Estimating the burden and modeling mitigation strategies of pork-related hepatitis E virus foodborne transmission in representative European countries.
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ABSTRACT:
SUBMITTER: Ji Y
PROVIDER: S-EPMC8606544 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:The use of residential heating devices is a key source of black carbon and other short-lived climate forcer emissions in Arctic and other high latitude regions, with important impacts to the Arctic climate and human health. The types of combustion technologies and fuels used varies by region, which impacts the emission profiles of these pollutants and thus the magnitude of Arctic climate responses. Using emission inventory data from 14 European countries, we derive wood-fueled residential heating emissions of black carbon, organic carbon, and sulfate from six appliance types in 2016. Using previously derived equilibrium Arctic temperature responses, we estimate Arctic temperature influences from each appliance type. Using the 2016 appliance emission data as a baseline, we compute the emission mass and Arctic temperature mitigation potential from hypothetical stove conversion scenarios. A total of 43.2 gigagrams (Gg) of black carbon, 175.7 Gg of organic carbon, and 10.3 Gg of sulfate were emitted in 2016 from the six appliance types in the 14 countries. The combined emissions increased Arctic surface temperatures by +2.8 millikelvin. If each country converted its appliance fleet to the technologically advanced pellet stoves and boilers, the combined black carbon, organic carbon, and sulfate emissions from heating appliances could be reduced by 94% and the Arctic temperature response reduced by 85%. The specific source and originating region of emissions are important factors in resolving the magnitude of their impacts. Improved country-level accounting of specific appliances and their emission characteristics can lead to a better understanding of potential mitigation options.
| S-EPMC7425647 | biostudies-literature
Project description: Not available
| S-EPMC4214313 | biostudies-literature
Project description:BackgroundReturning universities to full on-campus operations while the coronavirus disease 2019 pandemic is ongoing has been a controversial discussion in many countries. The risk of large outbreaks in dense course settings is contrasted by the benefits of in-person teaching. Transmission risk depends on a range of parameters, such as vaccination coverage and efficacy, number of contacts, and adoption of nonpharmaceutical intervention measures. Owing to the generalized academic freedom in Europe, many universities are asked to autonomously decide on and implement intervention measures and regulate on-campus operations. In the context of rapidly changing vaccination coverage and parameters of the virus, universities often lack sufficient scientific insight on which to base these decisions.MethodsTo address this problem, we analyzed a calibrated, data-driven agent-based simulation of transmission dynamics among 13 284 students and 1482 faculty members in a medium-sized European university. Wed use a colocation network reconstructed from student enrollment data and calibrate transmission risk based on outbreak size distributions in education institutions. We focused on actionable interventions that are part of the already existing decision process of universities to provide guidance for concrete policy decisions.ResultsHere we show that, with the Omicron variant of the severe acute respiratory syndrome coronavirus 2, even a reduction to 25% occupancy and universal mask mandates are not enough to prevent large outbreaks, given the vaccination coverage of about 85% reported for students in Austria.ConclusionsOur results show that controlling the spread of the virus with available vaccines in combination with nonpharmaceutical intervention measures is not feasible in the university setting if presence of students and faculty on campus is required.
| S-EPMC9761892 | biostudies-literature
Project description:In the agricultural setting, core global food safety elements, such as hand hygiene and worker furlough, should reduce the risk of norovirus contamination on fresh produce. However, the effect of these practices has not been characterized. Using a quantitative microbial risk model, we evaluated the individual and combined effect of farm-based hand hygiene and worker furlough practices on the maximum risk of norovirus infection from three produce commodities (open leaf lettuce, vine tomatoes, and raspberries). Specifically, we tested two scenarios where a harvester's and packer's norovirus infection status was: 1) assumed positive; or 2) assigned based on community norovirus prevalence estimates. In the first scenario with a norovirus-positive harvester and packer, none of the individual interventions modeled reduced produce contamination to below the norovirus infectious dose. However, combined interventions, particularly high handwashing compliance (100%) and efficacy (6 log10 virus removal achieved using soap and water for 30 s), reduced produce contamination to <1-82 residual virus. Translating produce contamination to maximum consumer infection risk, 100% handwashing with a 5 log10 virus removal was necessary to achieve an infection risk below the threshold of 0.032 infections per consumption event. When community-based norovirus prevalence estimates were applied to the harvester and packer, the single interventions of 100% handwashing with 3 log10 virus removal (average 0.02 infection risk per consumption event) or furlough of the packer (average 0.03 infection risk per consumption event) reduced maximum infection risk to below the 0.032 threshold for all commodities. Bundled interventions (worker furlough, 100% glove compliance, and 100% handwashing with 1-log10 virus reduction) resulted in a maximum risk of 0.02 per consumption event across all commodities. These results advance the evidence-base for global produce safety standards as effective norovirus contamination and risk mitigation strategies.
