Scholarship opportunities for future cohorts will be posted later in 2024.About Applied Epi:
Applied Epi is a grassroots, nonprofit organisation that is leading public health's transition to R. Our free
Epidemiologist R Handbook has been used over 2 million times by 600,000 people, and we have delivered R courses to 800 epis from dozens of health agencies including the US CDC, European CDC, Doctors without Borders, WHO, and the Nigeria Field Epidemiology and Laboratory Training Program (FELTP).
Course overview:
This course teaches the use of R to produce maps and perform simple analyses and data management tasks with spatial data to public health practitioners and applied epidemiologists.
Sessions include live coding demonstrations, lectures, interactive facilitated coding exercises, and 1-on-1 support meetings with instructors. There is approximately 1 instructor for each 6 participants You can read more in
our brochure or our
training page.
Structure: Two sessions of 3.5 hours each. Each session begins with a brief lecture and live coding demonstration. Most of the session is spent completing a case study/ guided exercise with instructors on-hand to answer questions in1-on-1 coaching and code troubleshooting side-room sessions. Each session concludes with a review. Office hours are available between sessions if needed. Sessions are recorded. Topics: The course teaches participants to use the {ggplot2}, {sf}, and {plotly} R packages (among others) to make descriptive maps and perform simple spatial analyses. After a brief review of GIS principles, coordinate systems/projections, and shapefiles, we move to exercises using data from Ebola and COVID-19 outbreaks. We practice importing and cleaning spatial data, plotting points and polygons (administrative boundaries), conducting spatial joins and unions, aggregating case counts and plotting choropleth maps with case incidence, adjusting scales and colors, adding population denominators, labeling plotted features, adjusting projections, adding north arrows, scale bars, and legends, adding basemaps and inset maps, nearest neighbor analysis, buffer analysis, making maps iteratively, creating interactive maps, and embedding maps into PDF and HTML reports. Certificates of completion are awarded based on participation, submission of final R script, and completion of a feedback survey.
Language: This course is delivered in English.
Schedule: The classroom instruction will consist of 2 virtual, synchronous sessions of 3.5 hours each. Before the course, you are expected to complete software installations (R, RStudio, and RTools, R packages) and download of course materials.
Meeting platform: The course will occur via Google Meets. Please join via Google Chrome web browser.
Price per seat: 18 seats are available for immediate reservation at USD $ 450.00. Payment is preferred by bank transfer (accepted in USD, Euro, or GBP). Credit/debit cards are also accepted through our PayPal platform, but additional fees may apply. Within a few days of receiving your reservation, you will receive an email with payment or waitlist instructions, as applicable. Payment must be made within 10 business days of receiving the invoice or we may cancel your reservation.
