Debusho Legesse Kassa, Gemechu Leta Lencha
Department of Statistics, University of South Africa, c/o Christiaan de Wet Road & Pioneer Avenue, Private Bag X6, Florida, 1710, Johannesburg, South Africa.
BMC Public Health. 2025 Jan 30;25(1):377. doi: 10.1186/s12889-024-20996-7.
The aim of this paper was to evaluate the distribution of HIV and TB in Ethiopia during four years (2015-2018) at the district level, considering both spatial and temporal patterns.
Consolidated data on the count of TB case notifications and the number of patients with HIV for four years, 2015-2018, were provided by the Ethiopian Federal Ministry of Health. The data was analyzed using the Bayesian hierarchical approach, employing joint spatiotemporal modelling. The integrated nested Laplace approximation available in the R-INLA package was used to fit six models, each with different priors, for the precision parameters of the random effects variances. The best-fitting model with the best predictive capacity was selected using the Deviance Information Criterion and the negative sum of cross-validatory predictive log-likelihood.
According to the findings of the selected model, about 53% of the variability in TB and HIV incidences in the study period was explained by the shared temporal component, disease-specific spatial effect of HIV, and space-time interaction effect. The shared temporal trend and disease-specific temporal trend of HIV risk showed a slight upward trend between 2015 and 2017, followed by a slight decrease in 2018. However, the disease-specific temporal trend of TB risk had almost constant trend with minimal variation over the study period. The distribution of the shared relative risks was similar to the distribution of disease-specific TB relative risk, whereas that of HIV had more districts as high-risk areas.
The study showed the spatial similarity in the distribution of HIV and TB case notifications in specific districts within various provinces. Moreover, the shared relative risks exhibit a temporal pattern and spatial distribution that closely resemble those of the relative risks specific to HIV illness. The existence of districts with shared relative risks implies the need for collaborative surveillance of HIV and TB, as well as integrated interventions to control the two diseases jointly.
本文旨在评估埃塞俄比亚在2015年至2018年这四年间地区层面的艾滋病毒和结核病分布情况,同时考虑空间和时间模式。
埃塞俄比亚联邦卫生部提供了2015年至2018年四年间结核病病例通报计数和艾滋病毒患者数量的综合数据。使用贝叶斯分层方法对数据进行分析,采用联合时空建模。利用R-INLA软件包中的集成嵌套拉普拉斯近似法,针对随机效应方差的精度参数拟合六个不同先验的模型。使用偏差信息准则和交叉验证预测对数似然的负和来选择具有最佳预测能力的最佳拟合模型。
根据所选模型的结果,在研究期间,结核病和艾滋病毒发病率约53%的变异性可由共享时间成分、艾滋病毒特定疾病空间效应以及时空交互效应来解释。艾滋病毒风险的共享时间趋势和特定疾病时间趋势在2015年至2017年之间呈轻微上升趋势,随后在2018年略有下降。然而,结核病风险的特定疾病时间趋势在研究期间几乎呈恒定趋势,变化极小。共享相对风险的分布与特定疾病结核病相对风险的分布相似,而艾滋病毒的分布则有更多地区为高风险地区。
该研究表明,各省特定地区的艾滋病毒和结核病病例通报分布存在空间相似性。此外,共享相对风险呈现出一种时间模式和空间分布,与艾滋病毒疾病特定的相对风险极为相似。存在共享相对风险的地区意味着需要对艾滋病毒和结核病进行联合监测,并采取综合干预措施来共同控制这两种疾病。