RESUMEN
Vibrio spp. thrive in warm water and moderate salinity, and they are associated with aquatic invertebrates, notably crustaceans and zooplankton. At least 12 Vibrio spp. are known to cause infection in humans, and Vibrio cholerae is well documented as the etiological agent of pandemic cholera. Pathogenic non-cholera Vibrio spp., e.g., Vibrio parahaemolyticus and Vibrio vulnificus, cause gastroenteritis, septicemia, and other extra-intestinal infections. Incidence of vibriosis is rising globally, with evidence that anthropogenic factors, primarily emissions of carbon dioxide associated with atmospheric warming and more frequent and intense heatwaves, significantly influence environmental parameters, e.g., temperature, salinity, and nutrients, all of which can enhance growth of Vibrio spp. in aquatic ecosystems. It is not possible to eliminate Vibrio spp., as they are autochthonous to the aquatic environment and many play a critical role in carbon and nitrogen cycling. Risk prediction models provide an early warning that is essential for safeguarding public health. This is especially important for regions of the world vulnerable to infrastructure instability, including lack of 'water, sanitation, and hygiene' (WASH), and a less resilient infrastructure that is vulnerable to natural calamity, e.g., hurricanes, floods, and earthquakes, and/or social disruption and civil unrest, arising from war, coups, political crisis, and economic recession. Incorporating environmental, social, and behavioural parameters into such models allows improved prediction, particularly of cholera epidemics. We have reported that damage to WASH infrastructure, coupled with elevated air temperatures and followed by above average rainfall, promotes exposure of a population to contaminated water and increases the risk of an outbreak of cholera. Interestingly, global predictive risk models successful for cholera have the potential, with modification, to predict diseases caused by other clinically relevant Vibrio spp. In the research reported here, the focus was on environmental parameters associated with incidence and distribution of clinically relevant Vibrio spp. and their role in disease transmission. In addition, molecular methods designed for detection and enumeration proved useful for predictive modelling and are described, namely in the context of prediction of environmental conditions favourable to Vibrio spp., hence human health risk.