African Institute for Mathematical Sciences (AIMS), Kigali, Rwanda.
African Centre of Excellence in Data Science, University of Rwanda, Kigali, Rwanda.
PLoS One. 2024 Apr 22;19(4):e0298259. doi: 10.1371/journal.pone.0298259. eCollection 2024.
In sub-Saharan Africa, malaria and anemia contribute substantially to the high burden of morbidity and mortality among under-five children. In Rwanda, both diseases have remained public health challenge over the years in spite of the numerous intervention programs and policies put in place. This study aimed at understanding the geographical variations between the joint and specific risks of both diseases in the country while quantifying the effects of some socio-demographic and climatic factors. Using data extracted from Rwanda Demographic and Health Survey, a shared component model was conceived and inference was based on integrated nested Laplace approximation. The study findings revealed similar spatial patterns for the risk of malaria and the shared risks of both diseases, thus confirming the strong link between malaria and anaemia. The spatial patterns revealed that the risks for contracting both diseases are higher among children living in the districts of Rutsiro, Nyabihu, Rusizi, Ruhango, and Gisagara. The risks for both diseases are significantly associated with type of place of residence, sex of household head, ownership of bed net, wealth index and mother's educational attainment. Temperature and precipitation also have substantial association with both diseases. When developing malaria intervention programs and policies, it is important to take into account climatic and environmental variability in Rwanda. Also, potential intervention initiatives focusing on the lowest wealth index, children of uneducated mothers, and high risky regions need to be reinforced.
在撒哈拉以南非洲,疟疾和贫血在很大程度上导致了五岁以下儿童发病率和死亡率居高不下。在卢旺达,尽管多年来实施了许多干预方案和政策,但这两种疾病仍然是公共卫生挑战。本研究旨在了解该国疟疾和两种疾病共同和特定风险之间的地域差异,同时量化一些社会人口和气候因素的影响。本研究使用从卢旺达人口与健康调查中提取的数据,构思了一个共享分量模型,并基于集成嵌套拉普拉斯近似进行推断。研究结果表明,疟疾风险和两种疾病共同风险具有相似的空间模式,从而证实了疟疾和贫血之间的密切联系。空间模式表明,在 Rutsiro、Nyabihu、Rusizi、Ruhango 和 Gisagara 等地区生活的儿童感染这两种疾病的风险更高。这两种疾病的风险与居住地点类型、家庭户主性别、蚊帐拥有情况、财富指数和母亲受教育程度显著相关。温度和降水也与这两种疾病有实质性关联。在制定疟疾干预方案和政策时,必须考虑卢旺达的气候和环境变化。此外,还需要加强针对最低财富指数、母亲未受教育的儿童和高风险地区的潜在干预举措。