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
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Publicado: American Society for Microbiology 2020
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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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