Advancing data analytics for field epidemiologists using R: the R4epis innovation project

Abstract

Data analysis is integral to informing operational elements of humanitarian medical responses. Field epidemiologists play a central role in informing such responses as they aim to rapidly collect, analyse and disseminate results to support Médecins Sans Frontières (MSF) and partners with timely and targeted intervention strategies. However, a lack of standardised analytical methods within MSF challenges this process. The R4epis project group consists of 18 professionals with expertise in: R programming, field epidemiology, data science, health information systems, geographic information systems, and public health. Between October 2018 and April 2019, R scripts were developed to address all aspects of data cleaning, data analysis, and automatic reporting for outbreaks (measles, meningitis, cholera and acute jaundice) and surveys (retrospective mortality, malnutrition and vaccination coverage). Analyses and outputs were piloted and validated by epidemiologists using historical data. The resulting templates were made available to field epidemiologists for field testing, which was conducted between February and April 2019. R4epis will contribute to the improvement of the quality, timeliness, consistency of data analyses and standardisation of outputs from field epidemiologists during emergency response.

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Zhian N. Kamvar
Research Software Engineer

I am a population geneticist, data scientist, plant pathologist, and R package developer. I currently work as the Lesson Infrastructure Technology Developer at The Carpentries.