Household Transmission of SARS-CoV-2 along the Evolution of Pandemic (preprint)

Over the past three years, we have gained some understanding of the transmission mechanisms of COVID-19. One of the key findings that experts have agreed on is that household transmission is an important pathway for the pandemic. However, most studies on the transmission patterns of COVID-19 focus on the community transmission only, while the equally important study on household transmission has lagged behind. We developed a stochastic dynamic model motivated by the cluster growth algorithm in Erdös–Rényi Random Graph to differentiate the COVID-19 transmission within households from that in the community by noting only a small fraction of the total susceptible population, replenished dynamically by the community transmission events, are indeed vulnerable to household transmission. Thus the model allowed us to the role and characteristics of household transmission within the full framework of virus transmission, beyond the intrinsic characteristics of household transmission. It was then applied to a comprehensive individual-level pandemic dataset collected in Yichang, China. Our findings showed that household transmission accounted for 25.1% and 38.5% of total infections before and during the lockdown, respectively, and that 80.9% of infections were unavoidable. Our model suggests that household-level contact tracing could have reduced the number of infections by over 50% and advanced the clearance date of active infection by 72 days. This model can be used to fit COVID-19 data outside Yichang or other infectious diseases, though modifications might be needed.

Do Lockdowns Bring about Additional Mortality Benefits or Costs? Evidence based on Death Records from 300 Million Chinese People (preprint)

After the COVID-19 outbreak, China immediately adopted stringent lockdown policies to contain the virus. Using comprehensive death records covering around 300 million Chinese people, we estimate the impacts of city and community lockdowns on non-COVID-19 mortality outside of Wuhan. Employing a difference-in-differences method, we find that lockdowns reduced the number of non-COVID-19 deaths by 4.9% (cardiovascular deaths by 6.2%, injuries by 9.2%, and non-COVID-19 pneumonia deaths by 14.3%). The health benefits are likely driven by significant reductions in air pollution, traffic, and human interactions. A back-of-the-envelope calculation shows that more than 32,000 lives could have been saved from non-COVID-19 diseases/causes during the 40 days of the lockdown on which we focus. The results suggest that the rapid and strict virus countermeasures not only effectively controlled the spread of COVID-19 but also brought about massive unintended public health benefits. These findings can help better inform policymakers around the world about the benefits and costs of city and community lockdowns policies in dealing with the COVID-19 pandemic.