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A mathematical model to estimate the incidence of child wasting in Yemen

INTRODUCTION: The ongoing civil war in Yemen has severely restricted imports of food and fuel, disrupted livelihoods and displaced millions, worsening already high pre-war levels of food insecurity. Paired with frequent outbreaks of disease and a collapsed health system, this has brought rates of wa...

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Autores principales: Hussein, Rana A., Suprenant, Mark P., Al-Dheeb, Najwa, Guerrero, Saul, Rogers, Eleanor, Shafique, Fouzia, Dyson, Meredith, Zaman, Muhammad H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8364017/
https://www.ncbi.nlm.nih.gov/pubmed/34391455
http://dx.doi.org/10.1186/s13031-021-00400-6
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author Hussein, Rana A.
Suprenant, Mark P.
Al-Dheeb, Najwa
Guerrero, Saul
Rogers, Eleanor
Shafique, Fouzia
Dyson, Meredith
Zaman, Muhammad H.
author_facet Hussein, Rana A.
Suprenant, Mark P.
Al-Dheeb, Najwa
Guerrero, Saul
Rogers, Eleanor
Shafique, Fouzia
Dyson, Meredith
Zaman, Muhammad H.
author_sort Hussein, Rana A.
collection PubMed
description INTRODUCTION: The ongoing civil war in Yemen has severely restricted imports of food and fuel, disrupted livelihoods and displaced millions, worsening already high pre-war levels of food insecurity. Paired with frequent outbreaks of disease and a collapsed health system, this has brought rates of wasting in children under five to the country’s highest recorded levels, which continue to increase as the crisis worsens and aid becomes increasingly limited. In their planning of services to treat and prevent wasting in children, humanitarian agencies rely on a standard calculation to estimate the expected number of cases for the coming year, where incidence is estimated from prevalence and the average duration of an episode of wasting. The average duration of an episode of moderate and severe wasting is currently estimated at 7.5 months—a globally-used value derived from historical cohort studies. Given that incidence varies considerably by context—where food production and availability, treatment coverage and disease rates all vary—a single estimate cannot be applied to all contexts, and especially not a highly unstable crisis setting such as Yemen. While recent studies have aimed to derive context-specific incidence estimates in several countries, little has been done to estimate the incidence of both moderate and severe wasting in Yemen. METHODS: In order to provide context-specific estimates of the average duration of an episode, and resultingly, incidence correction factors for moderate and severe wasting, we have developed a Markov model. Model inputs were estimated using a combination of treatment admission and outcome records compiled by the Yemen Nutrition Cluster, 2018 and 2019 SMART surveys, and other estimates from the literature. The model derived estimates for the governorate of Lahj, Yemen; it was initialized using August 2018 SMART survey prevalence data and run until October 2019—the date of the subsequent SMART survey. Using a process of repeated model calibration, the incidence correction factors for severe wasting and moderate wasting were found, validating the resulting prevalence against the recorded value from the 2019 SMART survey. RESULTS: The average durations of an episode of moderate and severe wasting were estimated at 4.86 months, for an incidence correction factor k of 2.59, and 3.86 months, for an incidence correction factor k of 3.11, respectively. It was found that the annual caseload of moderate wasting was 36% higher and the annual caseload of severe wasting 58% higher than the originally-assumed values, estimated with k = 1.6. CONCLUSION: The model-derived incidence rates, consistent with findings from other contexts that a global incidence correction factor cannot be sufficient, allow for improved, context-specific estimates of the burden of wasting in Yemen. In crisis settings such as Yemen where funding and resources are extremely limited, the model’s outputs holistically capture the burden of wasting in a way that may guide effective decision-making and may help ensure that limited resources are allocated most effectively. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13031-021-00400-6.
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spelling pubmed-83640172021-08-17 A mathematical model to estimate the incidence of child wasting in Yemen Hussein, Rana A. Suprenant, Mark P. Al-Dheeb, Najwa Guerrero, Saul Rogers, Eleanor Shafique, Fouzia Dyson, Meredith Zaman, Muhammad H. Confl Health Research INTRODUCTION: The ongoing civil war in Yemen has severely restricted imports of food and fuel, disrupted livelihoods and displaced millions, worsening already high pre-war levels of food insecurity. Paired with frequent outbreaks of disease and a collapsed health system, this has brought rates of wasting in children under five to the country’s highest recorded levels, which continue to increase as the crisis worsens and aid becomes increasingly limited. In their planning of services to treat and prevent wasting in children, humanitarian agencies rely on a standard calculation to estimate the expected number of cases for the coming year, where incidence is estimated from prevalence and the average duration of an episode of wasting. The average duration of an episode of moderate and severe wasting is currently estimated at 7.5 months—a globally-used value derived from historical cohort studies. Given that incidence varies considerably by context—where food production and availability, treatment coverage and disease rates all vary—a single estimate cannot be applied to all contexts, and especially not a highly unstable crisis setting such as Yemen. While recent studies have aimed to derive context-specific incidence estimates in several countries, little has been done to estimate the incidence of both moderate and severe wasting in Yemen. METHODS: In order to provide context-specific estimates of the average duration of an episode, and resultingly, incidence correction factors for moderate and severe wasting, we have developed a Markov model. Model inputs were estimated using a combination of treatment admission and outcome records compiled by the Yemen Nutrition Cluster, 2018 and 2019 SMART surveys, and other estimates from the literature. The model derived estimates for the governorate of Lahj, Yemen; it was initialized using August 2018 SMART survey prevalence data and run until October 2019—the date of the subsequent SMART survey. Using a process of repeated model calibration, the incidence correction factors for severe wasting and moderate wasting were found, validating the resulting prevalence against the recorded value from the 2019 SMART survey. RESULTS: The average durations of an episode of moderate and severe wasting were estimated at 4.86 months, for an incidence correction factor k of 2.59, and 3.86 months, for an incidence correction factor k of 3.11, respectively. It was found that the annual caseload of moderate wasting was 36% higher and the annual caseload of severe wasting 58% higher than the originally-assumed values, estimated with k = 1.6. CONCLUSION: The model-derived incidence rates, consistent with findings from other contexts that a global incidence correction factor cannot be sufficient, allow for improved, context-specific estimates of the burden of wasting in Yemen. In crisis settings such as Yemen where funding and resources are extremely limited, the model’s outputs holistically capture the burden of wasting in a way that may guide effective decision-making and may help ensure that limited resources are allocated most effectively. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13031-021-00400-6. BioMed Central 2021-08-14 /pmc/articles/PMC8364017/ /pubmed/34391455 http://dx.doi.org/10.1186/s13031-021-00400-6 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Hussein, Rana A.
Suprenant, Mark P.
Al-Dheeb, Najwa
Guerrero, Saul
Rogers, Eleanor
Shafique, Fouzia
Dyson, Meredith
Zaman, Muhammad H.
A mathematical model to estimate the incidence of child wasting in Yemen
title A mathematical model to estimate the incidence of child wasting in Yemen
title_full A mathematical model to estimate the incidence of child wasting in Yemen
title_fullStr A mathematical model to estimate the incidence of child wasting in Yemen
title_full_unstemmed A mathematical model to estimate the incidence of child wasting in Yemen
title_short A mathematical model to estimate the incidence of child wasting in Yemen
title_sort mathematical model to estimate the incidence of child wasting in yemen
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8364017/
https://www.ncbi.nlm.nih.gov/pubmed/34391455
http://dx.doi.org/10.1186/s13031-021-00400-6
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