Malvisi Lucio, Troisi Catherine L, Selwyn Beatrice J
Department of Epidemiology, Human Genetics & Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA.
Parasitol Res. 2018 Sep;117(9):2807-2822. doi: 10.1007/s00436-018-5968-6. Epub 2018 Jun 23.
The risk of malaria infection displays spatial and temporal variability that is likely due to interaction between the physical environment and the human population. In this study, we performed a spatial analysis at three different time points, corresponding to three cross-sectional surveys conducted as part of an insecticide-treated bed nets efficacy study, to reveal patterns of malaria incidence distribution in an area of Northern Guatemala characterized by low malaria endemicity. A thorough understanding of the spatial and temporal patterns of malaria distribution is essential for targeted malaria control programs. Two methods, the local Moran's I and the Getis-Ord G(d), were used for the analysis, providing two different statistical approaches and allowing for a comparison of results. A distance band of 3.5 km was considered to be the most appropriate distance for the analysis of data based on epidemiological and entomological factors. Incidence rates were higher at the first cross-sectional survey conducted prior to the intervention compared to the following two surveys. Clusters or hot spots of malaria incidence exhibited high spatial and temporal variations. Findings from the two statistics were similar, though the G(d) detected cold spots using a higher distance band (5.5 km). The high spatial and temporal variability in the distribution of clusters of high malaria incidence seems to be consistent with an area of unstable malaria transmission. In such a context, a strong surveillance system and the use of spatial analysis may be crucial for targeted malaria control activities.
疟疾感染风险呈现出空间和时间上的变异性，这可能是由于自然环境与人群之间的相互作用所致。在本研究中，我们在三个不同时间点进行了空间分析，这三个时间点对应于作为一项经杀虫剂处理的蚊帐功效研究一部分而开展的三次横断面调查，以揭示危地马拉北部一个疟疾流行程度较低地区的疟疾发病率分布模式。深入了解疟疾分布的空间和时间模式对于有针对性的疟疾控制项目至关重要。我们使用了局部莫兰指数（local Moran's I）和Getis-Ord G(d)这两种方法进行分析，提供了两种不同的统计方法并允许对结果进行比较。基于流行病学和昆虫学因素，3.5公里的距离带被认为是分析数据的最合适距离。与随后的两次调查相比，在干预前进行的第一次横断面调查中的发病率更高。疟疾发病率的聚集区或热点呈现出高度的空间和时间变化。两种统计方法的结果相似，尽管G(d)使用更高的距离带（5.5公里）检测到了冷点。高疟疾发病率聚集区分布的高度空间和时间变异性似乎与疟疾传播不稳定的地区一致。在这种情况下，强大的监测系统和空间分析的使用对于有针对性的疟疾控制活动可能至关重要。
