SARS-CoV-2 transmission dynamics in Mozambique and Zimbabwe during the first 3 years of the pandemic
The 2019 emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its rapid spread created a public health emergency of international concern. However, the impact of the pandemic in Sub-Saharan Africa, as documented in cases, hospitalizations and deaths, appears far lower than i...
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The Royal Society
2025-01-01
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| Series: | Royal Society Open Science |
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| Online Access: | https://royalsocietypublishing.org/doi/10.1098/rsos.241275 |
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| author | Roselyn F. Kaondera-Shava Marta Galanti Matteo Perini Jiyeon Suh Shannon M. Farley Sergio Chicumbe Ilesh Jani Annette Cassy Ivalda Macicame Naisa Manafe Wafaa El-Sadr Jeffrey Shaman |
| author_facet | Roselyn F. Kaondera-Shava Marta Galanti Matteo Perini Jiyeon Suh Shannon M. Farley Sergio Chicumbe Ilesh Jani Annette Cassy Ivalda Macicame Naisa Manafe Wafaa El-Sadr Jeffrey Shaman |
| author_sort | Roselyn F. Kaondera-Shava |
| collection | DOAJ |
| description | The 2019 emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its rapid spread created a public health emergency of international concern. However, the impact of the pandemic in Sub-Saharan Africa, as documented in cases, hospitalizations and deaths, appears far lower than in the Americas, Europe and Asia. Characterization of the transmission dynamics is critical for understanding how SARS-CoV-2 spreads and the true scale of the pandemic. Here, to better understand SARS-CoV-2 transmission dynamics in two southern African countries, Mozambique and Zimbabwe, we developed a dynamic model-Bayesian inference system to estimate key epidemiological parameters, namely the transmission and ascertainment rates. Total infection burdens (reported and unreported) during the first 3 years of the pandemic were reconstructed using a model-inference approach. Transmission rates rose with each successive wave, which aligns with observations in other continents. Ascertainment rates were found to be low and consistent with other African countries. Overall, the estimated disease burden was higher than the documented cases, indicating a need for improved reporting and surveillance. These findings aid understanding of COVID-19 disease and respiratory virus transmission dynamics in two African countries little investigated to date and can help guide future public health planning and control strategies. |
| format | Article |
| id | doaj-art-5122ed5f8c684e1e921543252cfc1f93 |
| institution | Kabale University |
| issn | 2054-5703 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | The Royal Society |
| record_format | Article |
| series | Royal Society Open Science |
| spelling | doaj-art-5122ed5f8c684e1e921543252cfc1f932025-01-22T00:16:49ZengThe Royal SocietyRoyal Society Open Science2054-57032025-01-0112110.1098/rsos.241275SARS-CoV-2 transmission dynamics in Mozambique and Zimbabwe during the first 3 years of the pandemicRoselyn F. Kaondera-Shava0Marta Galanti1Matteo Perini2Jiyeon Suh3Shannon M. Farley4Sergio Chicumbe5Ilesh Jani6Annette Cassy7Ivalda Macicame8Naisa Manafe9Wafaa El-Sadr10Jeffrey Shaman11Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY 10032, USADepartment of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY 10032, USADepartment of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY 10032, USADepartment of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY 10032, USADepartment of Population and Family Health, Mailman School of Public Health, Columbia University, New York, NY 10032, USAInstituto Nacional de Saúde (INS) EN1, Bairro da Vila-Parcela n 3943, Distrito de Marracuene, Maputo, C.P. 264, MozambiqueInstituto Nacional de Saúde (INS) EN1, Bairro da Vila-Parcela n 3943, Distrito de Marracuene, Maputo, C.P. 264, MozambiqueInstituto Nacional de Saúde (INS) EN1, Bairro da Vila-Parcela n 3943, Distrito de Marracuene, Maputo, C.P. 264, MozambiqueInstituto Nacional de Saúde (INS) EN1, Bairro da Vila-Parcela n 3943, Distrito de Marracuene, Maputo, C.P. 264, MozambiqueInstituto Nacional de Saúde (INS) EN1, Bairro da Vila-Parcela n 3943, Distrito de Marracuene, Maputo, C.P. 264, MozambiqueDepartment of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY 10032, USADepartment of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY 10032, USAThe 2019 emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its rapid spread created a public health emergency of international concern. However, the impact of the pandemic in Sub-Saharan Africa, as documented in cases, hospitalizations and deaths, appears far lower than in the Americas, Europe and Asia. Characterization of the transmission dynamics is critical for understanding how SARS-CoV-2 spreads and the true scale of the pandemic. Here, to better understand SARS-CoV-2 transmission dynamics in two southern African countries, Mozambique and Zimbabwe, we developed a dynamic model-Bayesian inference system to estimate key epidemiological parameters, namely the transmission and ascertainment rates. Total infection burdens (reported and unreported) during the first 3 years of the pandemic were reconstructed using a model-inference approach. Transmission rates rose with each successive wave, which aligns with observations in other continents. Ascertainment rates were found to be low and consistent with other African countries. Overall, the estimated disease burden was higher than the documented cases, indicating a need for improved reporting and surveillance. These findings aid understanding of COVID-19 disease and respiratory virus transmission dynamics in two African countries little investigated to date and can help guide future public health planning and control strategies.https://royalsocietypublishing.org/doi/10.1098/rsos.241275SARS-CoV-2COVID-19dynamic modelBayesian inferencetransmission rateascertainment rate |
| spellingShingle | Roselyn F. Kaondera-Shava Marta Galanti Matteo Perini Jiyeon Suh Shannon M. Farley Sergio Chicumbe Ilesh Jani Annette Cassy Ivalda Macicame Naisa Manafe Wafaa El-Sadr Jeffrey Shaman SARS-CoV-2 transmission dynamics in Mozambique and Zimbabwe during the first 3 years of the pandemic Royal Society Open Science SARS-CoV-2 COVID-19 dynamic model Bayesian inference transmission rate ascertainment rate |
| title | SARS-CoV-2 transmission dynamics in Mozambique and Zimbabwe during the first 3 years of the pandemic |
| title_full | SARS-CoV-2 transmission dynamics in Mozambique and Zimbabwe during the first 3 years of the pandemic |
| title_fullStr | SARS-CoV-2 transmission dynamics in Mozambique and Zimbabwe during the first 3 years of the pandemic |
| title_full_unstemmed | SARS-CoV-2 transmission dynamics in Mozambique and Zimbabwe during the first 3 years of the pandemic |
| title_short | SARS-CoV-2 transmission dynamics in Mozambique and Zimbabwe during the first 3 years of the pandemic |
| title_sort | sars cov 2 transmission dynamics in mozambique and zimbabwe during the first 3 years of the pandemic |
| topic | SARS-CoV-2 COVID-19 dynamic model Bayesian inference transmission rate ascertainment rate |
| url | https://royalsocietypublishing.org/doi/10.1098/rsos.241275 |
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