Integrating rapid risk mapping and mobile phone call record data for strategic malaria elimination planning
Malaria Journal, ISSN: 1475-2875, Vol: 13, Issue: 1, Page: 52
2014
- 139Citations
- 233Captures
- 1Mentions
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Citations139
- Citation Indexes126
- 126
- CrossRef63
- Policy Citations13
- Policy Citation13
- Captures233
- Readers233
- 233
- Mentions1
- News Mentions1
- News1
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Article Description
Abstract. Background: As successful malaria control programmes re-orientate towards elimination, the identification of transmission foci, targeting of attack measures to high-risk areas and management of importation risk become high priorities. When resources are limited and transmission is varying seasonally, approaches that can rapidly prioritize areas for surveillance and control can be valuable, and the most appropriate attack measure for a particular location is likely to differ depending on whether it exports or imports malaria infections. Methods/Results. Here, using the example of Namibia, a method for targeting of interventions using surveillance data, satellite imagery, and mobile phone call records to support elimination planning is described. One year of aggregated movement patterns for over a million people across Namibia are analyzed, and linked with case-based risk maps built on satellite imagery. By combining case-data and movement, the way human population movements connect transmission risk areas is demonstrated. Communities that were strongly connected by relatively higher levels of movement were then identified, and net export and import of travellers and infection risks by region were quantified. These maps can aid the design of targeted interventions to maximally reduce the number of cases exported to other regions while employing appropriate interventions to manage risk in places that import them. Conclusions: The approaches presented can be rapidly updated and used to identify where active surveillance for both local and imported cases should be increased, which regions would benefit from coordinating efforts, and how spatially progressive elimination plans can be designed. With improvements in surveillance systems linked to improved diagnosis of malaria, detailed satellite imagery being readily available and mobile phone usage data continually being collected by network providers, the potential exists to make operational use of such valuable, complimentary and contemporary datasets on an ongoing basis in infectious disease control and elimination. © 2014 Tatem et al.; licensee BioMed Central Ltd.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=84893700265&origin=inward; http://dx.doi.org/10.1186/1475-2875-13-52; http://www.ncbi.nlm.nih.gov/pubmed/24512144; https://malariajournal.biomedcentral.com/articles/10.1186/1475-2875-13-52; https://dx.doi.org/10.1186/1475-2875-13-52; http://malariajournal.biomedcentral.com/articles/10.1186/1475-2875-13-52; https://malariajournal.biomedcentral.com/counter/pdf/10.1186/1475-2875-13-52; http://europepmc.org/abstract/med/24512144; http://europepmc.org/articles/PMC3927223; http://www.malariajournal.com/content/13/1/52
Springer Nature
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