LAUSR

During the span of August–October, 2017 a major outbreak of Dengue fever happened in Khyber Pakhtunkhwa province of Pakistan. Cases were reported from all the major cities and rural areas, but Peshawar was more severely hit with more than half of the total cases belonging to central Peshawar city. The epidemic patterns reveal that dengue fever cases were mostly reported for plain areas and also low altitude mountainous regions. We employed the principle of maximum entropy to establish the underlying distribution of dengue presences and background data. A geostatistical analysis was conducted by modelling the spatial structure of the dengue fever risk and estimating the prediction maps with corresponding uncertainty taking into account some of the most significant covariates. The prediction maps were created using binomial kriging with a binary logistic drift. The analysis was carried out for the whole province as well as subregions to have a closer look of the spatial distribution at local level. Our results show that our methodology performed well. Vector distribution, population density, and distance to roads were found to significantly affecting the spatial distribution of risk and gives very informative pattern.