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DOE OSTI2022

Assessing the impact of human mobility to predict regional excess death in Ecuador

Abstract COVID-19 outbreaks have had high mortality in low- and middle-income countries such as Ecuador. Human mobility is an important factor influencing the spread of diseases possibly leading to a high burden of disease at the country level. Drastic control measures, such as complete lockdown, are effective epidemic controls, yet in practice one hopes that a partial shutdown would suffice. It is an open problem to determine how much mobility can be allowed while controlling an outbreak. In this paper, we use statistical models to relate human mobility to the excess death in Ecuador while controlling for demographic factors. The mobility index provided by GRANDATA, based on mobile phone users, represents the change of number of out-of-home events with respect to a benchmark date (March 2nd, 2020). The study confirms the global trend that more men are dying than expected compared to women, and that people under 30 show less deaths than expected, particularly individuals younger than 20 with a death rate reduction between 22 and 27%. The weekly median mobility time series shows a sharp decrease in human mobility immediately after a national lockdown was declared on March 17, 2020 and a progressive increase towards the pre-lockdown level within two months. Relating median mobility to excess deaths shows a lag in its effect: first, a decrease in mobility in the previous two to three weeks decreases excess death and, more novel, we found an increase of mobility variability four weeks prior increases the number of excess deaths.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

National serosurvey and risk mapping reveal widespread distribution of Coxiella burnetii in Kenya

Coxiella burnetii, the causative agent of Q fever, is an emerging pathogen that has the potential to cause severe chronic infections in animals and humans worldwide. The detrimental impact on public health is projected to be higher in the low- and middle-income countries given their lower capacity to sustain effective surveillance and response measures. We implemented a national serosurvey of cattle in Kenya to map the spatial distribution of the pathogen. The study used serum samples that were collected from randomly selected cattle in different ago-ecological zones across the country. These samples were screened for the pathogen using PrioCHECK Ruminant Q Fever AB Plate ELISA kit. The laboratory findings were analyzed using INLA package to identify risk factors for C. burnetii exposure from herd- and animal-level factors, area, and bioclimatic datasets accessed from online databases. A total of 6,593 cattle were recruited for the study; of these, 7.9% (95% CI; 7.2–8.5) were seropositive. Outputs from the multivariable analysis revealed that the animal age and some of the geographical variables including wind speed, area under shrubs and “petric calcisols” type of soil were significantly associated with C. burnetii seropositivity. Being a calf, weaner or subadult was associated with lower odds of exposure compared to being an adult by 0.24 (credibility interval: 2.5% and 97.5%), 0.41 (0.30–0.55) and 0.51 (0.38–0.69), respectively. In addition, a unit increase in the wind speed increased the odds of C. burnetii seropositivity by 1.27 (1.05–1.52) while an increase on the land area under shrubs was associated with lower odds of exposure (0.67 [0.47–0.69]). The effect of petric calcisols was non-linear; an increase of the land area with this soil type was associated with an exponential increase in C. burnetii seropositivity. This study provides new data on C. burnetii seroprevalence, information of its risk factors and a prevalence map that can be used for C. burnetii risk surveillance and control. The identification of environmental risk factors for C. burnetii exposure, and the increasing awareness of the zoonotic potential of the pathogen, calls for the need to enhance the existing collaborations for the surveillance and control of C. burnetii in line with the One Health framework. The evidence generated on the potential role of environmental factors can also be used to design nature-based interventions, such as replacement of vegetation in denuded areas, to reduce potential for the aerosolization of the pathogen. Livestock vaccination in the hotspots would also reduce animal infections and hence the contamination of the environment.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

High-ambition climate action in all sectors can achieve a 65% greenhouse gas emissions reduction in the United States by 2035

Under the next cycle of target setting under the Paris Agreement, countries will be updating and submitting new nationally determined contributions (NDCs) over the coming year. To this end, there is a growing need for the United States to assess potential pathways toward a new, maximally ambitious 2035 NDC. In this study, we use an integrated assessment model with state-level detail to model existing policies from both federal and non-federal actors, including the Inflation Reduction Act, Bipartisan Infrastructure Law, and key state policies, across all sectors and gases. Additionally, we develop a high-ambition scenario, which includes new and enhanced policies from these actors. We find that existing policies can reduce net greenhouse gas (GHG) emissions by 44% (with a range of 37% to 52%) by 2035, relative to 2005 levels. The high-ambition scenario can deliver net GHG reductions up to 65% (with a range of 59% to 71%) by 2035 under accelerated implementation of federal regulations and investments, as well as state policies such as renewable portfolio standards, EV sales targets, and zero-emission appliance standards. This level of reductions would provide a basis for continued progress toward the country’s 2050 net-zero emissions goal.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

