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<h4>Introduction</h4>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.<h4>Methods and analysis</h4>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 Relevant grey literature sources such as unpublished reports, conference proceedings and dissertations will also be incorporated in the search.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.<h4>Ethics and dissemination</h4>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.<h4>Prospero registration number</h4>CRD42017076427.

Original publication

DOI

10.1136/bmjopen-2018-023071

Type

Journal

BMJ open

Publication Date

05/09/2018

Volume

8

Addresses

Discipline of Public Health Medicine, School of Nursing and Public Health, College of Health Sciences, University of KwaZulu-Natal, Durban, South Africa.

Keywords

Humans, Malaria, Developing Countries, Spatio-Temporal Analysis