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.

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.

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.

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.

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.

Surgical management of periprosthetic shoulder infections.

BACKGROUND: The treatment of periprosthetic joint infection is a difficult challenge in shoulder arthroplasty. This study investigated 1-stage modular component exchange vs. 1-stage complete removal and reimplantation (CRR) vs. 2-stage revision arthroplasty for periprosthetic joint infection. METHODS: Between January 1, 2004, and December 31, 2012, 79 patients received a component exchange (n = 15), CRR (n = 45), or a 2-stage (n = 19) revision for infection. A binary logistic regression analysis was performed to determine factors presenting the greatest risk of reinfection. Complications and functional outcomes were also evaluated. RESULTS: Overall, 4 of 15 (27%) component exchanges, 2 of 45 (4%) CRRs, and 4 of 19 (21%) 2-stage procedures required a reoperation for infection with a minimum of 1 year of follow-up. The difference between the CRR group and exchange group was significant (P = .030); however, the difference between the CRR group and 2-stage group did not reach statistical significance (P = .059). No preoperative and intraoperative selection bias between the groups was found. Binary logistic regression predicted that reinfection was highest in patients whose cultures grew Staphylococcus aureus (P = .004) or coagulase-negative Staphylococcus species (P = .041) or those treated with a component exchange (P = .015). The difference between groups for noninfection-related complications was not significant (P = .703). All procedures provided improved functional outcomes and pain relief. CONCLUSION: Patients with infection caused by Staphylococcus aureus or coagulase-negative Staphylococcus species may require additional operations to treat the infection. Although effective in some cases, component exchange presents an increased risk for reinfection. A 1-stage CRR procedure had similar reinfection rates as a 2-stage procedure in our patient population.

Emissions of Ultrafine Particles and Volatile Organic Compounds from Commercially Available Desktop Three-Dimensional Printers with Multiple Filaments.

Previous research has shown that desktop 3D printers can emit large numbers of ultrafine particles (UFPs, particles less than 100 nm) and some hazardous volatile organic compounds (VOCs) during printing, although very few filament and 3D printer combinations have been tested to date. Here we quantify emissions of UFPs and speciated VOCs from five commercially available filament extrusion desktop 3D printers utilizing up to nine different filaments by controlled experiments in a test chamber. Median estimates of time-varying UFP emission rates ranged from ∼10(8) to ∼10(11) min(-1) across all tested combinations, varying primarily by filament material and, to a lesser extent, bed temperature. The individual VOCs emitted in the largest quantities included caprolactam from nylon-based and imitation wood and brick filaments (ranging from ∼2 to ∼180 µg/min), styrene from acrylonitrile butadiene styrene (ABS) and high-impact polystyrene (HIPS) filaments (ranging from ∼10 to ∼110 µg/min), and lactide from polylactic acid (PLA) filaments (ranging from ∼4 to ∼5 µg/min). Results from a screening analysis of potential exposure to these products in a typical small office environment suggest caution should be used when operating many of the printer and filament combinations in poorly ventilated spaces or without the aid of combined gas and particle filtration systems.

Revision for a failed reverse: a 12-year review of a lateralized implant.

BACKGROUND: The purpose of this study was (1) to evaluate the rates of reverse shoulder arthroplasty (RSA) revisions during a 12-year period, (2) to assess the influence of primary diagnosis and the impact of implant modifications on revisions, (3) to describe surgical management of failed RSA, and (4) to analyze outcomes of patients with minimum 24-month follow-up. METHODS: A retrospective database review identified primary diagnosis for 1418 patients who underwent RSA from 2000 to 2012. A subgroup of 85 patients required return to the operating room for removal or exchange of components. Indication to reoperate, intraoperative management, and outcomes were reviewed. Indications were grouped into 7 categories: baseplate failure, humeral component dissociation, glenosphere dissociation, glenohumeral dislocation, aseptic humeral loosening, periprosthetic fracture, and infection. During the study, design modifications were made to the baseplate, humeral socket, and glenosphere. Surgical strategies were analyzed through operative reports. Range of motion, American Shoulder and Elbow Surgeons scores, and Simple Shoulder Test scores were collected before and after surgery and compared for 58 patients with 2-year follow-up. RESULTS: Overall revision rate was 6%. Patients undergoing RSA for failed hemiarthroplasty had the highest revision rate (10%). Indications for revision included baseplate failure (2.5%), infection (1.3%), humeral dissociation (0.7%), glenosphere dissociation (0.6%), periprosthetic fracture (0.4%), glenohumeral dislocation (0.4%), and aseptic humeral loosening (0.3%). Baseplate modifications reduced the incidence of baseplate failure to 0.3%. Range of motion and the Simple Shoulder Test and American Shoulder and Elbow Surgeons scores improved. CONCLUSION: Although revision RSA is challenging, with higher risk for complications compared with primary RSA, patients still exhibit significant clinical improvements.

Indoor air pollution in developing countries: research and implementation needs for improvements in global public health.

Exposure to indoor air pollution (IAP) from the burning of solid fuels for cooking, heating, and lighting accounts for a significant portion of the global burden of death and disease, and disproportionately affects women and children in developing regions. Clean cookstove campaigns recently received more attention and investment, but their successes might hinge on greater integration of the public health community with a variety of other disciplines. To help guide public health research in alleviating this important global environmental health burden, we synthesized previous research on IAP in developing countries, summarized successes and challenges of previous cookstove implementation programs, and provided key research and implementation needs from structured discussions at a recent symposium.

HVAC filtration for controlling infectious airborne disease transmission in indoor environments: Predicting risk reductions and operational costs.

This work describes and applies a methodology for estimating the impact of recirculating heating, ventilating, and air-conditioning (HVAC) particle filters on the control of size-resolved infectious aerosols in indoor environments using a modified version of the Wells-Riley model for predicting risks of infectious disease transmission. Estimates of risk reductions and associated operational costs of both HVAC filtration and equivalent outdoor air ventilation are modeled and compared using a case study of airborne transmission of influenza in a hypothetical office space. Overall, recirculating HVAC filtration was predicted to achieve risk reductions at lower costs of operation than equivalent levels of outdoor air ventilation, particularly for MERV 13-16 filters. Medium efficiency filtration products (MERV 7-11) are also inexpensive to operate but appear less effective in reducing infectious disease risks.

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.

Measuring the penetration of ambient ozone into residential buildings.

Much of human exposure to ambient ozone and ozone reaction byproducts occurs inside buildings. However, there are currently no experimental data on the ability of ozone to penetrate through building envelopes and into residences. This paper presents a method to determine the penetration factor for ozone in buildings, and applies it in an unoccupied test house and seven single-family residences. The mean (±SD) ozone penetration factor was measured as 0.79 ± 0.13 in the eight homes using this method, ranging from 0.62 ± 0.09 to 1.02 ± 0.15. An analysis of tests across the homes revealed that ozone penetration was significantly higher in homes with more painted wood envelope materials, homes with larger air leakage exponents from fan pressurization tests, and older homes. The test method utilizes a large calibrated fan to elevate air exchange rates and steady-state indoor ozone concentrations to levels that can be accurately measured, so there is a potential for overpredicting ozone penetration factors. However, evidence suggests that this bias is likely small in most of the homes, and, even if a bias exists, the measured ozone penetration factors were lower than the usual assumption of unity in seven of the eight tested homes.

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.

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.

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.

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).