Impacts of residential indoor air quality and environmental risk factors on adult asthma-related health outcomes in Chicago, IL.

BACKGROUND: Residential environments are known to contribute to asthma. OBJECTIVE: To examine the joint impacts of exposures to residential indoor and outdoor air pollutants and housing risk factors on adult asthma-related health outcomes. METHODS: We analyzed >1-year of data from 53 participants from 41 homes in the pre-intervention period of the Breathe Easy Project prior to ventilation and filtration retrofits. Health outcomes included surveys of asthma control, health-related quality of life, stress, and healthcare utilizations. Environmental assessments included quarterly measurements of indoor and outdoor pollutants (e.g., HCHO, CO, CO2, NO2, O3, and PM), home walk-throughs, and surveys of environmental risk factors. Indoor pollutant concentrations were also matched with surveys of time spent at home to estimate indoor pollutant exposures. RESULTS: Cross-sectional analyses using mixed-effects models indicated that lower annual average asthma control test (ACT) scores were associated (p < 0.05) with higher indoor NO2 (concentration/exposure: ß = -2.42/-1.57), indoor temperature (ß = -1.03 to -0.94), and mold/dampness (ß = -3.09 to -2.41). In longitudinal analysis, lower ACT scores were also associated (p < 0.05) with higher indoor NO2 concentrations (ß = -0.29), PM1 (concentration/exposure: ß = -0.12/-0.24), PM2.5 (concentration/exposure: ß = -0.12/-0.26), and PM10 (concentration/exposure: ß = 10.14/-0.28). Emergency department visits were associated with poorer asthma control [incidence rate ratio (IRR) = 0.84; p < 0.001], physical health (IRR = 0.95; p < 0.05), mental health (IRR = 0.95; p < 0.05), higher I/O NO2 ratios (IRR = 1.30; p < 0.05), and higher indoor temperatures (IRR = 1.41; p < 0.05). SIGNIFICANCE: Findings suggest that residential risk factors, including indoor air pollution (especially NO2 and particulate matter), higher indoor temperature, and mold/dampness, may contribute to poorer asthma control. IMPACT: This study highlights the importance of residential indoor air quality and environmental risk factors for asthma control, health-related quality of life, and emergency department visits for asthma. Two timescales of mixed models suggest that exposure to indoor NO2 and particulate matter, higher indoor temperature, and mold/dampness was associated with poorer asthma control. Additionally, emergency department visits were associated with poorer asthma control and health-related quality of life, as well as higher I/O NO2 ratios and indoor temperatures. These findings deepen our understanding of the interrelationships between housing, air quality, and health, and have important implications for programs and policy.

Indoor air quality impacts of residential mechanical ventilation system retrofits in existing homes in Chicago, IL.

Mechanical ventilation systems are used in residences to introduce ventilation air and dilute indoor-generated pollutants. A variety of ventilation system types can be used in home retrofits, influencing indoor air quality (IAQ) in different ways. Here we describe the Breathe Easy Project, a >2-year longitudinal, pseudo-randomized, crossover study designed to assess IAQ and adult asthma outcomes before and after installing residential mechanical ventilation systems in 40 existing homes in Chicago, IL. Each home received one of three types of ventilation systems: continuous exhaust-only, intermittent powered central-fan-integrated-supply (CFIS), or continuous balanced system with an energy recovery ventilator (ERV). Homes with central heating and/or cooling systems also received MERV 10 filter replacements. Approximately weeklong field measurements were conducted at each home on a quarterly basis throughout the study to monitor environmental conditions, ventilation operation, and indoor and outdoor pollutants, including size-resolved particles (0.3-10 µm), ozone (O3), nitrogen dioxide (NO2), carbon dioxide (CO2), carbon monoxide (CO), and indoor formaldehyde (HCHO). Mean reductions in indoor/outdoor (I/O) ratios across all systems after the intervention were approximately 12% (p = 0.001), 10% (p = 0.008), 42% (p < 0.001), 39% (p = 0.002), and 33% (p = 0.007), for CO2, NO2, and estimated PM1, PM2.5, and PM10, respectively. There was a reduction in I/O ratios for all measured constituents with each type of system, on average, but with varying magnitude and levels of statistical significance. The magnitudes of mean differences in I/O pollutant concentrations ratios were generally largest for most pollutants in the homes that received continuous balanced with ERV and smallest in the homes that received intermittent CFIS systems, with apparent benefits to providing ventilation continuously rather than intermittently. All ventilation system types maintained similar indoor temperatures during pre- and post-intervention periods.

