Cargando…

The Potential Impact of Improving Appropriate Treatment for Fever on Malaria and Non-Malarial Febrile Illness Management in Under-5s: A Decision-Tree Modelling Approach

BACKGROUND: As international funding for malaria programmes plateaus, limited resources must be rationally managed for malaria and non-malarial febrile illnesses (NMFI). Given widespread unnecessary treatment of NMFI with first-line antimalarial Artemisinin Combination Therapies (ACTs), our aim was...

Descripción completa

Detalles Bibliográficos
Autores principales: Rao, V. Bhargavi, Schellenberg, David, Ghani, Azra C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3726763/
https://www.ncbi.nlm.nih.gov/pubmed/23922770
http://dx.doi.org/10.1371/journal.pone.0069654
_version_ 1782278706212896768
author Rao, V. Bhargavi
Schellenberg, David
Ghani, Azra C.
author_facet Rao, V. Bhargavi
Schellenberg, David
Ghani, Azra C.
author_sort Rao, V. Bhargavi
collection PubMed
description BACKGROUND: As international funding for malaria programmes plateaus, limited resources must be rationally managed for malaria and non-malarial febrile illnesses (NMFI). Given widespread unnecessary treatment of NMFI with first-line antimalarial Artemisinin Combination Therapies (ACTs), our aim was to estimate the effect of health-systems factors on rates of appropriate treatment for fever and on use of ACTs. METHODS: A decision-tree tool was developed to investigate the impact of improving aspects of the fever care-pathway and also evaluate the impact in Tanzania of the revised WHO malaria guidelines advocating diagnostic-led management RESULTS: Model outputs using baseline parameters suggest 49% malaria cases attending a clinic would receive ACTs (95% Uncertainty Interval:40.6–59.2%) but that 44% (95% UI:35–54.8%) NMFI cases would also receive ACTs. Provision of 100% ACT stock predicted a 28.9% increase in malaria cases treated with ACT, but also an increase in overtreatment of NMFI, with 70% NMFI cases (95% UI:56.4–79.2%) projected to receive ACTs, and thus an overall 13% reduction (95% UI:5–21.6%) in correct management of febrile cases. Modelling increased availability or use of diagnostics had little effect on malaria management outputs, but may significantly reduce NMFI overtreatment. The model predicts the early rollout of revised WHO guidelines in Tanzania may have led to a 35% decrease (95% UI:31.2–39.8%) in NMFI overtreatment, but also a 19.5% reduction (95% UI:11–27.2%), in malaria cases receiving ACTs, due to a potential fourfold decrease in cases that were untested or tested false-negative (42.5% vs.8.9%) and so untreated. DISCUSSION: Modelling multi-pronged intervention strategies proved most effective to improve malaria treatment without increasing NMFI overtreatment. As malaria transmission declines, health system interventions must be guided by whether the management priority is an increase in malaria cases receiving ACTs (reducing the treatment gap), reducing ACT waste through unnecessary treatment of NMFI or expanding appropriate treatment of all febrile illness.
format Online
Article
Text
id pubmed-3726763
institution National Center for Biotechnology Information
language English
publishDate 2013
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-37267632013-08-06 The Potential Impact of Improving Appropriate Treatment for Fever on Malaria and Non-Malarial Febrile Illness Management in Under-5s: A Decision-Tree Modelling Approach Rao, V. Bhargavi Schellenberg, David Ghani, Azra C. PLoS One Research Article BACKGROUND: As international funding for malaria programmes plateaus, limited resources must be rationally managed for malaria and non-malarial febrile illnesses (NMFI). Given widespread unnecessary treatment of NMFI with first-line antimalarial Artemisinin Combination Therapies (ACTs), our aim was to estimate the effect of health-systems factors on rates of appropriate treatment for fever and on use of ACTs. METHODS: A decision-tree tool was developed to investigate the impact of improving aspects of the fever care-pathway and also evaluate the impact in Tanzania of the revised WHO malaria guidelines advocating diagnostic-led