Innovative platforms for data aggregation, linkage and analysis in the context of pandemic and epidemic intelligence.

During the COVID-19 pandemic, open-access platforms that aggregate, link and analyse data were transformative for global public health surveillance. This perspective explores the work of three of these platforms: Our World In Data (OWID), Johns Hopkins University (JHU) COVID-19 Dashboard (later complemented by the Coronavirus Resource Center), and Global.Health, which were presented in the second World Health Organization (WHO) Pandemic and Epidemic Intelligence Innovation Forum. These platforms, operating mostly within academic institutions, added value to public health data that are collected by government agencies by providing additional real-time public health intelligence about the spread of the virus and the evolution of the public health emergency. Information from these platforms was used by health professionals, political decision-makers and members of the public alike. Further engagement between government and non-governmental surveillance efforts can accelerate the improvements needed in public health surveillance overall. Increasing the diversity of public health surveillance initiatives beyond the government sector comes with several benefits: technology innovation in data science, engagement of additional highly skilled professionals, greater transparency and accountability for government agencies, and new opportunities to engage with members of society.

The Missing COVID-19 Demographic Data: A Statewide Analysis of COVID-19-Related Demographic Data From Local Government Sources and a Comparison With Federal Public Surveillance Data.

Objectives. To collect and standardize COVID-19 demographic data published by local public-facing Web sites and analyze how this information differs from Centers for Disease Control and Prevention (CDC) public surveillance data. Methods. We aggregated and standardized COVID-19 data on cases and deaths by age, gender, race, and ethnicity from US state and territorial governmental sources between May 24 and June 4, 2021. We describe the standardization process and compare it with the CDC's process for public surveillance data. Results. As of June 2021, the CDC's public demographic data set included 80.9% of total cases and 46.7% of total deaths reported by states, with significant variation across jurisdictions. Relative to state and territorial data sources, the CDC consistently underreports cases and deaths among African American and Hispanic or Latino individuals and overreports deaths among people older than 65 years and White individuals. Conclusions. Differences exist in amounts of data included and demographic composition between the CDC's public surveillance data and state and territory reporting, with large heterogeneity across jurisdictions. A lack of standardization and reporting mechanisms limits the production of complete real-time demographic data.

Disparities in SARS-CoV-2 Testing for Hispanic/Latino Populations: An Analysis of State-Published Demographic Data.

Racial and ethnic minorities in the United States have been disproportionately affected by the COVID-19 pandemic, experiencing increased risk of infection, hospitalization, and death. In this study, we sought to examine race- and ethnicity-based differences in SARS-CoV-2 testing. We used publicly available US state dashboards to extract demographic data for COVID-19 cases and tests. Poisson regression models were used to model the effect of race and ethnicity on the number of SARS-CoV-2 tests performed per case. In total, just 8 states reported testing data by race and ethnicity. In regression models, race and ethnicity was a significant predictor of testing rate per case. In all states, Hispanic/Latino patients had a significantly lower testing rate than their non-Hispanic/Latino counterparts, with an incident rate ratio varying from 0.45 to 0.81, depending on the state and referent race category. These results suggest disparities in testing access among Hispanic/Latino individuals, who are already at a disproportionate risk for infection and severe outcomes.