| S-EPMC8510003 | biostudies-literature
Project description:The COVID-19 pandemic has inflicted major economic and health burdens across the world. On the other hand, the potential airborne transmission of SARS-COV-2 via air can deeply undermine the effectiveness of countermeasures against spreading the disease. Therefore, there is an intense focus to look for ways to mitigate the COVID-19 spread within various indoor settings. This work systematically reviewed articles regarding airborne transmission of SARS-COV2 in various indoor settings since the onset of the pandemic. The systematic search was performed in Scopus, Web of Science, and PubMed databases and has returned 19 original articles carefully screened with regard to inclusion and exclusion criteria. The results showed that the facilities, such as dormitories and classrooms, received the most attention followed by office buildings, healthcare facilities, residential buildings, and other potential enclosed spaces such as a metro wagon. Besides, the majority of the studies were conducted experimentally while other studies were done using computer simulations. United States (n = 5), Spain (n = 4) and China (n = 3) were the top three countries based on the number of performed research. Ventilation rate was the most influential parameter in controlling the infection spread. CO2 was the primary reference for viral spread in the buildings. The use of natural ventilation or a combination of mechanical and natural ventilations was found to be highly effective in the studies. The current work helps in furthering research on effective interventions to improve indoor air quality and control the spread of COVID-19 and other respiratory diseases.Supplementary informationThe online version contains supplementary material available at 10.1007/s40201-023-00847-0.
| S-EPMC9968468 | biostudies-literature
Project description:BackgroundDespite being the most widely distributed mosquito-borne viral infection, estimates of dengue transmission intensity and associated burden remain ambiguous. With advances in the development of novel control measures, obtaining robust estimates of average dengue transmission intensity is key for assessing the burden of disease and the likely impact of interventions.Methodology/principle findingsWe estimated the force of infection (λ) and corresponding basic reproduction numbers (R0) by fitting catalytic models to age-stratified incidence data identified from the literature. We compared estimates derived from incidence and seroprevalence data and assessed the level of under-reporting of dengue disease. In addition, we estimated the relative contribution of primary to quaternary infections to the observed burden of dengue disease incidence. The majority of R0 estimates ranged from one to five and the force of infection estimates from incidence data were consistent with those previously estimated from seroprevalence data. The baseline reporting rate (or the probability of detecting a secondary infection) was generally low (<25%) and varied within and between countries.Conclusions/significanceAs expected, estimates varied widely across and within countries, highlighting the spatio-temporally heterogeneous nature of dengue transmission. Although seroprevalence data provide the maximum information, the incidence models presented in this paper provide a method for estimating dengue transmission intensity from age-stratified incidence data, which will be an important consideration in areas where seroprevalence data are not available.
| S-EPMC4939939 | biostudies-literature
Project description:BackgroundEstimates of dengue transmission intensity remain ambiguous. Since the majority of infections are asymptomatic, surveillance systems substantially underestimate true rates of infection. With advances in the development of novel control measures, obtaining robust estimates of average dengue transmission intensity is key for assessing both the burden of disease from dengue and the likely impact of interventions.Methodology/principal findingsThe force of infection (λ) and corresponding basic reproduction numbers (R0) for dengue were estimated from non-serotype (IgG) and serotype-specific (PRNT) age-stratified seroprevalence surveys identified from the literature. The majority of R0 estimates ranged from 1-4. Assuming that two heterologous infections result in complete immunity produced up to two-fold higher estimates of R0 than when tertiary and quaternary infections were included. λ estimated from IgG data were comparable to the sum of serotype-specific forces of infection derived from PRNT data, particularly when inter-serotype interactions were allowed for.Conclusions/significanceOur analysis highlights the highly heterogeneous nature of dengue transmission. How underlying assumptions about serotype interactions and immunity affect the relationship between the force of infection and R0 will have implications for control planning. While PRNT data provides the maximum information, our study shows that even the much cheaper ELISA-based assays would provide comparable baseline estimates of overall transmission intensity which will be an important consideration in resource-constrained settings.
