Health Impact Model Research Articles

The impact of energy sector pollution on human development and inequality amidst climate change

Abstract The provision of energy is a primary contributor to climate change and environmental pollution, the latter including air pollution from aerosol emissions and a broad range of other human health effects and ecosystem damages. At the same time, aerosol emissions also reduce radiative forcing, leading to a masking of part of the warming due to rising CO$_2$ concentrations and temporarily reducing the adverse impacts of climate change. Using an energy-economy-climate model linked to atmospheric chemistry, health impact and life cycle assessment models, we show that the societal costs of the health impacts of environmental pollution substantially exceed the economic benefits from masked warming. We further highlight the unequal burden of these issues on developing countries and explore the implications for human development, global inequality and international climate policy.

Regional disparities in health and employment outcomes of China’s transition to a low-carbon electricity system

Understanding the costs and the spatial distribution of health and employment outcomes of low-carbon electricity pathways is critical to enable an equitable transition. We integrate an electricity system planning model (GridPath), a health impact model (InMAP), and a multiregional input–output model to quantify China’s provincial-level impacts of electricity system decarbonization on costs, health outcomes, employment, and labor compensation. We find that even without specific CO2 constraints, declining renewable energy and storage costs enable a 26% decline in CO2 emissions in 2040 compared to 2020 under the Reference scenario. Compared to the Reference scenario, pursuing 2 °C and 1.5 °C compatible carbon emission targets (85% and 99% decrease in 2040 CO2 emissions relative to 2020 levels, respectively) reduces air pollution-related premature deaths from electricity generation over 2020–2040 by 51% and 63%, but substantially increases annual average costs per unit of electricity demand in 2040 (21% and 39%, respectively). While the 2 °C pathway leads to a 3% increase in electricity sector-related net labor compensation, the 1.5 °C pathway results in a 19% increase in labor compensation driven by greater renewable energy deployment. Although disparities in health impacts across provinces narrow as fossil fuels phase out, disparities in labor compensation widen with wealthier East Coast provinces gaining the most in labor compensation because of materials and equipment manufacturing, and offshore wind deployment.

Assessing climate change impacts on public health in Haiti: a comprehensive study of disease distribution, modeling, and adaptation strategies

This study examines the relationship between climate change and public health in Haiti, a country already facing socioeconomic challenges. The well-being of Haiti’s vulnerable population is expected to be further affected by climate change, leading to an increase in vector-borne, water-borne, and heat-related diseases. As one of the most vulnerable countries to climate change effects, Haiti is currently experiencing an increase in vector-borne diseases such as malaria, dengue, and chikungunya, as well as water-borne diseases and emerging zoonotic outbreaks. This study aims to improve planning, decision-making, and responses to public health challenges by utilizing health data, climatic information, and impact models. The methodology involves the creation of a comprehensive climate and health database to uncover detailed spatial-temporal relationships on a national scale. By evaluating disease indicators from historical periods (1950-2014) and future projections (2015-2100) using the Shared Socio-Economic Pathways (SSPs) from the multi-model ensemble mean of the CMIP6 models, target diseases, including malaria, meningitis, dengue, and heat-sensitive chronic diseases are assessed. Our results highlight a decrease in rainfall and a strong increase in temperatures, especially within western Haiti under the extreme SSP585 scenario. The ability of the impact models to simulate the seasonality and spatial distribution of malaria incidence, dengue and heatwaves was performed. The analysis of risks related to climate-sensitive diseases’ climatic parameters shows that Haiti’s west and central regions are mostly exposed to vector-borne and water-borne diseases. Models predict a decrease in malaria cases due to climate change with hot temperatures and a decline in rainfall, while dengue transmission patterns may undergo changes. These findings will inform the implementation of context-specific early-warning systems and adaptation strategies for climate-sensitive diseases while acknowledging the challenges of integrating climate-altered data into health policies.

