Stemming cholera tides in Zimbabwe through mass vaccination

Int J Infect Dis. 2020 Jul:96:222-227. doi: 10.1016/j.ijid.2020.03.077. Epub 2020 May 1.

Abstract

Background: In 2018, Zimbabwe declared another major cholera outbreak a decade after recording one of the worst cholera outbreaks in Africa.

Methods: A mathematical model for cholera was used to estimate the magnitude of the cholera outbreak and vaccination coverage using cholera cases reported data. A Markov chain Monte Carlo method based on a Bayesian framework was used to fit the model in order to estimate the basic reproductive number and required vaccination coverage for cholera control.

Results: The results showed that the outbreak had a basic reproductive number of 1.82 (95% credible interval [CrI] 1.53-2.11) and required vaccination coverage of at least 58% (95% Crl 45-68%) to be contained using an oral cholera vaccine of 78% efficacy. Sensitivity analysis demonstrated that a vaccine with at least 55% efficacy was sufficient to contain the outbreak but at higher coverage of 75% (95% Crl 58-88%). However, high-efficacy vaccines would greatly reduce the required coverage, with 100% efficacy vaccine reducing coverage to 45% (95% Crl 35-53%).

Conclusions: These findings reinforce the crucial need for oral cholera vaccines to control cholera in Zimbabwe, considering that the decay of water reticulation and sewerage infrastructure is unlikely to be effectively addressed in the coming years.

Keywords: Basic reproductive number; Cholera; Mathematical model; Prevention; Vaccination.

MeSH terms

  • Bayes Theorem
  • Cholera / epidemiology
  • Cholera / prevention & control*
  • Cholera Vaccines / adverse effects*
  • Disease Outbreaks / prevention & control
  • Humans
  • Mass Vaccination* / methods
  • Models, Biological
  • Monte Carlo Method
  • Vaccination Coverage
  • Zimbabwe / epidemiology

Substances

  • Cholera Vaccines