The Connecticut COVID-19 Test Spotter App (Part 1)

Episode 30 of the Shiny Developer Series reveals just how the power of open source software can be used to provide meaningful improvement to our daily lives. In the first of a two-part series, chief data scientist Mike Thomas reveals the motivation behind his brilliant COVID-19 test locator Shiny application, empowering a local community in Connecticut to efficiently report and track availability of test kits in a huge time of need. After a tour of the application interface, Mike shares his favorite techniques to bring an efficient user experience and the backend integrations with APIs to bring production-grade features to life.

Resources mentioned in the episode

• COVID-19 At-Home Test Spotter (App) - ketchbrookanalytics.shinyapps.io/covid_test_spotter
• COVID-19 At-Home Test Spotter (Code) - github.com/ketchbrookanalytics/covid_test_spotter
• App blog post - www.ketchbrookanalytics.com/post/ketchbrook-analytics-launches-website-to-help-connecticut-residents-find-covid-19-test-kits
• Olivia Adams' interview with CNN - www.cnn.com/videos/health/2021/02/08/software-developer-builds-simple-massachusetts-covid-19-vaccine-website-olivia-adams-intv-newday-vpx.cnn
• R Packages by Hadley Wickham and Jenny Bryan - r-pkgs.org
• {googleWay} Shiny vignette - symbolixau.github.io/googleway/articles/googleway-vignette.html#shiny

Episode Timestamps

00:00:00 Episode Introduction

00:01:31 Mike's introductiona and journey with R & Shiny

00:07:20 Data science consulting and Ketchbrook Analytics

00:11:40 Olivia Adams' inspiring story

00:17:40 Demo of Mike's COVID-19 At-Home Test Spotter App

00:31:55 App code introduction

00:32:10 googleway package integrating the Google Maps API

00:36:25 Pulling addresses from map searches

00:41:10 Using MongoDB for records collection

00:43:15 bslib to simulate the multi-page app experience

00:46:20 Episode wrapup

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