Abstract:
The interactions of environmental, geographic, socio-demographic, and epidemiological factors in shaping mosquito-borne disease transmission dynamics are complex and changeable, influencing the abundance and distribution of vectors and the pathogens they transmit. In this study, 27 years of cross-sectional malaria survey data (1990-2017) were used to examine the effects of these factors on Plasmodium falciparum and Plasmodium vivax malaria presence at the community level in Africa and Asia. Monthly long-term, open-source data for each factor were compiled and analyzed using generalized linear models and classification and regression trees. Both temperature and precipitation exhibited unimodal relationships with malaria, with a positive effect up to a point after which a negative effect was observed as temperature and precipitation increased. Overall decline in malaria from 2000 to 2012 was well captured by the models, as was the resurgence after that. The models also indicated higher malaria in regions with lower economic and development indicators. Malaria is driven by a combination of environmental, geographic, socioeconomic, and epidemiological factors, and in this study, we demonstrated two approaches to capturing this complexity of drivers within models. Identifying these key drivers, and describing their associations with malaria, provides key information to inform planning and prevention strategies and interventions to reduce malaria burden.
摘要:
环境的相互作用,地理,社会人口统计学,影响蚊媒传播疾病传播动态的流行病学因素复杂多变,影响媒介的丰度和分布以及它们传播的病原体。在这项研究中,使用27年的横断面疟疾调查数据(1990-2017年)来研究这些因素对非洲和亚洲社区一级的恶性疟原虫和间日疟原虫疟疾的影响。每月长期,使用广义线性模型以及分类和回归树,对每个因素的开源数据进行了编译和分析。温度和降水都与疟疾表现出单峰关系,随着温度和降水的增加,观察到负面影响。模型很好地捕捉到了从2000年到2012年疟疾的总体下降,之后的复苏也是如此。这些模型还表明,在经济和发展指标较低的地区,疟疾较高。疟疾是由环境、地理,社会经济,和流行病学因素,在这项研究中,我们展示了两种方法来捕获模型中驱动因素的复杂性。识别这些关键驱动因素,描述了他们与疟疾的联系,提供关键信息,为减少疟疾负担的规划和预防战略和干预措施提供信息。