Tagged "epidata"

Back to the Future - From Delphi Epidata to COVIDcast, and Back

When the pandemic broke out, Delphi naturally turned our focus to COVID-19. Our collection of signals grew dramatically, from a few dozen to several hundred, with all new signals focusing on COVID-19 in the US. We also created a new Delphi Epidata ingestion pipeline, database schema, API endpoint, and visualization website, all focusing on COVID-19 signals, and gave it the name COVIDcast. As a result, COVIDcast is the portion of Delphi Epidata that focuses on COVID-19 related signals. It is currently the biggest portion of Delphi Epidata, and constitutes what we believe may be the largest public repository of real-time, geographically-detailed indicators of COVID-19 activity in the U.S.

As the pandemic’s critical phase began to subside, we have been gradually returning to our long-term mission: to develop the theory and practice of epidemic forecasting for all existing and emerging pathogens and other fast moving public health concerns. At the signals level, this means zooming out from just COVIDcast to the bigger picture, returning the focus to Delphi Epidata. We have recently reconfigured our website accordingly. The move from COVIDcast to Delphi Epidata is not a rename, but rather a post-pandemic return to our original broader concept.

Identifying Changing Variant Behavior during a Pandemic: An Exploratory Analysis

We use changepoint detection algorithms to analyze Delphi’s indicators and classify them as early, on-time, late, undefined, or undetermined.

New package released! Epidatr, an R client for Delphi Epidata API

epidatr is designed to streamline the downloading and usage of data from the Delphi Epidata API. It provides a simple R interface to the API, including functions for downloading data, parsing the results, and converting the data into a tidy format.

Introducing Epidata v4

Epidata v0.4.0 (“v4” for short) launched on September 26, 2022, bringing about a major revision to how we store data served by the Epidata API. The changes prioritize fast access to the most up-to-date data while retaining the deep data revision history needed by researchers. The launch included a prototype of a modular data organization system intended to generalize across multiple pathogens, with stubs for more advanced and efficient timestamping and greater flexibility in data stratification.