Liyew Alemneh Mekuriaw, Clements Archie C A, Wagnew Fasil, Gilmour Beth, Alene Kefyalew Addis
Institute of Public Health, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia; School of Population Health, Faculty of Health Sciences, Curtin University, Perth, Australia; Geospatial and Tuberculosis Research Team, Telethon Kids Institute, Perth, Australia.
Geospatial and Tuberculosis Research Team, Telethon Kids Institute, Perth, Australia; Research and Enterprise, Queen's University Belfast, Belfast, UK.
Int J Infect Dis. 2025 Apr;153:107777. doi: 10.1016/j.ijid.2025.107777. Epub 2025 Jan 8.
To map subnational and local prevalence of drug-resistant tuberculosis (DR-TB) across Africa.
We assembled a geolocated dataset from 173 sources across 31 African countries, comprising drug susceptibility test results and covariate data from publicly available databases. We used Bayesian model-based geostatistical framework with multivariate Bayesian logistic regression model to estimate DR-TB prevalence at lower administrative levels.
We estimated 148,239 DR-TB cases (95% uncertainty interval: 17,499-313,683) in Africa, showing significant variation by country. Eswatini and South Africa had highest case numbers, while Algeria and Egypt had the lowest. The highest DR-TB prevalence was estimated in Eswatini (53.26; 95% uncertainty interval 13.13-66.12), Morocco, Tunisia, and South Africa, while the lowest prevalence was found in Gabon, the Republic of Congo, Sierra Leone, and Mali. Marked subnational variation in DR-TB prevalence was noted, where 91 subnational areas across 12 countries had prevalence rates higher than their respective national averages. Factors such as mean temperature (β = 2.01; 95% CrI: 1.21, 3.42), population density (β = 0.41; 95% CrI: 0.19, 0.95), and fine particulate matter (β = 0.66; 95% CrI: 0.20, 0.80) were positively associated with DR-TB prevalence.
The study highlights substantial national and subnational variability in DR-TB prevalence across Africa, aiding policymakers in designing localized TB control interventions.
绘制非洲各国及地方耐多药结核病（DR-TB）的患病率。
我们整合了来自31个非洲国家173个来源的地理定位数据集，包括来自公开可用数据库的药敏试验结果和协变量数据。我们使用基于贝叶斯模型的地质统计框架和多元贝叶斯逻辑回归模型来估计较低行政级别地区的耐多药结核病患病率。
我们估计非洲有148,239例耐多药结核病病例（95%不确定区间：17,499 - 313,683），各国之间存在显著差异。斯威士兰和南非的病例数最高，而阿尔及利亚和埃及的病例数最低。估计斯威士兰（53.26；95%不确定区间13.13 - 66.12）、摩洛哥、突尼斯和南非的耐多药结核病患病率最高，而加蓬、刚果共和国、塞拉利昂和马里的患病率最低。注意到耐多药结核病患病率在国家以下层面存在显著差异，12个国家的91个国家以下地区的患病率高于各自国家的平均水平。平均温度（β = 2.01；95%可信区间：1.21，3.42）、人口密度（β = 0.41；95%可信区间：0.19，0.95）和细颗粒物（β = 0.66；95%可信区间：0.20，0.80）等因素与耐多药结核病患病率呈正相关。
该研究突出了非洲耐多药结核病患病率在国家和国家以下层面的显著差异，有助于政策制定者设计本地化的结核病控制干预措施。