A regional nuclear conflict would compromise global food security

A limited nuclear war between India and Pakistan could ignite fires large enough to emit more than 5 Tg of soot into the stratosphere. Climate model simulations have shown severe resulting climate perturbations with declines in global mean temperature by 1.8 °C and precipitation by 8%, for at least 5 y. Here we evaluate impacts for the global food system. Six harmonized state-of-the-art crop models show that global caloric production from maize, wheat, rice, and soybean falls by 13 (±1)%, 11 (±8)%, 3 (±5)%, and 17 (±2)% over 5 y. Total single-year losses of 12 (±4)% quadruple the largest observed historical anomaly and exceed impacts caused by historic droughts and volcanic eruptions. Colder temperatures drive losses more than changes in precipitation and solar radiation, leading to strongest impacts in temperate regions poleward of 30°N, including the United States, Europe, and China for 10 to 15 y. Integrated food trade network analyses show that domestic reserves and global trade can largely buffer the production anomaly in the first year. Persistent multiyear losses, however, would constrain domestic food availability and propagate to the Global South, especially to food-insecure countries. By year 5, maize and wheat availability would decrease by 13% globally and by more than 20% in 71 countries with a cumulative population of 1.3 billion people. In view of increasing instability in South Asia, this study shows that a regional conflict using <1% of the worldwide nuclear arsenal could have adverse consequences for global food security unmatched in modern history.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Developing new pathways for energy and environmental decision-making in India: a review

Abstract India faces a dual challenge of economic development and responding to climate change. Although India’s per capita emissions are well below global average, the country is one of the world’s largest greenhouse gas emitters. Indian policymakers and stakeholders require high-quality data and research to assess low-emissions, sustainable development strategies. Peer-reviewed literature is a key source of this information and also a key venue for conversation amongst research leaders. This paper examines the recent peer-reviewed literature on India’s 2030 and 2050 pathways. We conducted a systematic literature review to identify key quantitative national modeling studies. From the 34 studies identified, we synthesized scenario data to draw common conclusions and identify critical research gaps. The main focus was on examining the coverage and the state of information available on low-carbon pathways. Overall, we find a few scenarios that are potentially consistent with a 2070 net-zero goal, but more limited assessment of pathways to reach net-zero emissions before this date. Mitigation pathways with greater ambition are required across all energy sectors to ensure a smooth transition to net-zero emissions by or before 2070. The scenarios confirm that reducing emissions to below 2 GtCO 2 yr −1 by mid-century would necessitate significant transformations of the Indian energy sector, such as, a decrease in unabated coal power capacity, transportation modal shift, and industrial process switching. The assessment also finds substantial differences in final energy estimates reported across studies, particularly in transportation. The lack of consistency in, and transparency about underlying drivers, assumptions, and even outputs across studies points to the critical need for the sorts of coordinated, multi-model studies that have proven exceptionally valuable for decision makers in other major emitting countries.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Long-term trends of impacts of global gasoline and diesel emissions on ambient PM 2.5 and O 3 pollution and the related health burden for 2000–2015

Global economic development and urbanization during the past two decades have driven the increases in demand of personal and commercial vehicle fleets, especially in developing countries, which has likely resulted in changes in year-to-year vehicle tailpipe emissions associated with aerosols and trace gases. However, long-term trends of impacts of global gasoline and diesel emissions on air quality and human health are not clear. In this study, we employ the Community Earth System Model in conjunction with the newly developed Community Emissions Data System as anthropogenic emission inventory to quantify the long-term trends of impacts of global gasoline and diesel emissions on ambient air quality and human health for the period of 2000–2015. Global gasoline and diesel emissions contributed to regional increases in annual mean surface PM 2.5 (particulate matter with aerodynamic diameters ≤2.5 μm) concentrations by up to 17.5 and 13.7 µg m –3 , and surface ozone (O 3 ) concentrations by up to 7.1 and 7.2 ppbv, respectively, for 2000–2015. However, we also found substantial declines of surface PM 2.5 and O 3 concentrations over Europe, the US, Canada, and China for the same period, which suggested the co-benefits of air quality and human health from improving gasoline and diesel fuel quality and tightening vehicle emissions standards. Globally, we estimate the mean annual total PM 2.5- and O 3 -induced premature deaths are 139 700–170 700 for gasoline and 205 200–309 300 for diesel, with the corresponding years of life lost of 2.74–3.47 and 4.56–6.52 million years, respectively. Diesel and gasoline emissions create health-effect disparities between the developed and developing countries, which are likely to aggravate afterwards.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Two decades of aerosol trends over India: seasonal characteristics and urban-rural dynamics

