Locally measured variables such as temperature and rainfall have been positively associated with increased cholera incidence in multiple studies. The study examined the effect of rainfall, temperature and relative humidity on cholera incidence in the City of Maroua, located in the Far North of Cameroon. The relative individual contribution of rainfall, temperature and humidity and then their combined contribution on the occurrence of cholera were examined. Using monthly time series of cholera epidemiological data, average monthly rainfall (mm), average monthly air temperature (degree Celsius), and average monthly relative humidity (percent) data from 1996 to 2011.We implemented Generalized Additive Modeling (GAM) procedures to measure the contribution of each weather parameter to the incidence of cholera and identified the most influential parameter on cholera incidence. We found that taken individually, rainfall, temperature and humidity are correlated with cholera incidence but temperature seems more determinant since it has a higher deviance explained (26%). Furthermore, the association between temperature and rainfall in the multivariate model with interaction has the highest deviance explained is 64.4%, the lowest AIC is 1911.963, and the highest R2 (0.6). These results indicate that statistical time series models in general and the Generalized Additive models in particular should lead to a better understanding of the disease mechanism that can assist in the planning of public health interventions. These results contribute also to the growing debate on climate and cholera.
- GAM model
ASJC Scopus subject areas
- Geography, Planning and Development
- Earth-Surface Processes
- Computers in Earth Sciences