Nonlinear optimization model for the control of leishmaniasis in Bihar, India using insecticide intervention

Kaushik K. Gorahava, Jay M. Rosenberger, Anuj Mubayi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Leishmaniasis is an infectious disease that is spread by the sandfly. Bihar, a state in India, has the highest visceral leishmaniasis (VL) incidence and mortality rate in the world. The Bihar government undertakes biannual insecticide spraying to reduce the sandfly population. A number of models that study the spread of VL have previously been described. Here, we present a simplified transmission dynamics model with insecticide intervention, to account for the effects of insecticide on the spread of VL in Bihar. Since sandflies responsible for the spread of VL in Bihar are zoophilic in nature, this model includes both houses and cattle sheds, which are visited by sandflies in search of a blood meal. Entomological, insecticide toxicity, and demographical parameters are incorporated in the model. Due to limited financial resources, an insecticide intervention campaign cannot spray insecticide in all houses and cattle sheds present in a district. An optimization model presented in this paper determines the number of houses and cattle sheds to be sprayed with insecticide in order to prevent the maximum number of VL infections with an available budget.

Original languageEnglish (US)
Title of host publicationIIE Annual Conference and Expo 2013
PublisherInstitute of Industrial Engineers
Pages2610-2619
Number of pages10
StatePublished - 2013
Externally publishedYes
EventIIE Annual Conference and Expo 2013 - San Juan, Puerto Rico
Duration: May 18 2013May 22 2013

Other

OtherIIE Annual Conference and Expo 2013
CountryPuerto Rico
CitySan Juan
Period5/18/135/22/13

Keywords

  • Coupled ordinary differential equations system
  • Insecticide intervention
  • Leishmaniasis
  • Nonlinear optimization model
  • Vector-host model

ASJC Scopus subject areas

  • Industrial and Manufacturing Engineering

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