. Similarly, we show that the apparent oscillation in mortality in the U.S. data are mostly an artifact of reporting, which disappears in data sets that record death by episode date, such as the NYC and LA data sets. Periodic oscillations in COVID-19 incidence and mortality data reflect testing and reporting practices and contingencies. Thus, these contingencies should be considered first prior to suggesting biological mechanisms. IMPORTANCE The incidence and mortality data for the COVID-19 data in the United States show periodic oscillations, giving the curve a distinctive serrated pattern. In this study, we show that these periodic highs and lows in incidence and mortality data are due to daily differences in testing for the virus and death reporting, respectively. These findings are important because they provide an explanation based on public health practices and shortcomings rather than biological explanations, such as infection dynamics. In other words, when oscillations occur in epidemiological data, a search for causes should begin with how the public health system produces and reports the information before considering other causes, such as infection cycles and higher incidences of events on certain days. Our results suggest that when oscillations occur in epidemiological data, this may be a signal that there are shortcomings in the public health system generating that information.
format	article
author	Aviv Bergman Yehonatan Sella Peter Agre Arturo Casadevall
author_facet	Aviv Bergman Yehonatan Sella Peter Agre Arturo Casadevall
author_sort	Aviv Bergman
title	Oscillations in U.S. COVID-19 Incidence and Mortality Data Reflect Diagnostic and Reporting Factors
title_short	Oscillations in U.S. COVID-19 Incidence and Mortality Data Reflect Diagnostic and Reporting Factors
title_full	Oscillations in U.S. COVID-19 Incidence and Mortality Data Reflect Diagnostic and Reporting Factors
title_fullStr	Oscillations in U.S. COVID-19 Incidence and Mortality Data Reflect Diagnostic and Reporting Factors
title_full_unstemmed	Oscillations in U.S. COVID-19 Incidence and Mortality Data Reflect Diagnostic and Reporting Factors
title_sort	oscillations in u.s. covid-19 incidence and mortality data reflect diagnostic and reporting factors
publisher	American Society for Microbiology
publishDate	2020
url	https://doaj.org/article/d026d75f016248bcb3eb9aa93f217fc3
work_keys_str_mv	AT avivbergman oscillationsinuscovid19incidenceandmortalitydatareflectdiagnosticandreportingfactors AT yehonatansella oscillationsinuscovid19incidenceandmortalitydatareflectdiagnosticandreportingfactors AT peteragre oscillationsinuscovid19incidenceandmortalitydatareflectdiagnosticandreportingfactors AT arturocasadevall oscillationsinuscovid19incidenceandmortalitydatareflectdiagnosticandreportingfactors
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Oscillations in U.S. COVID-19 Incidence and Mortality Data Reflect Diagnostic and Reporting Factors

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