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		<title>How Data Quality Shapes the Measured Impact of Indoor Residual Spraying Against Malaria in Côte d&#8217;Ivoire</title>
		<link>https://bioengineer.org/how-data-quality-shapes-the-measured-impact-of-indoor-residual-spraying-against-malaria-in-cote-divoire/</link>
		
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		<pubDate>Sat, 17 Oct 2026 11:30:19 +0000</pubDate>
				<category><![CDATA[Health]]></category>
		<category><![CDATA[Bayesian structural time series]]></category>
		<category><![CDATA[Côte d'Ivoire]]></category>
		<category><![CDATA[counterfactual modeling]]></category>
		<category><![CDATA[data quality]]></category>
		<category><![CDATA[DHIS2]]></category>
		<category><![CDATA[entomological inoculation rate]]></category>
		<category><![CDATA[Health Information Systems]]></category>
		<category><![CDATA[indoor residual spraying]]></category>
		<category><![CDATA[malaria]]></category>
		<category><![CDATA[President's Malaria Initiative]]></category>
		<category><![CDATA[surveillance]]></category>
		<category><![CDATA[vector control]]></category>
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					<description><![CDATA[A new Bayesian analysis of Côte d'Ivoire's indoor residual spraying program shows that poor-quality routine surveillance data can inflate estimated malaria reductions from 12–19% to as much as 30–43%, underscoring the need for rigorous data validation and control districts in impact evaluations.]]></description>
		
		
		
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