Analyzing transmission dynamics of cholera with public health interventions

Drew Posny, Jin Wang, Zindoga Mukandavire, Chairat Modnak

Research output: Contribution to journalArticle

24 Citations (Scopus)

Abstract

Cholera continues to be a serious public health concern in developing countries and the global increase in the number of reported outbreaks suggests that activities to control the diseases and surveillance programs to identify or predict the occurrence of the next outbreaks are not adequate. These outbreaks have increased in frequency, severity, duration and endemicity in recent years. Mathematical models for infectious diseases play a critical role in predicting and understanding disease mechanisms, and have long provided basic insights in the possible ways to control infectious diseases. In this paper, we present a new deterministic cholera epidemiological model with three types of control measures incorporated into a cholera epidemic setting: treatment, vaccination and sanitation. Essential dynamical properties of the model with constant intervention controls which include local and global stabilities for the equilibria are carefully analyzed. Further, using optimal control techniques, we perform a study to investigate cost-effective solutions for time-dependent public health interventions in order to curb disease transmission in epidemic settings. Our results show that the basic reproductive number (R0) remains the model's epidemic threshold despite the inclusion of a package of cholera interventions. For time-dependent controls, the results suggest that these interventions closely interplay with each other, and the costs of controls directly affect the length and strength of each control in an optimal strategy.

Original languageEnglish
Pages (from-to)38-53
Number of pages16
JournalMathematical Biosciences
Volume264
Early online date28 Mar 2015
DOIs
Publication statusPublished - Jun 2015
Externally publishedYes

Keywords

  • Basic Reproduction Number
  • Cholera
  • Communicable Disease Control
  • Humans
  • Models, Theoretical
  • Journal Article
  • Research Support, U.S. Gov't, Non-P.H.S.

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