GAS PURIFICATION USING A STATE-OF-THE-ART-SOLID-VAPOR-SEPARATION-UNIT: MODELING AND SIMULATION

In spite of the increasing levels of greenhouse gases in the atmosphere and their sever impact on the environment, the demand for natural/bio gas is expected to increase significantly in the coming decades. To cover this demand, the global energy industry is continuously exploiting sour gas reserves located around the world. Nonetheless, sour gas has to be sweetened before the practical utilization of natural or biogas. On the other hand, the combustion of fossil fuels produces flue gases that contain huge amounts of carbon dioxide (CO2) every year. CO2 is a major greenhouse gas, which has negative impact on the environmental systems. Therefore, it is important to reduce or eliminate CO2 from flue gases before being released to the environment. On the other side, radioactive isotope byproducts (e.g., krypton and xenon) are found in off-gas streams released from nuclear power plants with light water reactors or from fuel reprocessing plants, and have to be separated from the off-gas stream. To our knowledge, so far there are no known processes to separate such noble gases, so this work will be the first to address this issue. The cryogenic separation technologies have emerged as a new approach to separate carbon dioxide (CO2) and hydrogen sulfide (H2S) from natural gas, and to capture CO2 gas from flue gas streams. To design cryogenic separation equipment, vapor-liquid equilibrium (VLE), solid-liquid equilibrium (SLE), solid-vapor equilibrium (SVE), and solid-liquid-vapor equilibrium (SLVE) data for the corresponding binary and ternary systems composing the corresponding gas mixtures. In this study, we successfully develop an empirical correlation model based on the Peng-Robinson equation of state (PR EoS), with fugacity expressions, that is able to describe the SLVE behaviors for the ternary systems of CH4-CO2-H2S (resembling a sample natural gas mixture), N2-kr-Xe (resembling noble gases in nitrogen), and N2-O2-CO2 (resembling flue gas mixtures) over wide ranges of pressures and temperatures. Additionally, and based on this model, an equilibrium stage separation unit was modeled and used to construct phase diagrams of the solid-fluid regions for the above-mentioned systems. The results showed that separating the unwanted gases in the solid-vapor equilibrium (SVE) region by selective freezing (solidification) is efficient and results in high recovery rates, the recovery of acid gases (such as CO2) could exceed 99%. Based on that, and by implementing the model developed, a state-of-the art solid-vapor (SV) separation unit was modeled using the Aspen Custom Modeler (ACM) software. The SV unit was then simulated by importing the ACM code into an Aspen Plus simulator; and its performance was studied and analyzed. The SV separation unit offers some key advantages over the traditional technologies (such as amine scrubbing units);including lower energy requirements, less capital costs, lower maintenance and operation expenses and the avoidance of contaminating the gases with other components (such as solvents). In natural gas sweetening, the developed SV unit consumes only ~27% of the energy required by the amine sweetening unit; while for CO2 capture from flue gases, it saves about half of the energy needed by traditional units. For separating noble gases from nitrogen, the SV unit also achieved high recoveries, especially for xenon gas; however the operating temperature would be too low, thus requiring high energy for cooling

An empirical correlation-based model to predict solid-fluid phase equilibria and phase separation of the ternary system CH4-CO2-H2S

To cover the expected increased demand for natural gas, energy industry has to exploit sour gas reserves located around the world. However, acid gases have to be removed before the natural gas produced from these fields could be used. One of the novel concepts in this field is the utilization of solid phase formation of carbon dioxide and/or hydrogen sulfide. The main aim of this study is to develop an empirical correlation model based on Peng-Robinson equation of state (PR EoS), with fugacity expressions, that is able for the first time to describe the solid-fluid phase equilibria for the ternary system of CH4-CO2-H2S at pressures from 5 to 30 bar and over a wide range of temperature (130-200 K). The model was first tested on the binary systems of CH4-CO2, CO2-H2S and CH4-H2S with optimized interaction parameters. When proven to be successful, it was then expanded in a predictive manner to describe the ternary system of CH4-CO2-H2S. The model predictions for the solidification points of 5 different mixtures were within the acceptable error when compared to the experimental data available in the literature. A model based on equilibrium stage separation unit was used to study the separation of three different feed compositions of this ternary system. Overall, it was found that separation of CO2 in solid phase improves when increasing the operating pressure up to 20 bar, and decreases at higher temperatures. Similarly, the separation of H2S in either liquid or solid phase improves at higher pressures and lower temperatures. The recovery of CH4 was high over the entire ranges of operating conditions, expect at high pressure (30 Bar) at temperatures below 190 K. This work provides scientists and engineers with an accurate tool that may be used with confidence for predicting solid-fluid phase equilibria. Consequently, this model eliminates difficulties associated with the need for experiments on ternary system solid-fluid phase equilibria. 2021 The Author(s)The publication of this article was funded by the Qatar National Library .Scopus2-s2.0-8510917127