Opportunities to Improve Health Economic Outcomes in Coronary Artery Disease: A Review of Care Pathways in the United States Healthcare System

Background: Despite medical advances, coronary artery disease remains the leading cause of death worldwide. Evidence suggests that current uptake and efficacy of strategies in coronary care are suboptimal. This review aimed to investigate key areas for improvements in coronary care in the United States, and to estimate the potential health gains if existing strategies were improved. Methods: A targeted literature review of the acute and chronic coronary artery disease care pathways was conducted to identify areas where health outcomes could be improved in the United States if uptake or efficacy of existing strategies were optimal. Using hypothetical scenarios of maximally improved efficacy or uptake from published literature and health impact modeling, we calculated potential additional lives saved and potential reductions in direct medical costs, using Medicare rates as proxy, if improvements were realized. Results: We identified the following areas where improvements in uptake or efficacy of existing strategies could positively impact coronary artery disease outcomes in the United States: primary prevention, early detection, efficient diagnosis, reducing time to reperfusion, and secondary prevention. Improvements in primary and secondary coronary artery disease prevention have the potential to reduce annual direct medical costs by approximately $17 billion USD and $5 billion USD, respectively. Further, if the efficacy of existing preventive strategies was improved to 80%, then 102,000 (primary prevention) and 32,000 (secondary prevention) lives could be saved annually. Improvements in early detection, more efficient diagnosis, and reducing time to reperfusion could also substantially increase lives saved by increasing the uptake and efficacy of timelier percutaneous interventions, and potentially reduce annual direct medical costs by $1 billion USD. Conclusions: Improvements in primary prevention offer the greatest potential for lives saved and medical costs avoided. Future innovations should focus on advancing existing primary preventive strategies, while simultaneously driving innovation towards developing effective novel strategies in each of the key areas for improvement.

1145. Meningococcal B Immunization for Adolescents in the Presence of Added Gonorrhea Protection: A Public Health Impact Modelling Study in the United States

Abstract Background Several observational studies showed the added gonorrhea protection of outer membrane vesicle (OMV)-containing meningococcal B (MenB) vaccines, raising hopes for achieving WHO gonorrhea control targets. With evolving meningococcal vaccine recommendations in the United States (US), a key policy consideration can be the optimal age for adolescent MenB immunization considering added gonorrhea protection. This study assessed the additional gonorrhea public health impact that could be achieved in the two major existing meningococcal vaccination platforms at 11 and 16-18 years of age in the US. Methods A single cohort Markov model was built to simulate primary and recurrent gonorrhea infections (Figure 1). Vaccine effectiveness was assumed to follow recent observational evidence in the US (40% [95% Confidence Interval: 23%, 53%]) post two-doses. Based on clinical evidence on the OMV antigen decay of the 4CMenB vaccine, protection was assumed to wane exponentially over 72 months. The impact was assessed based on (i) uptake rates for completed immunization series (20% to 90%) and (ii) two age groups to mimic the existing MenACWY and MenB vaccination recommendation features for adolescents: 11 vs 17-year-old as a proxy for 16-18-year vaccine recommendation. Results Substantial reductions in gonorrhea prevalence were observed for the cohort following vaccination at age 17 years, ranging from 3.0% [Credibility Interval (CrI): 1.7%, 4.0%] to 13.5% [CrI: 7.8%, 18.0%] for low (20%) to high (90%) uptake scenarios. The reductions in prevalence were substantially lower for vaccination at 11 years of age, ranging from 0.6% [CrI: 0.3%, 0.8%] to 2.7% [CrI: 1.5%, 3.5%] for the same uptake scenarios (Figure 2). Scenario analyses on shorter durations of protection confirmed the directionality of the results (Table 1). Conclusion Even with low coverage and without considering disease transmission, an OMV-containing MenB vaccine recommendation for older adolescents could result in significantly higher gonorrhea public health impact compared to younger adolescents. Dual effects for MenB and gonorrhea could be considered when recommending vaccines based on age of vaccination. Disclosures Zeki Kocaata, PhD, GSK: Stocks/Bonds Menaka Bhor, PhD, GSK: Stocks/Bonds Woo-Yun Sohn, MD, GSK: Stocks/Bonds Kinga Meszaros, MBA, GSK: Employee|GSK: Stocks/Bonds

Global health burden and cost of lead exposure in children and adults: a health impact and economic modelling analysis

