Predicting dengue outbreak in the metropolitan city Lahore, Pakistan, using dengue vector indices and selected climatological variables as predictors.

OBJECTIVE: Dengue viruses have rapidly spread in Southeast Asia, particularly in Pakistan, during the last few years, so the present study was undertaken to formulate a model for predicting dengue outbreak.

METHODOLOGY: A panel data using STRATA statistical software was employed to determine the effects of entomological indices, Per Man Hour Density (PMHD), Minimum Infection Rate (MIR) and selected climatic variables on dengue patients by using Fixed Effects (FE) and Random Effects (RE) models.

RESULTS: Results showed that R2 value, reflecting fitness of model was 0.3026 in FE model and 0.3028 in RE model, while the Coefficient and P [Z] values in RE model, indicating individual fitness of any variable in the model, revealed that PMHD, MIR, Air Temperature and Relative Humidity had positive impact on the number of dengue patients, while rainfall exhibited negative impact..

CONCLUSIONS: For every 10 unit rise in PMHD, MIR, atmospheric temperature and relative humidity, the number of patients increased by 4.01, 15.88, 3.10 and 5.73, respectively, while an increase in rainfall by 10 mm will result in decrease in the number of dengue patients by -1.01. Further analysis of socioeconomic and demographic variables of participants is suggested.