A review on the solid-liquid-vapor phase equilibria of acid gases in methane

In spite of the increasing levels of greenhouse gases in the atmosphere, and their impact on the environment, the demand for natural/biogas will increase significantly in the coming few decades. To cover this demand, the global energy industry is continuously exploiting sour gas reserves located around the world. Nonetheless, sour gas has to be sweetened before the practical utilization of natural or biogas. The cryogenic separation technologies have emerged as a new technology to separate carbon dioxide (CO2) and hydrogen sulfide (H2S gases) from natural/biogas. The cryogenic separation produces less harmful gases, and can be less expensive to operate and maintain in comparison to the conventional technologies. To design cryogenic separation equipment, vapor-liquid equilibrium (VLE), solid-liquid equilibrium (SLE), solid-vapor equilibrium (SVE), and solid-liquid-vapor equilibrium (SLVE) data for the corresponding binary systems (of CH4-CO2, CH4-H2S, and H2S-CO2) and ternary system (of CH4-H2S-CO2) are required. The main target of this article is to review the SLVE data for the acid gases (CO2 and H2S) in methane (CH4) as the main constituent of natural/biogas. It will address SLVE data for the binary systems of CH4-CO2, CH4-H2S and H2S-CO2 as well as the ternary system of CH4-H2S-CO2. It will not only address the available laboratory data, but it will also discuss, compare and evaluate the different models used to correlate/predict these data.Open Access funding provided by the Qatar National Library.Scopus2-s2.0-8513234129

Prediction of solid-liquid-vapor phase equilibria of noble gases in nitrogen

The primary objective of this study is to develop an empirical correlation model that is able to predict the solid-liquid-vapour phase equilibria (SLVE) for the ternary system of N2-Kr-Xe at pressures ranging from 1 to 45 bar and temperatures ranging from 80 to 180 K. The model was based on Peng-Robinson equation of state. To optimize the interaction parameters that are needed in the model, it was first used to correlate the experimental SLVE data found in the literature for the N2-Kr, and N2-Xe and Kr-Xe binary systems. When the corresponding interaction parameters were optimized, the model was then expanded to predict the SLVE and construct the phase envelope of the ternary system of N2 -Kr-Xe.Open Access funding provided by the Qatar National Library. Not applicable. Although the scientific literature has extensively covered the thermodynamics of air components and air separation; there are little studies that cover the solid-fluid phase equilibria of nitrogen-noble gas mixture systems for their separation, despite their importance and presence in several industries. In this study, and for the first time, we attempt to model the solid-liquid-vapor equilibria (SLVE) of the ternary system Kr-Xe-N2 and its binary constituent systems (Kr-Xe, Xe-N2, and Kr-N2) using an empirical-correlation based model. Additionally, a three-phase solid-liquid-vapor (SLV) separation unit is developed to study and describe the SLVE phase envelope of the ternary system Kr-Xe-N2. Developing this model successfully will provide a useful tool to predict the SLV phase equilibrium behavior for the ternary system Kr-Xe-N2 and evaluate the performances of the corresponding three-phase SLV separation equipment without the need to conduct expensive and time-costly experiments. Furthermore, the model could be further developed and extended to different systems and gases mixtures.Scopus2-s2.0-8512734661

Natural Gas Sweetening Using an Energy-Efficient, State-of-the-Art, Solid-Vapor Separation Process