Lead exposure is a worldwide health risk despite substantial declines in blood lead levels following the leaded gasoline phase-out. For the first time, to our knowledge, we aimed to estimate the global burden and cost of intelligence quotient (IQ) loss and cardiovascular disease mortality from lead exposure. In this modelling study, we used country blood lead level estimates from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019. We estimated IQ loss (presented as estimated loss in IQ points with 95% CIs) in the global population of children younger than 5 years using the blood lead level-IQ loss function from an international pooled analysis. We estimated the cost of IQ loss, which was calculated only for the proportion of children expected to enter the labour force, as the present value of loss in lifetime income from the IQ loss (presented as cost in US dollars and percentage of gross domestic product with a range). We estimated cardiovascular deaths (with 95% CIs) due to lead exposure among people aged 25 years or older using a health impact model that captures the effect of lead exposure on cardiovascular disease mortality that is mediated through mechanisms other than hypertension. Finally, we used values of statistical life to estimate the welfare cost of premature mortality (presented as cost in US dollars and percentage of GDP). All estimates were calculated by World Bank income classification and region (for low-income and middle-income countries [LMICs] only) for 2019. We estimated that children younger than 5 years lost 765 million (95% CI 443-1098) IQ points and that 5 545 000 (2 305 000-8 271 000) adults died from cardiovascular disease in 2019 due to lead exposure. 729 million of the IQ points lost (95·3% of the total global IQ loss) and 5 004 000 (90·2% of total) cardiovascular disease deaths due to lead exposure occurred in LMICs. IQ loss in LMICs was nearly 80% higher than a previous estimate. Cardiovascular disease deaths were six times higher than the GBD 2019 estimate. The global cost of lead exposure was US$6·0 trillion (range 2·6-9·0) in 2019, which was equivalent to 6·9% (3·1-10·4) of the global gross domestic product. 77% (range 70-78) of the cost was the welfare cost of cardiovascular disease mortality, and 23% (22-30) was the present value of future income losses from IQ loss. Our findings suggest that global lead exposure has health and economic costs at par with PM2·5 air pollution. However, much work remains to improve the quality of blood lead level measurement data, especially in LMICs. The Korea Green Growth Trust Fund and the World Bank's Pollution Management and Environmental Health Program.

Health and economic benefits of heavy-duty diesel truck emission control policies in Beijing

PM2.5 emissions from heavy-duty diesel trucks (HDDTs) have a significant impact on air quality, human health, and climate change, and seriously threaten the UN Sustainable Development Goals. Globally, a series of emission control measures have been implemented to reduce pollution emissions from HDDTs. Current studies assessing the impact of these measures on air quality and human health have mainly used coarse-grained emission data as input to dispersion model, resulting in the inability to capture the spatiotemporal variability of pollutant concentrations and tending to increase the uncertainty of health impact assessment results. In this study, we quantified the impact of pollution control policies for HDDTs in Beijing on PM2.5 concentrations, human health, and economic losses by integrating policy scenario analysis, pollution dispersion simulation, public health impact and economic benefit assessment models, supported by high spatiotemporal resolution emission data from HDDTs. The results show that PM2.5 concentrations from HDDTs exhibit significant spatial aggregation characteristics, with the intensity of aggregation at night being about twice as high as that during the day. The emission hotspots are mainly concentrated in the sixth, fifth and fourth rings and major highways. Compared to the “business as usual” scenario in 2018, the current policy of updating the fuel standard to China VI and the emission standard to China 6 can reduce PM2.5 concentrations by 96.72%, thereby avoiding 612 premature deaths, which is equivalent to obtaining economic benefits of 1.65 billion CNY. This study further emphasizes the importance of high spatiotemporal resolution emission data during traffic dispersion modeling. The results can help improve the understanding of the effectiveness of emission reduction measures for HDDTs from a health benefit perspective.

Economic and health impact modelling of a whole genome sequencing-led intervention strategy for bacterial healthcare-associated infections for England and for the USA.

