Department of Preventive Medicine and Institute for Global Health, Northwestern University, Chicago, IL, USA.
Institute for Disease Modeling, Seattle, WA, USA.
Malar J. 2021 Mar 1;20(1):122. doi: 10.1186/s12936-021-03646-w.
In malaria-endemic countries, prioritizing intervention deployment to areas that need the most attention is crucial to ensure continued progress. Global and national policy makers increasingly rely on epidemiological data and mathematical modelling to help optimize health decisions at the sub-national level. The Demographic and Health Surveys (DHS) Program is a critical data source for understanding subnational malaria prevalence and intervention coverage, which are used for parameterizing country-specific models of malaria transmission. However, data to estimate indicators at finer resolutions are limited, and surveys questions have a narrow scope. Examples from the Nigeria DHS are used to highlight gaps in the current survey design. Proposals are then made for additional questions and expansions to the DHS and Malaria Indicator Survey sampling strategy that would advance the data analyses and modelled estimates that inform national policy recommendations. Collaboration between the DHS Program, national malaria control programmes, the malaria modelling community, and funders is needed to address the highlighted data challenges.
在疟疾流行的国家，优先考虑将干预措施部署到最需要关注的地区，对于确保持续取得进展至关重要。全球和国家政策制定者越来越依赖流行病学数据和数学模型，以帮助在国家以下各级优化卫生决策。人口与健康调查（DHS）项目是了解国家以下疟疾流行率和干预措施覆盖范围的重要数据来源，这些数据用于对疟疾传播的特定国家模型进行参数化。然而，用于更精细分辨率指标估计的数据有限，且调查问题的范围狭窄。以尼日利亚 DHS 为例，突出了当前调查设计中的差距。然后提出了 DHS 和疟疾指标调查抽样策略的补充问题和扩展建议，这将推进数据分析和建模估计，为国家政策建议提供信息。需要 DHS 项目、国家疟疾控制规划、疟疾建模界和供资方之间的合作，以应对突出的数据挑战。