With the anticipated rise in global demand for natural gas (NG) and liquefied natural gas (LNG), sour gas reserves are attracting the attention of the gas industry as a potential resource. However, to monetize these reserves, sour natural gas has to be sweetened by removing acid gases (carbon dioxide and/or hydrogen sulfide) before liquefaction. The solidification of these acid gases could be the basis for their separation from natural gas. In this study, a state-of-the art solid-vapor (SV) separation unit is developed for removal of acid gases from methane and simulated using a customized Aspen Plus operation unit. The operating principles and conditions, mathematical model, and performance results are presented for the SV unit. Further performance analyses, means of optimization and comparisons to conventional methods used by the industry were studied. Results showed that for similar sweet gas purity, the developed SV unit consumes only 27% of the energy required by the amine sweetening unit. Furthermore, it saves on capital costs, as it requires less equipment and does not suffer from high levels of corrosion.Scopus2-s2.0-8513643009

Spatial, temporal, and demographic patterns in prevalence of smoking tobacco use and attributable disease burden in 204 countries and territories, 1990-2019 : a systematic analysis from the Global Burden of Disease Study 2019

Background Ending the global tobacco epidemic is a defining challenge in global health. Timely and comprehensive estimates of the prevalence of smoking tobacco use and attributable disease burden are needed to guide tobacco control efforts nationally and globally. Methods We estimated the prevalence of smoking tobacco use and attributable disease burden for 204 countries and territories, by age and sex, from 1990 to 2019 as part of the Global Burden of Diseases, Injuries, and Risk Factors Study. We modelled multiple smoking-related indicators from 3625 nationally representative surveys. We completed systematic reviews and did Bayesian meta-regressions for 36 causally linked health outcomes to estimate non-linear dose-response risk curves for current and former smokers. We used a direct estimation approach to estimate attributable burden, providing more comprehensive estimates of the health effects of smoking than previously available. Findings Globally in 2019, 1.14 billion (95% uncertainty interval 1.13-1.16) individuals were current smokers, who consumed 7.41 trillion (7.11-7.74) cigarette-equivalents of tobacco in 2019. Although prevalence of smoking had decreased significantly since 1990 among both males (27.5% [26. 5-28.5] reduction) and females (37.7% [35.4-39.9] reduction) aged 15 years and older, population growth has led to a significant increase in the total number of smokers from 0.99 billion (0.98-1.00) in 1990. Globally in 2019, smoking tobacco use accounted for 7.69 million (7.16-8.20) deaths and 200 million (185-214) disability-adjusted life-years, and was the leading risk factor for death among males (20.2% [19.3-21.1] of male deaths). 6.68 million [86.9%] of 7.69 million deaths attributable to smoking tobacco use were among current smokers. Interpretation In the absence of intervention, the annual toll of 7.69 million deaths and 200 million disability-adjusted life-years attributable to smoking will increase over the coming decades. Substantial progress in reducing the prevalence of smoking tobacco use has been observed in countries from all regions and at all stages of development, but a large implementation gap remains for tobacco control. Countries have a dear and urgent opportunity to pass strong, evidence-based policies to accelerate reductions in the prevalence of smoking and reap massive health benefits for their citizens. Copyright (C) 2021 The Author(s). Published by Elsevier Ltd.Peer reviewe

Surgical site infection after gastrointestinal surgery in high-income, middle-income, and low-income countries: a prospective, international, multicentre cohort study

