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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. 

Abstract The incidence of vibriosis is rising globally with evidence of climate variability influencing environmental processes that support growth of pathogenicVibrio spp. The waterborne pathogen,Vibrio vulnificuscan invade wounds and has one of the highest case fatality rates in humans. The bacterium cannot be eradicated from the aquatic environment, hence climate driven environmental conditions enhancing growth and dissemination ofV.vulnificusneed to be understood to provide preemptive assessment of its presence and distribution in aquatic systems. To achieve this objective, satellite remote sensing was employed to quantify the association of sea surface temperature (SST) and chlorophyll‐a(chl‐a) in locations with reportedV.vulnificusinfections. Monthly analysis was done in two populated regions of the Gulf of Mexico—Tampa Bay, Florida, and Galveston Bay, Texas. Results indicate warm water, characterized by a 2‐month lag in SST, high concentration of phytoplankton, proxied for zooplankton using 1 month lagged chl‐avalues, was statistically linked to higher odds ofV.vulnificusinfection in the human population. Identification of climate and ecological processes thresholds is concluded to be useful for development of an heuristic prediction system designed to determine risk of infection for coastal populations.