Abstract India faces significant air quality challenges, with one of the highest air pollution levels of any country in the world. Here, we examine two decades (2001–2019) of both particulate matter (PM 2.5 ) concentration and aerosol optical depth (AOD) over the country. Increases are seen between the two decadal averages, for 2001–2010 and 2011–2019, in western India, particularly in the Indo-Gangetic Plain (IGP). IGP region, including Bihar, West Bengal, Jharkhand, and Uttar Pradesh, shows the highest increases in AOD (+0.03, 13%) and PM 2.5, s (+8 µ g m −3 ). Seasonal AOD patterns fluctuate, with the IGP experiencing the highest wintertime increase, especially in Bihar (+0.07). In summer, there are increases in AOD along the southern and eastern coastal areas. Monsoons cause a slight rise in AOD, except in Rajasthan. In the post-monsoon season, the IGP experiences a notable increase in AOD (+0.057, 25%), potentially driven by biomass burning in Bihar (+0.11) and Uttar Pradesh (+0.075). Dividing our study area into urban and peri-urban clusters ( n = 2791), AOD is found to be similar, possibly due to advective mixing. However, the differences between urban and rural areas become more noticeable, especially in the second decade. Correlations between AOD and PM 2.5, g vary across locations, with the highest found in Kanpur ( R 2 = 0.61) and weaker in Delhi ( R 2 = 0.42), highlighting the need for more ground monitoring. However, it suggests that satellite-derived AOD can generally be used to examine trends in PM 2.5 over longer time frames.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Development of wind turbine blade recycling baselines in the United States

Over the past several years, the wind energy industry has received scrutiny regarding wind turbine blade (WTB) recycling due to the landfilling of WTBs caused by a lack of industrially viable recycling solutions. The amount of WTBs that will need to be recycled is set to increase in the United States as the deployment of wind energy is expected to rapidly grow to meet the nation's energy goals by 2035. While significant progress has been made worldwide, it is still unclear which WTB recycling solutions would be the most cost and energy effective within the United States for the existing fleet of wind turbines. To guide researchers and industry with a clear path forward, a range of options for WTB recycling in the United States are modeled through development of baseline scenarios and the use of formal life cycle assessment (LCA). Model data have been collected through literature review, industry engagement, and expert opinion regarding current end of life practices and considerations surrounding equipment, labor, and logistics. A detailed baseline for WTB decommissioning processes has been developed and used to assess alternative approaches, such as on-site shredding to compare the impacts on greenhouse gas (GHG) emissions. The developed LCA model and baseline scenarios for WTB recycling is used to assess the current WTB decommissioning practices in the United States along with emerging recycling pathways, including cement kiln co-processing and pyrolysis. Initial findings indicate that there are different approaches to decommissioning WTBs in the United States, each of which has unique implications for recycling. In light of this finding, additional results from the modeling will be used to better understand decommissioning practices and assist in making educated decisions on recycling pathways for the future. Throughout the analysis, focus was given to where international efforts might differ from the United States. WTB recycling is occurring worldwide, and different countries have different drivers for creating markets for recycled WTB materials. The contrasts and similarities between the United States and other countries offer insight to areas of opportunity that the United States could investigate and areas that can be readily transferred from existing solutions. By modeling and characterizing the current decommissioning practices and potential recycling solutions for the United States, a clearer vision will be created for pathways forward as to how to handle end of life WTBs to enable more efficient and cost-effective opportunities for material recovery from end-of-life WTBs.

