Modeling serological testing to inform relaxation of social distancing for COVID-19 control.

Serological testing remains a passive component of the public health response to the COVID-19 pandemic. Using a transmission model, we examine how serological testing could have enabled seropositive individuals to increase their relative levels of social interaction while offsetting transmission risks. We simulate widespread serological testing in New York City, South Florida, and Washington Puget Sound and assume seropositive individuals partially restore their social contacts. Compared to no intervention, our model suggests that widespread serological testing starting in late 2020 would have averted approximately 3300 deaths in New York City, 1400 deaths in South Florida and 11,000 deaths in Washington State by June 2021. In all sites, serological testing blunted subsequent waves of transmission. Findings demonstrate the potential benefit of widespread serological testing, had it been implemented in the pre-vaccine era, and remain relevant now amid the potential for emergence of new variants.

Causes and Consequences of COVID-19-Associated Bacterial Infections.

The COVID-19 literature highlights that bacterial infections are more common in fatal cases than recovered cases. If bacterial infections drive mortality in COVID-19, this has clear implications for patient management. However, it is possible that the enrichment of bacterial infections in COVID-19 fatalities is simply a by-product of late-stage pathology, leading to different advice for patient management. To address this question, we review current knowledge on bacterial infections in COVID-19, assess information from past viral respiratory pandemics, and simulate alternate causal models of interactions between virus, bacteria, and mortality in COVID-19. From these models, we conclude that currently available data are not sufficient to discriminate between these alternate causal pathways, and we highlight what data are required to determine the relative contribution of bacterial infection to COVID-19 morbidity and mortality. We further summarize the potential long-term consequences of SARS-CoV-2 infection.

Modeling shield immunity to reduce COVID-19 epidemic spread.

The COVID-19 pandemic has precipitated a global crisis, with more than 1,430,000 confirmed cases and more than 85,000 confirmed deaths globally as of 9 April 20201-4. Mitigation and suppression of new infections have emerged as the two predominant public health control strategies5. Both strategies focus on reducing new infections by limiting human-to-human interactions, which could be both socially and economically unsustainable in the long term. We have developed and analyzed an epidemiological intervention model that leverages serological tests6,7 to identify and deploy recovered individuals8 as focal points for sustaining safer interactions via interaction substitution, developing what we term 'shield immunity' at the population scale. The objective of a shield immunity strategy is to help to sustain the interactions necessary for the functioning of essential goods and services9 while reducing the probability of transmission. Our shield immunity approach could substantively reduce the length and reduce the overall burden of the current outbreak, and can work synergistically with social distancing. The present model highlights the value of serological testing as part of intervention strategies, in addition to its well-recognized roles in estimating prevalence10,11 and in the potential development of plasma-based therapies12-15.