{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,30]],"date-time":"2026-07-30T13:57:55Z","timestamp":1785419875339,"version":"3.56.0"},"reference-count":0,"publisher":"Cambridge University Press (CUP)","license":[{"start":{"date-parts":[[2026,2,20]],"date-time":"2026-02-20T00:00:00Z","timestamp":1771545600000},"content-version":"unspecified","delay-in-days":50,"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":[[2026]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>This study analyses 18\u00a0years of weekly reported dengue cases (January 2002\u2013December 2020; 988\u00a0weeks) from Costa Rica\u2019s Central Valley to examine seasonal and multi-year patterns. To model the spatio-temporal dynamics of dengue, we employ three statistical approaches for case counts: the spatial hurdle integer-valued generalized autoregressive conditional heteroskedasticity (INGARCH) model, the spatial zero-inflated generalized Poisson (ZIGP)-INGARCH model, and the endemic\u2013epidemic (EE) model. Covariates include rainfall and maximum temperature or alternatively seasonal Fourier terms to represent annual seasonality. Using a Bayesian framework, we fit the spatial INGARCH-family models to weekly dengue cases. The EE model and the ZIGP-INGARCH model, both with Fourier seasonal terms, show the best predictive accuracy and provide estimates of seasonal intensity and peak timing relevant for dengue surveillance. Incorporating annual seasonality improves modelling of multivariate weekly dengue cases in Costa Rica\u2019s Central Valley, underscoring the importance of cyclical patterns for strengthening early warning systems and guiding targeted vector control.<\/jats:p>","DOI":"10.1017\/s0950268826101204","type":"journal-article","created":{"date-parts":[[2026,2,20]],"date-time":"2026-02-20T02:34:22Z","timestamp":1771554862000},"update-policy":"https:\/\/doi.org\/10.1017\/policypage","source":"Crossref","is-referenced-by-count":0,"title":["Spatio-temporal modelling of dengue counts in the Central Valley of Costa Rica"],"prefix":"10.1017","volume":"154","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8727-8168","authenticated-orcid":false,"given":"Cathy W. S.","family":"Chen","sequence":"first","affiliation":[{"id":[{"id":"https:\/\/ror.org\/05vhczg54","id-type":"ROR","asserted-by":"publisher"}],"name":"Feng Chia University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5495-2486","authenticated-orcid":false,"given":"Shu Wei","family":"Chou-Chen","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/02yzgww51","id-type":"ROR","asserted-by":"publisher"}],"name":"University of Costa Rica"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-7655-6481","authenticated-orcid":false,"given":"Hsiao-Hsuan","family":"Liao","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/05vhczg54","id-type":"ROR","asserted-by":"publisher"}],"name":"Feng Chia University"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"56","published-online":{"date-parts":[[2026,2,20]]},"container-title":["Epidemiology and Infection"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.cambridge.org\/core\/services\/aop-cambridge-core\/content\/view\/S0950268826101204","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,26]],"date-time":"2026-03-26T10:31:54Z","timestamp":1774521114000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.cambridge.org\/core\/product\/identifier\/S0950268826101204\/type\/journal_article"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"references-count":0,"alternative-id":["S0950268826101204"],"URL":"https:\/\/doi.org\/10.1017\/s0950268826101204","relation":{},"ISSN":["0950-2688","1469-4409"],"issn-type":[{"value":"0950-2688","type":"print"},{"value":"1469-4409","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026]]},"assertion":[{"value":"\u00a9 The Author(s), 2026. Published by Cambridge University Press","name":"copyright","label":"Copyright","group":{"name":"copyright_and_licensing","label":"Copyright and Licensing"}},{"value":"This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http:\/\/creativecommons.org\/licenses\/by\/4.0), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.","name":"license","label":"License","group":{"name":"copyright_and_licensing","label":"Copyright and Licensing"}},{"value":"This content has been made available to all.","name":"free","label":"Free to read"}],"article-number":"e34"}}