Background: Surgical site infection (SSI) is one of the most common infections associated with health care, but its importance as a global health priority is not fully understood. We quantified the burden of SSI after gastrointestinal surgery in countries in all parts of the world. Methods: This international, prospective, multicentre cohort study included consecutive patients undergoing elective or emergency gastrointestinal resection within 2-week time periods at any health-care facility in any country. Countries with participating centres were stratified into high-income, middle-income, and low-income groups according to the UN's Human Development Index (HDI). Data variables from the GlobalSurg 1 study and other studies that have been found to affect the likelihood of SSI were entered into risk adjustment models. The primary outcome measure was the 30-day SSI incidence (defined by US Centers for Disease Control and Prevention criteria for superficial and deep incisional SSI). Relationships with explanatory variables were examined using Bayesian multilevel logistic regression models. This trial is registered with ClinicalTrials.gov, number NCT02662231. Findings: Between Jan 4, 2016, and July 31, 2016, 13 265 records were submitted for analysis. 12 539 patients from 343 hospitals in 66 countries were included. 7339 (58·5%) patient were from high-HDI countries (193 hospitals in 30 countries), 3918 (31·2%) patients were from middle-HDI countries (82 hospitals in 18 countries), and 1282 (10·2%) patients were from low-HDI countries (68 hospitals in 18 countries). In total, 1538 (12·3%) patients had SSI within 30 days of surgery. The incidence of SSI varied between countries with high (691 [9·4%] of 7339 patients), middle (549 [14·0%] of 3918 patients), and low (298 [23·2%] of 1282) HDI (p < 0·001). The highest SSI incidence in each HDI group was after dirty surgery (102 [17·8%] of 574 patients in high-HDI countries; 74 [31·4%] of 236 patients in middle-HDI countries; 72 [39·8%] of 181 patients in low-HDI countries). Following risk factor adjustment, patients in low-HDI countries were at greatest risk of SSI (adjusted odds ratio 1·60, 95% credible interval 1·05–2·37; p=0·030). 132 (21·6%) of 610 patients with an SSI and a microbiology culture result had an infection that was resistant to the prophylactic antibiotic used. Resistant infections were detected in 49 (16·6%) of 295 patients in high-HDI countries, in 37 (19·8%) of 187 patients in middle-HDI countries, and in 46 (35·9%) of 128 patients in low-HDI countries (p < 0·001). Interpretation: Countries with a low HDI carry a disproportionately greater burden of SSI than countries with a middle or high HDI and might have higher rates of antibiotic resistance. In view of WHO recommendations on SSI prevention that highlight the absence of high-quality interventional research, urgent, pragmatic, randomised trials based in LMICs are needed to assess measures aiming to reduce this preventable complication

Burden of disease scenarios for 204 countries and territories, 2022–2050: a forecasting analysis for the Global Burden of Disease Study 2021