Korey, Matt↗
DOE OSTI2024

Ongoing Cooperative Engagement Facilitates Agile Pandemic and Outbreak Response: Lessons Learned Through Cooperative Engagement Between Uganda and the United States

Pathogens threaten human lives and disrupt economies around the world. This has been clearly illustrated by the current COVID-19 pandemic and outbreaks in livestock and food crops. Here, to manage pathogen emergence and spread, cooperative engagement programs develop and strengthen biosafety, biosecurity, and biosurveillance capabilities among local researchers to detect pathogens. In this case study, we describe the efforts of a collaboration between the Los Alamos National Laboratory and the Uganda Virus Research Institute, the primary viral diagnostic laboratory in Uganda, to implement and ensure the sustainability of sequencing for biosurveillance. We describe the process of establishing this capability along with the lessons learned from both sides of the partnership to inform future cooperative engagement efforts in low- and middle-income countries. We found that by strengthening sequencing capabilities at the Uganda Virus Research Institute before the COVID-19 pandemic, the institute was able to successfully sequence SARS-CoV-2 samples and provide data to the scientific community. We highlight the need to strengthen and sustain capabilities through in-country training, collaborative research projects, and trust.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Protein intake is more stable than carbohydrate or fat intake across various US demographic groups and international populations

The optimal macronutrient composition of the diet is controversial and many adults attempt to regulate the intake of specific macronutrients for various health-related reasons. The objective was to compare stability and ranges of intakes of different macronutrients across diverse adult populations in the USA and globally. US dietary intake data from NHANES 2009–2014 were used to determine macronutrient intake as a percentage of total energy intake. Variability in macronutrient intake was estimated by calculating the difference between 75th and 25th percentile (Q3–Q1) IQRs of macronutrient intake distributions. In addition, intake data from 13 other countries with per capita gross domestic product (GDP) over $10,000 US dollars (USD) were used to assess variability of intake internationally since there are large differences in types of foods consumed in different countries. Protein, carbohydrate, and fat intake (NHANES 2009–2014) was 15.7 ± 0.1, 48.1 ± 0.1, and 32.9 ± 0.1% kcal, respectively, in US adults. The IQR of protein intake distribution (3.73 ± 0.11% kcal) was 41% of carbohydrate intake distribution (9.18 ± 0.20% kcal) and 58% of fat intake distribution (6.40 ± 0.14% kcal). The IQRs of carbohydrate and fat intake distributions were significantly (P <0.01) influenced by age and race; however, the IQR of protein intake was not associated with demographic and lifestyle factors including sex, race, income, physical activity, and body weight. International mean protein intake was 16.3 ± 0.2% kcal, similar to US intake, and there was less variation in protein than carbohydrate or fat intake. Protein intake of the US population and multiple international populations, regardless of demographic and lifestyle factors, was consistently ~16% of total energy, suggesting biological control mechanism(s) tightly regulate protein intake and, consequently, influence intake of other macronutrients and food constituents. Substantial differences in intake of the other macronutrients observed in US and international populations had little influence on protein intake. This trial was registered at the ISRCTN registry as ISRCTN46157745

dietary preferences↗
DOE OSTI2022

Exploring the Effects of Geopolitical Shifts on Global Wildlife Trade

Abstract International wildlife trade is a major driver of species extinction and biological invasions. Anticipating environmental risks requires inferences about trade patterns, which are shaped by geopolitics. Although the future cannot be predicted, scenarios can help deal with the uncertainty of future geopolitical dynamics. We propose a framework for generating and analyzing scenarios based on four geopolitical storylines, distinguished by combinations of international trade barrier strength and domestic law enforcement degree across countries supplying and demanding wildlife. We then use historical data on bird trade to classify countries into geopolitical profiles and confirm that trade barriers and law enforcement allow predicting bird trade patterns, supporting our scenarios’ plausibility and enabling projections for future global bird trade. Our framework can be used to examine the consequences of geopolitical changes for wildlife trade and to advise policy and legislation. Reducing demand for wildlife and ameliorating global inequality are key for curbing trade related risks.

Ribeiro, Joana (ORCID:0000000237555785)↗
DOE OSTI2024

Climate change, malaria and neglected tropical diseases: a scoping review

Abstract To explore the effects of climate change on malaria and 20 neglected tropical diseases (NTDs), and potential effect amelioration through mitigation and adaptation, we searched for papers published from January 2010 to October 2023. We descriptively synthesised extracted data. We analysed numbers of papers meeting our inclusion criteria by country and national disease burden, healthcare access and quality index (HAQI), as well as by climate vulnerability score. From 42 693 retrieved records, 1543 full-text papers were assessed. Of 511 papers meeting the inclusion criteria, 185 studied malaria, 181 dengue and chikungunya and 53 leishmaniasis; other NTDs were relatively understudied. Mitigation was considered in 174 papers (34%) and adaption strategies in 24 (5%). Amplitude and direction of effects of climate change on malaria and NTDs are likely to vary by disease and location, be non-linear and evolve over time. Available analyses do not allow confident prediction of the overall global impact of climate change on these diseases. For dengue and chikungunya and the group of non-vector-borne NTDs, the literature privileged consideration of current low-burden countries with a high HAQI. No leishmaniasis papers considered outcomes in East Africa. Comprehensive, collaborative and standardised modelling efforts are needed to better understand how climate change will directly and indirectly affect malaria and NTDs.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

