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Anticipatory decision-making for cholera in Malawi.
Jutla, Antarpreet; Usmani, Moiz; Brumfield, Kyle D; Singh, Komalpreet; McBean, Fergus; Potter, Amy; Gutierrez, Angelica; Gama, Samuel; Huq, Anwar; Colwell, Rita R.
Afiliação
  • Jutla A; Department of Environmental Engineering Sciences, GeoHealth and Hydrology Laboratory, University of Florida, Gainesville, Florida, USA.
  • Usmani M; Department of Environmental Engineering Sciences, GeoHealth and Hydrology Laboratory, University of Florida, Gainesville, Florida, USA.
  • Brumfield KD; Maryland Pathogen Research Institute, University of Maryland, College Park, Maryland, USA.
  • Singh K; University of Maryland Institute for Advanced Computer Studies, University of Maryland, College Park, Maryland, USA.
  • McBean F; Department of Environmental Engineering Sciences, GeoHealth and Hydrology Laboratory, University of Florida, Gainesville, Florida, USA.
  • Potter A; Foreign, Commonwealth & Development Office, London, United Kingdom.
  • Gutierrez A; Foreign, Commonwealth & Development Office, London, United Kingdom.
  • Gama S; Office of Water Prediction, National Oceanic and Atmospheric Administration (NOAA), Silver Spring, Maryland, USA.
  • Huq A; Department of Disaster Management Affairs, Office of the President and Cabinet, Lilongwe, Malawi.
  • Colwell RR; Maryland Pathogen Research Institute, University of Maryland, College Park, Maryland, USA.
mBio ; : e0052923, 2023 Nov 14.
Article em En | MEDLINE | ID: mdl-37962395
ABSTRACT
Climate change raises an old disease to a new level of public health threat. The causative agent, Vibrio cholerae, 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.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article