Cargando…
Modelling to explore the potential impact of asymptomatic human infections on transmission and dynamics of African sleeping sickness
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 asymptomat...
Autores principales: | , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8459990/ https://www.ncbi.nlm.nih.gov/pubmed/34516544 http://dx.doi.org/10.1371/journal.pcbi.1009367 |
_version_ | 1784571648356122624 |
---|---|
author | Aliee, Maryam Keeling, Matt J. Rock, Kat S. |
author_facet | Aliee, Maryam Keeling, Matt J. Rock, Kat S. |
author_sort | Aliee, Maryam |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-8459990 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-84599902021-09-24 Modelling to explore the potential impact of asymptomatic human infections on transmission and dynamics of African sleeping sickness Aliee, Maryam Keeling, Matt J. Rock, Kat S. PLoS Comput Biol Research Article 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. Public Library of Science 2021-09-13 /pmc/articles/PMC8459990/ /pubmed/34516544 http://dx.doi.org/10.1371/journal.pcbi.1009367 Text en © 2021 Aliee et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Aliee, Maryam Keeling, Matt J. Rock, Kat S. Modelling to explore the potential impact of asymptomatic human infections on transmission and dynamics of African sleeping sickness |
title | Modelling to explore the potential impact of asymptomatic human infections on transmission and dynamics of African sleeping sickness |
title_full | Modelling to explore the potential impact of asymptomatic human infections on transmission and dynamics of African sleeping sickness |
title_fullStr | Modelling to explore the potential impact of asymptomatic human infections on transmission and dynamics of African sleeping sickness |
title_full_unstemmed | Modelling to explore the potential impact of asymptomatic human infections on transmission and dynamics of African sleeping sickness |
title_short | Modelling to explore the potential impact of asymptomatic human infections on transmission and dynamics of African sleeping sickness |
title_sort | modelling to explore the potential impact of asymptomatic human infections on transmission and dynamics of african sleeping sickness |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8459990/ https://www.ncbi.nlm.nih.gov/pubmed/34516544 http://dx.doi.org/10.1371/journal.pcbi.1009367 |
work_keys_str_mv | AT alieemaryam modellingtoexplorethepotentialimpactofasymptomatichumaninfectionsontransmissionanddynamicsofafricansleepingsickness AT keelingmattj modellingtoexplorethepotentialimpactofasymptomatichumaninfectionsontransmissionanddynamicsofafricansleepingsickness AT rockkats modellingtoexplorethepotentialimpactofasymptomatichumaninfectionsontransmissionanddynamicsofafricansleepingsickness |