| S-EPMC4400108 | biostudies-literature
Project description:To estimate the incidence of foodborne gastroenteritis caused by nontyphoidal Salmonella enterica, Shigella, and Vibrio parahaemolyticus in China, population surveys and sentinel hospital surveillance were implemented in six provinces from July 2010 to July 2011, and a multiplier calculation model for the burden of disease was constructed. The multiplier for salmonellosis and V. parahaemolyticus gastroenteritis was estimated at 4,137 [95% confidence interval (CI) 2,320-5,663], and for shigellosis at 4,356 (95% CI 2,443-5,963). Annual incidence per 100,000 population was estimated as 245 (95% CI 138-336), 67 (95% CI 38-92), and 806 (95% CI 452-1,103) for foodborne salmonellosis, shigellosis, and V. parahaemolyticus gastroenteritis, respectively, indicating that foodborne infection caused by these three pathogens constitutes an important burden to the Chinese healthcare system. Continuous implementation of active surveillance of foodborne diseases, combined with multiplier models to estimate disease burden, makes it possible for us to better understand food safety status in China.
| S-EPMC9639838 | biostudies-literature
Project description:BackgroundInjury is the major cause of death and suffering among children and adolescents, but awareness of the problem and political commitment for preventive actions remain unacceptably low. We have assessed variation in the burden of injuries in childhood and adolescence in eight European countries.MethodsHospital, emergency department, and mortality databases of injury patients aged 0-24 years were analyzed for Austria, Denmark, Ireland, Latvia, Netherlands, Norway, Slovenia and the United Kingdom (England, Wales). Years lost due to premature mortality (YLL), years lived with disability (YLD), and disability adjusted life years (DALYs) were calculated.ResultsDifferences in the burden of injury in childhood and adolescence are large, with a fourfold gap between the safest countries (Netherlands and UK) in western-Europe and the relatively unsafe countries (Latvia and Slovenia) in the east. Variation between countries is attributable to high variation in premature mortality (YLL varied from 14-58 per 1000 persons) and disability (YLD varied from 3-10 per 1000 persons). Highest burden is observed among males ages 15-24. If childhood and adolescence injuries are reduced to the level of current best injury prevention practices, 6 DALYs per 1000 child years can be avoided.ConclusionsInjuries in childhood and adolescence cause a high disability and mortality burden in Europe. In all developmental stages large inequalities between west and east are observed. Potential benefits up to almost 1 million healthy child years gained across Europe are possible, if proven ways for prevention are more widely implemented. Our children deserve action now.
| S-EPMC2824737 | biostudies-literature
Project description:BackgroundPolicy decisions regarding climate change mitigation are increasingly incorporating the beneficial and adverse health impacts of greenhouse gas emission reduction strategies. Studies of such co-benefits and co-harms involve modeling approaches requiring a range of analytic decisions that affect the model output.ObjectiveOur objective was to assess analytic decisions regarding model framework, structure, choice of parameters, and handling of uncertainty when modeling health co-benefits, and to make recommendations for improvements that could increase policy uptake.MethodsWe describe the assumptions and analytic decisions underlying models of mitigation co-benefits, examining their effects on modeling outputs, and consider tools for quantifying uncertainty.DiscussionThere is considerable variation in approaches to valuation metrics, discounting methods, uncertainty characterization and propagation, and assessment of low-probability/high-impact events. There is also variable inclusion of adverse impacts of mitigation policies, and limited extension of modeling domains to include implementation considerations. Going forward, co-benefits modeling efforts should be carried out in collaboration with policy makers; these efforts should include the full range of positive and negative impacts and critical uncertainties, as well as a range of discount rates, and should explicitly characterize uncertainty. We make recommendations to improve the rigor and consistency of modeling of health co-benefits.ConclusionModeling health co-benefits requires systematic consideration of the suitability of model assumptions, of what should be included and excluded from the model framework, and how uncertainty should be treated. Increased attention to these and other analytic decisions has the potential to increase the policy relevance and application of co-benefits modeling studies, potentially helping policy makers to maximize mitigation potential while simultaneously improving health.
| S-EPMC4014758 | biostudies-literature