Modelling to explore the potential impact of asymptomatic human infections on transmission and dynamics of African sleeping sickness

PLoS Comput Biol. 2021 Sep 13;17(9):e1009367. doi: 10.1371/journal.pcbi.1009367. eCollection 2021 Sep.

Abstract

Gambiense human African trypanosomiasis (gHAT, sleeping sickness) is one of several neglected tropical diseases (NTDs) where there is evidence of asymptomatic human infection but there is uncertainty of the role it plays in transmission and maintenance. To explore possible consequences of asymptomatic infections, particularly in the context of elimination of transmission-a goal set to be achieved by 2030-we propose a novel dynamic transmission model to account for the asymptomatic population. This extends an established framework, basing infection progression on a number of experimental and observation gHAT studies. Asymptomatic gHAT infections include those in people with blood-dwelling trypanosomes, but no discernible symptoms, or those with parasites only detectable in skin. Given current protocols, asymptomatic infection with blood parasites may be diagnosed and treated, based on observable parasitaemia, in contrast to many other diseases for which treatment (and/or diagnosis) may be based on symptomatic infection. We construct a model in which exposed people can either progress to either asymptomatic skin-only parasite infection, which would not be diagnosed through active screening algorithms, or blood-parasite infection, which is likely to be diagnosed if tested. We add extra parameters to the baseline model including different self-cure, recovery, transmission and detection rates for skin-only or blood infections. Performing sensitivity analysis suggests all the new parameters introduced in the asymptomatic model can impact the infection dynamics substantially. Among them, the proportion of exposures resulting in initial skin or blood infection appears the most influential parameter. For some plausible parameterisations, an initial fall in infection prevalence due to interventions could subsequently stagnate even under continued screening due to the formation of a new, lower endemic equilibrium. Excluding this scenario, our results still highlight the possibility for asymptomatic infection to slow down progress towards elimination of transmission. Location-specific model fitting will be needed to determine if and where this could pose a threat.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Asymptomatic Infections / epidemiology*
  • Basic Reproduction Number / statistics & numerical data
  • Computational Biology
  • Computer Simulation
  • Endemic Diseases / prevention & control
  • Endemic Diseases / statistics & numerical data
  • Humans
  • Models, Biological*
  • Prevalence
  • Trypanosoma brucei gambiense*
  • Trypanosomiasis, African / epidemiology*
  • Trypanosomiasis, African / prevention & control
  • Trypanosomiasis, African / transmission*
  • Tsetse Flies / parasitology

Grants and funding

This work was supported by the Bill and Melinda Gates Foundation (www.gatesfoundation.org) through the NTD Modelling Consortium [OPP1184344] (M.A., M.J.K. and K.S.R.) and the Human African Trypanosomiasis Modelling and Economic Predictions for Policy (HAT MEPP) project [OPP1177824] (M.J.K. and K.S.R.). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.