ArticleInternational health2017
Adaptation of a malaria surveillance system for use in a visceral leishmaniasis elimination programme.
Article in International health, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
10 authors at 4 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Successful public practice relies on generation and use of high-quality data. A data surveillance system (the Disease Data Management System [DDMS]) in use for malaria was adapted for use in the Indian visceral leishmaniasis elimination programme. Methods: A situational analysis identified the data flows in current use. Taxonomic trees for the vector of visceral leishmaniasis in India, Phlebotomus argentipes, were incorporated into the DDMS to allow entry of quality assurance and insecticide susceptibility data. A new quality assurance module was created to collate the concentration of DDT that was applied to walls during the indoor residual spraying (IRS) vector control programme. Results: The DDMS was implemented in Bihar State and used to collate and manage data from sentinel sites in eight districts. Quality assurance data showed that DDT was under-applied to walls during IRS; this, combined with insecticide susceptibility data showing widespread vector resistance to DDT prompted a national policy change to using compression pumps and alpha-cypermethrin insecticide for IRS. Conclusions: The adapted DDMS centralises programmatic data and enhances evidence-based decision making and active policy change. Moving forward, further modules of the system will be implemented, allowing extended data capture and streamlined transmission of key information to decision makers.
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