Reveal
Reveal
Reveal is an open-source digital global good that enables country governments and implementing partners to use geospatial data and technology to efficiently and effectively microplan and then deliver life-saving intervention campaigns.
Approach
Reveal supports decision-makers and intervention managers by guiding and tracking the delivery of in-field activities with precision and holding field teams accountable for action. Reveal uses smart maps and technology appropriate for low-resource settings to monitor the coverage of interventions as they happen. Modeled on the mSpray and DiSARM tools, Reveal helps to optimize available resources and ensure no one is missed in the process. To date, Reveal has been used to plan and deploy routine data collection and campaigns for malaria, neglected tropical disease, as well as social behavior change data. Other use cases include vaccine planning and delivery, TB treatment, Vitamin A campaigns, and routine child health services. Reveal users include government and implementers of health programs who are involved in the planning/microplanning and delivery of health interventions. This includes central-level Ministry of Health staff, as well as district-based managers. End users of the mobile client include field teams, community health workers or community drug distributors.
Implementations
Reveal is currently being actively used, or has been used recently in the following countries: Mali, Senegal, Nigeria, Kenya, Angola, Zambia, Namibia, Mozambique.
Resources
- Website: www.revealprecision.com
- Source Code: https://github.com/akrosinc
- Product Summary
- Product Video
- Articles:
- Larsen et al (2020). Leveraging risk maps of malaria vector abundance to guide control efforts reduces malaria incidence in Eastern Province, Zambia. Nature Scientific Reports. 10: 10307
- Keating, J., Yukich, J.O., Miller, J.M. et al. Retrospective evaluation of the effectiveness of indoor residual spray with pirimiphosâ€methyl (Actellic) on malaria transmission in Zambia. Malar J 20, 173 (2021)
- Tropical Health (Josh Yukich). Cost and cost-effectiveness of 3GIRS in sub-Saharan Africa: results of data collection and analysis in the nGenIRS project. January 2019.
