Can we clinically identify pre-symptomatic and asymptomatic COVID-19?

Area of Science:

• Infectious Disease Epidemiology
• Geriatric Medicine
• Public Health Surveillance

Background:

• Nursing home residents face high morbidity and mortality from COVID-19.
• Early detection of SARS-CoV-2 is crucial for mitigating outbreaks in long-term care settings.
• Standard temperature screening thresholds may miss early, pre-symptomatic, or asymptomatic infections.

Approach:

• Retrospective cohort study utilizing electronic health records from 6,176 VA nursing home residents.
• Developed a hypothetical model to analyze temperature trends and variations in relation to SARS-CoV-2 infection.
• Collected data on demographics, baseline temperature, and comorbidities.

Key Points:

• A temperature change >0.4C from baseline identified 47% of SARS-CoV-2 positive residents earlier by 42.2 hours.
• Combining a >0.4C change with a 0.7C range detected 52% of infections early, improving detection by over 3 days in 22% of residents.
• This enhanced detection strategy, while increasing the number of tests, offers significant improvements over current methods.

Conclusions:

• Current COVID-19 screening in nursing homes can be improved by using patient-derived baseline temperatures.
• Implementing a 0.4C relative elevation or 0.7C temperature variability as a trigger threshold for SARS-CoV-2 testing is recommended.
• Automating these temperature-based triggers in electronic health records can enhance early detection and outbreak control.