<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Sandfort M</submitter><funding>Sorbonne Université</funding><funding>European Research Council</funding><funding>NIAID NIH HHS</funding><funding>National Health and Medical Research Council</funding><funding>National Institutes of Health</funding><funding>NIH HHS</funding><pagination>75</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC9985228</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>22(1)</volume><pubmed_abstract>&lt;h4>Background&lt;/h4>Over the last decades, enormous successes have been achieved in reducing malaria burden globally. In Latin America, South East Asia, and the Western Pacific, many countries now pursue the goal of malaria elimination by 2030. It is widely acknowledged that Plasmodium spp. infections cluster spatially so that interventions need to be spatially informed, e.g. spatially targeted reactive case detection strategies. Here, the spatial signature method is introduced as a tool to quantify the distance around an index infection within which other infections significantly cluster.&lt;h4>Methods&lt;/h4>Data were considered from cross-sectional surveys from Brazil, Thailand, Cambodia, and Solomon Islands, conducted between 2012 and 2018. Household locations were recorded by GPS and finger-</pubmed_abstract><journal>Malaria journal</journal><pubmed_title>The spatial signature of Plasmodium vivax and Plasmodium falciparum infections: quantifying the clustering of infections in cross-sectional surveys and cohort studies.</pubmed_title><pmcid>PMC9985228</pmcid><funding_grant_id>n°2695/2017</funding_grant_id><funding_grant_id>1U19AI129392-01</funding_grant_id><funding_grant_id>804744</funding_grant_id><funding_grant_id>U19 AI129392</funding_grant_id><funding_grant_id>GNT1161627</funding_grant_id><funding_grant_id>852373</funding_grant_id><funding_grant_id>GNT1092789</funding_grant_id><pubmed_authors>Nguitragool W</pubmed_authors><pubmed_authors>Witkowski B</pubmed_authors><pubmed_authors>Sandfort M</pubmed_authors><pubmed_authors>Mueller I</pubmed_authors><pubmed_authors>White M</pubmed_authors><pubmed_authors>Robinson LJ</pubmed_authors><pubmed_authors>Waltmann A</pubmed_authors><pubmed_authors>Vantaux A</pubmed_authors><pubmed_authors>Monteiro W</pubmed_authors><pubmed_authors>Sattabongkot J</pubmed_authors><pubmed_authors>Lacerda M</pubmed_authors><pubmed_authors>Salje H</pubmed_authors></additional><is_claimable>false</is_claimable><name>The spatial signature of Plasmodium vivax and Plasmodium falciparum infections: quantifying the clustering of infections in cross-sectional surveys and cohort studies.</name><description>&lt;h4>Background&lt;/h4>Over the last decades, enormous successes have been achieved in reducing malaria burden globally. In Latin America, South East Asia, and the Western Pacific, many countries now pursue the goal of malaria elimination by 2030. It is widely acknowledged that Plasmodium spp. infections cluster spatially so that interventions need to be spatially informed, e.g. spatially targeted reactive case detection strategies. Here, the spatial signature method is introduced as a tool to quantify the distance around an index infection within which other infections significantly cluster.&lt;h4>Methods&lt;/h4>Data were considered from cross-sectional surveys from Brazil, Thailand, Cambodia, and Solomon Islands, conducted between 2012 and 2018. Household locations were recorded by GPS and finger-</description><dates><release>2023-01-01T00:00:00Z</release><publication>2023 Mar</publication><modification>2026-06-03T18:30:52.272Z</modification><creation>2025-02-18T23:35:42.51Z</creation></dates><accession>S-EPMC9985228</accession><cross_references><pubmed>36870976</pubmed><doi>10.1186/s12936-023-04515-4</doi></cross_references></HashMap>