Ngwira Alfred, Manda Samuel, Karimuribo Esron Daniel, Kimera Sharadhuli Iddi
Department of Veterinary Medicine and Public Health, Sokoine University of Agriculture, Morogoro, Tanzania.
Department of Basic Sciences, Lilongwe University of Agriculture and Natural Resources, Lilongwe, Malawi.
One Health. 2024 Oct 5;19:100905. doi: 10.1016/j.onehlt.2024.100905. eCollection 2024 Dec.
Identification of common spatial disease trends between cattle bovine tuberculosis (BTB) and human extrapulmonary tuberculosis (EPTB) and drug-resistant tuberculosis (DRTB) can support integrated disease control and monitoring programmes. We employed the recently developed multivariate disease mapping methods to examine whether the diseases exhibited any spatial correlation.
A retrospective study of cattle BTB and human EPTB and DRTB cases from 2018 to 2022 was conducted. Bivariate shared spatiotemporal components models were fitted to a) cattle BTB and human EPTB and b) cattle BTB and human DRTB at the district level in Malawi, with cattle density, human density and climatic variables as independent variables.
Disease specific spatial effects were higher in the southern half of the country, while the shared spatial effects were more dominant in both the south and western parts of the country. The shared temporal effects showed constant trends, while disease specific temporal effects showed an increasing pattern for cattle BTB and a constant pattern for human EPTB and DRTB. The predicted disease incidence pattern for all forms of TB in the period without data showed a constant pattern over the years. Cattle density was positively associated with cattle BTB ( : 0.022; 95% Credible Interval (CI): 0.004, 0.042). Human density was positively associated with human EPTB ( : 0.005; 95% CI: 0.001, 0.009).
Cattle BTB and human EPTB and DRTB have a common spatial pattern in the west and southern parts of Malawi. Integrated interventions targeting high-density areas for cattle and human may have positive impacts on cattle BTB and human EPTB and DRTB.
识别牛型肺结核（BTB）与人类肺外结核（EPTB）及耐药结核病（DRTB）之间常见的空间疾病趋势，可为综合疾病控制和监测计划提供支持。我们采用最近开发的多变量疾病映射方法，来检验这些疾病是否呈现出任何空间相关性。
对2018年至2022年的牛型肺结核、人类肺外结核及耐药结核病病例进行回顾性研究。在马拉维的地区层面，将双变量共享时空成分模型分别应用于：a）牛型肺结核与人类肺外结核，以及b）牛型肺结核与人类耐药结核病，以牛密度、人类密度和气候变量作为自变量。
该国南部地区疾病特定的空间效应较高，而共享空间效应在该国南部和西部地区更为显著。共享时间效应呈现出恒定趋势，而疾病特定的时间效应显示牛型肺结核呈上升模式，人类肺外结核及耐药结核病呈恒定模式。在无数据期间，所有形式结核病的预测疾病发病率模式多年来呈现出恒定模式。牛密度与牛型肺结核呈正相关（β：0.022；95%可信区间（CI）：0.004，0.042）。人类密度与人类肺外结核呈正相关（β：0.005；95%CI：0.001，0.009）。
在马拉维西部和南部地区，牛型肺结核与人类肺外结核及耐药结核病具有共同的空间模式。针对牛和人类高密度地区的综合干预措施，可能对牛型肺结核以及人类肺外结核和耐药结核病产生积极影响。
