<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Paireau J</submitter><funding>LabEx “Integrative Biology of Emerging Infectious Diseases (IBEID)”</funding><pagination>772-779</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC6185885</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>12(6)</volume><pubmed_abstract>&lt;h4>Background&lt;/h4>Maps of influenza activity are important tools to monitor influenza epidemics and inform policymakers. In France, the availability of a high-quality data set from the Oscour&lt;sup>®&lt;/sup> surveillance network, covering 92% of hospital emergency department (ED) visits, offers new opportunities for disease mapping. Traditional geostatistical mapping methods such as Kriging ignore underlying population sizes, are not suited to non-Gaussian data and do not account for uncertainty in parameter estimates.&lt;h4>Objective&lt;/h4>Our objective was to create reliable weekly interpolated maps of influenza activity in the ED setting, to inform Santé publique France (the French national public health agency) and local healthcare authorities.&lt;h4>Methods&lt;/h4>We used Oscour&lt;sup>®&lt;/sup> data of</pubmed_abstract><journal>Influenza and other respiratory viruses</journal><pubmed_title>Mapping influenza activity in emergency departments in France using Bayesian model-based geostatistics.</pubmed_title><pmcid>PMC6185885</pmcid><funding_grant_id>ANR-10-LABX-62-IBEID</funding_grant_id><pubmed_authors>Caserio-Schonemann C</pubmed_authors><pubmed_authors>Paireau J</pubmed_authors><pubmed_authors>Pontais I</pubmed_authors><pubmed_authors>Pelat C</pubmed_authors><pubmed_authors>Cauchemez S</pubmed_authors><pubmed_authors>Le Strat Y</pubmed_authors><pubmed_authors>Levy-Bruhl D</pubmed_authors></additional><is_claimable>false</is_claimable><name>Mapping influenza activity in emergency departments in France using Bayesian model-based geostatistics.</name><description>&lt;h4>Background&lt;/h4>Maps of influenza activity are important tools to monitor influenza epidemics and inform policymakers. In France, the availability of a high-quality data set from the Oscour&lt;sup>®&lt;/sup> surveillance network, covering 92% of hospital emergency department (ED) visits, offers new opportunities for disease mapping. Traditional geostatistical mapping methods such as Kriging ignore underlying population sizes, are not suited to non-Gaussian data and do not account for uncertainty in parameter estimates.&lt;h4>Objective&lt;/h4>Our objective was to create reliable weekly interpolated maps of influenza activity in the ED setting, to inform Santé publique France (the French national public health agency) and local healthcare authorities.&lt;h4>Methods&lt;/h4>We used Oscour&lt;sup>®&lt;/sup> data of</description><dates><release>2018-01-01T00:00:00Z</release><publication>2018 Nov</publication><modification>2025-04-22T06:43:02.468Z</modification><creation>2019-03-27T00:05:09Z</creation></dates><accession>S-EPMC6185885</accession><cross_references><pubmed>30055089</pubmed><doi>10.1111/irv.12599</doi></cross_references></HashMap>