Bacterial healthcare-associated infections (HAIs) are a substantial source of global morbidity and mortality. The estimated cost associated with HAIs ranges from $35 to $45 billion in the USA alone. The costs and accessibility of whole genome sequencing (WGS) of bacteria and the lack of sufficiently accurate, high-resolution, scalable and accessible analysis for strain identification are being addressed. Thus, it is timely to determine the economic viability and impact of routine diagnostic bacterial genomics. The aim of this study was to model the economic impact of a WGS surveillance system that proactively detects and directs interventions for nosocomial infections and outbreaks compared to the current standard of care, without WGS. Using a synthesis of published models, inputs from national statistics, and peer-reviewed articles, the economic impacts of conducting a WGS-led surveillance system addressing the 11 most common nosocomial pathogen groups in England and the USA were modelled. This was followed by a series of sensitivity analyses. England was used to establish the baseline model because of the greater availability of underpinning data, and this was then modified using USA-specific parameters where available. The model for the NHS in England shows bacterial HAIs currently cost the NHS around £3 billion. WGS-based surveillance delivery is predicted to cost £61.1 million associated with the prevention of 74 408 HAIs and 1257 deaths. The net cost saving was £478.3 million, of which £65.8 million were from directly incurred savings (antibiotics, consumables, etc.) and £412.5 million from opportunity cost savings due to re-allocation of hospital beds and healthcare professionals. The USA model indicates that the bacterial HAI care baseline costs are around $18.3 billion. WGS surveillance costs $169.2 million, and resulted in a net saving of ca.$3.2 billion, while preventing 169 260 HAIs and 4862 deaths. From a 'return on investment' perspective, the model predicts a return to the hospitals of £7.83 per £1 invested in diagnostic WGS in the UK, and US$18.74 per $1 in the USA. Sensitivity analyses show that substantial savings are retained when inputs to the model are varied within a wide range of upper and lower limits. Modelling a proactive WGS system addressing HAI pathogens shows significant improvement in morbidity and mortality while simultaneously achieving substantial savings to healthcare facilities that more than offset the cost of implementing diagnostic genomics surveillance.

Retracted: Thought and Politics Teaching Students’ Mental Health Impact Model Based on Fuzzy Control Algorithm

Retracted: Thought and Politics Teaching Students’ Mental Health Impact Model Based on Fuzzy Control Algorithm

Bayesian multistate modelling of incomplete chronic disease burden data.

A widely-used model for determining the long-term health impacts of public health interventions, often called a "multistate lifetable", requires estimates of incidence, case fatality, and sometimes also remission rates, for multiple diseases by age and gender. Generally, direct data on both incidence and case fatality are not available in every disease and setting. For example, we may know population mortality and prevalence rather than case fatality and incidence. This paper presents Bayesian continuous-time multistate models for estimating transition rates between disease states based on incomplete data. This builds on previous methods by using a formal statistical model with transparent data-generating assumptions, while providing accessible software as an R package. Rates for people of different ages and areas can be related flexibly through splines or hierarchical models. Previous methods are also extended to allow age-specific trends through calendar time. The model is used to estimate case fatality for multiple diseases in the city regions of England, based on incidence, prevalence and mortality data from the Global Burden of Disease study. The estimates can be used to inform health impact models relating to those diseases and areas. Different assumptions about rates are compared, and we check the influence of different data sources.

Does bike sharing improve public health? A case study in New York City

Bike sharing contributes to public health by providing physical exercise opportunities. Meanwhile, the shift of vehicular travel demand to bike sharing may cut vehicular emissions and severe crashes. However, according to each city’s different composition of travel modes, the net health benefits are not clear and worth studying case by case. In this paper, we focus on the Citi Bike bike-sharing program in New York City. We modify the Integrated Transport Health Impact Model and assess the net health effects by comparing a baseline scenario (with Citi Bike) against a hypothetical scenario (without Citi Bike). For each scenario, we investigate the overall health effects of the Citi Bike program in the unit of Disability Adjusted Life Years (DALYs) in three categories: physical activity, fine inhalable particles (i.e., PM 2.5) exposure, and road traffic injuries. The results indicate that the implementation of Citi Bike plays a positive role in improving public health. It is worth noting that the emission reduction due to the shift from vehicular transport to Citi Bike contributes the most health benefit to the public. Hence we further propose a sensitivity analysis of the Citi Bike market share illustrating the potential benefits of promoting Citi Bike among non-users.

