Malaria control and elimination from every angle: Mapping and applying larval source management with Reveal
Malaria is prevented through use of many tools, one being the management of larval breeding areas, also known as “larval source management” (LSM). The objective of LSM is to reduce the number of mosquito larvae and pupae so as to reduce the potential for malaria transmission.
Today, there is renewed interest in LSM, especially in areas where other interventions may not be as effective—for example where mosquitos are biting outside (versus indoors during sleeping hours when ITNs are most effective) or where insecticide resistance is growing.
Akros has contributed significantly to geo-enabling disease surveillance and response activities, including malaria interventions. Some of this work has included microplanning and delivery of health campaigns to ensure they achieve the highest coverage for impact. Through this work, Reveal, a digital global good, has been conceived and deployed across 10 countries. The robust Reveal datasets have facilitated enhanced microplanning and analysis of operational and programmatic performance to identify gaps, improve targeting and resource mobilization, and increase vector control coverage over time.
In 2022, Reveal was applied to a new challenge through USAID’s VectorLink Project to map potential larval breeding sites across select health facility catchments in Eastern Province, Zambia for a LSM feasibility study. This was the first time Reveal had been used for LSM, and the aim was to guide larval site management to areas where mosquito breeding sites are “few, fixed, and findable” as recommended by WHO.
First, Akros produced maps highlighting potential larval habitat using available data on water bodies extracted from global surface water maps and overlaid malaria vector abundance data, road network, population data, as well as relevant climate and topography data. These maps were loaded into the Reveal system to guide team plans for larval site management survey visits to understand whether LSM was an appropriate intervention for these areas. Two health facility catchments from each district were chosen to focus on for the LSM feasibility study.
As this was a new use case, Reveal was configured to include two new data collection forms, which were each tied to different location types: the larval habitat form for potential breeding sites (which pertains to habitat eligibility, characterization, and larval occupancy and density) and the household data collection form for houses (that includes form fields pertaining to previous spraying, select household demographics, and mosquito landing catches). Akros also configured the web dashboard of Reveal so that teams could track and monitor data collection progress of habitats and households over the course of the feasibility study.
Two four-day trainings were conducted for data collection teams in each district (approximately 16 data collectors, four team leaders, and two data collectors per district) on the use of the Reveal platform to capture both geographic and entomological data required to map the different Anopheles larval habitats.
Two rounds of LSM data collection were conducted, the first starting in December 2022. During data collection, teams navigated to mapped water bodies using the Reveal mobile client. They then captured data against each water body, including the habitat types of the larval sites surveyed. The majority in both rounds included drainage/ditches followed by streams and riverbeds. Anopheles larvae were found in 14.3% of habitats in Round 1 and 7.1% in Round 2.
Previously, selection of larval sites for LSM studies was often based on malaria transmission intensity and other epidemiologic factors in conjunction with general knowledge of proximity to water bodies, with less focus on geospatial characteristics as part of the selection methodology. With this first phase of the feasibility study complete, the PMI Evolve project (formerly VectorLink) is planning to partner with Akros to conduct additional mapping and geospatial analyses in the future. The ability to use satellite imagery and surface water detection algorithms to guide where these studies are conducted, and to further utilize tools such as Reveal to collect geospatial data for analysis, holds much promise for efficient and effective targeting of resources for LSM.