We aim to build an open data exchange and modeling toolkit for responsible epidemiology.

Created on: March 30, 2020
Last update: May 26, 2020

by John Urbanik

Participating to challenge(s): Data analysis and simulation, Covid19 Prevention

3Good Health and Well-being
9Industry, Innovation, and Infrastructure
11Sustainable Cities and Communities
Public health
Computational modeling
Data engineering
Data science
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We would like to build a toolkit that makes building 'responsible' epidemiological forecasting models easy and computationally efficient. It should make sane assumptions about variable distributions, include ways to integrate many types of empirical data in a straightforward way, allow for sensitivity analysis and understanding of uncertainty, capture possible dynamics of different types of suppression, mitigation and control tactics.

With sufficient resources, we would also try to design systems that maintain up to date, easily ingestible, empirical data on population level statistics ranging from demography and network connectedness on a granular level to granular public health data.

Please see https://github.com/epi-center/planning for a more detailed proposal.

  • Status: Active/Ongoing