EPH64 Public Health Impact of COVID-19 in French Ambulatory Patients With at Least One Risk Factor for Severe Disease

In the fight against the pandemic, it was essential to join forces with professionals to better understand the resources involved in the care ecosystem. A public health impact model was developed to estimate the health and economic burden of COVID-19, to support future choices of resource allocations and to allow comparison with other diseases. A Markov model was used to estimate life years, costs, number of hospitalisations, number of deaths and long/prolonged COVID forms over a time horizon of 2 years. Data from the literature suggest that the age of patients can affect the risk of hospitalisation and the risk of death during hospitalisation, hence the model was stratified by age group. The hospitalisation probabilities were derived from a Temporary Use Authorisation cohort, and the hospitalisation stays characteristics were derived from the French national hospital discharge database. Several scenarios were conducted. Over the model time horizon and in a situation where patients were not treated, the number of hospitalisations reached 256 per 1,000 patients in the acute phase and 382 per 1,000 patients overall. The number of deaths in the acute phase was 37 per 1,000 patients, and the number of long/prolonged COVID forms reached 407 per 1,000 patients. These translated into a reduction of 0.7 days of life per patient in the acute phase (versus the maximum lifetime during the acute phase: 30.4 days), with an average cost of €1,578, and a reduction of 27 days of life over the time horizon (versus the maximum lifetime during the whole simulation considering natural mortality: 2 years and 15.8 days), with an average cost of €4,280. This study shows that the health and economic burden is considerable especially for the elderly and/or unvaccinated and goes beyond the acute phase because of the effects and consequences of the long/prolonged COVID forms.

European aerosol phenomenology - 8: Harmonised source apportionment of organic aerosol using 22 Year-long ACSM/AMS datasets.

Organic aerosol (OA) is a key component of total submicron particulate matter (PM1), and comprehensive knowledge of OA sources across Europe is crucial to mitigate PM1 levels. Europe has a well-established air quality research infrastructure from which yearlong datasets using 21 aerosol chemical speciation monitors (ACSMs) and 1 aerosol mass spectrometer (AMS) were gathered during 2013-2019. It includes 9 non-urban and 13 urban sites. This study developed a state-of-the-art source apportionment protocol to analyse long-term OA mass spectrum data by applying the most advanced source apportionment strategies (i.e., rolling PMF, ME-2, and bootstrap). This harmonised protocol was followed strictly for all 22 datasets, making the source apportionment results more comparable. In addition, it enables quantification of the most common OA components such as hydrocarbon-like OA (HOA), biomass burning OA (BBOA), cooking-like OA (COA), more oxidised-oxygenated OA (MO-OOA), and less oxidised-oxygenated OA (LO-OOA). Other components such as coal combustion OA (CCOA), solid fuel OA (SFOA: mainly mixture of coal and peat combustion), cigarette smoke OA (CSOA), sea salt (mostly inorganic but part of the OA mass spectrum), coffee OA, and ship industry OA could also be separated at a few specific sites. Oxygenated OA (OOA) components make up most of the submicron OA mass (average=71.1%, range from 43.7 to 100%). Solid fuel combustion-related OA components (i.e., BBOA, CCOA, and SFOA) are still considerable with in total 16.0% yearly contribution to the OA, yet mainly during winter months (21.4%). Overall, this comprehensive protocol works effectively across all sites governed by different sources and generates robust and consistent source apportionment results. Our work presents a comprehensive overview of OA sources in Europe with a unique combination of high time resolution (30-240min) and long-term data coverage (9-36months), providing essential information to improve/validate air quality, health impact, and climate models.

Thought and Politics Teaching Students’ Mental Health Impact Model Based on Fuzzy Control Algorithm

