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Rotavirus (RV) vaccines have demonstrated substantial effectiveness in reducing the healthcare burden caused by gastroenteritis (RVGE) worldwide. This study aims to understand the differential impact of RV vaccination in reducing RVGE burden in children under 7 years old in China. A Markov Model was used to investigate the health impact of introducing two different RV vaccines into the Chinese population. The analysis was conducted for RV5, a live pentavalent human-bovine reassortant vaccine, and Lanzhou Lamb RV (LLR), a live-attenuated monovalent RV vaccine, separately, by comparing the strategy of each vaccine to no vaccination within a Chinese birth cohort, including 100,000 children modeled until 7 years of age. The vaccination scenario assumed a vaccination coverage of 2.5%, 2.5%, 90% and 5% for doses one, two, three and no vaccine, respectively, for both vaccines. Strategies with RV5, LLR, and no vaccination were associated with 9,895, 49,069, and 64,746 symptomatic RV infections, respectively. RV5 and LLR were associated with an 85% and 24% reduction in the total symptomatic RV infections, respectively, suggesting that the health benefits of RV5 are at least three-fold greater than those associated with the LLR. Further, strategies with RV5 and LLR resulted in an estimated 206 and 59-year increase in quality-adjusted life years (QALYs), respectively. Sensitivity and scenario analyses supported the robustness of the base-case findings. Use of RV vaccine is expected to improve RV-associated health outcomes and its adoption will help alleviate the burden of RVGE in China. RV5 use will result in significantly better health outcomes.

BackgroundTropospheric ozone and black carbon (BC), a component of fine particulate matter (PM ≤ 2.5 µm in aerodynamic diameter; PM(2.5)), are associated with premature mortality and they disrupt global and regional climate.ObjectivesWe examined the air quality and health benefits of 14 specific emission control measures targeting BC and methane, an ozone precursor, that were selected because of their potential to reduce the rate of climate change over the next 20-40 years.MethodsWe simulated the impacts of mitigation measures on outdoor concentrations of PM(2.5) and ozone using two composition-climate models, and calculated associated changes in premature PM(2.5)- and ozone-related deaths using epidemiologically derived concentration-response functions.ResultsWe estimated that, for PM(2.5) and ozone, respectively, fully implementing these measures could reduce global population-weighted average surface concentrations by 23-34% and 7-17% and avoid 0.6-4.4 and 0.04-0.52 million annual premature deaths globally in 2030. More than 80% of the health benefits are estimated to occur in Asia. We estimated that BC mitigation measures would achieve approximately 98% of the deaths that would be avoided if all BC and methane mitigation measures were implemented, due to reduced BC and associated reductions of nonmethane ozone precursor and organic carbon emissions as well as stronger mortality relationships for PM(2.5) relative to ozone. Although subject to large uncertainty, these estimates and conclusions are not strongly dependent on assumptions for the concentration-response function.ConclusionsIn addition to climate benefits, our findings indicate that the methane and BC emission control measures would have substantial co-benefits for air quality and public health worldwide, potentially reversing trends of increasing air pollution concentrations and mortality in Africa and South, West, and Central Asia. These projected benefits are independent of carbon dioxide mitigation measures. Benefits of BC measures are underestimated because we did not account for benefits from reduced indoor exposures and because outdoor exposure estimates were limited by model spatial resolution.

Abstract Vehicle electrification is a common climate change mitigation strategy, with policymakers invoking co‐beneficial reductions in carbon dioxide (CO2) and air pollutant emissions. However, while previous studies of U.S. electric vehicle (EV) adoption consistently predict CO2 mitigation benefits, air quality outcomes are equivocal and depend on policies assessed and experimental parameters. We analyze climate and health co‐benefits and trade‐offs of six U.S. EV adoption scenarios: 25% or 75% replacement of conventional internal combustion engine vehicles, each under three different EV‐charging energy generation scenarios. We transfer emissions from tailpipe to power generation plant, simulate interactions of atmospheric chemistry and meteorology using the GFDL‐AM4 chemistry climate model, and assess health consequences and uncertainties using the U.S. Environmental Protection Agency Benefits Mapping Analysis Program Community Edition (BenMAP‐CE). We find that 25% U.S. EV adoption, with added energy demand sourced from the present‐day electric grid, annually results in a ~242 M ton reduction in CO2 emissions, 437 deaths avoided due to PM2.5 reductions (95% CI: 295, 578), and 98 deaths avoided due to lesser ozone formation (95% CI: 33, 162). Despite some regions experiencing adverse health outcomes, ~$16.8B in damages avoided are predicted. Peak CO2 reductions and health benefits occur with 75% EV adoption and increased emission‐free energy sources (~$70B in damages avoided). When charging‐electricity from aggressive EV adoption is combustion‐only, adverse health outcomes increase substantially, highlighting the importance of low‐to‐zero emission power generation for greater realization of health co‐benefits. Our results provide a more nuanced understanding of the transportation sector's climate change mitigation‐health impact relationship.

