ArticlePLOS global public health2025
A geo-enabled digital tool for microplanning and delivery of indoor residual spray in Zambia: A case study, 2016-2020.
Article in PLOS global public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
2 citing papers in PubMed.
- Assessing the impact of building footprint dataset choice for health programme planning: a case study of indoor residual spraying (IRS) in Zambia.International journal of health geographics · 2025Article
- Cost and cost effectiveness of geospatial planning and delivery tools added to standard health campaigns in Luapula Province, Zambia.Oxford open digital health · 2024Article
Corrections and comments
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Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Indoor residual spraying (IRS) is a vector control tool recommended by the WHO in areas of high malaria burden. Effective IRS implementation is complicated when up-to-date and accurate counts of structures eligible for IRS are unavailable; resultingly, programmatic spray coverage is typically calculated as the proportion of found structures that are sprayed. From 2016 - 2020 in Zambia, an open-source tool termed "Reveal," was used to support digital mapping, microplanning, campaign monitoring and evaluation of IRS. Satellite imagery was used to enumerate structures and identify "spray areas," clusters of structures for operational planning. Spray areas were visualized in the Reveal tool web-based planning module where campaign planners selected which would be sprayed and determined the resources required. Field teams used the Reveal tool mobile application to navigate and to record spray data against each structure. True coverage was calculated as the proportion of enumerated structures that were sprayed. Reveal was implemented in 21 districts across five years and coverage is reported for each district and year. Logistic regression models explored whether structures were more or less likely to be found and sprayed depending on a given calendar year's targeting strategy, partner support level, and the year of Reveal implementation in a given district (first, second, third, or fourth). District-level programmatic IRS coverages overestimated the true adjusted coverages by an average 31.5 percentage points (range 2.8 - 69.4). The odds of finding and spraying structures increased with year of implementation; in the fourth year of implementation in a district, the odds of a household being sprayed and found were two times higher than in the first year of implementation. Digital tools improve structure and population estimates for planning and deployments in IRS campaigns, which may lead to more accurate coverage measurements and increased coverage over time.
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Registered trials
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