biostudies-literaturePiovezan RConselho Nacional de Desenvolvimento Científico e TecnológicoFundação de Amparo à Pesquisa do Estado de São PauloConselho Nacional das Fundações Estaduais de Amparo à Pesquisa100003https://www.ebi.ac.uk/biostudies/studies/S-EPMC10954012biostudies-literatureUnknown1<h4>Background</h4><i>Aedes aegypti</i> is the dominant vector of several arboviruses that threaten urban populations in tropical and subtropical countries. Because of the climate changes and the spread of the disease worldwide, the population at risk of acquiring the disease is increasing.<h4>Methods</h4>This study investigated the impact of the larval habitats control (CC), nebulization (NEB), and both methods (CC + NEB) using the distribution of Ae. aegypti eggs collected in urban area of Santa Bárbara d'Oeste, São Paulo State, Brazil. A total of 142,469 eggs were collected from 2014 to 2017. To verify the effects of control interventions, a spatial trend, and a predictive machine learning modeling analytical approaches were adopted.<h4>Results</h4>The spatial analysis revealed sites wiDialogues in healthAssessing the effect of <i>Aedes</i> (<i>Stegomyia</i>) <i>aegypti</i> (Linnaeus, 1762) control based on machine learning for predicting the spatiotemporal distribution of eggs in ovitraps.PMC109540122017/21174–8301,877/2016–5Piovezan RVon Zuben CJVeroneze RFaria Ede Azevedo TSSallum MAMVon Zuben FJfalseAssessing the effect of <i>Aedes</i> (<i>Stegomyia</i>) <i>aegypti</i> (Linnaeus, 1762) control based on machine learning for predicting the spatiotemporal distribution of eggs in ovitraps.<h4>Background</h4><i>Aedes aegypti</i> is the dominant vector of several arboviruses that threaten urban populations in tropical and subtropical countries. Because of the climate changes and the spread of the disease worldwide, the population at risk of acquiring the disease is increasing.<h4>Methods</h4>This study investigated the impact of the larval habitats control (CC), nebulization (NEB), and both methods (CC + NEB) using the distribution of Ae. aegypti eggs collected in urban area of Santa Bárbara d'Oeste, São Paulo State, Brazil. A total of 142,469 eggs were collected from 2014 to 2017. To verify the effects of control interventions, a spatial trend, and a predictive machine learning modeling analytical approaches were adopted.<h4>Results</h4>The spatial analysis revealed sites wi2022-01-01T00:00:00Z2022 Dec2026-07-14T18:11:32.723Z2025-04-05T14:46:17.34ZS-EPMC109540123851590510.1016/j.dialog.2022.100003