Vehicle electrification is a common climate change mitigation strategy, with policymakers invoking co‐beneficial reductions in carbon dioxide (CO2) and air pollutant emissions. However, while previous studies of U.S. electric vehicle (EV) adoption consistently predict CO2 mitigation benefits, air quality outcomes are equivocal and depend on policies assessed and experimental parameters. We analyze climate and health co‐benefits and trade‐offs of six U.S. EV adoption scenarios: 25% or 75% replacement of conventional internal combustion engine vehicles, each under three different EV‐charging energy generation scenarios. We transfer emissions from tailpipe to power generation plant, simulate interactions of atmospheric chemistry and meteorology using the GFDL‐AM4 chemistry climate model, and assess health consequences and uncertainties using the U.S. Environmental Protection Agency Benefits Mapping Analysis Program Community Edition (BenMAP‐CE). We find that 25% U.S. EV adoption, with added energy demand sourced from the present‐day electric grid, annually results in a ~242 M ton reduction in CO2 emissions, 437 deaths avoided due to PM2.5 reductions (95% CI: 295, 578), and 98 deaths avoided due to lesser ozone formation (95% CI: 33, 162). Despite some regions experiencing adverse health outcomes, ~$16.8B in damages avoided are predicted. Peak CO2 reductions and health benefits occur with 75% EV adoption and increased emission‐free energy sources (~$70B in damages avoided). When charging‐electricity from aggressive EV adoption is combustion‐only, adverse health outcomes increase substantially, highlighting the importance of low‐to‐zero emission power generation for greater realization of health co‐benefits. Our results provide a more nuanced understanding of the transportation sector's climate change mitigation‐health impact relationship. Key Points: Electrifying vehicles consistently reduces carbon dioxide emissions; air quality benefits vary spatially and depend on charging energy mixTwenty‐five percent U.S. electric vehicle adoption with energy sourced from current electric grid prevents ~$17B in health and climate damages annuallyPeak co‐benefits occur with greater fractions of EV adoption and emission‐free energy sources [ABSTRACT FROM AUTHOR]

As much of the population lives in close proximity to high-traffic roads, there is the potential for health impact assessments based on regional air quality modeling to underpredict health impacts. We compare the estimated health impacts from fine particulate matter (PM2.5) using local (0.04 × 0.04 km upscaled to census block group resolution) compared to regional (12 × 12 km resolution) modeled concentrations for three locations in Connecticut: Hartford, New Haven, and Willimantic. We use concentration estimates from the Comprehensive Air Quality Model with Extensions (CAMx) regional model and a hybrid model combining CAMx with a near road model (HYCAMR) in the Environmental Benefits Mapping and Analysis Program—Community Edition (BenMAP-CE) to calculate the difference in estimated human health impacts using different resolution air quality estimates from PM2.5 exposure including mortality, emergency room visits, hospitalizations, and asthma exacerbation. This provides an estimate of the potential underprediction of health impacts resulting from not accounting for the sharp concentration gradients in near road environments in urban areas. The fine-scale estimates capture the elevated concentrations near the roadways leading to increased estimates of overall mortality and morbidity in the population. We find an increase in the estimated likelihood of emergency department visits and mortality in the urban core. We also compare the impact of model resolution on the health impact estimates for different demographic groups. Of the locations investigated, we see the largest differences between demographic groups in Willimantic, CT. Our results indicate that using regional air pollutant concentrations may lead to an underprediction of human health impacts from air pollution exposure. [ABSTRACT FROM AUTHOR]

