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Determinants of differences in RT-PCR testing rates among Southeast Asian countries during the first six months of the COVID-19 pandemic

A positive correlation has been demonstrated between gross domestic product (GDP) per capita and COVID-19 tests per 1000 people. Although frequently used as an indicator of economic performance, GDP per capita does not directly reflect income distribution inequalities and imposed health costs. In th...

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Autores principales: Van Haute, Michael, Agagon, Alexandra, Gumapac, Franz Froilan, Anticuando, Marie Abigail, Coronel, Dianne Nicole, David, Mary Coleen, Davocol, Dan Ardie, Din, Eunice Jairah, Grey, Carlos Alfonso, Lee, Young Hee, Muyot, Marvin Bryan, Ragasa, Charissma Leiah, Shao, Genesis, Tamaña, Cailin Adrienne, Uy, Trixia Scholastica, De Silos, Jeriel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10629619/
https://www.ncbi.nlm.nih.gov/pubmed/37934719
http://dx.doi.org/10.1371/journal.pgph.0002593
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author Van Haute, Michael
Agagon, Alexandra
Gumapac, Franz Froilan
Anticuando, Marie Abigail
Coronel, Dianne Nicole
David, Mary Coleen
Davocol, Dan Ardie
Din, Eunice Jairah
Grey, Carlos Alfonso
Lee, Young Hee
Muyot, Marvin Bryan
Ragasa, Charissma Leiah
Shao, Genesis
Tamaña, Cailin Adrienne
Uy, Trixia Scholastica
De Silos, Jeriel
author_facet Van Haute, Michael
Agagon, Alexandra
Gumapac, Franz Froilan
Anticuando, Marie Abigail
Coronel, Dianne Nicole
David, Mary Coleen
Davocol, Dan Ardie
Din, Eunice Jairah
Grey, Carlos Alfonso
Lee, Young Hee
Muyot, Marvin Bryan
Ragasa, Charissma Leiah
Shao, Genesis
Tamaña, Cailin Adrienne
Uy, Trixia Scholastica
De Silos, Jeriel
author_sort Van Haute, Michael
collection PubMed
description A positive correlation has been demonstrated between gross domestic product (GDP) per capita and COVID-19 tests per 1000 people. Although frequently used as an indicator of economic performance, GDP per capita does not directly reflect income distribution inequalities and imposed health costs. In this longitudinal ecological study, we aimed to determine if, besides GDP per capita, indicators relating to governance, public health measures enforcement, and health and research investment explain differences in RT-PCR testing rates among countries in Southeast Asia (SEA) during the first six months of the COVID-19 pandemic. Using open-access COVID-19 panel data, we estimated the effect of various indicators (GDP per capita, health expenditure per capita, number of researchers per one million population, corruption perceptions index, stringency index, regional authority index) on daily COVID-19 testing by performing fixed-effects negative binomial regression. After accounting for all indicators, the number of daily confirmed COVID-19 cases, and population density, the model provided a 2019 GDP per capita coefficient of 0.0046330 (95% CI: 0.0040171, 0.0052488; p <0.001), indicating that a rise in 2019 GDP per capita by 100 international dollars is associated with a 46.33% increase in the number of daily tests performed. Additionally, all indicators were significantly associated with the daily number of RT-PCR testing on multivariable analysis. In conclusion, we identified different country-level indicators significantly associated with differences in COVID-19 testing rates among SEA countries. Due to the study’s ecological design, we caution on applying our results to the individual level given potential for systematic differences between the included countries. Additional investigation is likewise needed to understand how government expenditure on healthcare may have impacted COVID-19 testing capacity during the initial stages of the pandemic.
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spelling pubmed-106296192023-11-08 Determinants of differences in RT-PCR testing rates among Southeast Asian countries during the first six months of the COVID-19 pandemic Van Haute, Michael Agagon, Alexandra Gumapac, Franz Froilan Anticuando, Marie Abigail Coronel, Dianne Nicole David, Mary Coleen Davocol, Dan Ardie Din, Eunice Jairah Grey, Carlos Alfonso Lee, Young Hee Muyot, Marvin Bryan Ragasa, Charissma Leiah Shao, Genesis Tamaña, Cailin Adrienne Uy, Trixia Scholastica De Silos, Jeriel PLOS Glob Public Health Research Article A positive correlation has been demonstrated between gross domestic product (GDP) per capita and COVID-19 tests per 1000 people. Although frequently used as an indicator of economic performance, GDP per capita does not directly reflect income distribution inequalities and imposed health costs. In this longitudinal ecological study, we aimed to determine if, besides GDP per capita, indicators relating to governance, public health measures enforcement, and health and research investment explain differences in RT-PCR testing rates among countries in Southeast Asia (SEA) during the first six months of the COVID-19 pandemic. Using open-access COVID-19 panel data, we estimated the effect of various indicators (GDP per capita, health expenditure per capita, number of researchers per one million population, corruption perceptions index, stringency index, regional authority index) on daily COVID-19 testing by performing fixed-effects negative binomial regression. After accounting for all indicators, the number of daily confirmed COVID-19 cases, and population density, the model provided a 2019 GDP per capita coefficient of 0.0046330 (95% CI: 0.0040171, 0.0052488; p <0.001), indicating that a rise in 2019 GDP per capita by 100 international dollars is associated with a 46.33% increase in the number of daily tests performed. Additionally, all indicators were significantly associated with the daily number of RT-PCR testing on multivariable analysis. In conclusion, we identified different country-level indicators significantly associated with differences in COVID-19 testing rates among SEA countries. Due to the study’s ecological design, we caution on applying our results to the individual level given potential for systematic differences between the included countries. Additional investigation is likewise needed to understand how government expenditure on healthcare may have impacted COVID-19 testing capacity during the initial stages of the pandemic. Public Library of Science 2023-11-07 /pmc/articles/PMC10629619/ /pubmed/37934719 http://dx.doi.org/10.1371/journal.pgph.0002593 Text en © 2023 Van Haute et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Van Haute, Michael
Agagon, Alexandra
Gumapac, Franz Froilan
Anticuando, Marie Abigail
Coronel, Dianne Nicole
David, Mary Coleen
Davocol, Dan Ardie
Din, Eunice Jairah
Grey, Carlos Alfonso
Lee, Young Hee
Muyot, Marvin Bryan
Ragasa, Charissma Leiah
Shao, Genesis
Tamaña, Cailin Adrienne
Uy, Trixia Scholastica
De Silos, Jeriel
Determinants of differences in RT-PCR testing rates among Southeast Asian countries during the first six months of the COVID-19 pandemic
title Determinants of differences in RT-PCR testing rates among Southeast Asian countries during the first six months of the COVID-19 pandemic
title_full Determinants of differences in RT-PCR testing rates among Southeast Asian countries during the first six months of the COVID-19 pandemic
title_fullStr Determinants of differences in RT-PCR testing rates among Southeast Asian countries during the first six months of the COVID-19 pandemic
title_full_unstemmed Determinants of differences in RT-PCR testing rates among Southeast Asian countries during the first six months of the COVID-19 pandemic
title_short Determinants of differences in RT-PCR testing rates among Southeast Asian countries during the first six months of the COVID-19 pandemic
title_sort determinants of differences in rt-pcr testing rates among southeast asian countries during the first six months of the covid-19 pandemic
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10629619/
https://www.ncbi.nlm.nih.gov/pubmed/37934719
http://dx.doi.org/10.1371/journal.pgph.0002593
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