Abstract

Background: An unwelcome guest after the devastating 2010 earthquake in Haiti was the shocking emergence of cholera. Four months after the earthquake, 215936 cases had been reported and of these 4131 patients had been infected and died. Mathematical models have been developed to predict the spread of cholera across the entire country and to explore the effects of disease-control interventions. Methods & Materials: Objective: to predict the timing and spread of regional cholera epidemics in Haiti using a mathematical model and to examine the efficacy of disease-controlled interventions. Design: A mathematical model was employed showing person-to-person within and between the 10 geographic regions of the country. Data was obtained from Haitian hospitalization sources plus the 2009 census data. The model involves both waterborne and person-to-person transmission of cholera in order to predict its spread across the country. The model also attempts to assess the effects of 2 distinct interventions, namely vacination on a limited scale and the provision of clean water. Results: The model predicted a rate of transmission between 2.06 to 2.78 and this closely matched empirical observations. The model also suggested an intervention would reduce the risk of cholera spreading by 3%, and this was estimated to be twice the reduction that would result from simply implementing clean water to the same number of individuals. Although the model purports to project the spread of cholera and offer an intervention, it also acknowledges cholera continuing to take a toll on the population for the near future. Conclusion: Despite limited surveillance data, the model comes close to reported disease patterns. The model is a tool that planners can use to manage the epidemic, gain insights into the behavior of this infectious disease, and provide a useful tool for decision making. The possibility of eradicating cholera is yet to be determined. Should cholera become epidemic in Haiti, it will represent a threat to other countries in the region.

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