Air quality health impact assessment (HIA) synthesizes information about air pollution exposures, health effects, and population vulnerability for regulatory decision-making and public engagement. HIAs often use annual average county or regional data to estimate health outcome incidence rates that vary substantially by season and at the subcounty level. Using New York City as an example, we assessed the sensitivity of estimated citywide morbidity and mortality attributable to ambient fine particulate matter (PM) and ozone to the geographic (county vs. neighborhood) and temporal (seasonal vs. annual average) resolution of health incidence data. We also used the neighborhood-level analysis to assess variation in estimated air pollution impacts by neighborhood poverty concentration. Estimated citywide health impacts attributable to PM and ozone were relatively insensitive to the geographic resolution of health incidence data. However, the neighborhood-level analysis demonstrated increasing impacts with greater neighborhood poverty levels, particularly for PM-attributable asthma emergency department visits, which were 4.5 times greater in high compared to low-poverty neighborhoods. PM-attributable health impacts were similar using seasonal and annual average incidence rates. Citywide ozone-attributable asthma morbidity was estimated to be 15 % lower when calculated from seasonal, compared to annual average incidence rates, as asthma morbidity rates are lower during the summer ozone season than the annual average rate. Within the ozone season, 57 % of estimated ozone-attributable emergency department for asthma in children occurred in the April-June period when average baseline incidence rates are higher than in the July-September period when ozone concentrations are higher. These analyses underscore the importance of utilizing spatially and temporally resolved data in local air quality impact assessments to characterize the overall city burden and identify areas of high vulnerability. [ABSTRACT FROM AUTHOR]

Background: The U.S. Environmental Protection Agency (U.S. EPA) has estimated the neurological benefits of reductions in prenatal methylmercury (MeHg) exposure in past assessments of rules controlling mercury (Hg) emissions. A growing body of evidence suggests that MeHg exposure can also lead to increased risks of adverse cardiovascular impacts in exposed populations. Data extraction: The U.S. EPA assembled the authors of this article to participate in a workshop, where we reviewed the current science concerning cardiovascular health effects of MeHg exposure via fish and seafood consumption and provided recommendations concerning whether cardiovascular health effects should be included in future Hg regulatory impact analyses. Data synthesis: We found the body of evidence exploring the link between MeHg and acute myocardial infarction (MI) to be sufficiently strong to support its inclusion in future benefits analyses, based both on direct epidemiological evidence of an MeHg-MI link and on MeHg's association with intermediary impacts that contribute to MI risk. Although additional research in this area would be beneficial to further clarify key characteristics of this relationship and the biological mechanisms that underlie it, we consider the current epidemiological literature sufficiently robust to support the development of a dose-response function. Conclusions: We recommend the development of a dose-function relating MeHg exposures with MIs for use in regulatory benefits analyses of future rules targeting Hg air emissions. [ABSTRACT FROM AUTHOR]

This paper presents a first attempt at the inclusion of some biological impacts and influences in the authors' continued research on coupled transport phenomena through unsaturated porous media. The work presented here forms an extension to an existing coupled Thermo-Hydraulic-Chemical-Mechanical Model (THCM) to include the biological aspects, as a first attempt towards a new THCMB framework. The biological model incorporates biodegradation kinetics of organic substrates and resultant effects in the inorganic geochemistry. In order to achieve this, the biological aspects of the model are coupled to an equilibrium geochemical model following a two-step partial equilibrium approach. Additionally, of concern in contaminant/pollutant transport studies, including the biological aspects, is the effect on human health. This paper therefore also presents some aspects of a health impact analysis model adopted in this study. [ABSTRACT FROM AUTHOR]

BACKGROUND: Ground-level concentrations of ozone (O3) and fine particulate matter [≤ 2.5 µm in aerodynamic diameter (PM2.5)] have increased since preindustrial times in urban and rural regions and are associated with cardiovascular and respiratory mortality. OBJECTIVES: We estimated the global burden of mortality due to O3 and PM2.5 from anthropogenic emissions using global atmospheric chemical transport model simulations of preindustrial and present-day (2000) concentrations to derive exposure estimates. METHODS: Attributable mortalities were estimated using health impact functions based on long-term relative risk estimates for O3 and PM2.5 from the epidemiology literature. Using simulated concentrations rather than previous methods based on measurements allows the inclusion of rural areas where measurements are often unavailable and avoids making assumptions for background air pollution. RESULTS: Anthropogenic O3 was associated with an estimated 0.7 ± 0.3 million respiratory mortalities (6.3 ± 3.0 million years of life lost) annually. Anthropogenic PM2.5 was associated with 3.5 ± 0.9 million cardiopulmonary and 220,000 ± 80,000 lung cancer mortalities (30 ± 7.6 million years of life lost) annually. Mortality estimates were reduced approximately 30% when we assumed low-concentration thresholds of 33.3. ppb for O3 and 5.8. µg/m3 for PM2.5. These estimates were sensitive to concentration thresholds and concentration.mortality relationships, often by > 50%. CONCLUSIONS: Anthropogenic O3 and PM2.5 contribute substantially to global premature mortality. PM2.5 mortality estimates are about 50% higher than previous measurement-based estimates based on common assumptions, mainly because of methodologic differences. Specifically, we included rural populations, suggesting higher estimates; however, the coarse resolution of the global atmospheric model may underestimate urban PM2.5 exposures. [ABSTRACT FROM AUTHOR]

