Odhiambo Julius Nyerere, Sartorius Benn
Discipline of Public Health Medicine, School of Nursing and Public Health, College of Health Sciences, University of KwaZulu-Natal, Durban, South Africa.
BMJ Open. 2018 Sep 5;8(9):e023071. doi: 10.1136/bmjopen-2018-023071.
Spatio - temporal modelling of malaria has proven to be a valuable tool for forecasting as well as control and elimination activities. This has been triggered by an increasing availability of spatially indexed data, enabling not only the characterisation of malaria at macrospatial and microspatial levels but also the development of geospatial techniques and tools that enable health policy planners to use these available data more effectively. However, there has been little synthesis regarding the variety of spatio - temporal approaches employed, covariates employed and 'best practice' type recommendations to guide future modelling decisions. This review will seek to summarise available evidence on the current state of spatio - temporal modelling approaches that have been employed in malaria modelling in low and middle-income countries within malaria transmission limits, so as to guide future modelling decisions.
A comprehensive search for articles published from January 1968 to April 2018 will be conducted using of the following electronic databases: PubMed, Web of Science, JSTOR, Cochrane CENTRAL via Wiley, Academic Search Complete via EBSCOhost, MasterFILE Premier via EBSCOhost, CINAHL via EBSCOhost, MEDLINE via EBSCOhost and Google Scholar. Relevant grey literature sources such as unpublished reports, conference proceedings and dissertations will also be incorporated in the search. Two reviewers will independently conduct the title screening, abstract screening and, thereafter, a full-text review of all potentially eligible articles. Preferred Reporting Items for Systematic Reviews and Meta-Analysis Protocols guidelines will be used as the standard reporting format. A qualitative thematic analysis will be used to group and evaluate selected studies around their aim, spatio - temporal methodology employed, covariates used and model validation techniques.
Ethical approval is not applicable to this study. The results will be disseminated through a peer-reviewed journal and presented in conferences related to malaria and spatial epidemiology.
CRD42017076427.
疟疾的时空建模已被证明是预测以及控制和消除疟疾活动的宝贵工具。空间索引数据的可用性不断提高引发了这一情况，这不仅能够在宏观空间和微观空间层面描述疟疾特征，还能开发地理空间技术和工具，使卫生政策规划者能够更有效地利用这些可用数据。然而，对于所采用的各种时空方法、所使用的协变量以及指导未来建模决策的“最佳实践”类型建议，几乎没有进行综合总结。本综述旨在总结关于在疟疾传播范围内的低收入和中等收入国家疟疾建模中所采用的时空建模方法现状的现有证据，以指导未来的建模决策。
将使用以下电子数据库全面检索1968年1月至2018年4月发表的文章：PubMed、科学网、JSTOR、通过Wiley获取的Cochrane CENTRAL、通过EBSCOhost获取的学术搜索完整版、通过EBSCOhost获取的MasterFILE Premier、通过EBSCOhost获取的护理学与健康领域数据库、通过EBSCOhost获取的医学索引以及谷歌学术。未发表报告、会议论文集和学位论文等相关灰色文献来源也将纳入检索范围。两名评审员将独立进行标题筛选、摘要筛选，然后对所有潜在符合条件的文章进行全文评审。系统评价和Meta分析方案的首选报告项目指南将用作标准报告格式。将采用定性主题分析方法，围绕所选研究的目的、所采用的时空方法、所使用的协变量和模型验证技术进行分组和评估。
本研究无需伦理批准。研究结果将通过同行评审期刊发表，并在与疟疾和空间流行病学相关的会议上展示。
PROSPERO注册号：CRD42017076427。