management RESULTS: Model outputs using baseline parameters suggest 49% malaria cases attending a clinic would receive ACTs (95% Uncertainty Interval:40.6–59.2%) but that 44% (95% UI:35–54.8%) NMFI cases would also receive ACTs. Provision of 100% ACT stock predicted a 28.9% increase in malaria cases treated with ACT, but also an increase in overtreatment of NMFI, with 70% NMFI cases (95% UI:56.4–79.2%) projected to receive ACTs, and thus an overall 13% reduction (95% UI:5–21.6%) in correct management of febrile cases. Modelling increased availability or use of diagnostics had little effect on malaria management outputs, but may significantly reduce NMFI overtreatment. The model predicts the early rollout of revised WHO guidelines in Tanzania may have led to a 35% decrease (95% UI:31.2–39.8%) in NMFI overtreatment, but also a 19.5% reduction (95% UI:11–27.2%), in malaria cases receiving ACTs, due to a potential fourfold decrease in cases that were untested or tested false-negative (42.5% vs.8.9%) and so untreated. DISCUSSION: Modelling multi-pronged intervention strategies proved most effective to improve malaria treatment without increasing NMFI overtreatment. As malaria transmission declines, health system interventions must be guided by whether the management priority is an increase in malaria cases receiving ACTs (reducing the treatment gap), reducing ACT waste through unnecessary treatment of NMFI or expanding appropriate treatment of all febrile illness. Public Library of Science 2013-07-29 /pmc/articles/PMC3726763/ /pubmed/23922770 http://dx.doi.org/10.1371/journal.pone.0069654 Text en © 2013 Rao 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, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Rao, V. Bhargavi
Schellenberg, David
Ghani, Azra C.
The Potential Impact of Improving Appropriate Treatment for Fever on Malaria and Non-Malarial Febrile Illness Management in Under-5s: A Decision-Tree Modelling Approach
title The Potential Impact of Improving Appropriate Treatment for Fever on Malaria and Non-Malarial Febrile Illness Management in Under-5s: A Decision-Tree Modelling Approach
title_full The Potential Impact of Improving Appropriate Treatment for Fever on Malaria and Non-Malarial Febrile Illness Management in Under-5s: A Decision-Tree Modelling Approach
title_fullStr The Potential Impact of Improving Appropriate Treatment for Fever on Malaria and Non-Malarial Febrile Illness Management in Under-5s: A Decision-Tree Modelling Approach
title_full_unstemmed The Potential Impact of Improving Appropriate Treatment for Fever on Malaria and Non-Malarial Febrile Illness Management in Under-5s: A Decision-Tree Modelling Approach
title_short The Potential Impact of Improving Appropriate Treatment for Fever on Malaria and Non-Malarial Febrile Illness Management in Under-5s: A Decision-Tree Modelling Approach
title_sort potential impact of improving appropriate treatment for fever on malaria and non-malarial febrile illness management in under-5s: a decision-tree modelling approach
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3726763/
https://www.ncbi.nlm.nih.gov/pubmed/23922770
http://dx.doi.org/10.1371/journal.pone.0069654
work_keys_str_mv AT raovbhargavi thepotentialimpactofimprovingappropriatetreatmentforfeveronmalariaandnonmalarialfebrileillnessmanagementinunder5sadecisiontreemodellingapproach
AT schellenbergdavid thepotentialimpactofimprovingappropriatetreatmentforfeveronmalariaandnonmalarialfebrileillnessmanagementinunder5sadecisiontreemodellingapproach
AT ghaniazrac thepotentialimpactofimprovingappropriatetreatmentforfeveronmalariaandnonmalarialfebrileillnessmanagementinunder5sadecisiontreemodellingapproach
AT raovbhargavi potentialimpactofimprovingappropriatetreatmentforfeveronmalariaandnonmalarialfebrileillnessmanagementinunder5sadecisiontreemodellingapproach
AT schellenbergdavid potentialimpactofimprovingappropriatetreatmentforfeveronmalariaandnonmalarialfebrileillnessmanagementinunder5sadecisiontreemodellingapproach
AT ghaniazrac potentialimpactofimprovingappropriatetreatmentforfeveronmalariaandnonmalarialfebrileillnessmanagementinunder5sadecisiontreemodellingapproach