Mapping and enumerating houses and households to support malaria control interventions on Bioko Island
Mapping and enumerating houses and households to support malaria control interventions on Bioko Island
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DOI：
10.1186/s12936-019-2920-x
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发表时间：
2019-08-22
期刊：
影响因子：
3
通讯作者：
Guerra, Carlos A.
中科院分区：
文献类型：
--
作者：
Garcia, Guillermo A.;Hergott, Dianna E. B.;Guerra, Carlos A.
背景 住房绘图和家庭普查对于疟疾控制干预措施的规划、实施、目标确定和监测至关重要。在许多疟疾流行国家，控制工作因住房制图和家庭普查不完整或不存在而受到阻碍。本文介绍了支持比奥科岛疟疾控制项目 (BIMCP) 的综合绘图和计数系统的开发。结果 开发了一个非常详细的数据库，其中包括比奥科岛上的每个住房单元，并唯一地列举了居住在这些房屋中的相关家庭。首先，该岛被划分为一个虚拟的、地理解引用的网格，该网格由 1 x 1 km 连续编号的地图区域组成，每个区域又细分为一百个 100 x 100 m 连续编号的地图扇区。其次，使用高分辨率卫星图像来顺序且唯一地识别每个地图扇区内的所有住房单元。第三，在无法获得卫星图像的情况下，全球定位系统（GPS）被用作按顺序唯一识别和绘制住房单元地图的基础。截至 2018 年，共绘制了 97,048 个住房单元的地图，其中 56% 集中在仅占比奥科岛绘制地图总面积的 5.2% 的区域。在这些住房单元中，70.7% 已被占用，因此代表了独特的家庭。结论 为比奥科岛开发的住房单元绘图和家庭计数系统使 BIMCP 能够更有效地规划、实施、瞄准和监测疟疾控制干预措施。自 2014 年以来，BIMCP 使用独特的家庭标识符来监测所有家庭层面的干预措施，包括室内滞留喷洒、长效驱虫蚊帐分发以及年度疟疾指标调查。用于创建唯一住房单元和家庭标识符的编码系统非常直观，无需 GPS 即可快速定位网格内的任何房屋。其灵活性使 BIMCP 能够轻松考虑住房基础设施的快速而重大的变化。重要的是，通过利用该编码系统，收集到了数量和多样性前所未有的详细、地理参考的人口和健康数据，事实证明，这些数据对于为疟疾控制和比奥科岛更广泛的公共卫生议程提供决策信息高度相关。
Background Housing mapping and household enumeration are essential for the planning, implementation, targeting, and monitoring of malaria control interventions. In many malaria endemic countries, control efforts are hindered by incomplete or non-existent housing cartography and household enumeration. This paper describes the development of a comprehensive mapping and enumeration system to support the Bioko Island Malaria Control Project (BIMCP). Results A highly detailed database was developed to include every housing unit on Bioko Island and uniquely enumerate the associated households residing in these houses. First, the island was divided into a virtual, geo-dereferenced grid of 1 x 1 km sequentially numbered map-areas, each of which was in turn subdivided into one hundred, 100 x 100 m sequentially numbered map-sectors. Second, high-resolution satellite imagery was used to sequentially and uniquely identify all housing units within each map-sector. Third, where satellite imagery was not available, global positioning systems (GPS) were used as the basis for uniquely identifying and mapping housing units in a sequential manner. A total of 97,048 housing units were mapped by 2018, 56% of which were concentrated in just 5.2% of Bioko Island's total mapped area. Of these housing units, 70.7% were occupied, thus representing uniquely identified households. Conclusions The housing unit mapping and household enumeration system developed for Bioko Island enabled the BIMCP to more effectively plan, implement, target, and monitor malaria control interventions. Since 2014, the BIMCP has used the unique household identifiers to monitor all household-level interventions, including indoor residual spraying, long-lasting insecticide-treated nets distribution, and annual malaria indicator surveys. The coding system used to create the unique housing unit and household identifiers is highly intuitive and allows quick location of any house within the grid without a GPS. Its flexibility has permitted the BIMCP to easily take into account the rapid and substantial changes in housing infrastructure. Importantly, by utilizing this coding system, an unprecedented quantity and diversity of detailed, geo-referenced demographic and health data have been assembled that have proved highly relevant for informing decision-making both for malaria control and potentially for the wider public health agenda on Bioko Island.