The rapid development of modern science and technology has led to the increasing scale of production systems and the formation of large and complex systems, resulting in the increasing complexity of control objects, controllers, and control tasks and purposes. The problem of how to better play the nurturing function of professional courses and realize the combination of knowledge transfer and value leadership is addressed. Compared with traditional teaching methods, the combination of mental health knowledge and ideological and political content can effectively improve the life satisfaction of college students and thus promote the completion of teaching objectives. Based on the background of the current new social development, the values of college students are gradually tending to diversify, which brings certain difficulties to the development of thought and politics teaching in schools. In the new era, the psychological health and thought dynamics of college students are getting more and more attention from the society and schools. To establish positive and healthy “three views,” students are closely related to teaching of psychological fitness and thought and politics teaching. In this paper, we study the influence model of thought and politics teaching based on fuzzy control algorithm (FL) in order to achieve a scientific and systematic teaching method and good teaching effect. In this paper, the construction of FL-based thought and politics teaching students’ mental health influence model is studied, in order to achieve a scientific and systematic teaching method and good teaching effect. The experimental results show that the average correct rate of the endpoints corresponding to the endpoints detected by FL’s thought and politics teaching model is 76.99%, which is 42.85% higher than that of the nonlinear SISO system algorithm. Therefore, the endpoint detection algorithm of FL’s thought and politics teaching model combined with amplitude and phase information has a higher correct rate. Therefore, this paper can analyze the psychology of different groups of college students, so as to draw more accurate conclusions in the field of student psychology, and then improve the psychological health of individual college students. Therefore, the research in this paper can meet the intrinsic requirements of the psychological and ideological health development of college students, strengthen the theoretical research on the infiltration of teaching of psychological fitness into the teaching of civics, improve the teaching mode, and innovate the educational methods.

The role of NOx emission reductions in Euro 7/VII vehicle emission standards to reduce adverse health impacts in the EU27 through 2050

Air pollution is the single greatest environmental health hazard in Europe, responsible for over 300,000 premature deaths in the EU27 in 2019. Transport is a significant contributor toward the emission of air pollutants which reduce life expectancy through increased likelihood of morbidity-associated diseases. The introduction of the Euro vehicle emission standards has been successful in driving down the overall level of transport related air pollutants. However, the current regulatory limits have not been updated in nearly a decade. Furthermore, deviations are still evident between the type-approval standards and real-world emissions recorded through remote sensing. Based on the technology potential of current emission control systems, a feasible reduction in new vehicle emissions of nitrogen oxides (NOx) of up to 80% applicable to light- and heavy-duty vehicles that could be realized through the upcoming revision of the Euro standards is modelled. A multi-model approach is employed, combining a stock simulation model and a health impact model which applies the latest methodology of the Global Burden of Disease to quantify the cumulative emissions reduction and corresponding health impacts in the EU27 through 2050. Mandating such a NOx reduction for new vehicles from 2027 would result in a 93-98% reduction in annual NOx emissions from transport by 2050, and reduce cumulative emissions by 4.2-5 million tonnes over the 2027-2050 period. The corresponding reduction in levels of particulate matter and ozone would prevent 34,675 - 41,645 premature deaths, and 568,374 - 682,513 years of life lost. Heavy-duty vehicles experience greater relative emissions reductions compared to their light-duty counterparts due to the current slower deployment of zero-emission vehicles in the sector.

A human exposure-based traffic assignment model for minimizing fine particulate matter (PM2.5) intake from on-road vehicle emissions

An exposure-based traffic assignment (TA) model and accompanying analysis framework have been developed to quantify primary and secondary fine particulate matter (PM2.5) exposure due to modeled on-road vehicle flow on a regional network at a high spatial resolution. The Chicago Metropolitan Area transportation network is used to demonstrate the model’s decision-informing power. The study compares the spatially distributed exposure impacts due to traffic emissions of two TA optimization scenarios: a baseline user equilibrium with respect to travel time (UET) and a novel system optimal with respect to pollutant intake (SOI). The UET and SOI scenarios are developed through the use of (a) the TA model used for obtaining vehicle flow patterns and characteristics including emissions, (b) a source-receptor matrix for PM2.5 developed through a reduced-complexity air quality model to quantify primary and secondary PM2.5 concentrations across the exposure domain, (c) spatial analysis for assessing exposure profiles at the census tract level, and (d) a health impact model to quantify exposure damages. The SOI scenario yields a 9% – 10% total reduction in exposure damages, with the most impacted census tracts benefiting from up to 20% – 30% of reductions, but leads to a 16% increase in travel time costs. Further reduction to PM2.5 exposure by the SOI is hindered by network constraints, where travel demand in populous areas around the network must still be satisfied. The model can be used to systematically quantify the mitigation potential of different transportation exposure reduction strategies, to assess the exposure impacts of newly developed transportation infrastructure, and to address the equity implications of PM2.5 exposure from traffic, all under realistic system behavior and bounded by actual system constraints.