CovTransformer: A transformer model for SARS-CoV-2 lineage frequency forecasting

With hundreds of SARS-CoV-2 lineages circulating in the global population, there is an ongoing need for predicting and forecasting lineage frequencies and thus identifying rapidly expanding lineages. Accurate prediction would allow for more focused experimental efforts to understand pathogenicity of future dominating lineages and characterize the extent of their immune escape. Here, we first show that the inherent noise and biases in lineage frequency data make a commonly-used regression-based approach unreliable. To address this weakness, we constructed a machine learning model for SARS-CoV-2 lineage frequency forecasting, called CovTransformer, based on the transformer architecture. We designed our model to navigate challenges such as a limited amount of data with high levels of noise and bias. We first trained and tested the model using data from the UK and the USA, and then tested the generalization ability of the model to many other countries and US states. Remarkably, the trained model makes accurate predictions two months into the future with high levels of accuracy both globally (in 31 countries with high levels of sequencing effort) and at the US-state level. Our model performed substantially better than a widely used forecasting tool, the multinomial regression model implemented in Nextstrain, demonstrating its utility in SARS-CoV-2 monitoring. Assuming a newly emerged lineage is identified and assigned, our test using retrospective data shows that our model is able to identify the dominating lineages 7 weeks in advance on average before they became dominant. Overall, our work demonstrates that transformer models represent a promising approach for SARS-CoV-2 forecasting and pandemic monitoring.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Remarkably High Internal Transcribed Spacer Haplotype Diversity of the Fungal Select Agent Coniothyrium glycines Discovered Throughout Its Range in Sub-Saharan Africa

Red leaf blotch of soybean, caused by the fungus Coniothyrium glycines, is a foliar disease characterized by blotching, necrosis, and defoliation that has only been reported from Africa. The species is listed as a Select Agent by the Federal Select Agent Program due to its potentially devastating impacts to soybean production should it spread to the United States. Despite its potential import, very few isolates are available for study. Herein, we obtained 96 new C. glycines isolates from six soybean-producing countries throughout sub-Saharan Africa. Along with 12 previously collected ones, we sequenced each at the internal transcribed spacer (ITS) region. Between all isolates, we identified a total of 28 single-nucleotide polymorphisms and 23 haplotypes. One hypothesis to explain the tremendous diversity uncovered at the ITS—which is generally conserved within a species—is that our current species concept of C. glycines is too broad and that there may be multiple species that cause red leaf blotch. Zambia contained the highest haplotype diversity, a significant fraction of which remains unsampled. Most haplotypes were specific to a single country, except for two, which were found in Zambia and either neighboring Mozambique or Zimbabwe. This geographic specificity indicates that the ITS region may be useful for identifying source populations or routes of transmission should this pathogen spread beyond Africa. The observed geographic partitioning of this pathogen is likely the result of millions of years of replication on little-studied native hosts, given that soybean has only been cultivated in Africa since the early 1900s.

Plant Sciences↗
DOE OSTI2020

Isolation of potential plant growth-promoting bacteria from nodules of legumes grown in arid Botswana soil

As the world population increases, improvements in crop growth and yield will be needed to meet rising food demands, especially in countries that have not developed agricultural practices optimized for their own soils and crops. In many African countries, farmers improve agricultural productivity by applying synthetic fertilizers and pesticides to crops, but their continued use over the years has had serious environmental consequences including air and water pollution as well as loss of soil fertility. To reduce the overuse of synthetic amendments, we are developing inocula for crops that are based on indigenous soil microbes, especially those that enhance plant growth and improve agricultural productivity in a sustainable manner. We first isolated environmental DNA from soil samples collected from an agricultural region to study the composition of the soil microbiomes and then used Vigna unguiculata (cowpea), an important legume crop in Botswana and other legumes as “trap” plants using the collected soil to induce nitrogen-fixing nodule formation. We have identified drought-tolerant bacteria from Botswana soils that stimulate plant growth; many are species of Bacillus and Paenibacillus . In contrast, the cowpea nodule microbiomes from plants grown in these soils house mainly rhizobia particularly Bradyrhizobium , but also Methylobacterium spp. Hence, the nodule microbiome is much more limited in non-rhizobial diversity compared to the soil microbiome, but also contains a number of potential pathogenic bacteria.

