Year: 2009
Type: article
Abstract: BACKGROUNDThe 2007 Mozambique Malaria Indicator Survey reported used a multistage cluster design to collect information related to malaria prevention and prevalence.This paper demonstrates how large multistage cluster surveys can be designed to capture local LQAS analyses without sacrificing the accuracy of macro-level point estimates of malaria indicators. METHODSWe emulate a collection of LQAS surveys using data obtained during the 2007 Mozambique Malaria Indicator Survey to determine whether adequate bed net coverage has been reached within each enumeration area (EA).We then aggregate the EA-level data to obtain provincial and national coverage estimates.To assess whether similar coverage estimates can be arrived at with a smaller sample of clusters, we next emulate a Large-Country LQAS (LC-LQAS) application on the dataset. RESULTSProvincial-level estimates obtained using the LC-LQAS sub-sample and the complete LQAS sample are similar for possession of any bednet (provincial discrepancy: < 4%) and ITN possession (provincial discrepancy: <7%), and the national indicator estimates are within a single percentage point.Furthermore, LQAS analyses reveal significant local variation in performance otherwise hidden by the aggregate measures. CONCLUSIONSOur findings support the use of LQAS and LC-LQAS subsamples for making inference about malaria outcome indicators.These methods track coverage and provide important information simultaneously for local and national malaria control programs managers.
Authors: Caitlin Biedron, Michele Pagano, Bethany L. Hedt, Albert Kilian, Amy Ratcliffe, Samuel Mabunda, Joseph J. Valadez
Language: English
Topic: Malaria Research and Control
Field: Medicine
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W173759347