Integrating Personal Air Sensor and GPS to Determine Microenvironment-Specific Exposures to Volatile Organic Compounds.

Personal exposure to volatile organic compounds (VOCs) from indoor sources including consumer products is an understudied public health concern. To develop and evaluate methods for monitoring personal VOC exposures, we performed a pilot study and examined time-resolved sensor-based measurements of geocoded total VOC (TVOC) exposures across individuals and microenvironments (MEs). We integrated continuous (1 min) data from a personal TVOC sensor and a global positioning system (GPS) logger, with a GPS-based ME classification model, to determine TVOC exposures in four MEs, including indoors at home (Home-In), indoors at other buildings (Other-In), inside vehicles (In-Vehicle), and outdoors (Out), across 45 participant-days for five participants. To help identify places with large emission sources, we identified high-exposure events (HEEs; TVOC > 500 ppb) using geocoded TVOC time-course data overlaid on Google Earth maps. Across the 45 participant-days, the MEs ranked from highest to lowest median TVOC were: Home-In (165 ppb), Other-In (86 ppb), In-Vehicle (52 ppb), and Out (46 ppb). For the two participants living in single-family houses with attached garages, the median exposures for Home-In were substantially higher (209, 416 ppb) than the three participant homes without attached garages: one living in a single-family house (129 ppb), and two living in apartments (38, 60 ppb). The daily average Home-In exposures exceeded the estimated Leadership in Energy and Environmental Design (LEED) building guideline of 108 ppb for 60% of the participant-days. We identified 94 HEEs across all participant-days, and 67% of the corresponding peak levels exceeded 1000 ppb. The MEs ranked from the highest to the lowest number of HEEs were: Home-In (60), Other-In (13), In-Vehicle (12), and Out (9). For Other-In and Out, most HEEs occurred indoors at fast food restaurants and retail stores, and outdoors in parking lots, respectively. For Home-In HEEs, the median TVOC emission and removal rates were 5.4 g h-1 and 1.1 h-1, respectively. Our study demonstrates the ability to determine individual sensor-based time-resolved TVOC exposures in different MEs, in support of identifying potential sources and exposure factors that can inform exposure mitigation strategies.

Mechanistic transmission modeling of COVID-19 on the Diamond Princess cruise ship demonstrates the importance of aerosol transmission.

Several lines of existing evidence support the possibility of airborne transmission of coronavirus disease 2019 (COVID-19). However, quantitative information on the relative importance of transmission pathways of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) remains limited. To evaluate the relative importance of multiple transmission routes for SARS-CoV-2, we developed a modeling framework and leveraged detailed information available from the Diamond Princess cruise ship outbreak that occurred in early 2020. We modeled 21,600 scenarios to generate a matrix of solutions across a full range of assumptions for eight unknown or uncertain epidemic and mechanistic transmission factors. A total of 132 model iterations met acceptability criteria (R2 > 0.95 for modeled vs. reported cumulative daily cases and R2 > 0 for daily cases). Analyzing only these successful model iterations quantifies the likely contributions of each defined mode of transmission. Mean estimates of the contributions of short-range, long-range, and fomite transmission modes to infected cases across the entire simulation period were 35%, 35%, and 30%, respectively. Mean estimates of the contributions of larger respiratory droplets and smaller respiratory aerosols were 41% and 59%, respectively. Our results demonstrate that aerosol inhalation was likely the dominant contributor to COVID-19 transmission among the passengers, even considering a conservative assumption of high ventilation rates and no air recirculation conditions for the cruise ship. Moreover, close-range and long-range transmission likely contributed similarly to disease progression aboard the ship, with fomite transmission playing a smaller role. The passenger quarantine also affected the importance of each mode, demonstrating the impacts of the interventions.

Predicting U.S. Residential Building Energy Use and Indoor Pollutant Exposures in the Mid-21st Century.

