Health systems and global progress towards malaria elimination, 2000-2016.


Journal

Malaria journal
ISSN: 1475-2875
Titre abrégé: Malar J
Pays: England
ID NLM: 101139802

Informations de publication

Date de publication:
08 Apr 2020
Historique:
received: 04 02 2020
accepted: 23 03 2020
entrez: 10 4 2020
pubmed: 10 4 2020
medline: 11 11 2020
Statut: epublish

Résumé

As more countries progress towards malaria elimination, a better understanding of the most critical health system features for enabling and supporting malaria control and elimination is needed. All available health systems data relevant for malaria control were collated from 23 online data repositories. Principal component analysis was used to create domain specific health system performance measures. Multiple regression model selection approaches were used to identify key health systems predictors of progress in malaria control in the 2000-2016 period among 105 countries. Additional analysis was performed within malaria burden groups. There was large heterogeneity in progress in malaria control in the 2000-2016 period. In univariate analysis, several health systems factors displayed a strong positive correlation with reductions in malaria burden between 2000 and 2016. In multivariable models, delivery of routine services and hospital capacity were strongly predictive of reductions in malaria cases, especially in high burden countries. In low-burden countries approaching elimination, primary health center density appeared negatively associated with progress while hospital capacity was positively correlated with eliminating malaria. The findings presented in this manuscript suggest that strengthening health systems can be an effective strategy for reducing malaria cases, especially in countries with high malaria burden. Potential returns appear particularly high in the area of service delivery.

Sections du résumé

BACKGROUND BACKGROUND
As more countries progress towards malaria elimination, a better understanding of the most critical health system features for enabling and supporting malaria control and elimination is needed.
METHODS METHODS
All available health systems data relevant for malaria control were collated from 23 online data repositories. Principal component analysis was used to create domain specific health system performance measures. Multiple regression model selection approaches were used to identify key health systems predictors of progress in malaria control in the 2000-2016 period among 105 countries. Additional analysis was performed within malaria burden groups.
RESULTS RESULTS
There was large heterogeneity in progress in malaria control in the 2000-2016 period. In univariate analysis, several health systems factors displayed a strong positive correlation with reductions in malaria burden between 2000 and 2016. In multivariable models, delivery of routine services and hospital capacity were strongly predictive of reductions in malaria cases, especially in high burden countries. In low-burden countries approaching elimination, primary health center density appeared negatively associated with progress while hospital capacity was positively correlated with eliminating malaria.
CONCLUSIONS CONCLUSIONS
The findings presented in this manuscript suggest that strengthening health systems can be an effective strategy for reducing malaria cases, especially in countries with high malaria burden. Potential returns appear particularly high in the area of service delivery.

Identifiants

pubmed: 32268917
doi: 10.1186/s12936-020-03208-6
pii: 10.1186/s12936-020-03208-6
pmc: PMC7140365
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

141

Subventions

Organisme : World Health Organization
ID : 001
Pays : International

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Auteurs

Maitreyi Sahu (M)

Swiss Tropical and Public Health Institute and University of Basel, Basel, Switzerland. msahu@uw.edu.
University of Washington, Seattle, USA. msahu@uw.edu.

Fabrizio Tediosi (F)

Swiss Tropical and Public Health Institute and University of Basel, Basel, Switzerland.

Abdisalan M Noor (AM)

Global Malaria Programme, World Health Organization, Geneva, Switzerland.

John J Aponte (JJ)

Global Malaria Programme, World Health Organization, Geneva, Switzerland.

Günther Fink (G)

Swiss Tropical and Public Health Institute and University of Basel, Basel, Switzerland.

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Classifications MeSH