Potential Biases Arising From Epidemic Dynamics in Observational Seroprotection Studies

Area of Science:

• Epidemiology
• Immunology
• Infectious Diseases

Background:

• The duration and extent of immunity following SARS-CoV-2 infection remain critical questions.
• Evaluating serostatus effects on reinfection is essential for understanding SARS-CoV-2 epidemiology.
• Potential biases in serological studies need careful consideration for accurate interpretation.

Purpose of the Study:

• To investigate biases in serological studies assessing SARS-CoV-2 reinfection.
• To demonstrate how geographic structure and epidemic dynamics can induce noncausal associations.
• To propose methods for mitigating bias in the design and analysis of such studies.

Main Methods:

• Simulated serological studies under controlled and uncontrolled epidemic scenarios.
• Assessed the impact of prior infection on subsequent infection risk in simulations.
• Employed various study designs and analytical approaches to analyze simulated data.

Main Results:

• Geographic structure and epidemic dynamics can create noncausal associations in observational studies.
• Failure to account for these factors can lead to biased estimates of protection conferred by prior infection.
• Stratification or matching on geographic location and time of enrollment is crucial.

Conclusions:

• Accurate assessment of SARS-CoV-2 immunity requires careful study design to mitigate confounding.
• Geographic and temporal factors are significant sources of bias in serological studies.
• Comparing seropositive and seronegative individuals with similar exposure patterns is vital to prevent bias.