An agent-based model of exposure to human toxocariasis: a multi-country validation

K. Kanobana, B. Devleesschauwer, K. Polman, N. Speybroeck

Research output: Contribution to journalA1: Web of Science-article

Abstract

Seroprevalence data illustrate that human exposure to Toxocara is frequent. Environmental contamination with Toxocara spp. eggs is assumed to be the best indicator of human exposure, but increased risk of exposure has also been associated with many other factors. Reported associations are inconsistent, however, and there is still ambiguity regarding the factors driving the onset of Toxocara antibody positivity. The objective of this work was to assess the validity of our current conceptual understanding of the key processes driving human exposure to Toxocara. We constructed an agent-based model predicting Toxocara antibody positivity (as a measure of exposure) in children. Exposure was assumed to depend on the joint probability of 3 parameters: (1) environmental contamination with Toxocara spp. eggs, (2) larvation of these eggs and (3) the age-related contact with these eggs. This joint probability was linked to processes of acquired humoral immunity, influencing the rate of antibody seroreversion. The results of the simulation were validated against published data from 5 different geographical settings. Using simple rules and a stochastic approach with parameter estimates derived from the respective contexts, plausible serological patterns emerged from the model in nearly all settings. Our approach leads to novel insights in the transmission dynamics of Toxocara.
Original languageEnglish
JournalParasitology
Volume140
Issue number8
Pages (from-to)986-998
Number of pages13
ISSN0031-1820
DOIs
Publication statusPublished - 2013

Keywords

  • Helminthic diseases
  • Zoonoses
  • Toxocariasis
  • Toxocara
  • Dogs
  • Cats
  • Prevalence
  • Atopic diseases
  • Transmission dynamics
  • Prediction
  • Risk factors
  • Environmental exposure
  • Contamination
  • Antibodies
  • Larvae
  • Contact tracing
  • Children
  • Probabilities
  • Modeling
  • Review of the literature

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