Spatial modeling of rat bites and prediction of rat infestation in Peshawar valley using binomial kriging with logistic regression

Environ Monit Assess. 2018 Mar 24;190(4):245. doi: 10.1007/s10661-018-6615-5.

Abstract

In this study, we propose to develop a geostatistical computational framework to model the distribution of rat bite infestation of epidemic proportion in Peshawar valley, Pakistan. Two species Rattus norvegicus and Rattus rattus are suspected to spread the infestation. The framework combines strengths of maximum entropy algorithm and binomial kriging with logistic regression to spatially model the distribution of infestation and to determine the individual role of environmental predictors in modeling the distribution trends. Our results demonstrate the significance of a number of social and environmental factors in rat infestations such as (I) high human population density; (II) greater dispersal ability of rodents due to the availability of better connectivity routes such as roads, and (III) temperature and precipitation influencing rodent fecundity and life cycle.

Keywords: Binomial kriging; Logistic regression; Rat bite; Spatial modeling; Variogram.

MeSH terms

  • Animals
  • Environmental Monitoring / methods*
  • Humans
  • Logistic Models
  • Male
  • Pakistan
  • Population Density
  • Rats
  • Rodentia / growth & development*
  • Spatial Analysis*
  • Temperature