Evaluation of an accelerometer-based monitor for detecting bed net use and human entry/exit using a machine learning algorithm

Evaluation of an accelerometer-based monitor for detecting bed net use and human entry/exit using a machine learning algorithm

Abstract Background Distribution of long-lasting insecticidal bed nets (LLINs) is one of the main control strategies for malaria. Improving malaria prevention programmes requires understanding usage patterns in households receiving LLINs, but there are limits to what standard cross-sectional surveys...

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Bibliographic Details
Main Authors: Guibehi B. Koudou, April Monroe, Seth R. Irish, Michael Humes, Joseph D. Krezanoski, Hannah Koenker, David Malone, Janet Hemingway, Paul J. Krezanoski
Format: Article
Language:English
Published: BMC 2022-03-01
Series:Malaria Journal
Subjects:
Malaria prevention
Bed net use
Machine learning
Online Access:https://doi.org/10.1186/s12936-022-04102-z

Internet

https://doi.org/10.1186/s12936-022-04102-z

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