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Abstract The built environment provides an excellent setting for interdisciplinary research on the dynamics of microbial communities. The system is simplified compared to many natural settings, and to some extent the entire environment can be manipulated, from architectural design to materials use, air flow, human traffic, and capacity to disrupt microbial communities through cleaning. Here, we provide an overview of the ecology of the microbiome in the built environment. We address niche space and refugia, population, and community (metagenomic) dynamics, spatial ecology within a building, including the major microbial transmission mechanisms, as well as evolution. We also address landscape ecology, connecting microbiomes between physically separated buildings. At each stage, we pay particular attention to the actual and potential interface between disciplines, such as ecology, epidemiology, materials science, and human social behavior. We end by identifying some opportunities for future interdisciplinary research on the microbiome of the built environment. 

Abstract Objective: Current guidance states that asymptomatic screening for severe acute respiratory coronavirus virus 2 (SARS-CoV-2) prior to admission to an acute-care setting is at the facility’s discretion. This study’s objective was to estimate the number of undetected cases of SARS-CoV-2 admitted as inpatients under 4 testing approaches and varying assumptions. Design and setting: Individual-based microsimulation of 104 North Carolina acute-care hospitals Patients: All simulated inpatient admissions to acute-care hospitals from December 15, 2021, to January 13, 2022 [ie, during the SARS-COV-2 ο (omicron) variant surge]. Interventions: We simulated (1) only testing symptomatic patients, (2) 1-stage antigen testing with no confirmatory polymerase chain reaction (PCR) test, (3) 1-stage antigen testing with a confirmatory PCR for negative results, and (4) serial antigen screening (ie, repeat antigen test 2 days after a negative result). Results: Over 1 month, there were 77,980 admissions: 13.7% for COVID-19, 4.3% with but not for COVID-19, and 82.0% for non–COVID-19 indications without current infection. Without asymptomatic screening, 1,089 (credible interval [CI], 946–1,253) total SARS-CoV-2 infections (7.72%) went undetected. With 1-stage antigen screening, 734 (CI, 638–845) asymptomatic infections (67.4%) were detected, with 1,277 false positives. With combined antigen and PCR screening, 1,007 (CI, 875–1,159) asymptomatic infections (92.5%) were detected, with 5,578 false positives. A serial antigen testing policy detected 973 (CI, 845–1,120) asymptomatic infections (89.4%), with 2,529 false positives. Conclusions: Serial antigen testing identified >85% of asymptomatic infections and resulted in fewer false positives with less cost per identified infection compared to combined antigen plus PCR testing. 

COVID-19 is challenging many societal institutions, including our criminal justice systems. Some have proposed or enacted (e.g., the State of New Jersey) reductions in the jail and/or prison populations. We present a mathematical model to explore the epidemiologic impact of such interventions in jails and contrast them with the consequences of maintaining unaltered practices. We consider infection risk and likely in-custody deaths, and estimate how within-jail dynamics lead to spill-over risks, not only affecting incarcerated people but increasing exposure, infection, and death rates for both corrections officers and the broader community beyond the justice system. We show that, given a typical jail-community dynamic, operating in a business-as-usual way results in substantial, rapid, and ongoing loss of life. Our results are consistent with the hypothesis that large-scale reductions in arrest and speeding of releases are likely to save the lives of incarcerated people, jail staff, and the wider community.