Implementing an Urban Public Health Observatory for (Near) Real-Time Surveillance for the COVID-19 Pandemic

Area of Science:

• Public Health
• Epidemiology
• Health Informatics

Background:

• The COVID-19 pandemic has significantly impacted global health and economies, disproportionately affecting vulnerable populations.
• Effective pandemic surveillance requires integrating social determinants of health (SDoH) with traditional epidemiological data.
• Existing surveillance systems often lack the multi-dimensional integration needed to address health disparities.

Purpose of the Study:

• To describe the development and implementation of an Urban Public Health Observatory (UPHO) model.
• To provide near real-time analysis and dashboarding of COVID-19 conditions in a metropolitan region.
• To identify associations between SDoH and pandemic health outcomes to inform policy and planning.

Main Methods:

• Developed an Urban Public Health Observatory (UPHO) model.
• Integrated multi-dimensional SDoH data with epidemiological factors.
• Utilized near real-time analysis and dashboarding for ongoing COVID-19 surveillance.

Main Results:

• The UPHO model facilitates contextualized analysis of pandemic conditions.
• Near real-time data integration allows for timely identification of trends.
• Demonstrated the utility of integrating SDoH for public health insights.

Conclusions:

• The UPHO model offers a framework for enhanced pandemic surveillance.
• Integrating SDoH is crucial for understanding and addressing health disparities during pandemics.
• This approach can inform targeted public health interventions and policy decisions.