Speaker
Description
The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been widespread since 2020 and will likely continue to cause significant recurring epidemics. However, understanding the underlying infection burden (i.e., including undetected asymptomatic/mild infections) and dynamics, particularly since late 2021 when the Omicron variant emerged, is challenging due to the nature of SARS-CoV-2 infection, changes in testing practices, and changes in disease reporting. In this study, we leverage extensive surveillance data available in New York City (NYC) and a comprehensive model-inference system to reconstruct SARS-CoV-2 dynamics from the pandemic onset in March 2020 to August 2023, and further validate the estimates using independent wastewater surveillance data.
Accounting for undetected infections, we estimated a very high infection burden totaling twice the population size of NYC (17.4 million infections, 95% Credible interval (CrI): 14.2 – 21.5), 5.4 (95% CrI: 4.4 – 6.7) times documented case counts during its first 3.5 years of circulation. Estimated infection-fatality risk (IFR) decreased by >10-fold during this period. The detailed estimates also reveal highly complex variant dynamics and population immune landscape, showing fast turnover of new Omicron-subvariants and co-circulation of multiple Omicron-subvariants during more recent waves. Accounting for multiple factors including immune evasion, we estimate that SARS-CoV-2 viral transmissibility has increased by nearly 3-fold in three years, but has appeared to level off since the latter half of 2022. In addition, we estimated higher infection rates during winter months that peaked in December or January during the 3+ year study period in NYC (temperate climate). These transmission dynamics and drivers, albeit based on data in NYC, may be common to other populations and could inform future planning to help mitigate the public health burden of SARS-CoV-2.
