Quantifying proximity, confinement, and interventions in disease outbreaks: a decision support framework for air-transported pathogens

Includes bibliographical references (pages H-I).The inability to communicate how infectious diseases are transmitted in human environments has triggered avoidance of interactions during the COVID-19 pandemic. We define a metric, Effective ReBreathed Volume (ERBV), that encapsulates how infectious pathogens, including SARS-CoV-2, transport in air. ERBV separates environmental transport from other factors in the chain of infection, allowing quantitative comparisons among situations. Particle size affects transport, removal onto surfaces, and elimination by mitigation measures, so ERBV is presented for a range of exhaled particle diameters: 1, 10, and 100 μm. Pathogen transport depends on both proximity and confinement. If interpersonal distancing of 2 m is maintained, then confinement, not proximity, dominates rebreathing after 10–15 min in enclosed spaces for all but 100 μm particles. We analyze strategies to reduce this confinement effect. Ventilation and filtration reduce person-to-person transport of 1 μm particles (ERBV1) by 13–85% in residential and office situations. Deposition to surfaces competes with intentional removal for 10 and 100 μm particles, so the same interventions reduce ERBV10 by only 3–50%, and ERBV100 is unaffected. Prior knowledge of size-dependent ERBV would help identify transmission modes and effective interventions. This framework supports mitigation decisions in emerging situations, even before other infectious parameters are known

Cookstove startup material characterization and quantification and acute cardiopulmonary effects from controlled exposure to cookstove air pollution

2018 Fall.Includes bibliographical references.To view the abstract, please see the full text of the document

Applying a Weight-of-Evidence Approach to Evaluate Relevance of Molecular Landscapes in the Exposure-Disease Paradigm

Information on polymorphisms, mutations, and epigenetic events has become increasingly important in our understanding of molecular mechanisms associated with exposures-disease outcomes. Molecular landscapes can be developed to illustrate the molecular characteristics for environmental carcinogens as well as associated disease outcomes, although comparison of these molecular landscapes can often be difficult to navigate. We developed a method to organize these molecular data that uses a weight-of-evidence approach to rank overlapping molecular events by relative importance for susceptibility to an exposure-disease paradigm. To illustrate the usefulness of this approach, we discuss the example of benzene as an environmental carcinogen and myelodysplastic syndrome (MDS) as a causative disease endpoint. Using this weight-of-evidence method, we found overlapping polymorphisms in the genes for the metabolic enzymes GST and NQO1, both of which may infer risk of benzene-induced MDS. Polymorphisms in the tumor suppressor gene, TP53, and the inflammatory cytokine gene, TNF-α, were also noted, albeit inferring opposing outcomes. The alleles identified in the DNA repair gene RAD51 indicated an increased risk for MDS in MDS patients and low blood cell counts in benzene-exposed workers. We propose the weight-of-evidence approach as a tool to assist in organizing the sea of emerging molecular data in exposure-disease paradigms

Applying a Weight-of-Evidence Approach to Evaluate Relevance of Molecular Landscapes in the Exposure-Disease Paradigm

Information on polymorphisms, mutations, and epigenetic events has become increasingly important in our understanding of molecular mechanisms associated with exposures-disease outcomes. Molecular landscapes can be developed to illustrate the molecular characteristics for environmental carcinogens as well as associated disease outcomes, although comparison of these molecular landscapes can often be difficult to navigate. We developed a method to organize these molecular data that uses a weight-of-evidence approach to rank overlapping molecular events by relative importance for susceptibility to an exposure-disease paradigm. To illustrate the usefulness of this approach, we discuss the example of benzene as an environmental carcinogen and myelodysplastic syndrome (MDS) as a causative disease endpoint. Using this weight-of-evidence method, we found overlapping polymorphisms in the genes for the metabolic enzymes GST and NQO1, both of which may infer risk of benzene-induced MDS. Polymorphisms in the tumor suppressor gene, TP53, and the inflammatory cytokine gene, TNF-, were also noted, albeit inferring opposing outcomes. The alleles identified in the DNA repair gene RAD51 indicated an increased risk for MDS in MDS patients and low blood cell counts in benzene-exposed workers. We propose the weight-of-evidence approach as a tool to assist in organizing the sea of emerging molecular data in exposure-disease paradigms

The Fort Collins Commuter Study: Impact of Route Type and Transport Mode on Personal Exposure to Multiple Air Pollutants

Traffic-related air pollution is associated with increased mortality and morbidity, yet few studies have examined strategies to reduce individual exposure while commuting. The present study aimed to quantify how choice of mode and route type affects personal exposure to air pollutants during commuting. We analyzed within-person difference in exposures to multiple air pollutants (black carbon (BC), carbon monoxide (CO), ultrafine particle number concentration (PNC), and fine particulate matter (PM2.5)) during commutes between the home and workplace for 45 participants. Participants completed 8 days of commuting by car and bicycle on direct and alternative (reduced traffic) routes. Mean within-person exposures to BC, PM2.5, and PNC were higher when commuting by cycling than when driving, but mean CO exposure was lower when cycling. Exposures to CO and BC were reduced when commuting along alternative routes. When cumulative exposure was considered, the benefits from cycling were attenuated, in the case of CO, or exacerbated, in the case of particulate exposures, owing to the increased duration of the commute. Although choice of route can reduce mean exposure, the effect of route length and duration often offsets these reductions when cumulative exposure is considered. Furthermore, increased ventilation rate when cycling may result in a more harmful dose than inhalation at a lower ventilation rate

Chemical Composition and Emissions Factors for Cookstove Startup (Ignition) Materials

Air pollution from cookstoves creates a substantial human and environmental health burden. A disproportionate fraction of emissions can occur during stove ignition (startup) compared to main cooking, yet startup material emissions are poorly quantified. Laboratory tests were conducted to measure emissions from startups using kerosene, plastic bags, newspaper, fabric, food packaging, rubber tire tubes, kindling, footwear, and wood shims. Measured pollutants included: fine particulate matter mass (PM_2.5), PM_2.5 elemental and organic carbon, methane, carbon monoxide, carbon dioxide, benzene, and formaldehyde. Results demonstrate substantial variability in the measured emissions across materials on a per-startup basis. For example, kerosene emitted 496 mg PM_2.5 and 999 mg CO per startup, whereas plastic bags emitted 2 mg PM_2.5 and 30 mg CO. When considering emissions on a per-mass basis, the ordering of materials from highest-to-lowest emissions changes, emphasizing the importance of establishing how much material is needed to start a stove. The proportional contribution of startups to overall emissions varies depending on startup material type, stove type, and cooking event length; however, results demonstrate that startup materials can contribute substantially to a cookstove’s emissions. Startup material choice is especially important for cleaner stove-fuel combinations where the marginal benefits of reduced emissions are potentially greater