Mlacha Yeromin P, Chaki Prosper P, Malishee Alpha D, Mwakalinga Victoria M, Govella Nicodem J, Limwagu Alex J, Paliga John M, Msellemu Daniel F, Mageni Zawadi D, Terlouw Dianne J, Killeen Gerry F, Dongus Stefan
Environmental Health and Ecological Sciences Thematic Group, Ifakara Health Institute, Dar es Salaam, Tanzania; Vector Biology Department, Liverpool School of Tropical Medicine, Liverpool.
Geospat Health. 2017 May 11;12(1):494. doi: 10.4081/gh.2017.494.
This study investigated whether passively collected routine health facility data can be used for mapping spatial heterogeneities in malaria transmission at the level of local government housing cluster administrative units in Dar es Salaam, Tanzania. From June 2012 to January 2013, residential locations of patients tested for malaria at a public health facility were traced based on their local leaders' names and geo-referencing the point locations of these leaders' houses. Geographic information systems (GIS) were used to visualise the spatial distribution of malaria infection rates. Spatial scan statistics was deployed to detect spatial clustering of high infection rates. Among 2407 patients tested for malaria, 46.6% (1121) could be traced to their 411 different residential housing clusters. One small spatially aggregated cluster of neighbourhoods with high prevalence was identified. While the home residence housing cluster leader was unambiguously identified for 73.8% (240/325) of malaria-positive patients, only 42.3% (881/2082) of those with negative test results were successfully traced. It was concluded that recording simple points of reference during routine health facility visits can be used for mapping malaria infection burden on very fine geographic scales, potentially offering a feasible approach to rational geographic targeting of malaria control interventions. However, in order to tap the full potential of this approach, it would be necessary to optimise patient tracing success and eliminate biases by blinding personnel to test results.
本研究调查了被动收集的常规卫生机构数据是否可用于绘制坦桑尼亚达累斯萨拉姆地方政府住房集群行政单位层面疟疾传播的空间异质性。2012年6月至2013年1月，根据在公共卫生机构接受疟疾检测患者的当地领导人姓名以及对这些领导人房屋的点位进行地理定位，追踪了他们的居住地点。利用地理信息系统（GIS）可视化疟疾感染率的空间分布。采用空间扫描统计方法检测高感染率的空间聚集情况。在2407名接受疟疾检测的患者中，46.6%（1121名）可追溯到其411个不同的居住住房集群。识别出一个高患病率的小范围空间聚集社区集群。虽然73.8%（240/325）的疟疾阳性患者能明确确定其家庭居住住房集群负责人，但检测结果为阴性的患者中只有42.3%（881/2082）被成功追踪。研究得出结论，在常规卫生机构就诊期间记录简单的参考点可用于在非常精细的地理尺度上绘制疟疾感染负担图，这可能为疟疾控制干预措施的合理地理定位提供一种可行方法。然而，为充分发挥这种方法的潜力，有必要优化患者追踪成功率，并通过让工作人员对检测结果不知情来消除偏差。
