Math In A Time Of Cholera

Using mathematical models to analyze data from the World Health Organization, scientists in Japan accurately forecasted the peak of the 2017 cholera outbreak in Yemen.

AsianScientist (Aug. 30, 2017) – Scientists in Japan have developed a mathematical model which accurately forecasted the peak of a cholera epidemic in Yemen. Their findings are published in the journal Theoretical Biology and Medical Modelling.

Cholera is caused by the bacterium Vibrio cholerae which infects the small intestine through contaminated water and food. The symptoms of infection include diarrhea, abdominal cramps and dehydration. Although a cholera vaccine is currently available, poor sanitation and the lack of access to vaccines mean that occasional outbreaks still occur. For example, Yemen was recently hit by one of the world’s worst cholera epidemics. Between 27 April 2017 and 17 July 2017, a total of 356,591 suspected cases were reported and 1,802 people died from the disease.

Mathematical modelling has been used to investigate the transmission dynamics of major cholera epidemics, mostly focusing on the 2010 epidemic in Haiti. Many studies have also been conducted to evaluate measures to contain cholera epidemics, with the majority of them centering on how best to distribute limited resources. However, virtually no real-time analyses of data from devastating outbreaks were conducted to provide updated forecasts.

In this study, researchers at Hokkaido University compiled a real-time forecast based on weekly data collected by the World Health Organization about suspected cases and fatalities between 16 April 2017 and 1 July 2017. The team incorporated reporting delays—time lags between the onset of the disease and the reporting of cases—in the mathematical model by analyzing the epidemic curve that was updated every week.

Through the study of weekly death rates, they also discovered a way to correct for ascertainment bias—the tendency for more cholera cases to be reported in the later phases of the outbreak, after numerous reports have already been made. In doing so, they could improve the accuracy of the logistic model and the Richards model which are two well known methods for real-time monitoring of epidemics.

The team estimated that the cumulative number of cholera cases at the end of the epidemic would be 790,778 when they used the logistic model. When they applied the Richards model, this number was revised to 767,029. The researchers also predicted that the epidemic curve would peak by early July 2017 and then drop monotonically in the subsequent weeks. The forecasted monotonic decline was indeed observed in mid-August 2017.

“Our model succeeded in excluding two biases for the first time and the resulting forecast has been proven reliable so far. Real-time forecasting could enhance situation awareness about the ongoing epidemic communication between experts and citizens while avoiding excessive pessimism. The data can also be used to craft future measures against cholera,” said Professor Hiroshi Nishiura from Hokkaido University.

The article can be found at: Nishiura et al. (2017) Transmission Dynamics of Cholera in Yemen, 2017: A Real Time Forecasting.


Source: Hokkaido University; Photo: Pixabay.
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