{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,20]],"date-time":"2026-05-20T15:39:34Z","timestamp":1779291574671,"version":"3.51.4"},"reference-count":40,"publisher":"Cambridge University Press (CUP)","license":[{"start":{"date-parts":[[2020,12,1]],"date-time":"2020-12-01T00:00:00Z","timestamp":1606780800000},"content-version":"unspecified","delay-in-days":335,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["cambridge.org"],"crossmark-restriction":true},"short-container-title":["Epidemiol. Infect."],"published-print":{"date-parts":[[2020]]},"abstract":"<jats:title>Abstract<\/jats:title>\n\t  <jats:p>This study aimed to analyse the spatial\u2013temporal distribution of COVID-19 mortality in Sergipe, Northeast, Brazil. It was an ecological study utilising spatiotemporal analysis techniques that included all deaths confirmed by COVID-19 in Sergipe, from 2 April to 14 June 2020. Mortality rates were calculated per 100 000 inhabitants and the temporal trends were analysed using a segmented log-linear model. For spatial analysis, the Kernel estimator was used and the crude mortality rates were smoothed by the empirical Bayesian method. The space\u2013time prospective scan statistics applied the Poisson's probability distribution model. There were 391 COVID-19 registered deaths, with the majority among \u2a7e60 years old (62%) and males (53%). The most prevalent comorbidities were hypertension (40%), diabetes (31%) and cardiovascular disease (15%). An increasing mortality trend across the state was observed, with a higher increase in the countryside. An active spatiotemporal cluster of mortality comprising the metropolitan area and neighbouring cities was identified. The trend of COVID-19 mortality in Sergipe was increasing and the spatial distribution of deaths was heterogeneous with progression towards the countryside. Therefore, the use of spatial analysis techniques may contribute to surveillance and control of COVID-19 pandemic.<\/jats:p>","DOI":"10.1017\/s0950268820002915","type":"journal-article","created":{"date-parts":[[2020,12,1]],"date-time":"2020-12-01T07:46:12Z","timestamp":1606808772000},"update-policy":"https:\/\/doi.org\/10.1017\/policypage","source":"Crossref","is-referenced-by-count":12,"title":["COVID-19 mortality in an area of northeast Brazil: epidemiological characteristics and prospective spatiotemporal modelling"],"prefix":"10.1017","volume":"148","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5694-2094","authenticated-orcid":false,"given":"L. A.","family":"Andrade","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4181-2091","authenticated-orcid":false,"given":"D. 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