Snow R W, Gouws E, Omumbo J, Rapuoda B, Craig M H, Tanser F C, le Sueur D, Ouma J
Kenya Medical Research Institute/Wellcome Trust Collaborative Programme, Nairobi, Kenya.
Trans R Soc Trop Med Hyg. 1998 Nov-Dec;92(6):601-6. doi: 10.1016/s0035-9203(98)90781-7.
There is an increasing need to provide spatial distribution maps of the clinical burden of Plasmodium falciparum malaria in Africa. Recent evidence suggests that risk groups and the clinical spectrum of severe malaria are related to the intensity of P. falciparum transmission. Climate operates to affect the vectorial capacity of P. falciparum transmission and this is particularly important in the Horn of Africa and parts of East Africa. We have used a fuzzy logic climate suitability model to define areas of Kenya unsuitable for stable transmission. Kenya's unstable transmission areas can be divided into areas where transmission potential is limited by low rainfall or low temperature and, combined, encompass over 8 million people. Among areas of stable transmission we have used empirical data on P. falciparum infection rates among 124 childhood populations in Kenya to develop a climate-based statistical model of transmission intensity. This model correctly identified 75% (95% confidence interval CI 70-85) of 3 endemicity classes (low, < 20%; high, > or = 70%; and intermediate parasite prevalences). The model was applied to meteorological and remote sensed data using a geographical information system to provide estimates of endemicity for all of the 1080 populated fourth level administrative regions in Kenya. National census data for 1989 on the childhood populations within each administrative region were projected to provide 1997 estimates. Endemicity-specific estimates of morbidity and mortality were derived from published and unpublished sources and applied to their corresponding exposed-to-risk childhood populations. This combined transmission, population and disease-risk model suggested that every day in Kenya approximately 72 and 400 children below the age of 5 years either die or develop clinical malaria warranting in-patient care, respectively. Despite several limitations, such an approach goes beyond 'best guesses' to provide informed estimates of the geographical burden of malaria and its fatal consequences in Kenya.
绘制非洲恶性疟原虫疟疾临床负担的空间分布图的需求日益增长。最近的证据表明，高危人群和重症疟疾的临床谱与恶性疟原虫传播强度有关。气候会影响恶性疟原虫传播的媒介能力，这在非洲之角和东非部分地区尤为重要。我们使用模糊逻辑气候适宜性模型来确定肯尼亚不适合稳定传播的地区。肯尼亚的不稳定传播地区可分为传播潜力受低降雨量或低温限制的地区，这些地区加起来有超过800万人。在稳定传播地区，我们利用肯尼亚124个儿童群体中恶性疟原虫感染率的经验数据，建立了一个基于气候的传播强度统计模型。该模型正确识别了3种流行程度类别（低，<20%；高，>或 = 70%；以及中等寄生虫流行率）中的75%（95%置信区间CI 70 - 85）。该模型通过地理信息系统应用于气象和遥感数据，以提供肯尼亚所有1080个人口聚居的四级行政区的流行程度估计值。根据1989年各行政区内儿童群体的全国人口普查数据进行预测，以得出1997年的估计值。发病率和死亡率的特定流行程度估计值来自已发表和未发表的资料，并应用于相应的面临风险的儿童群体。这个综合了传播、人口和疾病风险的模型表明，在肯尼亚，每天分别约有72名和400名5岁以下儿童死亡或患上需要住院治疗的临床疟疾。尽管存在一些局限性，但这种方法超越了“猜测”，为肯尼亚疟疾的地理负担及其致命后果提供了有依据的估计。