The extent to which climate change and other factors will influence building energy use and population exposures to indoor pollutants is not well understood. Here, we develop and apply nationally representative residential energy and indoor pollutant model sets to estimate energy use, indoor pollutant concentrations, and associated chronic health outcomes across the U.S. residential building stock in the mid-21st century. The models incorporate expected changes in meteorological and ambient air quality conditions associated with IPCC RCP 8.5 and assumptions for changes in housing characteristics and population movements while keeping other less predictable factors constant. Site and source energy consumption for residential space-conditioning are predicted to decrease by ∼37-43 and ∼20-31%, respectively, in the 2050s compared to those in a 2010s reference scenario. Population-average indoor concentrations of pollutants of ambient origin are expected to decrease, except for O3. Holding indoor emission factors constant, indoor concentrations of pollutants with intermittent indoor sources are expected to decrease by <5% (PM2.5) to >30% (NO2); indoor concentrations of pollutants with persistent indoor sources (e.g., volatile organic compounds (VOCs)) are predicted to increase by ∼15-45%. We estimate negligible changes in disability-adjusted life-years (DALYs) lost associated with residential indoor pollutant exposures, well within uncertainty, although the attribution among pollutants is predicted to vary.

Adequate indoor air quality in nursing homes: An unmet medical need.

A small but growing body of literature indicates that concentrations of indoor particulate and gaseous pollutants in long-term care facilities (i.e., skilled nursing facilities) for older adults, hereafter referred to nursing homes, often exceed those recorded in nearby, comparable outdoor environments. Unlike the outdoors, indoor air quality (IAQ) in nursing homes is not regulated by legislation and is seldom monitored. To that end, residents of nursing homes commonly spend the vast majority of their time indoors where they are exposed to indoor air pollutants for long periods of time. Given that many nursing home residents, especially those of advanced age, are more susceptible to the effects of air pollutants, even at low concentrations, this prolonged exposure may adversely affect their health, well-being, quality of life and increase medical expenditures due to frequent, unscheduled acute care visits and hospitalizations. We propose an action plan for assessing IAQ in nursing homes, understanding the impacts of IAQ on adverse health outcomes of nursing home residents, and addressing vulnerabilities in these facilities to safeguard health, well-being, and quality of life of nursing home residents and minimizing unscheduled acute care visits and hospitalizations. We propose that IAQ should be regularly monitored in nursing homes to proactively identify and address vulnerabilities in these facilities and that resources should be provided for remedial interventions to improve IAQ in nursing homes, including but not limited to source control, improving ventilation and filtration, and deploying air cleaners where appropriate. This proactive approach may pave the way for establishing enforceable standards for indoor air quality in nursing homes that will promote health, well-being, and quality of life of nursing home residents and reduce medical expenditures.

Predicting intraurban PM2.5 concentrations using enhanced machine learning approaches and incorporating human activity patterns.

Urban areas contribute substantially to human exposure to ambient air pollution. Numerous statistical prediction models have been used to estimate ambient concentrations of fine particulate matter (PM2.5) and other pollutants in urban environments, with some incorporating machine learning (ML) algorithms to improve predictive power. However, many ML approaches for predicting ambient pollutant concentrations to date have used principal component analysis (PCA) with traditional regression algorithms to explore linear correlations between variables and to reduce the dimensionality of the data. Moreover, while most urban air quality prediction models have traditionally incorporated explanatory variables such as meteorological, land use, transportation/mobility, and/or co-pollutant factors, recent research has shown that local emissions from building infrastructure may also be useful factors to consider in estimating urban pollutant concentrations. Here we propose an enhanced ML approach for predicting urban ambient PM2.5 concentrations that hybridizes cascade and PCA methods to reduce the dimensionality of the data-space and explore nonlinear effects between variables. We test the approach using different durations of time series air quality datasets of hourly PM2.5 concentrations from three air quality monitoring sites in different urban neighborhoods in Chicago, IL to explore the influence of dynamic human-related factors, including mobility (i.e., traffic) and building occupancy patterns, on model performance. We test 9 state-of-the-art ML algorithms to find the most effective algorithm for modeling intraurban PM2.5 variations and we explore the relative importance of all sets of factors on intraurban air quality model performance. Results demonstrate that Gaussian-kernel support vector regression (SVR) was the most effective ML algorithm tested, improving accuracy by 118% compared to a traditional multiple linear regression (MLR) approach. Incorporating the enhanced approach with SVR algorithm increased model performance up to 18.4% for yearlong and 98.7% for month-long hourly datasets, respectively. Incorporating assumptions for human occupancy patterns in dominant building typologies resulted in improvements in model performance by between 4% and 37%. Combined, these innovations can be used to improve the performance and accuracy of urban air quality prediction models compared to conventional approaches.

