Analysis of overdispersion in airborne transmission of Covid-19

Superspreading events and overdispersion are hallmarks of the Covid-19 pandemic. To gain insight into the nature and controlling factors of these superspreading events and heterogeneity in transmission, we conducted mechanistic modeling of SARS-CoV-2 transmission by infectious aerosols using real-world occupancy data from a large number of full-service restaurants in ten US metropolises. Including a large number of factors that influence disease transmission in these settings, we demonstrate the emergence of a stretched tail in the probability density function of secondary infection numbers indicating strong heterogeneity in individual infectivity. Derived analytical results further demonstrate that variability in viral loads and variability in occupancy, together, lead to overdispersion in the number of secondary infections arising from individual index cases. Our analysis, connecting mechanistic understanding of SARS-CoV-2 transmission by aerosols with observed large-scale epidemiological characteristics of Covid-19 outbreaks, adds an important dimension to the mounting body of evidence with regards to the determinants of airborne transmission of SARS-CoV-2 by aerosols in indoor settings.

COVID-19: Effectiveness of Non-Pharmaceutical Interventions in the United States before Phased Removal of Social Distancing Protections Varies by Region

Although coronavirus disease 2019 (COVID-19) emerged in January 2020, there is no quantified effect size for non-pharmaceutical interventions (NPI) to control the outbreak in the continental US. Objective. To quantify national and sub-national effect sizes of NPIs in the US. Design. This is an observational study for which we obtained daily county level COVID-19 cases and deaths from January 22, 2020 through the phased removal of social distancing protections. A stepped-wedge cluster-randomized trial (SW-CRT) analytical approach is used, leveraging the phased implementation of policies. Data include 3142 counties from all 50 US states and the District of Columbia. Exposures. County-level NPIs were obtained from online county and state policy databases, then classified into four intervention levels: Level 1 (low) - declaration of a State of Emergency; Level 2 (moderate) - school closures, restricting nursing home access, or closing restaurants and bars; Level 3 (high) - non-essential business closures, suspending non-violent arrests, suspending elective medical procedures, suspending evictions, or restricting mass gatherings of at least 10 people; and Level 4 (aggressive) - sheltering in place / stay-at-home, public mask requirements, or travel restrictions. Additional county-level data were obtained to record racial (Black, Hispanic), economic (educational level, poverty), demographic (rural/urban) and climate factors (temperature, specific humidity, solar radiation). Main Outcomes. The primary outcomes are rates of COVID-19 cases, deaths and case doubling times. NPI effects are measured separately for nine US Census Region (Pacific, Mountain, West North Central, East North Central, West South Central, East South Central, South Atlantic, Middle Atlantic, New England). Results. Aggressive NPIs (level 4) significantly reduced COVID-19 case and death rates in all US Census Regions, with effect sizes ranging from 4.1% to 25.7% and 5.5% to 25.5%, respectively, for each day they were active. No other intervention level achieved significance across all US Regions. Intervention levels 3 and 4 both increased COVID-19 doubling times, with effects peaking at 25 and 40 days after initiation of each policy, respectively. The effectiveness of level 3 NPIs varied, reducing case rates in all regions except North Central states, but associated with significantly higher death rates in all regions except Pacific states. Intervention levels 1 and 2 did not indicate any effect on COVID-19 propagation and, in some regions, these interventions were associated with increased COVID-19 cases and deaths. Heterogeneity of NPI effects are associated with racial composition, poverty, urban-rural environment, and climate factors. Conclusion. Aggressive NPIs are effective tools to reduce COVID-19 propagation and mortality. Reducing social and environmental disparities may improve NPI effects in regions where less strict policies are in place.