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Development of an agent-based model to assess the impact of substandard and falsified anti-malarials: Uganda case study
BACKGROUND: Global efforts to address the burden of malaria have stagnated in recent years with malaria cases beginning to rise. Substandard and falsified anti-malarial treatments contribute to this stagnation. Poor quality anti-malarials directly affect health outcomes by increasing malaria morbidi...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6327614/ https://www.ncbi.nlm.nih.gov/pubmed/30626380 http://dx.doi.org/10.1186/s12936-018-2628-3 |
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author | Ozawa, Sachiko Evans, Daniel R. Higgins, Colleen R. Laing, Sarah K. Awor, Phyllis |
author_facet | Ozawa, Sachiko Evans, Daniel R. Higgins, Colleen R. Laing, Sarah K. Awor, Phyllis |
author_sort | Ozawa, Sachiko |
collection | PubMed |
description | BACKGROUND: Global efforts to address the burden of malaria have stagnated in recent years with malaria cases beginning to rise. Substandard and falsified anti-malarial treatments contribute to this stagnation. Poor quality anti-malarials directly affect health outcomes by increasing malaria morbidity and mortality, as well as threaten the effectiveness of treatment by contributing to artemisinin resistance. Research to assess the scope and impact of poor quality anti-malarials is essential to raise awareness and allocate resources to improve the quality of treatment. A probabilistic agent-based model was developed to provide country-specific estimates of the health and economic impact of poor quality anti-malarials on paediatric malaria. This paper presents the methodology and case study of the Substandard and Falsified Antimalarial Research Impact (SAFARI) model developed and applied to Uganda. RESULTS: The total annual economic impact of malaria in Ugandan children under age five was estimated at US$614 million. Among children who sought medical care, the total economic impact was estimated at $403 million, including $57.7 million in direct costs. Substandard and falsified anti-malarials were a significant contributor to this annual burden, accounting for $31 million (8% of care-seeking children) in total economic impact involving $5.2 million in direct costs. Further, 9% of malaria deaths relating to cases seeking treatment were attributable to poor quality anti-malarials. In the event of widespread artemisinin resistance in Uganda, we simulated a 12% yearly increase in costs associated with paediatric malaria cases that sought care, inflicting $48.5 million in additional economic impact annually. CONCLUSIONS: Improving the quality of treatment is essential to combat the burden of malaria and prevent the development of drug resistance. The SAFARI model provides country-specific estimates of the health and economic impact of substandard and falsified anti-malarials to inform governments, policy makers, donors and the malaria community about the threat posed by poor quality medicines. The model findings are useful to illustrate the significance of the issue and inform policy and interventions to improve medicinal quality. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12936-018-2628-3) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6327614 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-63276142019-01-15 Development of an agent-based model to assess the impact of substandard and falsified anti-malarials: Uganda case study Ozawa, Sachiko Evans, Daniel R. Higgins, Colleen R. Laing, Sarah K. Awor, Phyllis Malar J Methodology BACKGROUND: Global efforts to address the burden of malaria have stagnated in recent years with malaria cases beginning to rise. Substandard and falsified anti-malarial treatments contribute to this stagnation. Poor quality anti-malarials directly affect health outcomes by increasing malaria morbidity and mortality, as well as threaten the effectiveness of treatment by contributing to artemisinin resistance. Research to assess the scope and impact of poor quality anti-malarials is essential to raise awareness and allocate resources to improve the quality of treatment. A probabilistic agent-based model was developed to provide country-specific estimates of the health and economic impact of poor quality anti-malarials on paediatric malaria. This paper presents the methodology and case study of the Substandard and Falsified Antimalarial Research Impact (SAFARI) model developed and applied to Uganda. RESULTS: The total annual economic impact of malaria in Ugandan children under age five was estimated at US$614 million. Among children who sought medical care, the total economic impact was estimated at $403 million, including $57.7 million in direct costs. Substandard and falsified anti-malarials were a significant contributor to this annual burden, accounting for $31 million (8% of care-seeking children) in total economic impact involving $5.2 million in direct costs. Further, 9% of malaria deaths relating to cases seeking treatment were attributable to poor quality anti-malarials. In the event of widespread artemisinin resistance in Uganda, we simulated a 12% yearly increase in costs associated with paediatric malaria cases that sought care, inflicting $48.5 million in additional economic impact annually. CONCLUSIONS: Improving the quality of treatment is essential to combat the burden of malaria and prevent the development of drug resistance. The SAFARI model provides country-specific estimates of the health and economic impact of substandard and falsified anti-malarials to inform governments, policy makers, donors and the malaria community about the threat posed by poor quality medicines. The model findings are useful to illustrate the significance of the issue and inform policy and interventions to improve medicinal quality. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12936-018-2628-3) contains supplementary material, which is available to authorized users. BioMed Central 2019-01-09 /pmc/articles/PMC6327614/ /pubmed/30626380 http://dx.doi.org/10.1186/s12936-018-2628-3 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 | Methodology Ozawa, Sachiko Evans, Daniel R. Higgins, Colleen R. Laing, Sarah K. Awor, Phyllis Development of an agent-based model to assess the impact of substandard and falsified anti-malarials: Uganda case study |
title | Development of an agent-based model to assess the impact of substandard and falsified anti-malarials: Uganda case study |
title_full | Development of an agent-based model to assess the impact of substandard and falsified anti-malarials: Uganda case study |
title_fullStr | Development of an agent-based model to assess the impact of substandard and falsified anti-malarials: Uganda case study |
title_full_unstemmed | Development of an agent-based model to assess the impact of substandard and falsified anti-malarials: Uganda case study |
title_short | Development of an agent-based model to assess the impact of substandard and falsified anti-malarials: Uganda case study |
title_sort | development of an agent-based model to assess the impact of substandard and falsified anti-malarials: uganda case study |
topic | Methodology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6327614/ https://www.ncbi.nlm.nih.gov/pubmed/30626380 http://dx.doi.org/10.1186/s12936-018-2628-3 |
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