Markov Model Predicts Changes in STH Prevalence during Control Activities Even with a Reduced Amount of Baseline Information.
BACKGROUND:Estimating the reduction in levels of infection during implementation of soil-transmitted helminth (STH) control programmes is important to measure their performance and to plan interventions. Markov modelling techniques have been used with some success to predict changes in STH prevalenc...
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ftdoajarticles:oai:doaj.org/article:1d71a2506e764ee7a27c3e9a6c536935 2023-05-15T15:15:42+02:00 Markov Model Predicts Changes in STH Prevalence during Control Activities Even with a Reduced Amount of Baseline Information. Antonio Montresor Arminder Deol Natacha À Porta Nam Lethanh Dina Jankovic 2016-04-01T00:00:00Z https://doi.org/10.1371/journal.pntd.0004371 https://doaj.org/article/1d71a2506e764ee7a27c3e9a6c536935 EN eng Public Library of Science (PLoS) http://europepmc.org/articles/PMC4817985?pdf=render https://doaj.org/toc/1935-2727 https://doaj.org/toc/1935-2735 1935-2727 1935-2735 doi:10.1371/journal.pntd.0004371 https://doaj.org/article/1d71a2506e764ee7a27c3e9a6c536935 PLoS Neglected Tropical Diseases, Vol 10, Iss 4, p e0004371 (2016) Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 article 2016 ftdoajarticles https://doi.org/10.1371/journal.pntd.0004371 2022-12-31T00:49:32Z BACKGROUND:Estimating the reduction in levels of infection during implementation of soil-transmitted helminth (STH) control programmes is important to measure their performance and to plan interventions. Markov modelling techniques have been used with some success to predict changes in STH prevalence following treatment in Viet Nam. The model is stationary and to date, the prediction has been obtained by calculating the transition probabilities between the different classes of intensity following the first year of drug distribution and assuming that these remain constant in subsequent years. However, to run this model longitudinal parasitological data (including intensity of infection) are required for two consecutive years from at least 200 individuals. Since this amount of data is not often available from STH control programmes, the possible application of the model in control programme is limited. The present study aimed to address this issue by adapting the existing Markov model to allow its application when a more limited amount of data is available and to test the predictive capacities of these simplified models. METHOD:We analysed data from field studies conducted with different combination of three parameters: (i) the frequency of drug administration; (ii) the drug distributed; and (iii) the target treatment population (entire population or school-aged children only). This analysis allowed us to define 10 sets of standard transition probabilities to be used to predict prevalence changes when only baseline data are available (simplified model 1). We also formulated three equations (one for each STH parasite) to calculate the predicted prevalence of the different classes of intensity from the total prevalence. These equations allowed us to design a simplified model (SM2) to obtain predictions when the classes of intensity at baseline were not known. To evaluate the performance of the simplified models, we collected data from the scientific literature on changes in STH prevalence during the implementation ... Article in Journal/Newspaper Arctic Directory of Open Access Journals: DOAJ Articles Arctic PLOS Neglected Tropical Diseases 10 4 e0004371 |
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Directory of Open Access Journals: DOAJ Articles |
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English |
topic |
Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 |
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Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 Antonio Montresor Arminder Deol Natacha À Porta Nam Lethanh Dina Jankovic Markov Model Predicts Changes in STH Prevalence during Control Activities Even with a Reduced Amount of Baseline Information. |
topic_facet |
Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 |
description |
BACKGROUND:Estimating the reduction in levels of infection during implementation of soil-transmitted helminth (STH) control programmes is important to measure their performance and to plan interventions. Markov modelling techniques have been used with some success to predict changes in STH prevalence following treatment in Viet Nam. The model is stationary and to date, the prediction has been obtained by calculating the transition probabilities between the different classes of intensity following the first year of drug distribution and assuming that these remain constant in subsequent years. However, to run this model longitudinal parasitological data (including intensity of infection) are required for two consecutive years from at least 200 individuals. Since this amount of data is not often available from STH control programmes, the possible application of the model in control programme is limited. The present study aimed to address this issue by adapting the existing Markov model to allow its application when a more limited amount of data is available and to test the predictive capacities of these simplified models. METHOD:We analysed data from field studies conducted with different combination of three parameters: (i) the frequency of drug administration; (ii) the drug distributed; and (iii) the target treatment population (entire population or school-aged children only). This analysis allowed us to define 10 sets of standard transition probabilities to be used to predict prevalence changes when only baseline data are available (simplified model 1). We also formulated three equations (one for each STH parasite) to calculate the predicted prevalence of the different classes of intensity from the total prevalence. These equations allowed us to design a simplified model (SM2) to obtain predictions when the classes of intensity at baseline were not known. To evaluate the performance of the simplified models, we collected data from the scientific literature on changes in STH prevalence during the implementation ... |
format |
Article in Journal/Newspaper |
author |
Antonio Montresor Arminder Deol Natacha À Porta Nam Lethanh Dina Jankovic |
author_facet |
Antonio Montresor Arminder Deol Natacha À Porta Nam Lethanh Dina Jankovic |
author_sort |
Antonio Montresor |
title |
Markov Model Predicts Changes in STH Prevalence during Control Activities Even with a Reduced Amount of Baseline Information. |
title_short |
Markov Model Predicts Changes in STH Prevalence during Control Activities Even with a Reduced Amount of Baseline Information. |
title_full |
Markov Model Predicts Changes in STH Prevalence during Control Activities Even with a Reduced Amount of Baseline Information. |
title_fullStr |
Markov Model Predicts Changes in STH Prevalence during Control Activities Even with a Reduced Amount of Baseline Information. |
title_full_unstemmed |
Markov Model Predicts Changes in STH Prevalence during Control Activities Even with a Reduced Amount of Baseline Information. |
title_sort |
markov model predicts changes in sth prevalence during control activities even with a reduced amount of baseline information. |
publisher |
Public Library of Science (PLoS) |
publishDate |
2016 |
url |
https://doi.org/10.1371/journal.pntd.0004371 https://doaj.org/article/1d71a2506e764ee7a27c3e9a6c536935 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic |
genre_facet |
Arctic |
op_source |
PLoS Neglected Tropical Diseases, Vol 10, Iss 4, p e0004371 (2016) |
op_relation |
http://europepmc.org/articles/PMC4817985?pdf=render https://doaj.org/toc/1935-2727 https://doaj.org/toc/1935-2735 1935-2727 1935-2735 doi:10.1371/journal.pntd.0004371 https://doaj.org/article/1d71a2506e764ee7a27c3e9a6c536935 |
op_doi |
https://doi.org/10.1371/journal.pntd.0004371 |
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PLOS Neglected Tropical Diseases |
container_volume |
10 |
container_issue |
4 |
container_start_page |
e0004371 |
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