{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T20:30:25Z","timestamp":1790886625375,"version":"4.1.0"},"reference-count":51,"publisher":"American Society for Microbiology","issue":"6","license":[{"start":{"date-parts":[[2023,12,19]],"date-time":"2023-12-19T00:00:00Z","timestamp":1702944000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2023,12,19]],"date-time":"2023-12-19T00:00:00Z","timestamp":1702944000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.asm.org\/non-commercial-tdm-license"}],"funder":[{"name":"National Science Foundation","award":["CCF1918749"],"award-info":[{"award-number":["CCF1918749"]}]},{"DOI":"10.13039\/100000104","name":"NASA","doi-asserted-by":"crossref","award":["80NSSC22K1044"],"award-info":[{"award-number":["80NSSC22K1044"]}],"id":[{"id":"10.13039\/100000104","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["journals.asm.org"],"crossmark-restriction":true},"short-container-title":["mBio"],"published-print":{"date-parts":[[2023,12,19]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n          <jats:p>\n            Climate change raises an old disease to a new level of public health threat. The causative agent,\n            <jats:italic>Vibrio cholerae<\/jats:italic>\n            , native to aquatic ecosystems, is influenced by climate and weather processes. The risk of cholera is elevated in vulnerable populations lacking access to safe water and sanitation infrastructure. Predictive intelligence, employing mathematical algorithms that integrate earth observations and heuristics derived from microbiological, sociological, and weather data, can provide anticipatory decision-making capabilities to reduce the burden of cholera and save human lives. An example offered here is the recent outbreak of cholera in Malawi, predicted in advance by such algorithms.\n          <\/jats:p>","DOI":"10.1128\/mbio.00529-23","type":"journal-article","created":{"date-parts":[[2023,11,14]],"date-time":"2023-11-14T14:01:35Z","timestamp":1699970495000},"update-policy":"https:\/\/doi.org\/10.1128\/asmj-crossmark-policy-page","source":"Crossref","is-referenced-by-count":5,"title":["Anticipatory decision-making for cholera in Malawi"],"prefix":"10.1128","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8191-2348","authenticated-orcid":false,"given":"Antarpreet","family":"Jutla","sequence":"first","affiliation":[{"name":"Department of Environmental Engineering Sciences, GeoHealth and Hydrology Laboratory, University of Florida, Gainesville, Florida, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2718-8387","authenticated-orcid":false,"given":"Moiz","family":"Usmani","sequence":"additional","affiliation":[{"name":"Department of Environmental Engineering Sciences, GeoHealth and Hydrology Laboratory, University of Florida, Gainesville, Florida, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3234-3337","authenticated-orcid":false,"given":"Kyle D.","family":"Brumfield","sequence":"additional","affiliation":[{"name":"Maryland Pathogen Research Institute, University of Maryland, College Park, Maryland, USA"},{"name":"University of Maryland Institute for Advanced Computer Studies, University of Maryland, College Park, Maryland, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Komalpreet","family":"Singh","sequence":"additional","affiliation":[{"name":"Department of Environmental Engineering Sciences, GeoHealth and Hydrology Laboratory, University of Florida, Gainesville, Florida, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fergus","family":"McBean","sequence":"additional","affiliation":[{"name":"Foreign, Commonwealth &amp; 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