학술논문
malariaAtlas: an R interface to global malariometric data hosted by the Malaria Atlas Project
Document Type
Report
Author
Pfeffer, Daniel A.; Lucas, Timothy C. D.; May, Daniel; Harris, Joseph; Rozier, Jennifer; Twohig, Katherine A.; Dalrymple, Ursula; Guerra, Carlos A.; Moyes, Catherine L.; Thorn, Mike; Nguyen, Michele; Bhatt, Samir; Cameron, Ewan; Weiss, Daniel J.; Howes, Rosalind E.; Battle, Katherine E.; Gibson, Harry S.; Gething, Peter W.
Source
Malaria Journal. October 5, 2018, Vol. 17 Issue 1
Subject
Language
English
ISSN
1475-2875
Abstract
Author(s): Daniel A. Pfeffer[sup.1] , Timothy C. D. Lucas[sup.1] , Daniel May[sup.1] , Joseph Harris[sup.1] , Jennifer Rozier[sup.1] , Katherine A. Twohig[sup.1] , Ursula Dalrymple[sup.1] , Carlos A. Guerra[sup.2] , [...]
Background The Malaria Atlas Project (MAP) has worked to assemble and maintain a global open-access database of spatial malariometric data for over a decade. This data spans various formats and topics, including: geo-located surveys of malaria parasite rate; global administrative boundary shapefiles; and global and regional rasters representing the distribution of malaria and associated illnesses, blood disorders, and intervention coverage. MAP has recently released malariaAtlas, an R package providing a direct interface to MAP's routinely-updated malariometric databases and research outputs. Methods and results The current paper reviews the functionality available in malariaAtlas and highlights its utility for spatial epidemiological analysis of malaria. malariaAtlas enables users to freely download, visualise and analyse global malariometric data within R. Currently available data types include: malaria parasite rate and vector occurrence point data; subnational administrative boundary shapefiles; and a large suite of rasters covering a diverse range of metrics related to malaria research. malariaAtlas is here used in two mock analyses to illustrate how this data may be incorporated into a standard R workflow for spatial analysis. Conclusions malariaAtlas is the first open-access R-interface to malariometric data, providing a new and reproducible means of accessing such data within a freely available and commonly used statistical software environment. In this way, the malariaAtlas package aims to contribute to the environment of data-sharing within the malaria research community. Keywords: Malaria, Open-access, Malariometric data, Parasite rate, R package
Background The Malaria Atlas Project (MAP) has worked to assemble and maintain a global open-access database of spatial malariometric data for over a decade. This data spans various formats and topics, including: geo-located surveys of malaria parasite rate; global administrative boundary shapefiles; and global and regional rasters representing the distribution of malaria and associated illnesses, blood disorders, and intervention coverage. MAP has recently released malariaAtlas, an R package providing a direct interface to MAP's routinely-updated malariometric databases and research outputs. Methods and results The current paper reviews the functionality available in malariaAtlas and highlights its utility for spatial epidemiological analysis of malaria. malariaAtlas enables users to freely download, visualise and analyse global malariometric data within R. Currently available data types include: malaria parasite rate and vector occurrence point data; subnational administrative boundary shapefiles; and a large suite of rasters covering a diverse range of metrics related to malaria research. malariaAtlas is here used in two mock analyses to illustrate how this data may be incorporated into a standard R workflow for spatial analysis. Conclusions malariaAtlas is the first open-access R-interface to malariometric data, providing a new and reproducible means of accessing such data within a freely available and commonly used statistical software environment. In this way, the malariaAtlas package aims to contribute to the environment of data-sharing within the malaria research community. Keywords: Malaria, Open-access, Malariometric data, Parasite rate, R package