Quantitative profiling of built environment bacterial and fungal communities reveals dynamic material dependent growth patterns and microbial interactions.

Indoor microbial communities vary in composition and diversity depending on material type, moisture levels, and occupancy. In this study, we integrated bacterial cell counting, fungal biomass estimation, and fluorescence-assisted cell sorting (FACS) with amplicon sequencing of bacterial (16S rRNA) and fungal (ITS) communities to investigate the influence of wetting on medium density fiberboard (MDF) and gypsum wallboard. Surface samples were collected longitudinally from wetted materials maintained at high relative humidity (~95%). Bacterial and fungal growth patterns were strongly time-dependent and material-specific. Fungal growth phenotypes differed between materials: spores dominated MDF surfaces while fungi transitioned from spores to hyphae on gypsum. FACS confirmed that most of the bacterial cells were intact (viable) on both materials over the course of the study. Integrated cell count and biomass data (quantitative profiling) revealed that small changes in relative abundance often resulted from large changes in absolute abundance, while negative correlations in relative abundances were explained by rapid growth of only one group of bacteria or fungi. Comparisons of bacterial-bacterial and fungal-bacterial networks suggested a top-down control of fungi on bacterial growth, possibly via antibiotic production. In conclusion, quantitative profiling provides novel insights into microbial growth dynamics on building materials with potential implications for human health.

Chemical composition of material extractives influences microbial growth and dynamics on wetted wood materials.

The impact of material chemical composition on microbial growth on building materials remains relatively poorly understood. We investigate the influence of the chemical composition of material extractives on microbial growth and community dynamics on 30 different wood species that were naturally inoculated, wetted, and held at high humidity for several weeks. Microbial growth was assessed by visual assessment and molecular sequencing. Unwetted material powders and microbial swab samples were analyzed using reverse phase liquid chromatography with tandem mass spectrometry. Different wood species demonstrated varying susceptibility to microbial growth after 3 weeks and visible coverage and fungal qPCR concentrations were correlated (R2 = 0.55). Aspergillaceae was most abundant across all samples; Meruliaceae was more prevalent on 8 materials with the highest visible microbial growth. A larger and more diverse set of compounds was detected from the wood shavings compared to the microbial swabs, indicating a complex and heterogeneous chemical composition within wood types. Several individual compounds putatively identified in wood samples showed statistically significant, near-monotonic associations with microbial growth, including C11H16O4, C18H34O4, and C6H15NO. A pilot experiment confirmed the inhibitory effects of dosing a sample of wood materials with varying concentrations of liquid C6H15NO (assuming it presented as Diethylethanolamine).

Are Clinicians Contributing to Excess African American COVID-19 Deaths? Unbeknownst to Them, They May Be.

African Americans are overrepresented among reported coronavirus disease 2019 (COVID-19) cases and deaths. There are a multitude of factors that may explain the African American disparity in COVID-19 outcomes, including higher rates of comorbidities. While individual-level factors predictably contribute to disparate COVID-19 outcomes, systematic and structural factors have not yet been reported. It stands to reason that implicit biases may fuel the racial disparity in COVID-19 outcomes. To address this racial disparity, we must apply a health equity lens and disaggregate data explicitly for African Americans, as well as other populations at risk for biased treatment in the health-care system.

A framework for estimating the US mortality burden of fine particulate matter exposure attributable to indoor and outdoor microenvironments.

Exposure to fine particulate matter (PM2.5) is associated with increased mortality. Although epidemiology studies typically use outdoor PM2.5 concentrations as surrogates for exposure, the majority of PM2.5 exposure in the US occurs in microenvironments other than outdoors. We develop a framework for estimating the total US mortality burden attributable to exposure to PM2.5 of both indoor and outdoor origin in the primary non-smoking microenvironments in which people spend most of their time. The framework utilizes an exposure-response function combined with adjusted mortality effect estimates that account for underlying exposures to PM2.5 of outdoor origin that likely occurred in the original epidemiology populations from which effect estimates are derived. We demonstrate the framework using several different scenarios to estimate the potential magnitude and bounds of the US mortality burden attributable to total PM2.5 exposure across all non-smoking environments under a variety of assumptions. Our best estimates of the US mortality burden associated with total PM2.5 exposure in the year 2012 range from ~230,000 to ~300,000 deaths. Indoor exposure to PM2.5 of outdoor origin is typically the largest total exposure, accounting for ~40-60% of total mortality, followed by residential exposure to indoor PM2.5 sources, which also drives the majority of variability in each scenario.

