Investigating the effects of absolute humidity and movement on COVID-19 seasonality in the United States.

Mounting evidence suggests the primary mode of SARS-CoV-2 transmission is aerosolized transmission from close contact with infected individuals. While transmission is a direct result of human encounters, falling humidity may enhance aerosolized transmission risks similar to other respiratory viruses (e.g., influenza). Using Google COVID-19 Community Mobility Reports, we assessed the relative effects of absolute humidity and changes in individual movement patterns on daily cases while accounting for regional differences in climatological regimes. Our results indicate that increasing humidity was associated with declining cases in the spring and summer of 2020, while decreasing humidity and increase in residential mobility during winter months likely caused increases in COVID-19 cases. The effects of humidity were generally greater in regions with lower humidity levels. Given the possibility that COVID-19 will be endemic, understanding the behavioral and environmental drivers of COVID-19 seasonality in the United States will be paramount as policymakers, healthcare systems, and researchers forecast and plan accordingly.

Multi-hazard hospital evacuation planning during disease outbreaks using agent-based modeling.

As different types of hazards, including natural and man-made, can occur simultaneously, to implement an integrated and holistic risk management, a multi-hazard perspective on disaster risk management, including preparedness and planning, must be taken for a safer and more resilient society. Considering the emerging challenges that the COVID-19 pandemic has been introducing to regular hospital operations, there is a need to adapt emergency plans with the changing conditions, as well. Evacuation of patients with different mobility disabilities is a complicated process that needs planning, training, and efficient decision-making. These protocols need to be revisited for multi-hazard scenarios such as an ongoing disease outbreak during which additional infection control protocols might be in place to prevent transmission. Computational models can provide insights on optimal emergency evacuation strategies, such as the location of isolation units or alternative evacuation prioritization strategies. This study introduces a non-ICU patient classification framework developed based on available patient mobility data. An agent-based model was developed to simulate the evacuation of the emergency department at the Johns Hopkins Hospital during the COVID-19 pandemic due to a fire emergency. The results show a larger nursing team can reduce the median and upper bound of the 95% confidence interval of the evacuation time by 36% and 33%, respectively. A dedicated exit door for COVID-19 patients is relatively less effective in reducing the median time, while it can reduce the upper bound by more than 50%.

Analysis of the potential impact of durability, timing, and transmission blocking of COVID-19 vaccine on morbidity and mortality.

BACKGROUND: COVID-19 vaccines have been approved and made available. While questions of vaccine allocation strategies have received significant attention, important questions remain regarding the potential impact of the vaccine given uncertainties regarding efficacy against transmission, availability, timing, and durability. METHODS: We adapted a susceptible-exposed-infectious-recovered (SEIR) model to examine the potential impact on hospitalization and mortality assuming increasing rates of vaccine efficacy, coverage, and administration. We also evaluated the uncertainty of the vaccine to prevent infectiousness as well as the impact on outcomes based on the timing of distribution and the potential effects of waning immunity. FINDINGS: Increased vaccine efficacy against disease reduces hospitalizations and deaths from COVID-19; however, the relative benefit of transmission blocking varied depending on the timing of vaccine distribution. Early in an outbreak, a vaccine that reduces transmission will be relatively more effective than one introduced later in the outbreak. In addition, earlier and accelerated implementation of a less effective vaccine is more impactful than later implementation of a more effective vaccine. These findings are magnified when considering the durability of the vaccine. Vaccination in the spring will be less impactful when immunity is less durable. INTERPRETATION: Policy choices regarding non-pharmaceutical interventions, such as social distancing and face mask use, will need to remain in place longer if the vaccine is less effective at reducing transmission or distributed slower. In addition, the stage of the local outbreak greatly impacts the overall effectiveness of the vaccine in a region and should be considered when allocating vaccines. FUNDING: Centers for Disease Control and Prevention (CDC) MInD-Healthcare Program (U01CK000589, 1U01CK000536), James S. McDonnell Foundation 21st Century Science Initiative Collaborative Award in Understanding Dynamic and Multiscale Systems, National Science Foundation (CNS-2027908), National Science Foundation Expeditions (CCF1917819), C3.ai Digital Transformation Institute (AWD1006615), and Google, LLC.