Vaccine effectiveness against emerging COVID-19 variants using digital health data

Area of Science:

• Epidemiology
• Public Health
• Infectious Disease Surveillance

Background:

• Participatory surveillance supplements traditional methods for tracking infectious diseases and vaccine effectiveness.
• The University of Maryland COVID Trends and Impact Survey utilized Facebook users for real-time symptom and vaccination data.

Purpose of the Study:

• To develop a methodology for assessing changes in vaccine effectiveness and COVID-19 symptomatology.
• To analyze data from Guatemala, Mexico, and South Africa using the COVID Trends and Impact Survey.

Main Methods:

• Conditional logistic regression was employed to estimate vaccine effectiveness.
• Self-reported COVID-like illness definitions were used in place of confirmed diagnostic test results.

Main Results:

• Vaccine effectiveness decreased during Omicron-dominated waves compared to the Delta variant (median change: -0.40).
• COVID-19 symptomatology shifted towards upper respiratory symptoms (cough, sore throat) during Omicron periods.
• Vaccine protection remained consistent across mild and severe COVID-19 cases during the Omicron period.

Conclusions:

• Participatory surveillance and the described methodologies are valuable for resource-limited settings.
• This approach addresses limitations in diagnostic testing availability and timeliness.