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Graphical Trajectory Comparison to Identify Errors in Data of COVID-19: A Cross-Country Analysis

Data from the early stage of a novel infectious disease outbreak provide vital information in risk assessment, prediction, and precise disease management. Since the first reported case of COVID-19, the pattern of the novel coronavirus transmission in Wuhan has become the interest of researchers in e...

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Detalles Bibliográficos
Autores principales: Yao, Lan, Dong, Wei, Wan, Jim Y., Howard, Scott C., Li, Minghui, Graff, Joyce Carolyn
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8537769/
https://www.ncbi.nlm.nih.gov/pubmed/34683095
http://dx.doi.org/10.3390/jpm11100955
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author Yao, Lan
Dong, Wei
Wan, Jim Y.
Howard, Scott C.
Li, Minghui
Graff, Joyce Carolyn
author_facet Yao, Lan
Dong, Wei
Wan, Jim Y.
Howard, Scott C.
Li, Minghui
Graff, Joyce Carolyn
author_sort Yao, Lan
collection PubMed
description Data from the early stage of a novel infectious disease outbreak provide vital information in risk assessment, prediction, and precise disease management. Since the first reported case of COVID-19, the pattern of the novel coronavirus transmission in Wuhan has become the interest of researchers in epidemiology and public health. To thoroughly map the mechanism of viral spreading, we used the patterns of data at the early onset of COVID-19 from seven countries to estimate the time lag between peak days of cases and deaths. This study compared these data with those of Wuhan and estimated the natural history of disease across the infected population and the time lag. The findings suggest that comparative analyses of data from different regions and countries reveal the differences between peaks of cases and deaths caused by COVID-19 and the incomplete and underestimated cases in Wuhan. Different countries may show different patterns of cases peak days, deaths peak days, and peak periods. Error in the early COVID-19 statistics in Brazil was identified. This study provides sound evidence for policymakers to understand the local circumstances in diagnosing the health of a population and propose precise and timely public health interventions to control and prevent infectious diseases.
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spelling pubmed-85377692021-10-24 Graphical Trajectory Comparison to Identify Errors in Data of COVID-19: A Cross-Country Analysis Yao, Lan Dong, Wei Wan, Jim Y. Howard, Scott C. Li, Minghui Graff, Joyce Carolyn J Pers Med Article Data from the early stage of a novel infectious disease outbreak provide vital information in risk assessment, prediction, and precise disease management. Since the first reported case of COVID-19, the pattern of the novel coronavirus transmission in Wuhan has become the interest of researchers in epidemiology and public health. To thoroughly map the mechanism of viral spreading, we used the patterns of data at the early onset of COVID-19 from seven countries to estimate the time lag between peak days of cases and deaths. This study compared these data with those of Wuhan and estimated the natural history of disease across the infected population and the time lag. The findings suggest that comparative analyses of data from different regions and countries reveal the differences between peaks of cases and deaths caused by COVID-19 and the incomplete and underestimated cases in Wuhan. Different countries may show different patterns of cases peak days, deaths peak days, and peak periods. Error in the early COVID-19 statistics in Brazil was identified. This study provides sound evidence for policymakers to understand the local circumstances in diagnosing the health of a population and propose precise and timely public health interventions to control and prevent infectious diseases. MDPI 2021-09-25 /pmc/articles/PMC8537769/ /pubmed/34683095 http://dx.doi.org/10.3390/jpm11100955 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Yao, Lan
Dong, Wei
Wan, Jim Y.
Howard, Scott C.
Li, Minghui
Graff, Joyce Carolyn
Graphical Trajectory Comparison to Identify Errors in Data of COVID-19: A Cross-Country Analysis
title Graphical Trajectory Comparison to Identify Errors in Data of COVID-19: A Cross-Country Analysis
title_full Graphical Trajectory Comparison to Identify Errors in Data of COVID-19: A Cross-Country Analysis
title_fullStr Graphical Trajectory Comparison to Identify Errors in Data of COVID-19: A Cross-Country Analysis
title_full_unstemmed Graphical Trajectory Comparison to Identify Errors in Data of COVID-19: A Cross-Country Analysis
title_short Graphical Trajectory Comparison to Identify Errors in Data of COVID-19: A Cross-Country Analysis
title_sort graphical trajectory comparison to identify errors in data of covid-19: a cross-country analysis
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8537769/
https://www.ncbi.nlm.nih.gov/pubmed/34683095
http://dx.doi.org/10.3390/jpm11100955
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