Elemental: An Open-Source Wireless Hardware and Software Platform for Building Energy and Indoor Environmental Monitoring and Control.

This work demonstrates an open-source hardware and software platform for monitoring the performance of buildings, called Elemental, that is designed to provide data on indoor environmental quality, energy usage, HVAC operation, and other factors to its users. It combines: (i) custom printed circuit boards (PCBs) with RFM69 frequency shift keying (FSK) radio frequency (RF) transceivers for wireless sensors, control nodes, and USB gateway, (ii) a Raspberry Pi 3B with custom firmware acting as either a centralized or distributed backhaul, and (iii) a custom dockerized application for the backend called Brood that serves as the director software managing message brokering via Message Queuing Telemetry Transport (MQTT) protocol using VerneMQ, database storage using InfluxDB, and data visualization using Grafana. The platform is built around the idea of a private, secure, and open technology for the built environment. Among its many applications, the platform allows occupants to investigate anomalies in energy usage, environmental quality, and thermal performance via a comprehensive dashboard with rich querying capabilities. It also includes multiple frontends to view and analyze building activity data, which can be used directly in building controls or to provide recommendations on how to increase operational efficiency or improve operating conditions. Here, we demonstrate three distinct applications of the Elemental platform, including: (1) deployment in a research lab for long-term data collection and automated analysis, (2) use as a full-home energy and environmental monitoring solution, and (3) fault and anomaly detection and diagnostics of individual building systems at the zone-level. Through these applications we demonstrate that the platform allows easy and virtually unlimited datalogging, monitoring, and analysis of real-time sensor data with low setup costs. Low-power sensor nodes placed in abundance in a building can also provide precise and immediate fault-detection, allowing for tuning equipment for more efficient operation and faster maintenance during the lifetime of the building.

Measuring the Building Envelope Penetration Factor for Ambient Nitrogen Oxides.

Much of human exposure to nitrogen oxides (NOx) of ambient origin occurs indoors. Reactions with materials inside building envelopes are expected to influence the amount of ambient NOx that infiltrates indoors. However, envelope penetration factors for ambient NOx constituents have never been measured. Here, we develop and apply methods to measure the penetration factor and indoor loss rates for ambient NOx constituents using time-resolved measurements in an unoccupied apartment unit. Multiple test methods and parameter estimation approaches were tested, including natural and artificial indoor NOx elevation with and without accounting for indoor oxidation reactions. Twelve of 16 tests yielded successful estimates of penetration factors and indoor loss rates. The penetration factor for NO was confirmed to be ∼1 and the mean (±s.d.) NO2 penetration factor was 0.72 ± 0.06 with a mean relative uncertainty of ∼15%. The mean (±s.d.) indoor NO2 loss rate was 0.27 ± 0.12 h-1, ranging 0.06-0.47 h-1, with strong correlations with indoor relative and absolute humidity. Indoor NO loss rates were strongly correlated with the estimated ozone concentration in infiltrating air. Results suggest that envelope penetration factors and loss rates for NOx constituents can be reasonably estimated across a wide range of conditions using these approaches.

Fine and ultrafine particle removal efficiency of new residential HVAC filters.

Particle air filters used in central residential forced-air systems are most commonly evaluated for their size-resolved removal efficiency for particles 0.3-10 µm using laboratory tests. Little information exists on the removal efficiency of commercially available residential filters for particles smaller than 0.3 µm or for integral measures of mass-based aerosol concentrations (eg, PM2.5 ) or total number concentrations (eg, ultrafine particles, or UFPs) that are commonly used in regulatory monitoring and building measurements. Here, we measure the size-resolved removal efficiency of 50 new commercially available residential HVAC filters installed in a recirculating central air-handling unit in an unoccupied apartment unit using alternating upstream/downstream measurements with incense and NaCl as particle sources. Size-resolved removal efficiencies are then used to estimate integral measures of PM2.5 and total UFP removal efficiency for the filters assuming they are challenged by 201 residential indoor particle size distributions (PSDs) gathered from the literature. Total UFP and PM2.5 removal efficiencies generally increased with manufacturer-reported filter ratings and with filter thickness, albeit with numerous exceptions. PM2.5 removal efficiencies were more influenced by the assumption for indoor PSD than total UFP removal efficiencies. Filters with the same ratings but from different manufacturers often had different removal efficiencies for PM2.5 and total UFPs.

