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Challenges of Estimating the Annual Caseload of Severe Acute Malnutrition: The Case of Niger
INTRODUCTION: Reliable prospective estimates of annual severe acute malnutrition (SAM) caseloads for treatment are needed for policy decisions and planning of quality services in the context of competing public health priorities and limited resources. This paper compares the reliability of SAM casel...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5015826/ https://www.ncbi.nlm.nih.gov/pubmed/27606677 http://dx.doi.org/10.1371/journal.pone.0162534 |
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author | Deconinck, Hedwig Pesonen, Anaïs Hallarou, Mahaman Gérard, Jean-Christophe Briend, André Donnen, Philippe Macq, Jean |
author_facet | Deconinck, Hedwig Pesonen, Anaïs Hallarou, Mahaman Gérard, Jean-Christophe Briend, André Donnen, Philippe Macq, Jean |
author_sort | Deconinck, Hedwig |
collection | PubMed |
description | INTRODUCTION: Reliable prospective estimates of annual severe acute malnutrition (SAM) caseloads for treatment are needed for policy decisions and planning of quality services in the context of competing public health priorities and limited resources. This paper compares the reliability of SAM caseloads of children 6–59 months of age in Niger estimated from prevalence at the start of the year and counted from incidence at the end of the year. METHODS: Secondary data from two health districts for 2012 and the country overall for 2013 were used to calculate annual caseload of SAM. Prevalence and coverage were extracted from survey reports, and incidence from weekly surveillance systems. RESULTS: The prospective caseload estimate derived from prevalence and duration of illness underestimated the true burden. Similar incidence was derived from two weekly surveillance systems, but differed from that obtained from the monthly system. Incidence conversion factors were two to five times higher than recommended. DISCUSSION: Obtaining reliable prospective caseloads was challenging because prevalence is unsuitable for estimating incidence of SAM. Different SAM indicators identified different SAM populations, and duration of illness, expected contact coverage and population figures were inaccurate. The quality of primary data measurement, recording and reporting affected incidence numbers from surveillance. Coverage estimated in population surveys was rarely available, and coverage obtained by comparing admissions with prospective caseload estimates was unrealistic or impractical. CONCLUSIONS: Caseload estimates derived from prevalence are unreliable and should be used with caution. Policy and service decisions that depend on these numbers may weaken performance of service delivery. Niger may improve SAM surveillance by simplifying and improving primary data collection and methods using innovative information technologies for single data entry at the first contact with the health system. Lessons may be relevant for countries with a high burden of SAM, including for targeted emergency responses. |
format | Online Article Text |
id | pubmed-5015826 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-50158262016-09-27 Challenges of Estimating the Annual Caseload of Severe Acute Malnutrition: The Case of Niger Deconinck, Hedwig Pesonen, Anaïs Hallarou, Mahaman Gérard, Jean-Christophe Briend, André Donnen, Philippe Macq, Jean PLoS One Research Article INTRODUCTION: Reliable prospective estimates of annual severe acute malnutrition (SAM) caseloads for treatment are needed for policy decisions and planning of quality services in the context of competing public health priorities and limited resources. This paper compares the reliability of SAM caseloads of children 6–59 months of age in Niger estimated from prevalence at the start of the year and counted from incidence at the end of the year. METHODS: Secondary data from two health districts for 2012 and the country overall for 2013 were used to calculate annual caseload of SAM. Prevalence and coverage were extracted from survey reports, and incidence from weekly surveillance systems. RESULTS: The prospective caseload estimate derived from prevalence and duration of illness underestimated the true burden. Similar incidence was derived from two weekly surveillance systems, but differed from that obtained from the monthly system. Incidence conversion factors were two to five times higher than recommended. DISCUSSION: Obtaining reliable prospective caseloads was challenging because prevalence is unsuitable for estimating incidence of SAM. Different SAM indicators identified different SAM populations, and duration of illness, expected contact coverage and population figures were inaccurate. The quality of primary data measurement, recording and reporting affected incidence numbers from surveillance. Coverage estimated in population surveys was rarely available, and coverage obtained by comparing admissions with prospective caseload estimates was unrealistic or impractical. CONCLUSIONS: Caseload estimates derived from prevalence are unreliable and should be used with caution. Policy and service decisions that depend on these numbers may weaken performance of service delivery. Niger may improve SAM surveillance by simplifying and improving primary data collection and methods using innovative information technologies for single data entry at the first contact with the health system. Lessons may be relevant for countries with a high burden of SAM, including for targeted emergency responses. Public Library of Science 2016-09-08 /pmc/articles/PMC5015826/ /pubmed/27606677 http://dx.doi.org/10.1371/journal.pone.0162534 Text en © 2016 Deconinck et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://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 Deconinck, Hedwig Pesonen, Anaïs Hallarou, Mahaman Gérard, Jean-Christophe Briend, André Donnen, Philippe Macq, Jean Challenges of Estimating the Annual Caseload of Severe Acute Malnutrition: The Case of Niger |
title | Challenges of Estimating the Annual Caseload of Severe Acute Malnutrition: The Case of Niger |
title_full | Challenges of Estimating the Annual Caseload of Severe Acute Malnutrition: The Case of Niger |
title_fullStr | Challenges of Estimating the Annual Caseload of Severe Acute Malnutrition: The Case of Niger |
title_full_unstemmed | Challenges of Estimating the Annual Caseload of Severe Acute Malnutrition: The Case of Niger |
title_short | Challenges of Estimating the Annual Caseload of Severe Acute Malnutrition: The Case of Niger |
title_sort | challenges of estimating the annual caseload of severe acute malnutrition: the case of niger |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5015826/ https://www.ncbi.nlm.nih.gov/pubmed/27606677 http://dx.doi.org/10.1371/journal.pone.0162534 |
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