Pandemics, pathogenicity and changing molecular epidemiology of cholera in the era of global warming

Background: Vibrio cholerae, a Gram-negative, non-spore forming curved rod is found in diverse aquatic ecosystems around the planet. It is classified according to its major surface antigen into around 206 serogroups, of which O1 and O139 cause epidemic cholera. A recent spatial modelling technique estimated that around 2.86 million cholera cases occur globally every year, and of them approximately 95,000 die. About 1.3 billion people are currently at risk of infection from cholera. Meta-analysis and mathematical modelling have demonstrated that due to global warming the burden of vector-borne diseases like malaria, leishmaniasis, meningococcal meningitis, viral encephalitis, dengue and chikungunya will increase in the coming years in the tropics and beyond. Cholera and climate: This review offers an overview of the interplay between global warming and the pathogenicity and epidemiology of V. cholerae. Several distinctive features of cholera survival (optimal thriving at 15% salinity, 30 degrees C water temperature, and pH 8.5) indicate a possible role of climate change in triggering the epidemic process. Genetic exchange (ctxAB, zot, ace, cep, and orfU) between strains and transduction process allows potential emergence of new toxigenic clones. These processes are probably controlled by precise environmental signals such as optimum temperature, sunlight and osmotic conditions. Environmental influences on phytoplankton growth and chitin remineralization will be discussed alongside the interplay of poor sanitary conditions, overcrowding, improper sewage disposal and global warming in promoting the growth and transmission of this deadly disease. Conclusion: The development of an effective early warning system based on climate data could help to prevent and control future outbreaks. It may become possible to integrate real-time monitoring of oceanic regions, climate variability and epidemiological and demographic population dynamics to predict cholera outbreaks and support the design of cost-effective public health strategies.