Combating cholera by building predictive capabilities for pathogenic Vibrio cholerae in Yemen

Cholera remains a global public health threat in regions where social vulnerabilities intersect with climate and weather processes that impact infectious Vibrio cholerae. While access to safe drinking water and sanitation facilities limit cholera outbreaks, sheer cost of building such infrastructure limits the ability to safeguard the population. Here, using Yemen as an example where cholera outbreak was reported in 2016, we show how predictive abilities for forecasting risk, employing sociodemographical, microbiological, and climate information of cholera, can aid in combating disease outbreak. An epidemiological analysis using Bradford Hill Criteria was employed in near-real-time to understand a predictive model's outputs and cholera cases in Yemen. We note that the model predicted cholera risk at least four weeks in advance for all governorates of Yemen with overall 72% accuracy (varies with the year). We argue the development of anticipatory decision-making frameworks for climate modulated diseases to design intervention activities and limit exposure of pathogens preemptively.

Automated summary

Cholera remains a global public health threat in vulnerable regions, where climate and weather processes intersect with infectious Vibrio cholerae. Predictive abilities for forecasting cholera risk can aid in combating disease outbreaks, as demonstrated by a study in Yemen. The study developed a predictive model that accurately predicted cholera risk at least four weeks in advance for all governorates of Yemen.