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Identification of the first COVID-19 infections in the US using a retrospective analysis

Accurate detection of early COVID-19 cases is crucial to drastically reduce infection, hospitalization, and death rates. However, it remains a challenge and methods for identifying initial COVID-19 cases are urgently needed. Here, we used the results from a seroprevalence study in 50 US states to ap...

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Detalles Bibliográficos
Autores principales: García-García, David, Morales, Enrique, de la Fuente-Nunez, Cesar, Vigo, Isabel, Fonfría, Eva S., Bordehore, Cesar
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Journal Experts 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8312904/
https://www.ncbi.nlm.nih.gov/pubmed/34312619
http://dx.doi.org/10.21203/rs.3.rs-707353/v1
Descripción
Sumario:Accurate detection of early COVID-19 cases is crucial to drastically reduce infection, hospitalization, and death rates. However, it remains a challenge and methods for identifying initial COVID-19 cases are urgently needed. Here, we used the results from a seroprevalence study in 50 US states to apply our Retrospective Methodology to Estimate Daily Infections from Deaths (REMEDID) with the aim of analyzing the initial stages and spread of SARS-CoV-2 infections across the United States (US). Our retrospective data analysis revealed that the virus likely entered the country through California on December 28, 2019, which corresponds to 16 days before the officially recognized entry date established by the CDC. Thus, REMEDID provides evidence that SARS-CoV-2 entered the U.S. earlier than previously reflected in official data. Collectively, our mathematical modeling more accurately estimates the initial COVID-19 cases in the US, may be extrapolated to other countries, and may be used to retrospectively track the progress of the pandemic. Approaches such as REMEDID may enable health authorities to accelerate preventative measures aimed at controlling pandemics within weeks of their onset.