Background: Future trends in disease burden and drivers of health are of great interest to policy makers and the public at large. This information can be used for policy and long-term health investment, planning, and prioritisation. We have expanded and improved upon previous forecasts produced as part of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) and provide a reference forecast (the most likely future), and alternative scenarios assessing disease burden trajectories if selected sets of risk factors were eliminated from current levels by 2050. Methods: Using forecasts of major drivers of health such as the Socio-demographic Index (SDI; a composite measure of lag-distributed income per capita, mean years of education, and total fertility under 25 years of age) and the full set of risk factor exposures captured by GBD, we provide cause-specific forecasts of mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) by age and sex from 2022 to 2050 for 204 countries and territories, 21 GBD regions, seven super-regions, and the world. All analyses were done at the cause-specific level so that only risk factors deemed causal by the GBD comparative risk assessment influenced future trajectories of mortality for each disease. Cause-specific mortality was modelled using mixed-effects models with SDI and time as the main covariates, and the combined impact of causal risk factors as an offset in the model. At the all-cause mortality level, we captured unexplained variation by modelling residuals with an autoregressive integrated moving average model with drift attenuation. These all-cause forecasts constrained the cause-specific forecasts at successively deeper levels of the GBD cause hierarchy using cascading mortality models, thus ensuring a robust estimate of cause-specific mortality. For non-fatal measures (eg, low back pain), incidence and prevalence were forecasted from mixed-effects models with SDI as the main covariate, and YLDs were computed from the resulting prevalence forecasts and average disability weights from GBD. Alternative future scenarios were constructed by replacing appropriate reference trajectories for risk factors with hypothetical trajectories of gradual elimination of risk factor exposure from current levels to 2050. The scenarios were constructed from various sets of risk factors: environmental risks (Safer Environment scenario), risks associated with communicable, maternal, neonatal, and nutritional diseases (CMNNs; Improved Childhood Nutrition and Vaccination scenario), risks associated with major non-communicable diseases (NCDs; Improved Behavioural and Metabolic Risks scenario), and the combined effects of these three scenarios. Using the Shared Socioeconomic Pathways climate scenarios SSP2-4.5 as reference and SSP1-1.9 as an optimistic alternative in the Safer Environment scenario, we accounted for climate change impact on health by using the most recent Intergovernmental Panel on Climate Change temperature forecasts and published trajectories of ambient air pollution for the same two scenarios. Life expectancy and healthy life expectancy were computed using standard methods. The forecasting framework includes computing the age-sex-specific future population for each location and separately for each scenario. 95% uncertainty intervals (UIs) for each individual future estimate were derived from the 2·5th and 97·5th percentiles of distributions generated from propagating 500 draws through the multistage computational pipeline. Findings: In the reference scenario forecast, global and super-regional life expectancy increased from 2022 to 2050, but improvement was at a slower pace than in the three decades preceding the COVID-19 pandemic (beginning in 2020). Gains in future life expectancy were forecasted to be greatest in super-regions with comparatively low life expectancies (such as sub-Saharan Africa) compared with super-regions with higher life expectancies (such as the high-income super-region), leading to a trend towards convergence in life expectancy across locations between now and 2050. At the super-region level, forecasted healthy life expectancy patterns were similar to those of life expectancies. Forecasts for the reference scenario found that health will improve in the coming decades, with all-cause age-standardised DALY rates decreasing in every GBD super-region. The total DALY burden measured in counts, however, will increase in every super-region, largely a function of population ageing and growth. We also forecasted that both DALY counts and age-standardised DALY rates will continue to shift from CMNNs to NCDs, with the most pronounced shifts occurring in sub-Saharan Africa (60·1% [95% UI 56·8–63·1] of DALYs were from CMNNs in 2022 compared with 35·8% [31·0–45·0] in 2050) and south Asia (31·7% [29·2–34·1] to 15·5% [13·7–17·5]). This shift is reflected in the leading global causes of DALYs, with the top four causes in 2050 being ischaemic heart disease, stroke, diabetes, and chronic obstructive pulmonary disease, compared with 2022, with ischaemic heart disease, neonatal disorders, stroke, and lower respiratory infections at the top. The global proportion of DALYs due to YLDs likewise increased from 33·8% (27·4–40·3) to 41·1% (33·9–48·1) from 2022 to 2050, demonstrating an important shift in overall disease burden towards morbidity and away from premature death. The largest shift of this kind was forecasted for sub-Saharan Africa, from 20·1% (15·6–25·3) of DALYs due to YLDs in 2022 to 35·6% (26·5–43·0) in 2050. In the assessment of alternative future scenarios, the combined effects of the scenarios (Safer Environment, Improved Childhood Nutrition and Vaccination, and Improved Behavioural and Metabolic Risks scenarios) demonstrated an important decrease in the global burden of DALYs in 2050 of 15·4% (13·5–17·5) compared with the reference scenario, with decreases across super-regions ranging from 10·4% (9·7–11·3) in the high-income super-region to 23·9% (20·7–27·3) in north Africa and the Middle East. The Safer Environment scenario had its largest decrease in sub-Saharan Africa (5·2% [3·5–6·8]), the Improved Behavioural and Metabolic Risks scenario in north Africa and the Middle East (23·2% [20·2–26·5]), and the Improved Nutrition and Vaccination scenario in sub-Saharan Africa (2·0% [–0·6 to 3·6]). Interpretation: Globally, life expectancy and age-standardised disease burden were forecasted to improve between 2022 and 2050, with the majority of the burden continuing to shift from CMNNs to NCDs. That said, continued progress on reducing the CMNN disease burden will be dependent on maintaining investment in and policy emphasis on CMNN disease prevention and treatment. Mostly due to growth and ageing of populations, the number of deaths and DALYs due to all causes combined will generally increase. By constructing alternative future scenarios wherein certain risk exposures are eliminated by 2050, we have shown that opportunities exist to substantially improve health outcomes in the future through concerted efforts to prevent exposure to well established risk factors and to expand access to key health interventions

Cancer Incidence, Mortality, Years of Life Lost, Years Lived With Disability, and Disability-Adjusted Life Years for 29 Cancer Groups From 2010 to 2019: A Systematic Analysis for the Global Burden of Disease Study 2019.

