Evidence map›Paper›PMID 35878131›Full record

ArticleTropical medicine and infectious disease2022

Economic and Social Costs of Noma: Design and Application of an Estimation Model to Niger and Burkina Faso.

Emmanuel Kabengele Mpinga, Margaret Leila Srour, Marie-Solène Adamou Moussa, Marc Dupuis, Moubassira Kagoné, Maïna Sani Malam Grema, Ngoyi-Bukonda Zacharie, Denise Baratti-Mayer

Open access · goldAbstract read
In one paragraph

Article in Tropical medicine and infectious disease, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
2.8field-weighted citation impact, top 10% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 1 synthesis or guideline pooled it, 14 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 5 institutions in 5 countries.

Emmanuel Kabengele MpingaInstitute of Global Health, Faculty of Medicine, University of Geneva, 1202 Geneva, Switzerland.ORCID 0000-0002-5763-4843
Margaret Leila SrourHealth Frontiers, Vientiane, Laos.
Marie-Solène Adamou MoussaInstitute of Global Health, Faculty of Medicine, University of Geneva, 1202 Geneva, Switzerland.
Marc DupuisInstitute of Higher Education and Research in Healthcare, Lausanne University Hospital and University of Lausanne, 1011 Lausanne, Switzerland.ORCID 0000-0001-7580-559X
Moubassira KagonéCentre de Recherche en Santé de Nouna, National Institute of Public Health, Ouagadougou, Burkina Faso.
Maïna Sani Malam GremaFaculté des Lettres et Sciences Humaines, University Abdou Moumouni of Niamey, Niamey, Niger.
Ngoyi-Bukonda ZacharieDepartment of Public Health Sciences, Wichita State University, Wichita, KS 67260, USA.
Denise Baratti-MayerInstitute of Global Health, Faculty of Medicine, University of Geneva, 1202 Geneva, Switzerland.ORCID 0000-0003-3005-8935
University of Geneva · CHCentre de Recherche en Santé de Nouna · BFUniversité Abdou Moumouni · NEUniversity of Lausanne · CHWichita State University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWhile noma affects hundreds of thousands of children every year, taking their lives, disfiguring them and leaving them permanently disabled, the economic and social costs of the disease have not been previously estimated. An understanding of the nature and levels of these costs is much needed to formulate and implement strategies for the prevention and control of this disease, or to mitigate its burden. The objectives of our study were to develop a model for estimating the economic and social costs of noma and to provide estimates by applying this model to the specific contexts of two countries in the "noma belt", namely Burkina Faso and Niger.

methodsThree main approaches were used. The estimation of prevalence levels of potential noma cases and of cases that should receive and actually do receive medical care was carried out using a literature review. The documentary approach made it possible to estimate the direct costs of noma by analyzing the database of a non-governmental organization operating in this field and present in both countries. Indirect costs were estimated using the human capital method and the cost component analysis technique.

resultsThe direct costs of care and management of noma survivors amount to approximately USD 30 million per year in Burkina Faso, compared to approximately USD 31 million in Niger. They mainly include costs for medical treatment, surgery, hospital stays, physiological care, psychological care, social assistance, schooling, vocational training and care abroad. Indirect costs are estimated at around 20 million in lost production costs in Burkina and around 16 million in Niger. Costs related to premature deaths are estimated at more than USD 3.5 billion in Burkina Faso and USD 3 billion in Niger. Finally, the costs to survivors who are unable to marry are around USD 13.4 million in Burkina and around USD 15 million in Niger. Intangible costs were not calculated.

conclusionsThe neglect of noma and inaction in terms of prevention and control of the disease have enormous economic and social costs for households, communities and states. Future studies of this kind are necessary and useful to raise awareness and eradicate this disease, which impacts the health and well-being of children and results in lifelong suffering and severe economic and social costs to survivors and their families.

Indexed as

burdenBurkina Fasocosteconomicestimating modelNigernomasocial

Identifiers

PMID35878131
PMCPMC9317383
OpenAlexW4283661063

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.