The aim of this study was to characterize the role of the USA in the global exchange of wildlife and describe high volume trade with an eye toward prioritizing health risk assessment questions for further analysis. Here we summarize nearly 14 years (2000–2013) of the most comprehensive data available (USFWS LEMIS system), involving 11 billion individual specimens and an additional 977 million kilograms of wildlife. The majority of shipments contained mammals (27%), while the majority of specimens imported were shells (57%) and tropical fish (25%). Most imports were facilitated by the aquatic and pet industry, resulting in one-third of all shipments containing live animals. The importer reported origin of wildlife was 77.7% wild-caught and 17.7% captive-reared. Indonesia was the leading exporter of legal shipments, while Mexico was the leading source reported for illegal shipments. At the specimen level, China was the leading exporter of legal and illegal wildlife imports. The number of annual declared shipments doubled during the period examined, illustrating continually increasing demand, which reinforces the need to scale up capacity for border inspections, risk management protocols and disease surveillance. Most regulatory oversight of wildlife trade is aimed at conservation, rather than prevention of disease introduction.

Antimicrobial resistance (AMR) is a complex, multifaceted problem that threatens human and animal health, the global economy, and national and global security. In the USA, an estimated 2 million drug-resistant infections occur annually, accounting for 8 million extra hospital days, 23,000 deaths, and $20 billion in direct healthcare costs (Hughes 2011; Centers for Disease Control and Prevention 2013). Worldwide, AMR is increasing (Klein et al. 2018); if current trends continue unabated, there could be as many as 10 million annual AMR-associated deaths from a wide array of infections 1 by 2050 (Review on Antimicrobial Resistance 2016). The World Health Organization (WHO) has included AMR as one of the top ten threats to global health in 2019 (World Health Organization 2019). Two recent examples highlight the threat of emergence and rapid geographic dissemination of antibiotic resistance genes. An enzyme that confers resistance to a wide range of antibiotics, New Delhi metallo-beta-lactamase 1 (NDM-1), has emerged in the Indian subcontinent and spread to the UK as a result of medical tourism after first being detected in 2008 (Yong et al. 2009). The NDM-1 gene was subsequently detected in surface and tap water samples in India in 2010 and in the environment in Bangladesh, indicating the potential for environmental origin and worldwide spread of this gene and its variants (Walsh et al. 2011; Islam et al. 2017; Khan et al. 2017). The NDM-1 gene has recently been identified in nutrient-rich Arctic soil of a remote Norwegian archipelago, raising the possibility of spread by feces from migratory birds (McCann et al. 2019). The MCR-1 (mobilized colistin resistance-1) gene, a plasmidborne gene conferring colistin resistance, was identified in pigs in China in 2014 (Liu et al. 2016) and has subsequently spread to dozens of other countries (Marston et al. 2016; Wang et al. 2018). The purpose of this commentary is to highlight the importance of an integrated and holistic multisectoral One Health approach in combating AMR (Fig. 1) and in particular, the need for better integration of environmental, aquatic, and wildlife issues into current approaches (Andersson and Hughes 2014; Lammie and Hughes 2016; Robinson et al. 2016

Leptospirosis is a widespread zoonotic disease that causes hepatic and renal disease in dogs and human beings. The incidence of leptospirosis in dogs in the USA appears to be increasing. This study used 14 years of canine leptospirosis testing data across 3109 counties in the USA to analyze environmental and socio-economic correlates with rates of infection and to produce a map of locations of increased risk for canine leptospirosis. Boosted regression trees were used to identify the probability of a dog testing positive for leptospirosis based on microscopic agglutination test (MAT) results, and environmental and socio-economic data. The Midwest, East and Southwest were more likely to yield positive tests for leptospirosis, although specific counties in Appalachia had some of the highest predicted probabilities. Location (suburban areas or areas with deciduous forest) and climate (precipitation and temperature) were predictors for positive MAT results for leptospirosis, although the precise direction and strength of the effects was difficult to interpret. Wide geographic variation in predicted risk was identified. This risk mapping approach may provide opportunities for improved diagnosis, control and prevention of leptospirosis in dogs.

24The global wildlife trade network is a massive system that has been shown to threaten 25 biodiversity conservation, introduce non-native species and pathogens, and cause chronic animal 26 welfare concerns. Despite its scale and impact, comprehensive characterization of the global 27 wildlife trade is hampered by data that are limited in their temporal or taxonomic scope and 28 detail. To help fill this gap, we present data on 15 years of the importation of wildlife and their 29 derived products into the United States (2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014), originally collected by the United States 30Fish and Wildlife Service. We curated and cleaned the data and added taxonomic information to 31 improve data usability. These data include > 2 million wildlife or wildlife product shipments, 32representing > 60 biological classes and > 3.2 billion live organisms. These data will be broadly 33 useful to both scientists and policymakers seeking to better understand the volume, sources, 34 biological composition, and potential risks of the global wildlife trade. 35 36 37 38 39 40 41 42 43 44 45

The global wildlife trade network is a massive system that has been shown to threaten biodiversity, introduce non-native species and pathogens, and cause chronic animal welfare concerns. Despite its scale and impact, comprehensive characterization of the global wildlife trade is hampered by data that are limited in their temporal or taxonomic scope and detail. To help fill this gap, we present data on 15 years of the importation of wildlife and their derived products into the United States (2000–2014), originally collected by the United States Fish and Wildlife Service. We curated and cleaned the data and added taxonomic information to improve data usability. These data include >2 million wildlife or wildlife product shipments, representing >60 biological classes and >3.2 billion live organisms. Further, the majority of species in the dataset are not currently reported on by CITES parties. These data will be broadly useful to both scientists and policymakers seeking to better understand the volume, sources, biological composition, and potential risks of the global wildlife trade.

Despite considerable global surveillance of antimicrobial resistance (AMR), data on the global emergence of new resistance genotypes in bacteria has not been systematically compiled. We conducted a study of English-language scientific literature (2006-2017) and ProMED-mail disease surveillance reports (1994-2017) to identify global events of novel AMR emergence (first clinical reports of unique drug-bacteria resistance combinations). We screened 24,966 abstracts and reports, ultimately identifying 1,757 novel AMR emergence events from 268 peer-reviewed studies and 26 disease surveillance reports (294 total). Events were reported in 66 countries, with most events in the United States (152), China (128), and India (127). The most common bacteria demonstrating new resistance were Klebsiella pneumoniae (344) and Escherichia coli (218). Resistance was most common against antibiotic drugs imipenem (89 events), ciprofloxacin (84) and ceftazidime (83). We provide an open-access database of emergence events with standardized fields for bacterial species, drugs, location, and date. We discuss the impact of reporting and surveillance bias on database coverage, and we suggest guidelines for data analysis. This database may be broadly useful for understanding rates and patterns of AMR evolution, identifying global drivers and correlates, and targeting surveillance and interventions.

The covered clinical preventive services were recommended by the U.S. Preventive Services Task Force, the Advisory Committee on Immunization Practices, and the Health Resources and Services Administration. factors influencing use of recommended clinical preventive services can potentially help decision makers better identify policies to increase their use including strategies to increase insurance coverage.

No abstract