How to Estimate Optimal Malaria Readiness Indicators at Health-District Level: Findings from the Burkina Faso Service Availability and Readiness Assessment (SARA) Data.
Burkina Faso
SARA survey
binomial hierarchical Bayesian
geo-epidemiology
health district
malaria
service readiness
spatial analysis
Journal
International journal of environmental research and public health
ISSN: 1660-4601
Titre abrégé: Int J Environ Res Public Health
Pays: Switzerland
ID NLM: 101238455
Informations de publication
Date de publication:
01 06 2020
01 06 2020
Historique:
received:
22
04
2020
revised:
26
05
2020
accepted:
28
05
2020
entrez:
5
6
2020
pubmed:
5
6
2020
medline:
11
11
2020
Statut:
epublish
Résumé
One of the major contributors of malaria-related deaths in Sub-Saharan African countries is the limited accessibility to quality care. In these countries, malaria control activities are implemented at the health-district level (operational entity of the national health system), while malaria readiness indicators are regionally representative. This study provides an approach for estimating health district-level malaria readiness indicators from survey data designed to provide regionally representative estimates. A binomial-hierarchical Bayesian spatial prediction method was applied to Burkina Faso Service Availability and Readiness Assessment (SARA) survey data to provide estimates of essential equipment availability and readiness for malaria care. Predicted values of each indicator were adjusted by the type of health facility, location, and population density. Then, a health district composite readiness profile was built via hierarchical ascendant classification. All surveyed health-facilities were mandated by the Ministry of Health to manage malaria cases. The spatial distribution of essential equipment and malaria readiness was heterogeneous. Around 62.9% of health districts had a high level of readiness to provide malaria care and prevention during pregnancy. Low-performance scores for managing malaria cases were found in big cities. Health districts with low coverage for both first-line antimalarial drugs and rapid diagnostic tests were Baskuy, Bogodogo, Boulmiougou, Nongr-Massoum, Sig-Nonghin, Dafra, and Do. We provide health district estimates and reveal gaps in basic equipment and malaria management resources in some districts that need to be filled. By providing local-scale estimates, this approach could be replicated for other types of indicators to inform decision makers and health program managers and to identify priority areas.
Identifiants
pubmed: 32492901
pii: ijerph17113923
doi: 10.3390/ijerph17113923
pmc: PMC7312483
pii:
doi:
Substances chimiques
Antimalarials
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Déclaration de conflit d'intérêts
The authors declare no conflict of interest.
Références
Lancet Glob Health. 2019 May;7(5):e624-e632
pubmed: 30898495
PLoS Med. 2013;10(6):e1001467
pubmed: 23853551
Malar J. 2016 Apr 14;15:213
pubmed: 27075879
Lancet. 2004 Oct 30-Nov 5;364(9445):1583-94
pubmed: 15519628
BMJ Open. 2019 Jul 29;9(7):e028370
pubmed: 31362965
BMC Health Serv Res. 2017 Mar 1;17(1):172
pubmed: 28249578
Sci Rep. 2018 Dec 18;8(1):17928
pubmed: 30560884
Afr Health Sci. 2014 Dec;14(4):1036-45
pubmed: 25873942
Nature. 2015 Oct 8;526(7572):207-211
pubmed: 26375008
Bull World Health Organ. 2013 Dec 1;91(12):923-31
pubmed: 24347731
Lancet Glob Health. 2016 Nov;4(11):e845-e855
pubmed: 27670090
Environmetrics. 2011 Dec;22(8):1008-1022
pubmed: 22184483
N Engl J Med. 2016 Dec 22;375(25):2435-2445
pubmed: 27723434
BMC Health Serv Res. 2015 Dec 03;15:536
pubmed: 26634449
Malar J. 2016 Feb 06;15:67
pubmed: 26852118
Bull World Health Organ. 2011 Jan 1;89(1):12-21
pubmed: 21346886
Cad Saude Publica. 2007 Dec;23(12):2820-34
pubmed: 18157324
Clin Infect Dis. 2017 May 1;64(9):1236-1243
pubmed: 28431115
Ann Appl Stat. 2015 Dec;9(4):1889-1905
pubmed: 27468328
PLoS Med. 2016 Apr 12;13(4):e1001993
pubmed: 27071072
SSM Popul Health. 2017 Jan 10;3:179-184
pubmed: 29349214
J Data Sci. 2018 Jan;16(1):147-182
pubmed: 29520299
Spat Spatiotemporal Epidemiol. 2013 Mar;4:33-49
pubmed: 23481252
Spat Spatiotemporal Epidemiol. 2020 Jun;33:100333
pubmed: 32370941
Environ Health Perspect. 2004 Jun;112(9):1016-25
pubmed: 15198922
Malar J. 2019 Jul 9;18(1):229
pubmed: 31288835