Prioritizing vaccination based on analysis of community networks.

Many countries that had early access to COVID-19 vaccines implemented vaccination strategies that prioritized health care workers and the elderly. As barriers to access eased, vaccine prioritization strategies have been relaxed. However, these strategies are still an important tool for decision makers to manage new variants, plan for future booster shots, or stage mass vaccinations. This paper explores the impact of vaccine prioritization strategies using networks that represent communities with different demographics and connectivity. The impact of vaccination is compared to non-medical intervention to reduce transmission. Several sources of uncertainty are considered, including vaccine willingness and mask effectiveness. This paper finds that while prioritization strategies can have a large impact on reducing deaths and peak hospitalization, selecting the best strategy depends on community characteristics and the desired objective. Additionally, in some cases random vaccination performs as well as more targeted prioritization strategies. Understanding these trade-offs is important when planning vaccine distribution.

Population level SARS-CoV-2 fecal shedding rates determined via wastewater-based epidemiology.

Wastewater-based epidemiology (WBE) has been utilized as an early warning tool to anticipate disease outbreaks, especially during the COVID-19 pandemic. However, COVID-19 disease models built from wastewater-collected data have been limited by the complexities involved in estimating SARS-CoV-2 fecal shedding rates. In this study, wastewater from six municipalities in Arizona and Florida with distinct demographics were monitored for SARS-CoV-2 RNA between September 2020 and December 2021. Virus concentrations with corresponding clinical case counts were utilized to estimate community-wide fecal shedding rates that encompassed all infected individuals. Analyses suggest that average SARS-CoV-2 RNA fecal shedding rates typically occurred within a consistent range (7.53-9.29 log10 gc/g-feces); and yet, were unique to each community and influenced by population demographics. Age, ethnicity, and socio-economic factors may have influenced shedding rates. Interestingly, populations with median age between 30 and 39 had the greatest fecal shedding rates. Additionally, rates remained relatively constant throughout the pandemic provided conditions related to vaccination and variants were unchanged. Rates significantly increased in some communities when the Delta variant became predominant. Findings in this study suggest that community-specific shedding rates may be appropriate in model development relating wastewater virus concentrations to clinical case counts.

Demographics matter: the potentially disproportionate effect of COVID-19 on hospital ratings.

OBJECTIVE: To identify how features of the community in which a hospital serves differentially relate to its patients' experiences based on the quality of that hospital. DESIGN: A Finite Mixture Model (FMM) is used to uncover a mix of two latent groups of hospitals that differ in quality. In the FMM, a multinomial logistic equation relates hospital-level factors to the odds of being in either group. And a multiple linear regression relates the characteristics of communities served by hospitals to the patients' expected ratings of their experiences at hospitals in each group. Thus, this association potentially varies with hospital quality. The analysis was conducted via Stata. SETTING: Hospital Ratings are measured by Hospital Compare using the HCAHPS survey, a patient satisfaction survey required by the Centers for Medicare and Medicaid Services (CMS) for hospitals in the United States. Participants: 2,816 Medicare-certified acute care hospitals across all US states.