Emerging investigator series: primary emissions, ozone reactivity, and byproduct emissions from building insulation materials.

Building insulation materials can affect indoor air by (i) releasing primary volatile organic compounds (VOCs) from building enclosure cavities to the interior space, (ii) mitigating exposure to outdoor pollutants through reactive deposition (of oxidants, e.g., ozone) or filtration (of particles) in infiltration air, and (iii) generating secondary VOCs and other gas-phase byproducts resulting from oxidant reactions. This study reports primary VOC emission fluxes, ozone (O3) reaction probabilities (γ), and O3 reaction byproduct yields for eight common, commercially available insulation materials. Fluxes of primary VOCs from the materials, measured in a continuous flow reactor using proton transfer reaction-time of flight-mass spectrometry, ranged from 3 (polystyrene with thermal backing) to 61 (cellulose) µmol m-2 h-1 (with total VOC mass emission rates estimated to be between ∼0.3 and ∼3.3 mg m-2 h-1). Major primary VOC fluxes from cellulose were tentatively identified as compounds likely associated with cellulose chemical and thermal decomposition products. Ozone-material γ ranged from ∼1 × 10-6 to ∼30 × 10-6. Polystyrene with thermal backing and polyisocyanurate had the lowest γ, while cellulose and fiberglass had the highest. In the presence of O3, total observed volatile byproduct yields ranged from 0.25 (polystyrene) to 0.85 (recycled denim) moles of VOCs produced per mole of O3 consumed, or equivalent to secondary fluxes that range from 0.71 (polystyrene) to 10 (recycled denim) µmol m-2 h-1. Major emitted products in the presence of O3 were generally different from primary emissions and were characterized by yields of aldehydes and acetone. This work provides new data that can be used to evaluate and eventually model the impact of "hidden" materials (i.e., those present inside wall cavities) on indoor air quality. The data may also guide building enclosure material selection, especially for buildings in areas of high outdoor O3.

Microbial and metabolic succession on common building materials under high humidity conditions.

Despite considerable efforts to characterize the microbial ecology of the built environment, the metabolic mechanisms underpinning microbial colonization and successional dynamics remain unclear, particularly at high moisture conditions. Here, we applied bacterial/viral particle counting, qPCR, amplicon sequencing of the genes encoding 16S and ITS rRNA, and metabolomics to longitudinally characterize the ecological dynamics of four common building materials maintained at high humidity. We varied the natural inoculum provided to each material and wet half of the samples to simulate a potable water leak. Wetted materials had higher growth rates and lower alpha diversity compared to non-wetted materials, and wetting described the majority of the variance in bacterial, fungal, and metabolite structure. Inoculation location was weakly associated with bacterial and fungal beta diversity. Material type influenced bacterial and viral particle abundance and bacterial and metabolic (but not fungal) diversity. Metabolites indicative of microbial activity were identified, and they too differed by material.

Microbial Exchange via Fomites and Implications for Human Health.

PURPOSE OF REVIEW: Fomites are inanimate objects that become colonized with microbes and serve as potential intermediaries for transmission to/from humans. This review summarizes recent literature on fomite contamination and microbial survival in the built environment, transmission between fomites and humans, and implications for human health. RECENT FINDINGS: Applications of molecular sequencing techniques to analyze microbial samples have increased our understanding of the microbial diversity that exists in the built environment. This growing body of research has established that microbial communities on surfaces include substantial diversity, with considerable dynamics. While many microbial taxa likely die or lay dormant, some organisms survive, including those that are potentially beneficial, benign, or pathogenic. Surface characteristics also influence microbial survival and rates of transfer to and from humans. Recent research has combined experimental data, mechanistic modeling, and epidemiological approaches to shed light on the likely contributors to microbial exchange between fomites and humans and their contributions to adverse (and even potentially beneficial) human health outcomes. SUMMARY: In addition to concerns for fomite transmission of potential pathogens, new analytical tools have uncovered other microbial matters that can be transmitted indirectly via fomites, including entire microbial communities and antibiotic-resistant bacteria. Mathematical models and epidemiological approaches can provide insight on human health implications. However, both are subject to limitations associated with study design, and there is a need to better understand appropriate input model parameters. Fomites remain an important mechanism of transmission of many microbes, along with direct contact and short- and long-range aerosols.

