Assessing the impact of building footprint dataset choice for health programme planning: a case study of indoor residual spraying (IRS) in Zambia.

IF 3 2区 医学 Q2 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH
Heather R Chamberlain, Derek Pollard, Anna Winters, Silvia Renn, Olena Borkovska, Chisenga Abel Musuka, Garikai Membele, Attila N Lazar, Andrew J Tatem
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引用次数: 0

Abstract

Background: The increasing availability globally of building footprint datasets has brought new opportunities to support a geographic approach to health programme planning. This is particularly acute in settings with high disease burdens but limited geospatial data available to support targeted planning. The comparability of building footprint datasets has recently started to be explored, but the impact of utilising a particular dataset in analyses to support decision making for health programme planning has not been studied. In this study, we quantify the impact of utilising four different building footprint datasets in analyses to support health programme planning, with an example of malaria vector control initiatives in Zambia.

Methods: Using the example of planning indoor residual spraying (IRS) campaigns in Zambia, we identify priority locations for deployment of this intervention based on criteria related to the area, proximity and counts of building footprints per settlement. We apply the same criteria to four different building footprint datasets and quantify the count and geographic variability in the priority settlements that are identified.

Results: We show that nationally the count of potential priority settlements for IRS varies by over 230% with different building footprint datasets, considering a minimum threshold of 25 sprayable buildings per settlement. Differences are most pronounced for rural settlements, indicating that the choice of dataset may bias the selection to include or exclude settlements, and consequently population groups, in some areas.

Conclusions: The results of this study show that the choice of building footprint dataset can have a considerable impact on the potential settlements identified for IRS, in terms of (i) their location and count, and (ii) the count of building footprints within priority settlements. The choice of dataset potentially has substantial implications for campaign planning, implementation and coverage assessment. Given the magnitude of the differences observed, further work should more broadly assess the sensitivity of health programme planning metrics to different building footprint datasets, and across a range of geographic contexts and health campaign types.

评估建筑足迹数据集选择对卫生规划的影响:赞比亚室内残留喷洒(IRS)案例研究。
背景:建筑足迹数据集在全球范围内的可用性日益增加,为支持采用地理方法进行卫生规划带来了新的机会。在疾病负担高但可用于支持有针对性规划的地理空间数据有限的环境中,这种情况尤其严重。最近开始探索建筑足迹数据集的可比性,但尚未研究在分析中利用特定数据集支持卫生规划决策的影响。在本研究中,我们量化了在分析中利用四种不同的建筑足迹数据集来支持卫生规划的影响,并以赞比亚的疟疾病媒控制举措为例。方法:以赞比亚规划室内残留喷洒(IRS)活动为例,我们根据与面积、邻近程度和每个定居点建筑足迹计数相关的标准确定部署这种干预措施的优先地点。我们将相同的标准应用于四个不同的建筑足迹数据集,并量化确定的优先定居点的数量和地理变异性。结果:我们表明,考虑到每个定居点25个可喷洒建筑的最低阈值,在全国范围内,不同建筑足迹数据集的潜在优先IRS定居点数量差异超过230%。农村居民点的差异最为明显,这表明在某些地区,数据集的选择可能会对包括或排除居民点以及人口群体的选择产生偏见。结论:本研究结果表明,建筑足迹数据集的选择可以对IRS确定的潜在定居点产生相当大的影响,包括:(i)它们的位置和数量,以及(ii)优先定居点内建筑足迹的数量。数据集的选择可能对活动计划、实施和覆盖评估产生重大影响。鉴于所观察到的差异之大,进一步的工作应更广泛地评估卫生方案规划指标对不同建筑足迹数据集的敏感性,并跨越一系列地理背景和卫生运动类型。
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来源期刊
International Journal of Health Geographics
International Journal of Health Geographics PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH -
CiteScore
10.20
自引率
2.00%
发文量
17
审稿时长
12 weeks
期刊介绍: A leader among the field, International Journal of Health Geographics is an interdisciplinary, open access journal publishing internationally significant studies of geospatial information systems and science applications in health and healthcare. With an exceptional author satisfaction rate and a quick time to first decision, the journal caters to readers across an array of healthcare disciplines globally. International Journal of Health Geographics welcomes novel studies in the health and healthcare context spanning from spatial data infrastructure and Web geospatial interoperability research, to research into real-time Geographic Information Systems (GIS)-enabled surveillance services, remote sensing applications, spatial epidemiology, spatio-temporal statistics, internet GIS and cyberspace mapping, participatory GIS and citizen sensing, geospatial big data, healthy smart cities and regions, and geospatial Internet of Things and blockchain.
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