Mapping epidemics

This mini-hackfest was dedicated to mapping outbreak data and visualising associated spatial processes. Things we originally wanted to look into included:

  • ⚫ mapping incidence data using incidence objects.
  • ⚫ visualising contact data in the geographic space
  • ⚫ predicting and mapping spatial diffusion of cases based on passenger flow data
  • ⚫ ... and probably more!

We ended up creating the following:

  • ⚫ the GIS first aid website, which compiles a (growing) series of tutorials mapping epidemics
  • ⚫ the new R package epimaps which provides wrappers and helpers for maps and spatial clustering
  • ⚫ the new R package epiflows which provides tools for handling and visualising flow (e.g. air traffic) data

The Participants

Isobel Blake

/// Masterful R-ing in the realm of disease modelling and mapping.

// website

Paula Moraga

/// Spatial statistics mastery, and R-shiny-ing disease surveillance apps.

// website

Github profile Twitter profile

Thibaut Jombart

/// Organiser and purveyor of coffee, refreshments, and pizzas.

Imperial College London

// website

Github profile Twitter profile

Pawel Piatkowski

/// Shiny-ing and creative R-language fiddling.

// website

Github profile Twitter profile

Jonathan Polonsky

/// Epi-wisdom, shiny expertise and all-around R-ness.

// website

Github profile Twitter profile

Dirk Schumacher

/// Shiny things and infrastructure magic.

// website

Github profile Twitter profile

James Hayward

/// Logistics magic and admin awesomeness

MRC Centre for Outbreak Analysis and Modelling, Imperial College London

The Sponsors

The RECON Hackfest 2 is co-funded by:

RECON logo


Imperial College London logo