Effect of irrigation systems on temporal distribution of malaria vectors in semi-arid regions

Int J Biometeorol. 2014 Apr;58(3):349-59. doi: 10.1007/s00484-012-0630-y. Epub 2013 Jan 22.

Abstract

Previous research models have used climate data to explain habitat conditions of Anopheles mosquitoes transmitting malaria parasites. Although they can estimate mosquito populations with sufficient accuracy in many areas, observational data show that there is a tendency to underestimate the active growth and reproduction period of mosquitoes in semi-arid agricultural regions. In this study, a new, modified model that includes irrigation as a factor was developed to predict the active growing period of mosquitoes more precisely than the base model for ecophysiological and climatological distribution of mosquito generations (ECD-mg). Five sites with complete sets of observational data were selected in semi-arid regions of India for the comparison. The active growing period of mosquitoes determined from the modified ECD-mg model that incorporated the irrigation factor was in agreement with the observational data, whereas the active growing period was underestimated by the previous ECD-mg model that did not incorporate irrigation. This suggests that anthropogenic changes in the water supply due to extensive irrigation can encourage the growth of Anopheles mosquitoes through the alteration of the natural water balance in their habitat. In addition, it was found that the irrigation systems not only enable the active growth of mosquitoes in dry seasons but also play an important role in stabilizing the growth in rainy seasons. Consequently, the irrigation systems could lengthen the annual growing period of Anopheles mosquitoes and increase the maximum generation number of mosquitoes in semi-arid subtropical regions.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Agricultural Irrigation / statistics & numerical data*
  • Animals
  • Anopheles / physiology*
  • Computer Simulation
  • Desert Climate*
  • India
  • Insect Vectors / growth & development*
  • Insect Vectors / parasitology
  • Malaria / parasitology*
  • Models, Statistical*
  • Spatio-Temporal Analysis*