{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,23]],"date-time":"2026-09-23T17:42:55Z","timestamp":1790185375042,"version":"4.1.0"},"reference-count":61,"publisher":"Public Library of Science (PLoS)","issue":"4","license":[{"start":{"date-parts":[[2023,4,27]],"date-time":"2023-04-27T00:00:00Z","timestamp":1682553600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000060","name":"National Institute of Allergy and Infectious Diseases","doi-asserted-by":"publisher","award":["R01AI132372"],"award-info":[{"award-number":["R01AI132372"]}],"id":[{"id":"10.13039\/100000060","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["www.plosntds.org"],"crossmark-restriction":false},"short-container-title":["PLoS Negl Trop Dis"],"abstract":"<jats:p>For vector-borne diseases the basic reproduction number <jats:inline-formula id=\"pntd.0010839.e001\"><jats:alternatives><jats:graphic xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" id=\"pntd.0010839.e001g\" mimetype=\"image\" position=\"anchor\" xlink:href=\"info:doi\/10.1371\/journal.pntd.0010839.e001\" xlink:type=\"simple\"\/><mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" display=\"inline\" id=\"M1\"><mml:msub><mml:mi mathvariant=\"script\">R<\/mml:mi> <mml:mn>0<\/mml:mn><\/mml:msub><\/mml:math><\/jats:alternatives><\/jats:inline-formula>, a measure of a disease\u2019s epidemic potential, is highly temperature-dependent. Recent work characterizing these temperature dependencies has highlighted how climate change may impact geographic disease spread. We extend this prior work by examining how newly emerging diseases, like Zika, will be impacted by specific future climate change scenarios in four diverse regions of Brazil, a country that has been profoundly impacted by Zika. We estimated a <jats:inline-formula id=\"pntd.0010839.e002\"><jats:alternatives><jats:graphic xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" id=\"pntd.0010839.e002g\" mimetype=\"image\" position=\"anchor\" xlink:href=\"info:doi\/10.1371\/journal.pntd.0010839.e002\" xlink:type=\"simple\"\/><mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" display=\"inline\" id=\"M2\"><mml:mrow><mml:msub><mml:mi mathvariant=\"script\">R<\/mml:mi> <mml:mn>0<\/mml:mn><\/mml:msub> <mml:mrow><mml:mo>(<\/mml:mo> <mml:mi>T<\/mml:mi> <mml:mo>)<\/mml:mo><\/mml:mrow><\/mml:mrow><\/mml:math><\/jats:alternatives><\/jats:inline-formula>, derived from a compartmental transmission model, characterizing Zika (and, for comparison, dengue) transmission potential as a function of temperature-dependent biological parameters specific to <jats:italic>Aedes aegypti<\/jats:italic>. We obtained historical temperature data for the five-year period 2015\u20132019 and projections for 2045\u20132049 by fitting cubic spline interpolations to data from simulated atmospheric data provided by the CMIP-6 project (specifically, generated by the GFDL-ESM4 model), which provides projections under four Shared Socioeconomic Pathways (SSP). These four SSP scenarios correspond to varying levels of climate change severity. We applied this approach to four Brazilian cities (Manaus, Recife, Rio de Janeiro, and S\u00e3o Paulo) that represent diverse climatic regions. Our model predicts that the <jats:inline-formula id=\"pntd.0010839.e003\"><jats:alternatives><jats:graphic xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" id=\"pntd.0010839.e003g\" mimetype=\"image\" position=\"anchor\" xlink:href=\"info:doi\/10.1371\/journal.pntd.0010839.e003\" xlink:type=\"simple\"\/><mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" display=\"inline\" id=\"M3\"><mml:mrow><mml:msub><mml:mi mathvariant=\"script\">R<\/mml:mi> <mml:mn>0<\/mml:mn><\/mml:msub> <mml:mrow><mml:mo>(<\/mml:mo> <mml:mi>T<\/mml:mi> <mml:mo>)<\/mml:mo><\/mml:mrow><\/mml:mrow><\/mml:math><\/jats:alternatives><\/jats:inline-formula> for Zika peaks at 2.7 around 30\u00b0C, while for dengue it peaks at 6.8 around 31\u00b0C. We find that the epidemic potential of Zika will increase beyond current levels in Brazil in all of the climate scenarios. For Manaus, we predict that the annual <jats:inline-formula id=\"pntd.0010839.e004\"><jats:alternatives><jats:graphic xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" id=\"pntd.0010839.e004g\" mimetype=\"image\" position=\"anchor\" xlink:href=\"info:doi\/10.1371\/journal.pntd.0010839.e004\" xlink:type=\"simple\"\/><mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" display=\"inline\" id=\"M4\"><mml:msub><mml:mi mathvariant=\"script\">R<\/mml:mi> <mml:mn>0<\/mml:mn><\/mml:msub><\/mml:math><\/jats:alternatives><\/jats:inline-formula> range will increase from 2.1\u20132.5, to 2.3\u20132.7, for Recife we project an increase from 0.4\u20131.9 to 0.6\u20132.3, for Rio de Janeiro from 0\u20131.9 to 0\u20132.3, and for S\u00e3o Paulo from 0\u20130.3 to 0\u20130.7. As Zika immunity wanes and temperatures increase, there will be increasing epidemic potential and longer transmission seasons, especially in regions where transmission is currently marginal. Surveillance systems should be implemented and sustained for early detection.<\/jats:p>","DOI":"10.1371\/journal.pntd.0010839","type":"journal-article","created":{"date-parts":[[2023,4,27]],"date-time":"2023-04-27T17:23:23Z","timestamp":1682616203000},"page":"e0010839","update-policy":"https:\/\/doi.org\/10.1371\/journal.pntd.corrections_policy","source":"Crossref","is-referenced-by-count":32,"title":["Long-term projections of the impacts of warming temperatures on Zika and dengue risk in four Brazilian cities using a temperature-dependent basic reproduction number"],"prefix":"10.1371","volume":"17","author":[{"given":"Hannah","family":"Van Wyk","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Joseph N. 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