Kaondera-Shava Roselyn F, Galanti Marta, Perini Matteo, Suh Jiyeon, Farley Shannon M, Chicumbe Sergio, Jani Ilesh, Cassy Annette, Macicame Ivalda, Manafe Naisa, El-Sadr Wafaa, Shaman Jeffrey
Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY 10032, USA.
Department of Population and Family Health, Mailman School of Public Health, Columbia University, New York, NY 10032, USA.
R Soc Open Sci. 2025 Jan 22;12(1):241275. doi: 10.1098/rsos.241275. eCollection 2025 Jan.
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.
2019年严重急性呼吸综合征冠状病毒2(SARS-CoV-2)的出现及其迅速传播引发了一场国际关注的突发公共卫生事件。然而,从病例、住院人数和死亡人数记录来看,该疫情在撒哈拉以南非洲地区的影响似乎远低于美洲、欧洲和亚洲。了解传播动态特征对于理解SARS-CoV-2的传播方式以及疫情的真实规模至关重要。在此,为了更好地了解莫桑比克和津巴布韦这两个南部非洲国家的SARS-CoV-2传播动态,我们开发了一个动态模型——贝叶斯推理系统,以估计关键的流行病学参数,即传播率和确诊率。采用模型推理方法重建了疫情头三年的总感染负担(包括报告的和未报告的)。传播率随着每一波疫情上升,这与其他大洲的观察结果一致。确诊率较低,与其他非洲国家的情况相符。总体而言,估计的疾病负担高于记录的病例数,这表明需要改进报告和监测。这些发现有助于了解迄今很少被研究的两个非洲国家的新冠疫情及呼吸道病毒传播动态,并有助于指导未来的公共卫生规划和控制策略。