Information about COVID-19 pandemic dynamics is critical to understand the potential impacts on populations, design mitigation strategies, and evaluate the efficacy of their implementation. Centralization, standardization, and harmonization of data is critical to enable comparisons of the demographic impact of COVID-19 vis-à-vis differences in the age-compositions of confirmed infections and deaths. The international data landscape must keep pace with the global march of the pandemic, and researchers must work to triangulate the available data to create comparable measures to monitor and predict its demographic impacts.

COVerAGE-DB is a database that aims to provide global coverage of key demographic aspects of the COVID-19 pandemic as it unfolds in an up-to-date, transparent, and open-access format. COVerAGE-DB offers data with standardized count measures and harmonized age groups to allow comparisons between populations at national and subnational scales.

The database is currently under expansion through both the increase in coverage of national and subnational populations and the inclusion of more recent periods as the pandemic continues to unfold. At this writing, the database contains daily counts of COVID-19 cases, deaths, and tests performed by age and sex for 87 national and 195 subnational populations around the world, depending on the available data for each source. The date range available for each country or subpopulation varies. In several country series, the database includes the earliest confirmed cases in January 2020. For most populations the database includes daily time series, beginning from an initial starting date when the data were first released or collected by our team.

Official counts of COVID-19 cases, deaths, and tests are extracted from reports published by official governmental institutions, such as health ministries and statistical offices. We also collect standard metadata on each of the sources to capture various characteristics of the collected data, such as the primary collection channels, definitions used, and notes on major disruptions or events. Data is harmonized to standard metrics (counts), measures (cases, deaths, tests), and age bands (5- and 10-year age intervals). Harmonization procedures include various kinds of rescaling to ensure coherence in marginal sums.

Since collection efforts began for COVerAGE-DB in late March 2020, we are aware of several studies using the data, many of which provide R code online and are fully reproducible. These studies take a demographic perspective on the pandemic, taking advantage of age patterns of cases, deaths, or both to infer and better understand population-level impacts of the pandemic. These include standard demographic approaches and creative new methods proposals. A limitation of the COVerAGE-DB is the heterogeneous and difficult-to-evaluate quality of the underlying data. We describe such anomalies in the standardized metadata.