Microbiology of the built environment.

The built environment comprises all structures built by humans, including our homes, workplaces, schools and vehicles. As in any ecosystem on Earth, microorganisms have been found in every part of the built environment that has been studied. They exist in the air, on surfaces and on building materials, usually dispersed by humans, animals and outdoor sources. Those microbial communities and their metabolites have been implied to cause (or exacerbate) and prevent (or mitigate) human disease. In this Review, we outline the history of the field of microbiology of the built environment and discuss recent insights that have been gained into microbial ecology, adaptation and evolution of this ecosystem. Finally, we consider the implications of this research, specifically, how it is changing the types of materials we use in buildings and how our built environments affect human health.

Environmental Sources of Bacteria Differentially Influence Host-Associated Microbial Dynamics.

Host-associated microbial dynamics are influenced by dietary and immune factors, but how exogenous microbial exposure shapes host-microbe dynamics remains poorly characterized. To investigate this phenomenon, we characterized the skin, rectum, and respiratory tract-associated microbiota in four aquarium-housed dolphins daily over a period of 6 weeks, including administration of a probiotic during weeks 4 to 6. The environmental bacterial sources were also characterized, including the animals' human handlers, the aquarium air and water, and the dolphins' food supply. Continuous microbial exposure occurred between all sites, yet each environment maintained a characteristic microbiota, suggesting that the majority of exposure events do not result in colonization. Small changes in water physicochemistry had a significant but weak correlation with change in dolphin-associated bacterial richness but had no influence on phylogenetic diversity. Food and air microbiota were the richest and had the largest conditional influence on other microbiota in the absence of probiotics, but during probiotic administration, food alone had the largest influence on the stability of the dolphin microbiota. Our results suggest that respiratory tract and gastrointestinal epithelium interactions with air- and food-associated microbes had the biggest influence on host-microbiota dynamics, while other interactions, such as skin transmission, played only a minor role. Finally, direct oral stimulation with a foreign exogenous microbial source can have a profound effect on microbial stability. IMPORTANCE These results provide valuable insights into the ecological influence of exogenous microbial exposure, as well as laying the foundation for improving aquarium management practices. By comparing data for dolphins from aquaria that use natural versus artificial seawater, we demonstrate the potential influence of aquarium water disinfection procedures on dolphin microbial dynamics.

Bacterial colonization and succession in a newly opened hospital.

The microorganisms that inhabit hospitals may influence patient recovery and outcome, although the complexity and diversity of these bacterial communities can confound our ability to focus on potential pathogens in isolation. To develop a community-level understanding of how microorganisms colonize and move through the hospital environment, we characterized the bacterial dynamics among hospital surfaces, patients, and staff over the course of 1 year as a new hospital became operational. The bacteria in patient rooms, particularly on bedrails, consistently resembled the skin microbiota of the patient occupying the room. Bacterial communities on patients and room surfaces became increasingly similar over the course of a patient's stay. Temporal correlations in community structure demonstrated that patients initially acquired room-associated taxa that predated their stay but that their own microbial signatures began to influence the room community structure over time. The α- and ß-diversity of patient skin samples were only weakly or nonsignificantly associated with clinical factors such as chemotherapy, antibiotic usage, and surgical recovery, and no factor except for ambulatory status affected microbial similarity between the microbiotas of a patient and their room. Metagenomic analyses revealed that genes conferring antimicrobial resistance were consistently more abundant on room surfaces than on the skin of the patients inhabiting those rooms. In addition, persistent unique genotypes of Staphylococcus and Propionibacterium were identified. Dynamic Bayesian network analysis suggested that hospital staff were more likely to be a source of bacteria on the skin of patients than the reverse but that there were no universal patterns of transmission across patient rooms.