Health impacts of air pollution in Chinese coal-based clean energy industry: LCA-based and WTP-oriented modeling.

The evolution of energy system occupies an important position in economic development and quality of life. Influenced by the energy endowment in China, developing the coal-based clean energy industry has been regarded as a guaranteed path to realizing the clean and efficient use of coal resources. However, an evaluation paradigm that could systematically assess the health impacts of airborne pollution in this industry is still lacking, which is our concern. Combining with life cycle analysis, probabilistic risk models, and health impact models, this study proposes a series of models which are consistent enough to unite pollutant concentration, health risk, and health impact, and equip assessment results with more intuitive significance of life and economic loss. Further, case studies for three typical clean coal technologies, namely, coal mining, coal-fired power generation, and coal liquefaction, are presented to verify the reliability of these models. Results show that the most severe health impact occurred at the worksite of driving face, the substage of coal combustion, and coal mining and processing, respectively, for the three technologies. Further, coal dust brought about the greatest pollution to coal mining and coal liquefaction, and for coal-fired power generation, SO2, NO2, and PM10 were the commonest and toughest pollutants. In conclusion, the proposed evaluation paradigm can help to find out the worksite, substage, and airborne pollutant with the most severe impact and is more intuitive to provide references for minimizing or eliminating environmental pollution. Additionally, three aspects of implications are confirmed in this study, namely, social mobilization promoting, government policy making, and environmental pollution prejudging.

Dosing interval strategies for two-dose COVID-19 vaccination in 13 middle-income countries of Europe: Health impact modelling and benefit-risk analysis.

SummaryBackgroundIn settings where the COVID-19 vaccine supply is constrained, extending the intervals between the first and second doses of the COVID-19 vaccine may allow more people receive their first doses earlier. Our aim is to estimate the health impact of COVID-19 vaccination alongside benefit-risk assessment of different dosing intervals in 13 middle-income countries (MICs) of Europe.MethodsWe fitted a dynamic transmission model to country-level daily reported COVID-19 mortality in 13 MICs in Europe (Albania, Armenia, Azerbaijan, Belarus, Bosnia and Herzegovina, Bulgaria, Georgia, Republic of Moldova, Russian Federation, Serbia, North Macedonia, Turkey, and Ukraine). A vaccine product with characteristics similar to those of the Oxford/AstraZeneca COVID-19 (AZD1222) vaccine was used in the base case scenario and was complemented by sensitivity analyses around efficacies similar to other COVID-19 vaccines. Both fixed dosing intervals at 4, 8, 12, 16, and 20 weeks and dose-specific intervals that prioritise specific doses for certain age groups were tested. Optimal intervals minimise COVID-19 mortality between March 2021 and December 2022. We incorporated the emergence of variants of concern (VOCs) into the model and conducted a benefit-risk assessment to quantify the tradeoff between health benefits versus adverse events following immunisation.FindingsIn all countries modelled, optimal strategies are those that prioritise the first doses among older adults (60+ years) or adults (20+ years), which lead to dosing intervals longer than six months. In comparison, a four-week fixed dosing interval may incur 10.1% [range: 4.3% - 19.0%; n = 13 (countries)] more deaths. The rapid waning of the immunity induced by the first dose (i.e. with means ranging 60-120 days as opposed to 360 days in the base case) resulted in shorter optimal dosing intervals of 8-20 weeks. Benefit-risk ratios were the highest for fixed dosing intervals of 8-12 weeks.InterpretationWe infer that longer dosing intervals of over six months could reduce COVID-19 mortality in MICs of Europe. Certain parameters, such as rapid waning of first-dose induced immunity and increased immune escape through the emergence of VOCs, could significantly shorten the optimal dosing intervals.FundingWorld Health Organization.

