Journal article
Spatial and spatio-temporal methods for mapping malaria risk: a systematic review
- Abstract:
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BACKGROUND:
Approaches in malaria risk mapping continue to advance in scope with the advent of geostatistical techniques spanning both the spatial and temporal domains. A substantive review of the merits of the methods and covariates used to map malaria risk has not been undertaken. Therefore, this review aimed to systematically retrieve, summarise methods and examine covariates that have been used for mapping malaria risk in sub-Saharan Africa (SSA).
METHODS:
A systematic search of malaria risk mapping studies was conducted using PubMed, EBSCOhost, Web of Science and Scopus databases. The search was restricted to refereed studies published in English from January 1968 to April 2020. To ensure completeness, a manual search through the reference lists of selected studies was also undertaken. Two independent reviewers completed each of the review phases namely: identification of relevant studies based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, data extraction and methodological quality assessment using a validated scoring criterion.
RESULTS:
One hundred and seven studies met the inclusion criteria. The median quality score across studies was 12/16 (range: 7-16). Approximately half (44%) of the studies employed variable selection techniques prior to mapping with rainfall and temperature selected in over 50% of the studies. Malaria incidence (47%) and prevalence (35%) were the most commonly mapped outcomes, with Bayesian geostatistical models often (31%) the preferred approach to risk mapping. Additionally, 29% of the studies employed various spatial clustering methods to explore the geographical variation of malaria patterns, with Kulldorf scan statistic being the most common. Model validation was specified in 53 (50%) studies, with partitioning data into training and validation sets being the common approach.
CONCLUSIONS:
Our review highlights the methodological diversity prominent in malaria risk mapping across SSA. To ensure reproducibility and quality science, best practices and transparent approaches should be adopted when selecting the statistical framework and covariates for malaria risk mapping. Findings underscore the need to periodically assess methods and covariates used in malaria risk mapping; to accommodate changes in data availability, data quality and innovation in statistical methodology.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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- Files:
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(Preview, Version of record, 1.1MB, Terms of use)
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- Publisher copy:
- 10.1136/bmjgh-2020-002919
Authors
- Publisher:
- BMJ Publishing Group
- Journal:
- BMJ Global Health More from this journal
- Volume:
- 5
- Issue:
- 10
- Article number:
- e002919
- Publication date:
- 2020-10-01
- Acceptance date:
- 2020-08-24
- DOI:
- EISSN:
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2059-7908
- ISSN:
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2059-7908
- Pmid:
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33023880
- Language:
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English
- Keywords:
- Pubs id:
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1136805
- Local pid:
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pubs:1136805
- Deposit date:
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2020-10-30
Terms of use
- Copyright holder:
- Odhiambo et al.
- Copyright date:
- 2020
- Rights statement:
- ©2020 Author(s) (or their employer(s)). Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. http://creativecommons.org/licenses/by-nc/4.0/ This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.
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