Using PCA, Poisson and Negative Binomial Model to Study the Climatic Factor and Dengue Fever Outbreak in Lahore
Pages 8-16
Syed Afrozuddin Ahmed, Junaid Saghir Siddiqi,Sabah Quaiser and Shahid Kamal

DOI: http://dx.doi.org/10.6000/1927-5129.2015.11.02

Published: 07 January 2015

Abstract: Various studies have reported that global warming causes unstable climate and many serious impact to physical environment and public health. The increasing incidence of dengue incidence is now a priority health issue and become a health burden of Pakistan. The study aims to understand, explore and compare the climatic factors of Karachi and Lahore that causes the emergence or increasing rate of dengue fever incidence that effects the population and its health. Principal component analysis (PCA) is performed for the purpose of finding if there is/are any general environmental factor/structure which could be considered as Pakistani climate. We developed an early warning model for the prediction of dengue outbreak in Lahore. This has been done by using Poisson regression and Negative binomial regression model. For this purpose we use daily, weekly and monthly data of Lahore. The negative binomial model with lag (28) for Lahore daily data for climatic variable is best model. Lahore daily and weekly maximum temperature effect negatively and for the past 28 days it is estimated to negatively influence on the dengue occurrence by 26.1% times. Daily wind speed is effecting negatively by 14.7% times and minimum temperature effect positively for the past 28 days by 86.7%times.

Keywords: Dengue Fever, Principal component analysis, Negative Binomial Model.