Centre de Recherche en Epidémiologie, Biostatistique et recherche clinique, Ecole de Santé Publique, Université Libre de Bruxelles (ULB), Route de Lennik, 808 B-1070 Brussels, Belgium.
Clinical Research Unit of Nanoro, Institute for Research in Health Sciences, National Center for Scientific and Technological Research, 42, Avenue Kumda-Yoore, BP 218 Ouagadougou CMS 11, Ouagadougou, Burkina Faso.
Int J Environ Res Public Health. 2020 Jun 1;17(11):3923. doi: 10.3390/ijerph17113923.
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.
撒哈拉以南非洲国家疟疾相关死亡的主要原因之一是获得优质医疗服务的机会有限。在这些国家，疟疾控制活动在地区一级（国家卫生系统的业务实体）开展，而疟疾准备情况指标具有区域代表性。本研究提供了一种从旨在提供区域代表性估计的调查数据中估算卫生区疟疾准备情况指标的方法。采用二项式分层贝叶斯空间预测方法对布基纳法索服务提供和准备情况评估 (SARA) 调查数据进行分析，以提供基本设备供应和疟疾护理准备情况的估计。通过分层上升分类法构建了卫生区综合准备情况概况。所有接受调查的卫生机构都被卫生部授权管理疟疾病例。基本设备和疟疾准备情况的空间分布不均。约 62.9%的卫生区具备高水平的提供疟疾护理和预防妊娠期间疟疾的能力。在大城市发现管理疟疾病例的绩效得分较低。在基本抗疟药物和快速诊断检测覆盖率较低的卫生区包括 Baskuy、Bogodogo、Boulmiougou、Nongr-Massoum、Sig-Nonghin、Dafra 和 Do。我们提供了卫生区的估计数，并揭示了一些地区在基本设备和疟疾管理资源方面存在差距，需要加以弥补。通过提供地方尺度的估计，这种方法可以复制到其他类型的指标，以便为决策者和卫生规划管理人员提供信息，并确定优先领域。