Background: In the past 15 years, asthma prevalence has increased and is disproportionately distributed among children, minorities, and low-income persons. The National Institute of Environmental Health Sciences (NIEHS) Division of Extramural Research and Training developed a framework to measure the scientific and health impacts of its extramural asthma research to improve the scientific basis for reducing the health effects of asthma. Objectives: Here we apply the framework to characterize the NIEHS asthma portfolio's impact in terms of publications, clinical applications of findings, community interventions, and technology developments. Methods: A logic model was tailored to inputs, outputs, and outcomes of the NIEHS asthma portfolio. Data from existing National Institutes of Health (NIH) databases are used, along with publicly available bibliometric data and structured elicitation of expert judgment. Results: NIEHS is the third largest source of asthma-related research grant funding within the NIH between 1975 and 2005, after the National Heart, Lung, and Blood Institute and the National Institute of Allergy and Infectious Diseases. Much of NIEHS-funded asthma research focuses on basic research, but results are often published in journals focused on clinical investigation, increasing the likelihood that the work is moved into practice along the "bench to bedside" continuum. NIEHS support has led to key breakthroughs in scientific research concerning susceptibility to asthma, environmental conditions that heighten asthma symptoms, and cellular mechanisms that may be involved in treating asthma. Conclusions: If gaps and limitations in publicly available data receive adequate attention, further linkages can be demonstrated between research activities and public health improvements. This logic model approach to research impact assessment demonstrates that it is possible to conceptualize program components, mine existing databases, and begin to show longer-term impacts of program results. The next challenges will be to modify current data structures, improve the linkages among relevant databases, incorporate as much electronically available data as possible, and determine how to improve the quality and health impact of the science that we support. [ABSTRACT FROM AUTHOR]

Smoke from wildfires contains many air pollutants of concern and epidemiological studies have identified associations between exposure to wildfire smoke PM 2.5 and mortality and respiratory morbidity, and a possible association with cardiovascular morbidity. For this study, a retrospective analysis of air quality modelling was performed to quantify the exposure to wildfire-PM 2.5 across the Canadian population. The model included wildfire emissions from across North America for a 5-month period from May to September (i.e. wildfire season), between 2013 and 2015 and 2017–2018. Large variations in wildfire-PM 2.5 were noted year-to-year, geospatially, and within fire season. The model results were then used to estimate the national population health impacts attributable to wildfire-PM 2.5 and the associated economic valuation. The analysis estimated annual premature mortalities ranging from 54–240 premature mortalities attributable to short-term exposure and 570–2500 premature mortalities attributable to long-term exposure, as well as many non-fatal cardiorespiratory health outcomes. The economic valuation of the population health impacts was estimated per year at $410M–$1.8B for acute health impacts and $4.3B–$19B for chronic health impacts for the study period. The health impacts were greatest in the provinces with populations in close proximity to wildfire activity, though health impacts were also noted across many provinces indicating the long-range transport of wildfire-PM 2.5. Understanding the population health impacts of wildfire smoke is important as climate change is anticipated to increase wildfire activity in Canada and abroad. Unlabelled Image • Wildfire smoke impacts air quality and population health in Canada. • Hundreds to thousands of premature deaths per year attributable to wildfire-PM 2.5. • Mortality and morbidity health impacts had an economic value of billions of CDN$. • Health impacts greatest in populations in close proximity to the wildfire activity. • Population at distance also impacted due to long-range transport of wildfire-PM 2.5. [ABSTRACT FROM AUTHOR]