The Global Burden of Diseases, Injuries, and Risk Factors Study 2019 (GBD 2019) provided systematic estimates of incidence, morbidity, and mortality to inform local and international efforts toward reducing cancer burden. To estimate cancer burden and trends globally for 204 countries and territories and by Sociodemographic Index (SDI) quintiles from 2010 to 2019. The GBD 2019 estimation methods were used to describe cancer incidence, mortality, years lived with disability, years of life lost, and disability-adjusted life years (DALYs) in 2019 and over the past decade. Estimates are also provided by quintiles of the SDI, a composite measure of educational attainment, income per capita, and total fertility rate for those younger than 25 years. Estimates include 95% uncertainty intervals (UIs). In 2019, there were an estimated 23.6 million (95% UI, 22.2-24.9 million) new cancer cases (17.2 million when excluding nonmelanoma skin cancer) and 10.0 million (95% UI, 9.36-10.6 million) cancer deaths globally, with an estimated 250 million (235-264 million) DALYs due to cancer. Since 2010, these represented a 26.3% (95% UI, 20.3%-32.3%) increase in new cases, a 20.9% (95% UI, 14.2%-27.6%) increase in deaths, and a 16.0% (95% UI, 9.3%-22.8%) increase in DALYs. Among 22 groups of diseases and injuries in the GBD 2019 study, cancer was second only to cardiovascular diseases for the number of deaths, years of life lost, and DALYs globally in 2019. Cancer burden differed across SDI quintiles. The proportion of years lived with disability that contributed to DALYs increased with SDI, ranging from 1.4% (1.1%-1.8%) in the low SDI quintile to 5.7% (4.2%-7.1%) in the high SDI quintile. While the high SDI quintile had the highest number of new cases in 2019, the middle SDI quintile had the highest number of cancer deaths and DALYs. From 2010 to 2019, the largest percentage increase in the numbers of cases and deaths occurred in the low and low-middle SDI quintiles. The results of this systematic analysis suggest that the global burden of cancer is substantial and growing, with burden differing by SDI. These results provide comprehensive and comparable estimates that can potentially inform efforts toward equitable cancer control around the world.Funding/Support: The Institute for Health Metrics and Evaluation received funding from the Bill & Melinda Gates Foundation and the American Lebanese Syrian Associated Charities. Dr Aljunid acknowledges the Department of Health Policy and Management of Kuwait University and the International Centre for Casemix and Clinical Coding, National University of Malaysia for the approval and support to participate in this research project. Dr Bhaskar acknowledges institutional support from the NSW Ministry of Health and NSW Health Pathology. Dr Bärnighausen was supported by the Alexander von Humboldt Foundation through the Alexander von Humboldt Professor award, which is funded by the German Federal Ministry of Education and Research. Dr Braithwaite acknowledges funding from the National Institutes of Health/ National Cancer Institute. Dr Conde acknowledges financial support from the European Research Council ERC Starting Grant agreement No 848325. Dr Costa acknowledges her grant (SFRH/BHD/110001/2015), received by Portuguese national funds through Fundação para a Ciência e Tecnologia, IP under the Norma Transitória grant DL57/2016/CP1334/CT0006. Dr Ghith acknowledges support from a grant from Novo Nordisk Foundation (NNF16OC0021856). Dr Glasbey is supported by a National Institute of Health Research Doctoral Research Fellowship. Dr Vivek Kumar Gupta acknowledges funding support from National Health and Medical Research Council Australia. Dr Haque thanks Jazan University, Saudi Arabia for providing access to the Saudi Digital Library for this research study. Drs Herteliu, Pana, and Ausloos are partially supported by a grant of the Romanian National Authority for Scientific Research and Innovation, CNDS-UEFISCDI, project number PN-III-P4-ID-PCCF-2016-0084. Dr Hugo received support from the Higher Education Improvement Coordination of the Brazilian Ministry of Education for a sabbatical period at the Institute for Health Metrics and Evaluation, between September 2019 and August 2020. Dr Sheikh Mohammed Shariful Islam acknowledges funding by a National Heart Foundation of Australia Fellowship and National Health and Medical Research Council Emerging Leadership Fellowship. Dr Jakovljevic acknowledges support through grant OI 175014 of the Ministry of Education Science and Technological Development of the Republic of Serbia. Dr Katikireddi acknowledges funding from a NHS Research Scotland Senior Clinical Fellowship (SCAF/15/02), the Medical Research Council (MC_UU_00022/2), and the Scottish Government Chief Scientist Office (SPHSU17). Dr Md Nuruzzaman Khan acknowledges the support of Jatiya Kabi Kazi Nazrul Islam University, Bangladesh. Dr Yun Jin Kim was supported by the Research Management Centre, Xiamen University Malaysia (XMUMRF/2020-C6/ITCM/0004). Dr Koulmane Laxminarayana acknowledges institutional support from Manipal Academy of Higher Education. Dr Landires is a member of the Sistema Nacional de Investigación, which is supported by Panama’s Secretaría Nacional de Ciencia, Tecnología e Innovación. Dr Loureiro was supported by national funds through Fundação para a Ciência e Tecnologia under the Scientific Employment Stimulus–Institutional Call (CEECINST/00049/2018). Dr Molokhia is supported by the National Institute for Health Research Biomedical Research Center at Guy’s and St Thomas’ National Health Service Foundation Trust and King’s College London. Dr Moosavi appreciates NIGEB's support. Dr Pati acknowledges support from the SIAN Institute, Association for Biodiversity Conservation & Research. Dr Rakovac acknowledges a grant from the government of the Russian Federation in the context of World Health Organization Noncommunicable Diseases Office. Dr Samy was supported by a fellowship from the Egyptian Fulbright Mission Program. Dr Sheikh acknowledges support from Health Data Research UK. Drs Adithi Shetty and Unnikrishnan acknowledge support given by Kasturba Medical College, Mangalore, Manipal Academy of Higher Education. Dr Pavanchand H. Shetty acknowledges Manipal Academy of Higher Education for their research support. Dr Diego Augusto Santos Silva was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil Finance Code 001 and is supported in part by CNPq (302028/2018-8). Dr Zhu acknowledges the Cancer Prevention and Research Institute of Texas grant RP210042

