ClinicalTrials.gov
public full text
Public Domain
Novel mHealth Platform to Ensure Quality of Community-based Malaria Diagnosis
The investigators propose to implement a new mobile interface that automatically reads and troubleshoots malaria rapid diagnostic test (RDT) cassettes. This device, called a Deki reader (DR), will allow the investigators to establish an extensive quality assurance program of malaria diagnosis performed by trained community health volunteers (CHVs). The study will lease 10 DRs and rotate them amongst 200 CHVs performing community-based malaria diagnosis through rapid diagnostic testing. The study setting is Bungoma East subcounty and Kiminini subcounty in Kenya. The overall goal is to measure and improve the quality of malaria diagnosis by CHVs using malaria RDTs. The investigators aim for every CHW to exceed 90% sensitivity and specificity and zero operator errors within six months. There are no appreciable risks to the CHV associated with evaluation by the DR device. The investigators' analysis will focus on descriptive statistics of RDT use and accuracy amongst all participating CHVs.
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Mobile application for early detection of Malaria in children: case of Western Kenya#956618
- Community-based malaria surveillance in Cambodia using a mobile reporting app for village malaria workers: An implementation case study.#653504
- Community-based malaria surveillance in Cambodia using a mobile reporting app for village malaria workers: An implementation case study#646453
- Rapid Diagnostic Tests for Assessment of Initial Clearance and Detection of Recurrent Malaria Infections#898929
- Mobile-phone-based solution for disease outbreak reporting and surveillance#938794
Record · ID 1484432
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive