Smart testing and critical care bed sharing for COVID-19 control.

Area of Science:

• Epidemiology
• Public Health
• Data Science

Background:

• Social distancing measures showed varied success in controlling COVID-19 transmission globally.
• Developing countries like Brazil faced challenges due to limited systematic testing and economic disparities impacting disease spread.
• High population density and worker mobility in economic hubs exacerbate COVID-19 transmission dynamics.

Purpose of the Study:

• To develop and evaluate a smart testing strategy for optimizing COVID-19 testing deployment in developing countries.
• To identify high-impact geographic regions for testing to effectively limit disease transmission.
• To assess the potential of smart testing to reduce the need for extensive social distancing measures.

Main Methods:

• Developed an optimization platform for a "smart testing" protocol.
• Integrated anonymized mobility, demographic, and intensive care unit (ICU) occupancy data.
• Utilized city-specific social distancing measures and regional ICU bed availability.

Main Results:

• Smart testing strategies can rapidly limit COVID-19 transmission.
• The strategy proved effective even with limited daily testing capacities.
• Optimized testing reduced the overall need for broad social distancing measures.

Conclusions:

• Smart testing offers an effective approach to pandemic control in resource-limited settings.
• Data-driven optimization of testing is crucial for managing infectious disease outbreaks.
• This strategy can help developing countries overcome challenges in controlling widespread transmission.