Socializing One Health: an innovative strategy to investigate social and behavioral risks of emerging viral threats

In an effort to strengthen global capacity to prevent, detect, and control infectious diseases in animals and people, the United States Agency for International Development’s (USAID) Emerging Pandemic Threats (EPT) PREDICT project funded development of regional, national, and local One Health capacities for early disease detection, rapid response, disease control, and risk reduction. From the outset, the EPT approach was inclusive of social science research methods designed to understand the contexts and behaviors of communities living and working at human-animal-environment interfaces considered high-risk for virus emergence. Using qualitative and quantitative approaches, PREDICT behavioral research aimed to identify and assess a range of socio-cultural behaviors that could be influential in zoonotic disease emergence, amplification, and transmission. This broad approach to behavioral risk characterization enabled us to identify and characterize human activities that could be linked to the transmission dynamics of new and emerging viruses. This paper provides a discussion of implementation of a social science approach within a zoonotic surveillance framework. We conducted in-depth ethnographic interviews and focus groups to better understand the individual- and community-level knowledge, attitudes, and practices that potentially put participants at risk for zoonotic disease transmission from the animals they live and work with, across 6 interface domains. When we asked highly-exposed individuals (ie. bushmeat hunters, wildlife or guano farmers) about the risk they perceived in their occupational activities, most did not perceive it to be risky, whether because it was normalized by years (or generations) of doing such an activity, or due to lack of information about potential risks. Integrating the social sciences allows investigations of the specific human activities that are hypothesized to drive disease emergence, amplification, and transmission, in order to better substantiate behavioral disease drivers, along with the social dimensions of infection and transmission dynamics. Understanding these dynamics is critical to achieving health security--the protection from threats to health-- which requires investments in both collective and individual health security. Involving behavioral sciences into zoonotic disease surveillance allowed us to push toward fuller community integration and engagement and toward dialogue and implementation of recommendations for disease prevention and improved health security