Coronavirus data on HASH

In the early stages of any pandemic, one of the most useful resources available to policymakers is raw data. Understanding and effectively using that information requires intelligent analysis, and sometimes more data than was necessarily available upfront, as more becomes known about a disease.

As outbreaks progress (and indeed become endemic), policymakers shift their questioning to ask how best diseases can be managed, while continuing to safeguard vulnerable populations.

Since the COVID outbreak at the end of 2019, various institutions have collected data on the spread of the disease, mortality and hospitalization rates, as well as the number of vaccinations distributed. A number of the resulting datasets have made their way onto HASH’s platform as curated sets of useful data that can be used to build and backtest agent-based models of COVID. Please note that not all of these datasets are actively maintained, but these listings highlight the range of available data.

Transmission Data

  • Estimates of the effective reproduction rates of COVID provided policymakers with a clear sense of its likely problematic nature
  • A dataset of known superspreading events associated with the virus (clearly and interestingly showing very early on the high likely impact of ventilation/being outdoors for reducing transmission)

Infection Data

Patient Data

Treatment & Vaccine Data

Economic Data

A number of simulations related to COVID, including the City Infection Model, have already been published to HASH and are available for open-source download and use. For more information, check out the HASH Simulation Docs, or join our Discord to ask questions and get help directly.

24th May 2022 update: we’re tracking the outbreak of monkeypox, and the availability of monkeypox datasets on HASH over in a new post. Let’s hope we’re able to nip this one in the bud.