Kristan Mojca, Abeku Tarekegn A, Beard James, Okia Michael, Rapuoda Beth, Sang James, Cox Jonathan
London School of Hygiene & Tropical Medicine, London, UK.
Malar J. 2008 Nov 4;7:231. doi: 10.1186/1475-2875-7-231.
Malaria epidemics remain a significant public health issue in the East African highlands. The aim of this study was to monitor temporal variations in vector densities in relation to changes in meteorological factors and malaria incidence at four highland sites in Kenya and Uganda and to evaluate the implications of these relationships for epidemic prediction and control.
Mosquitoes were collected weekly over a period of 47 months while meteorological variables and morbidity data were monitored concurrently. Mixed-effects Poisson regression was used to study the temporal associations of meteorological variables to vector densities and of the latter to incidence rates of Plasmodium falciparum.
Anopheles gambiae s.s. was the predominant vector followed by Anopheles arabiensis. Anopheles funestus was also found in low densities. Vector densities remained low even during periods of malaria outbreaks. Average temperature in previous month and rainfall in previous two months had a quadratic and linear relationship with An. gambiae s.s. density, respectively. A significant statistical interaction was also observed between average temperature and rainfall in the previous month. Increases in densities of this vector in previous two months showed a linear relationship with increased malaria incidence.
Although epidemics in highlands often appear to follow abnormal weather patterns, interactions between meteorological, entomological and morbidity variables are complex and need to be modelled mathematically to better elucidate the system. This study showed that routine entomological surveillance is not feasible for epidemic monitoring or prediction in areas with low endemicity. However, information on unusual increases in temperature and rainfall should be used to initiate rapid vector surveys to assess transmission risk.
疟疾流行仍是东非高地一个重大的公共卫生问题。本研究的目的是监测肯尼亚和乌干达四个高地地点媒介密度的时间变化,及其与气象因素变化和疟疾发病率的关系,并评估这些关系对疫情预测和控制的意义。
在47个月的时间里每周收集蚊子,同时监测气象变量和发病数据。采用混合效应泊松回归研究气象变量与媒介密度以及媒介密度与恶性疟原虫发病率之间的时间关联。
冈比亚按蚊是主要媒介,其次是阿拉伯按蚊。也发现了少量的嗜人按蚊。即使在疟疾暴发期间,媒介密度仍保持在较低水平。前一个月的平均温度和前两个月的降雨量分别与冈比亚按蚊的密度呈二次和线性关系。还观察到前一个月平均温度和降雨量之间存在显著的统计交互作用。前两个月该媒介密度的增加与疟疾发病率的增加呈线性关系。
尽管高地的疫情似乎常常遵循异常的天气模式,但气象、昆虫学和发病变量之间的相互作用很复杂,需要进行数学建模以更好地阐明该系统。本研究表明,在低流行地区,常规昆虫学监测对于疫情监测或预测是不可行的。然而,应利用有关温度和降雨量异常增加的信息启动快速媒介调查,以评估传播风险。