Estimated Public Health Gains From German Smokers Switching to Reduced-Risk Alternatives: Results From Population Health Impact Modelling

Summary Background Smoking is associated with cancer and cardio-respiratory mortality. Reducing smoking prevalence will lead to fewer deaths and more life-years. Here, we estimate the impact of hypothetical introduction of reduced-risk products (heat-not-burn products and e-cigarettes) in Germany from 1995 to 2015 on mortality from lung cancer, chronic obstructive pulmonary disease, ischaemic heart disease, and stroke in men and women aged 30–79 years. Methods We used a previously described population health impact model, with individuals with a defined baseline cigarette smoking distribution followed under a “Null Scenario”, with reduced-risk products never introduced, and various “Alternative Scenarios” where they are. Transition probabilities allow product use to change annually, with the individual product histories allowing estimation of risks, relative to never users, which are then used to estimate reductions in deaths and life-years lost for each Alternative Scenario. Results In the Null Scenario, we estimated 852,000 deaths from cigarette smoking (42,600 per year), with 8.61 million life-years lost. Had everyone ceased smoking in 1995, and with no use of reduced-risk products, these numbers would reduce by 217,000 and 2.88 million. Compared to the Null Scenario, the estimated reductions would be 159,000 and 2.06 million with an immediate complete switch to heat-not-burn products and 179,000 and 2.34 million with 50% of smokers immediately switching to heat-not-burn products and 50% to e-cigarettes. In four Scenarios with a more gradual switch, the estimated decreases were 39,800–81,000 deaths and 0.50–1.05 million life-years, representing 17.5%–37.5% of the effect of immediate cessation in 1995. These estimates assume that switching to heat-not-burn products and e-cigarettes involves risk decreases of 80% and 95% of those from quitting, respectively. The reductions in mortality would be greater with more diseases and a wider age range considered or with a longer follow-up period, as the decreases increased markedly with time. Various limitations are discussed, none affecting the conclusion that introducing these new products into Germany in 1995 could have substantially reduced deaths and life-years lost. Conclusions Deaths from cigarette smoking could be substantially reduced not only by cessation but additionally by switching to reduced-risk products. Respective public health campaigns might increase such switching.

Estimated Public Health Gains From Smokers in Germany Switching to Reduced-Risk Alternatives: Results From Population Health Impact Modelling by Socioeconomic Group

Summary Background We previously estimated the impact of introducing heat-not-burn products and e-cigarettes in Germany on smoking-related disease mortality in men and women aged 30–79 years between 1995 and 2015. Here, we estimate the impact by socioeconomic group. Methods Individuals with a defined baseline cigarette smoking distribution were followed under a “Null Scenario” (no reduced-risk products) and “Alternative Scenarios” (reduced-risk products introduced). Transition probabilities allowed estimation of annual product use changes, with individual product histories used to estimate reductions in deaths and life-years lost. Here, however, individuals were classified into two socioeconomic groups defined by income and education, with allowance for variation by group in initial smoking prevalence and the probability of changing product use, or of changing socioeconomic group. Results With no allowance for socioeconomic group, deaths would have reduced by 217,000 (from 852,000 for continued smoking) had everyone immediately ceased smoking in 1995 and by 40,000 to 179,000 had one or two types of reduced-risk products – the heat-not-burn product and the e-cigarette – been adopted by smokers to varying extents. With such allowance, we estimate substantial drops in each socioeconomic group. Where all cigarette smokers switched immediately, half of them to heat-not-burn products, half to e-cigarettes, the estimated drops in deaths were 60,000 in group A (higher socioeconomic group) and 122,000 in group B (lower), about 82% of the drops associated with immediate cessation (73,000 in A and 148,000 in B). With more gradual conversion, the drops were 26,648 in A and 53,000 in B, about 35% of those from cessation. The drops in deaths and life-years saved were about 2 and 1.5 times higher in group B, respectively, associated with its greater numbers, older age, and higher smoking prevalence. The estimated reductions would increase upon considering more diseases, a wider age range, or longer follow-up. Methodological limitations would not affect the conclusion that introducing these products in 1995 in Germany could have substantially reduced deaths and life-years lost in both groups, more so in B. Conclusions Although cessation is optimal for reducing mortality, switching to reduced-risk products also provides substantial health gains. A public health approach encouraging lower socioeconomic group smokers to switch to reduced-risk products could diminish smoking-related health inequalities relative to continued smoking.