Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases · 2025
Utilization of population-wide digital contact tracing to estimate real-world vaccine effectiveness in a pandemic setting.
СтатьяНаблюдательное исследованиеНазвание и аннотация: Перевод пока не подготовлен
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Chan Jeremy Wei Quan, Wee Liang En, Abdul Malek Muhammad Ismail Bin, Chiew Calvin, Ho Zheng Jie Marc, Ong Benjamin, Heng Derrick, Lee Vernon, Lye David, Tan Kelvin Bryan
Аннотация
OBJECTIVES: Observational cohort methods for evaluating real-world vaccine effectiveness can introduce biases and yield negative vaccine-effectiveness estimates. We evaluated if utilization of digital contact tracing (DCT) data could yield more realistic estimates of vaccine effectiveness.
METHODS: Vaccine effectiveness against SARS-CoV-2 infection was estimated using an observational population-based cohort of older Singaporeans (≥60 years) and DCT data of contacts (≥60 years) significantly exposed to COVID-19 cases, during Delta/Omicron predominance. Person-day generalized Poisson regressions adjusted for sociodemographic characteristics were performed to estimate adjusted incidence rate ratios of infection at different time intervals from second/third vaccine doses up to 5 months post vaccination, with unvaccinated/partially vaccinated person-time as the reference group. Vaccine effectiveness against infection (VE-I) was calculated as 1 minus incidence rate ratio.
RESULTS: In total, 883 227 and 853 435 older Singaporeans were included in the observational cohort during Delta and Omicron predominance. Also, 102 208 and 347 817 case-contact pairs were identified from national DCT data during Delta and Omicron-predominant transmission. During Delta, estimates derived using the observational population-based cohort method mirrored DCT-based estimates (e.g. boosting, 60-69 years: VE-I = 0.60, 95% CI: 0.57-0.63 [observational cohort]; VE-I = 0.76, 95% CI: 0.72-0.78) [DCT-based estimates]). However, during the Omicron surge, observational cohort methods yielded negative vaccine-effectiveness estimates (e.g. boosting <2 months post vaccination, 60-69 years: VE-I = -1.12, 95% CI: -1.29 to -0.96). When DCT data were utilized to estimate vaccine effectiveness, boosting restored protection (e.g. boosting <2 months post-vaccination, 60-69 years: VE-I = 0.32, 95% CI: 0.23-0.39), with subsequent waning 2-month post-booster (e.g. boosting >5 months post-vaccination, 60-69 years: VE-I = 0.14, 95% CI: 0.04-0.23).
DISCUSSION: During an Omicron COVID-19 surge, observational cohort methods yielded negative vaccine-effectiveness estimates, whereas the use of national DCT data yielded more realistic estimates. DCT data can augment real-world estimates of vaccine effectiveness in the population at large and convey a more complete picture of vaccine-derived protection, especially in the context of a complex immunization landscape and an evolving pandemic situation.
METHODS: Vaccine effectiveness against SARS-CoV-2 infection was estimated using an observational population-based cohort of older Singaporeans (≥60 years) and DCT data of contacts (≥60 years) significantly exposed to COVID-19 cases, during Delta/Omicron predominance. Person-day generalized Poisson regressions adjusted for sociodemographic characteristics were performed to estimate adjusted incidence rate ratios of infection at different time intervals from second/third vaccine doses up to 5 months post vaccination, with unvaccinated/partially vaccinated person-time as the reference group. Vaccine effectiveness against infection (VE-I) was calculated as 1 minus incidence rate ratio.
RESULTS: In total, 883 227 and 853 435 older Singaporeans were included in the observational cohort during Delta and Omicron predominance. Also, 102 208 and 347 817 case-contact pairs were identified from national DCT data during Delta and Omicron-predominant transmission. During Delta, estimates derived using the observational population-based cohort method mirrored DCT-based estimates (e.g. boosting, 60-69 years: VE-I = 0.60, 95% CI: 0.57-0.63 [observational cohort]; VE-I = 0.76, 95% CI: 0.72-0.78) [DCT-based estimates]). However, during the Omicron surge, observational cohort methods yielded negative vaccine-effectiveness estimates (e.g. boosting <2 months post vaccination, 60-69 years: VE-I = -1.12, 95% CI: -1.29 to -0.96). When DCT data were utilized to estimate vaccine effectiveness, boosting restored protection (e.g. boosting <2 months post-vaccination, 60-69 years: VE-I = 0.32, 95% CI: 0.23-0.39), with subsequent waning 2-month post-booster (e.g. boosting >5 months post-vaccination, 60-69 years: VE-I = 0.14, 95% CI: 0.04-0.23).
DISCUSSION: During an Omicron COVID-19 surge, observational cohort methods yielded negative vaccine-effectiveness estimates, whereas the use of national DCT data yielded more realistic estimates. DCT data can augment real-world estimates of vaccine effectiveness in the population at large and convey a more complete picture of vaccine-derived protection, especially in the context of a complex immunization landscape and an evolving pandemic situation.