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Determining post-treatment surveillance criteria for predicting the elimination of Schistosoma mansoni transmission

BACKGROUND: The World Health Organization (WHO) has set elimination (interruption of transmission) as an end goal for schistosomiasis. However, there is currently little guidance on the monitoring and evaluation strategy required once very low prevalence levels have been reached to determine whether...

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Autores principales: Toor, Jaspreet, Truscott, James E., Werkman, Marleen, Turner, Hugo C., Phillips, Anna E., King, Charles H., Medley, Graham F., Anderson, Roy M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6745786/
https://www.ncbi.nlm.nih.gov/pubmed/31522690
http://dx.doi.org/10.1186/s13071-019-3611-8
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author Toor, Jaspreet
Truscott, James E.
Werkman, Marleen
Turner, Hugo C.
Phillips, Anna E.
King, Charles H.
Medley, Graham F.
Anderson, Roy M.
author_facet Toor, Jaspreet
Truscott, James E.
Werkman, Marleen
Turner, Hugo C.
Phillips, Anna E.
King, Charles H.
Medley, Graham F.
Anderson, Roy M.
author_sort Toor, Jaspreet
collection PubMed
description BACKGROUND: The World Health Organization (WHO) has set elimination (interruption of transmission) as an end goal for schistosomiasis. However, there is currently little guidance on the monitoring and evaluation strategy required once very low prevalence levels have been reached to determine whether elimination or resurgence of the disease will occur after stopping mass drug administration (MDA) treatment. METHODS: We employ a stochastic individual-based model of Schistosoma mansoni transmission and MDA impact to determine a prevalence threshold, i.e. prevalence of infection, which can be used to determine whether elimination or resurgence will occur after stopping treatment with a given probability. Simulations are run for treatment programmes with varying probabilities of achieving elimination and for settings where adults harbour low to high burdens of infection. Prevalence is measured based on using a single Kato-Katz on two samples per individual. We calculate positive predictive values (PPV) using PPV ≥ 0.9 as a reliable measure corresponding to ≥ 90% certainty of elimination. We analyse when post-treatment surveillance should be carried out to predict elimination. We also determine the number of individuals across a single community (of 500–1000 individuals) that should be sampled to predict elimination. RESULTS: We find that a prevalence threshold of 1% by single Kato-Katz on two samples per individual is optimal for predicting elimination at two years (or later) after the last round of MDA using a sample size of 200 individuals across the entire community (from all ages). This holds regardless of whether the adults have a low or high burden of infection relative to school-aged children. CONCLUSIONS: Using a prevalence threshold of 0.5% is sufficient for surveillance six months after the last round of MDA. However, as such a low prevalence can be difficult to measure in the field using Kato-Katz, we recommend using 1% two years after the last round of MDA. Higher prevalence thresholds of 2% or 5% can be used but require waiting over four years for post-treatment surveillance. Although, for treatment programmes where elimination is highly likely, these higher thresholds could be used sooner. Additionally, switching to more sensitive diagnostic techniques, will allow for a higher prevalence threshold to be employed. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13071-019-3611-8) contains supplementary material, which is available to authorized users.
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spelling pubmed-67457862019-09-18 Determining post-treatment surveillance criteria for predicting the elimination of Schistosoma mansoni transmission Toor, Jaspreet Truscott, James E. Werkman, Marleen Turner, Hugo C. Phillips, Anna E. King, Charles H. Medley, Graham F. Anderson, Roy M. Parasit Vectors Research BACKGROUND: The World Health Organization (WHO) has set elimination (interruption of transmission) as an end goal for schistosomiasis. However, there is currently little guidance on the monitoring and evaluation strategy required once very low prevalence levels have been reached to determine whether elimination or resurgence of the disease will occur after stopping mass drug administration (MDA) treatment. METHODS: We employ a stochastic individual-based model of Schistosoma mansoni transmission and MDA impact to determine a prevalence threshold, i.e. prevalence of infection, which can be used to determine whether elimination or resurgence will occur after stopping treatment with a given probability. Simulations are run for treatment programmes with varying probabilities of achieving elimination and for settings where adults harbour low to high burdens of infection. Prevalence is measured based on using a single Kato-Katz on two samples per individual. We calculate positive predictive values (PPV) using PPV ≥ 0.9 as a reliable measure corresponding to ≥ 90% certainty of elimination. We analyse when post-treatment surveillance should be carried out to predict elimination. We also determine the number of individuals across a single community (of 500–1000 individuals) that should be sampled to predict elimination. RESULTS: We find that a prevalence threshold of 1% by single Kato-Katz on two samples per individual is optimal for predicting elimination at two years (or later) after the last round of MDA using a sample size of 200 individuals across the entire community (from all ages). This holds regardless of whether the adults have a low or high burden of infection relative to school-aged children. CONCLUSIONS: Using a prevalence threshold of 0.5% is sufficient for surveillance six months after the last round of MDA. However, as such a low prevalence can be difficult to measure in the field using Kato-Katz, we recommend using 1% two years after the last round of MDA. Higher prevalence thresholds of 2% or 5% can be used but require waiting over four years for post-treatment surveillance. Although, for treatment programmes where elimination is highly likely, these higher thresholds could be used sooner. Additionally, switching to more sensitive diagnostic techniques, will allow for a higher prevalence threshold to be employed. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13071-019-3611-8) contains supplementary material, which is available to authorized users. BioMed Central 2019-09-16 /pmc/articles/PMC6745786/ /pubmed/31522690 http://dx.doi.org/10.1186/s13071-019-3611-8 Text en © The Author(s) 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Toor, Jaspreet
Truscott, James E.
Werkman, Marleen
Turner, Hugo C.
Phillips, Anna E.
King, Charles H.
Medley, Graham F.
Anderson, Roy M.
Determining post-treatment surveillance criteria for predicting the elimination of Schistosoma mansoni transmission
title Determining post-treatment surveillance criteria for predicting the elimination of Schistosoma mansoni transmission
title_full Determining post-treatment surveillance criteria for predicting the elimination of Schistosoma mansoni transmission
title_fullStr Determining post-treatment surveillance criteria for predicting the elimination of Schistosoma mansoni transmission
title_full_unstemmed Determining post-treatment surveillance criteria for predicting the elimination of Schistosoma mansoni transmission
title_short Determining post-treatment surveillance criteria for predicting the elimination of Schistosoma mansoni transmission
title_sort determining post-treatment surveillance criteria for predicting the elimination of schistosoma mansoni transmission
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6745786/
https://www.ncbi.nlm.nih.gov/pubmed/31522690
http://dx.doi.org/10.1186/s13071-019-3611-8
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