Epidemiology and Infection · 2007 · 31 citations · 14 references
Public HealthChild HealthInfectious DiseasesEpidemiologyInfectious Disease EpidemiologyTime Series AnalysisDisease ForecastingDisease Risk AssessmentEpidemic ForecastingPredictive Health ModelingTime-series Analysis In EpidemiologyClimate-based Disease ForecastingForecasting Disease OutbreaksMonthly ForecastingOutbreak Early Warning SystemsPearson Correlation CoefficientPrediction Model DevelopmentStatistical Forecasting ModelsWeather-based Disease Forecasting
To determine if a prediction of epidemic cholera using climate data can be made, we performed autoregression analysis using the data recorded in Dhaka City, Bangladesh over a 20-year period (1983-2002) comparing the number of children aged <10 years who were infected with Vibrio cholerae O1 to the maximum and minimum temperatures and rainfall. We formulated a simple autoregression model that predicts the monthly number of patients using earlier climate variables. The monthly number of patients predicted by this model agreed well with the actual monthly number of patients where the Pearson's correlation coefficient was 0.95. Arbitrarily defined, 39.4% of the predicted numbers during the study period were within 0.8-1.2 times the observed numbers. This prediction model uses the climate data recorded 2-4 months before. Therefore, our approach may be a good basis for establishing a practical early warning system for epidemic cholera.
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Cholera Dynamics and El Niño-Southern Oscillation
Mercedes Pascual, Xavier Rodó, Stephen P. Ellner et al. · Science · 2000 · 502 citations
B. Lobitz, Louisa R. Beck, Anwar Huq et al. · Proceedings of the National Academy of Sciences · 2000 · 427 citations · Full text
Refractory periods and climate forcing in cholera dynamics
Katia Koelle, Xavier Rodó, Mercedes Pascual et al. · Nature · 2005 · 426 citations · Full text