Kosty, Melissa↗
DOE OSTI2024

At Risk Population Estimates for Belarus, Poland and Slovakia with Machine Learning

High-resolution gridded population modeling is crucial for various applications, including disaster response planning, infectious disease spread modeling, climate change impact estimation, policy development, and more. Multiple gridded population datasets have been developed, each tailored to meet specific objectives. Among them, LandScan Global dataset is designed to represent ambient and unwarned population distributions. However, this dataset relies on a statistical approach that requires manual adjustments, making it time consuming and labour intensive. Existing machine learning (ML) methods often train and test at different spatial resolutions, potentially leading to inflated results, and they rely on Census population totals for disaggregation. To address these limitations, in this study we developed population estimates using ML models trained and tested at a consistent 30 arc-second resolution (≈1 square kilometer), specifically using Random Forest (RF) and XGBoost. These models were trained on 2020 datum to predict for 2021 for three countries: Belarus, Poland, and Slovakia. Our findings show that both RF (MAE varies from 5.75 to 13.25) and XGBoost (MAE varies from 8.15 to 23.44) model performance is close to LandScan Global estimates. Furthermore, neither of the models performed the best across all grid cells: the RF model was more effective in areas with lower populations, while XGBoost excelled in more densely populated regions. The proposed approach can be used for countries where the Census data is not available.

Lebakula, Viswadeep [ORNL] (ORCID:0000000152935914↗
DOE OSTI2023

Tigers at a crossroads: Shedding light on the role of Bangladesh in the illegal trade of this iconic big cat

Abstract Unsustainable wildlife trade is a major threat to many species, but quantifying trade remains challenging, as seizure data provides an incomplete understanding. For this reason, integrating multiple types of information, including interviews with actors involved in trade, is crucial if we are to understand the problem better. Hence, in this study, we digitized Bangladesh Forest Department tiger seizure records to identify trade routes and interviewed 163 individuals involved in trafficking tigers through Bangladesh's air, sea and land ports, including poachers, smugglers, and traders. We identified six ports used to import tigers, 14 ports used for tiger export and three ports showing bi‐directional trade. Elite Bangladeshis were the most important consumer group, and tigers were sourced from populations in NE India, Myanmar and Bangladesh Sundarbans to supply domestic demand. Tiger products were exported to 14 countries, including seven G20 nations, with Bangladeshi expatriates as the consumer group in three countries (United Kingdom, Germany and Qatar). Rising economic development in Bangladesh over the last decade, combined with deep‐rooted cultural ties to tiger consumption, has led to a rise in domestic demand. Additionally, rapid growth in international transport links has increased smuggling and connected local traders with global markets, increasing the complexity of global trade. These findings suggest Bangladesh is poised to play a pivotal role in tiger conservation over the next decade, requiring strong national strategies to reduce trade opportunities, disrupt networks and weaken demand.

Uddin, Nasir↗
DOE OSTI2020

Implementation of early psychosis services in Latin America: A scoping review

Abstract Aim The evidence of the effectiveness and cost‐effectiveness of early intervention for psychosis (EIP) services has motivated their implementation worldwide. However, complex interventions of such EIP services require local adaptations to successfully match population needs and cultural differences. Latin America is a heterogenous region where EIP services are progressively being adopted. Our aim is to map such initiatives in the region with a focus on implementation outcomes. Methods A scoping review following the Preferred Reporting Items for Systematic review and Meta‐Analysis extension for Scoping Reviews guidelines was conducted. International and regional databases were searched for publications describing EIP programmes in the region. Besides mapping the services, we described implementation outcomes based on the Standards for Reporting Implementation Studies Checklist. Results Ten articles describing seven EIP initiatives from the region were found. Four countries were represented: Argentina, Brazil, Chile and Mexico. The implementation outcomes reporting was heterogenous, although it was possible to ascertain EIP services are feasible and adequate for the region's context. Also, there is some evidence of effectiveness in terms of reducing hospitalizations and improving symptoms. Information about fidelity measures was scarce and there was no information about costs or cost‐effectiveness. Conclusions Only a small proportion of Latin American countries have adopted EIP services. Although these programmes seem to be feasible and effective, data on other implementation outcomes, such as fidelity, cultural appropriateness, cost‐effectiveness and affordability are not available. This might in part explain why this effective approach has not been yet scaled‐up at nationwide levels.

Aceituno, David↗