Musa Rabiu , Bosede Fagbemigun , Sunday Fadugba , Michael Shatalov , Kekana Malesela , Adejimi Adeniji
{"title":"Quantifying mpox transmission and control: A regional analysis of vaccination strategies in East Africa","authors":"Musa Rabiu , Bosede Fagbemigun , Sunday Fadugba , Michael Shatalov , Kekana Malesela , Adejimi Adeniji","doi":"10.1016/j.idm.2025.09.001","DOIUrl":null,"url":null,"abstract":"<div><div>Africa is home to the endemic mpox disease, especially in the tropical rain-forest regions of Central and West Africa. Although it is mostly found in the Democratic Republic of the Congo, reports of it have also come from other neighboring African nations. To understand the dynamics of mpox, we studied its spread in Burundi, Uganda, Rwanda, Congo, and Kenya before and after the implementation of interventions. Using a Bayesian framework, a simple mathematical model of Susceptible-Infected-Recovered type was calibrated and fitted to the 2022 mpox data covering the period before the introduction of intervention strategies. The model was then re-stratified to incorporate key epidemiological features, including vaccination with imperfect efficacy, partial immunity, exposure, and demographics. The transmission of mpox varied throughout East Africa, with Uganda exhibiting the highest basic reproduction number <span><math><msub><mrow><mi>R</mi></mrow><mrow><mn>0</mn></mrow></msub></math></span> = 2.51, suggesting the possibility of a rapid spread. Despite having the highest initial infection count and the lowest <span><math><msub><mrow><mi>R</mi></mrow><mrow><mn>0</mn></mrow></msub></math></span> (1.23), Congo may have had delayed detection. The moderate <span><math><msub><mrow><mi>R</mi></mrow><mrow><mn>0</mn></mrow></msub></math></span> values (1.35 and 1.88) in Rwanda and Burundi have implications for prompt intervention to control epidemics. Transmission and vaccination rates have a non-linear relationship with the thresholds required to contain mpox outbreaks. Our model shows that in high-transmission settings, substantially higher vaccination coverage (exceeding 80 % at an effectiveness of 70 %) is required to reduce the control reproduction number below unity, whereas in moderate-transmission contexts, coverage above 40 % may suffice. These quantitative thresholds provide actionable guidance for tailoring vaccination strategies to different epidemiological conditions. In particular, sustained vaccination strategies that achieve coverage above the threshold predicted by our model (approximately 80 %) can guarantee mpox eradication, even in situations with strong transmission rates. While real-world complexities such as heterogeneous risk groups and behavioral factors may affect outcomes, these findings shed light on potential quantitative thresholds and provide a foundation for more detailed, population-specific modeling of mpox interventions.</div></div>","PeriodicalId":36831,"journal":{"name":"Infectious Disease Modelling","volume":"11 1","pages":"Pages 29-46"},"PeriodicalIF":2.5000,"publicationDate":"2025-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Infectious Disease Modelling","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2468042725000892","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Medicine","Score":null,"Total":0}
引用次数: 0
Abstract
Africa is home to the endemic mpox disease, especially in the tropical rain-forest regions of Central and West Africa. Although it is mostly found in the Democratic Republic of the Congo, reports of it have also come from other neighboring African nations. To understand the dynamics of mpox, we studied its spread in Burundi, Uganda, Rwanda, Congo, and Kenya before and after the implementation of interventions. Using a Bayesian framework, a simple mathematical model of Susceptible-Infected-Recovered type was calibrated and fitted to the 2022 mpox data covering the period before the introduction of intervention strategies. The model was then re-stratified to incorporate key epidemiological features, including vaccination with imperfect efficacy, partial immunity, exposure, and demographics. The transmission of mpox varied throughout East Africa, with Uganda exhibiting the highest basic reproduction number = 2.51, suggesting the possibility of a rapid spread. Despite having the highest initial infection count and the lowest (1.23), Congo may have had delayed detection. The moderate values (1.35 and 1.88) in Rwanda and Burundi have implications for prompt intervention to control epidemics. Transmission and vaccination rates have a non-linear relationship with the thresholds required to contain mpox outbreaks. Our model shows that in high-transmission settings, substantially higher vaccination coverage (exceeding 80 % at an effectiveness of 70 %) is required to reduce the control reproduction number below unity, whereas in moderate-transmission contexts, coverage above 40 % may suffice. These quantitative thresholds provide actionable guidance for tailoring vaccination strategies to different epidemiological conditions. In particular, sustained vaccination strategies that achieve coverage above the threshold predicted by our model (approximately 80 %) can guarantee mpox eradication, even in situations with strong transmission rates. While real-world complexities such as heterogeneous risk groups and behavioral factors may affect outcomes, these findings shed light on potential quantitative thresholds and provide a foundation for more detailed, population-specific modeling of mpox interventions.
期刊介绍:
Infectious Disease Modelling is an open access journal that undergoes peer-review. Its main objective is to facilitate research that combines mathematical modelling, retrieval and analysis of infection disease data, and public health decision support. The journal actively encourages original research that improves this interface, as well as review articles that highlight innovative methodologies relevant to data collection, informatics, and policy making in the field of public health.