{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,29]],"date-time":"2026-07-29T00:30:48Z","timestamp":1785285048723,"version":"3.55.0"},"reference-count":58,"publisher":"Wiley","issue":"5","license":[{"start":{"date-parts":[[2024,3,12]],"date-time":"2024-03-12T00:00:00Z","timestamp":1710201600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Tropical Med Int Health"],"published-print":{"date-parts":[[2024,5]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Objectives<\/jats:title><jats:p>Arboviruses, such as dengue (DENV), zika (ZIKV), and chikungunya (CHIKV), constitute a growing urban public health threat. Focusing on <jats:italic>Aedes aegypti<\/jats:italic> mosquitoes, their primary vectors, is crucial for mitigation. While traditional immature\u2010stage mosquito surveillance has limitations, capturing adult mosquitoes through traps yields more accurate data on disease transmission. However, deploying traps presents logistical and financial challenges, demonstrating effective temporal predictions but lacking spatial accuracy. Our goal is to identify smaller representative areas within cities to enhance the early warning system for DENV outbreaks.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>We created Sentinel Geographic Units (SGUs), smaller areas of 1\u2009km<jats:sup>2<\/jats:sup> within each stratum, larger areas, with the aim of aligning the Trap Positivity Index (TPI) and Adult Density Index (ADI) with their respective strata. We conducted a two\u2010step evaluation of SGUs. First, we examined the equivalence of TPI and ADI between SGUs and strata from January 2017 to July 2022. Second, we assessed the ability of SGU's TPI and ADI to predict DENV outbreaks in comparison to Foz do Igua\u00e7u's Early\u2010Warning System, which forecasts outbreaks up to 4\u2009weeks ahead. Spatial and temporal analyses were carried out, including data interpolation and model selection based on Akaike information criteria (AIC).<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Entomological indicators produced in small SGUs can effectively replace larger sentinel areas to access dengue outbreaks. Based on historical data, the best predictive capability is achieved 2\u2009weeks after infestation verification. Implementing the SGU strategy with more frequent sampling can provide more precise space\u2013time estimates and enhance dengue control.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>The implementation of SGUs offers an efficient way to monitor mosquito populations, reducing the need for extensive resources. This approach has the potential to improve dengue transmission management and enhance the public health response in endemic cities.<\/jats:p><\/jats:sec>","DOI":"10.1111\/tmi.13985","type":"journal-article","created":{"date-parts":[[2024,3,12]],"date-time":"2024-03-12T10:38:26Z","timestamp":1710239906000},"page":"414-423","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Optimising the surveillance of <i>Aedes aegypti<\/i> in Brazil by selecting smaller representative areas within an endemic city"],"prefix":"10.1111","volume":"29","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9983-9559","authenticated-orcid":false,"given":"Andr\u00e9 de Souza","family":"Leandro","sequence":"first","affiliation":[{"name":"Centro de Controle de Zoonoses de Foz do Igua\u00e7u Secretaria Municipal de Sa\u00fade  Foz do Igua\u00e7u Paran\u00e1 Brazil"},{"name":"Laborat\u00f3rio de Mosquitos Transmissores de Hematozo\u00e1rios 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