A comparative analysis of COVID-19 seroprevalence rates, observed infection rates, and infection-related mortality
ObjectivesThe COVID-19 pandemic highlighted the need for data-driven decision making in managing public health crises. This study aims to extend previous research by incorporating infection-related mortality (IRM) to evaluate the discrepancies between seroprevalence data and infection rates reported...
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Frontiers Media S.A.
2025-01-01
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| Series: | Frontiers in Public Health |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fpubh.2025.1504524/full |
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| author | Eric W. Ford Kunal N. Patel Holly Ann Baus Shannon Valenti Jennifer A. Croker Robert P. Kimberly Steven E. Reis Matthew J. Memoli |
| author_facet | Eric W. Ford Kunal N. Patel Holly Ann Baus Shannon Valenti Jennifer A. Croker Robert P. Kimberly Steven E. Reis Matthew J. Memoli |
| author_sort | Eric W. Ford |
| collection | DOAJ |
| description | ObjectivesThe COVID-19 pandemic highlighted the need for data-driven decision making in managing public health crises. This study aims to extend previous research by incorporating infection-related mortality (IRM) to evaluate the discrepancies between seroprevalence data and infection rates reported to the Centers for Disease Control and Prevention (CDC), and to assess the implications for public health policy.Study designWe conducted a comparative analysis of seroprevalence data collected as part of an NIH study and CDC-reported infection rates across ten U.S. regions, focusing on their correlation with IRM calculations.MethodsThe analysis includes a revision of prior estimates of IRM using updated seroprevalence rates. Correlations were calculated and their statistical relevance assessed.ResultsFindings indicate that COVID-19 is approximately 2.7 times more prevalent than what CDC infection data suggest. Utilizing the lower CDC-reported rates to calculate IRM leads to a significant overestimation by a factor of 2.7. When both seroprevalence and CDC infection data are combined, the overestimation of IRM increases to a factor of 3.79.ConclusionThe study highlights the importance of integrating multiple data dimensions to accurately understand and manage public health emergencies. The results suggest that public health agencies should enhance their capacity for collecting and analyzing seroprevalence data regularly, given its stronger correlation with IRM than other estimates. This approach will better inform policy decisions and direct effective interventions. |
| format | Article |
| id | doaj-art-7313b0f4216242f69f333170862d18fa |
| institution | Kabale University |
| issn | 2296-2565 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Frontiers Media S.A. |
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| series | Frontiers in Public Health |
| spelling | doaj-art-7313b0f4216242f69f333170862d18fa2025-01-28T06:41:29ZengFrontiers Media S.A.Frontiers in Public Health2296-25652025-01-011310.3389/fpubh.2025.15045241504524A comparative analysis of COVID-19 seroprevalence rates, observed infection rates, and infection-related mortalityEric W. Ford0Kunal N. Patel1Holly Ann Baus2Shannon Valenti3Jennifer A. Croker4Robert P. Kimberly5Steven E. Reis6Matthew J. Memoli7School of Public Health, University of Alabama at Birmingham, Birmingham, AL, United StatesCollege of Health and Human Sciences, Northern Illinois University, Dekalb, IL, United StatesClinical Studies Unit, Laboratory of Infectious Diseases, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, United StatesClinical and Translational Science Institute, University of Pittsburgh, Pittsburgh, PA, United StatesCenter for Clinical and Translational Science, School of Medicine, University of Alabama at Birmingham, Birmingham, AL, United StatesCenter for Clinical and Translational Science, School of Medicine, University of Alabama at Birmingham, Birmingham, AL, United StatesClinical and Translational Science Institute, University of Pittsburgh, Pittsburgh, PA, United StatesClinical Studies Unit, Laboratory of Infectious Diseases, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, United StatesObjectivesThe COVID-19 pandemic highlighted the need for data-driven decision making in managing public health crises. This study aims to extend previous research by incorporating infection-related mortality (IRM) to evaluate the discrepancies between seroprevalence data and infection rates reported to the Centers for Disease Control and Prevention (CDC), and to assess the implications for public health policy.Study designWe conducted a comparative analysis of seroprevalence data collected as part of an NIH study and CDC-reported infection rates across ten U.S. regions, focusing on their correlation with IRM calculations.MethodsThe analysis includes a revision of prior estimates of IRM using updated seroprevalence rates. Correlations were calculated and their statistical relevance assessed.ResultsFindings indicate that COVID-19 is approximately 2.7 times more prevalent than what CDC infection data suggest. Utilizing the lower CDC-reported rates to calculate IRM leads to a significant overestimation by a factor of 2.7. When both seroprevalence and CDC infection data are combined, the overestimation of IRM increases to a factor of 3.79.ConclusionThe study highlights the importance of integrating multiple data dimensions to accurately understand and manage public health emergencies. The results suggest that public health agencies should enhance their capacity for collecting and analyzing seroprevalence data regularly, given its stronger correlation with IRM than other estimates. This approach will better inform policy decisions and direct effective interventions.https://www.frontiersin.org/articles/10.3389/fpubh.2025.1504524/fullCOVID-19 surveillanceseroprevalenceCOVID-19 mortality riskCOVID-19 disparitiesCOVID-19 regional differences |
| spellingShingle | Eric W. Ford Kunal N. Patel Holly Ann Baus Shannon Valenti Jennifer A. Croker Robert P. Kimberly Steven E. Reis Matthew J. Memoli A comparative analysis of COVID-19 seroprevalence rates, observed infection rates, and infection-related mortality Frontiers in Public Health COVID-19 surveillance seroprevalence COVID-19 mortality risk COVID-19 disparities COVID-19 regional differences |
| title | A comparative analysis of COVID-19 seroprevalence rates, observed infection rates, and infection-related mortality |
| title_full | A comparative analysis of COVID-19 seroprevalence rates, observed infection rates, and infection-related mortality |
| title_fullStr | A comparative analysis of COVID-19 seroprevalence rates, observed infection rates, and infection-related mortality |
| title_full_unstemmed | A comparative analysis of COVID-19 seroprevalence rates, observed infection rates, and infection-related mortality |
| title_short | A comparative analysis of COVID-19 seroprevalence rates, observed infection rates, and infection-related mortality |
| title_sort | comparative analysis of covid 19 seroprevalence rates observed infection rates and infection related mortality |
| topic | COVID-19 surveillance seroprevalence COVID-19 mortality risk COVID-19 disparities COVID-19 regional differences |
| url | https://www.frontiersin.org/articles/10.3389/fpubh.2025.1504524/full |
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