Antibiotic resistance genes of public health importance in livestock and humans in an informal urban community in Nepal.

Efforts to mitigate the increasing emergence of antimicrobial resistance (AMR) will benefit from a One Health perspective, as over half of animal antimicrobials are also considered medically important in humans, and AMR can be maintained in the environment. This is especially pertinent to low- and middle-income countries and in community settings, where an estimated 80% of all antibiotics are used. This study features AMR genes found among humans, animals, and water at an urban informal settlement in Nepal with intensifying livestock production. We sampled humans, chickens, ducks, swine, and water clustered by household, as well as rodents and shrews near dwellings, concurrently in time in July 2017 in southeastern Kathmandu along the Manohara river. Real-time qualitative PCR was performed to screen for 88 genes. Our results characterize the animal-human-environmental interfaces related to the occurrence of specific resistance genes (blaSHV-1 (SHV(238G240E) strain), QnrS, ermC, tetA, tetB, aacC2, aadA1) associated with antibiotics of global health importance that comprise several drug classes, including aminoglycosides, beta-lactams, tetracyclines, macrolides, and fluoroquinolones. By characterizing risk factors across AMR genes of public health importance, this research highlights potential transmission pathways for further investigation and provides prioritization of community-based prevention and intervention efforts for disrupting AMR transmission of critically important antibiotics used in both humans and animals in Nepal.

Global shifts in mammalian population trends reveal key predictors of virus spillover risk.

Emerging infectious diseases in humans are frequently caused by pathogens originating from animal hosts, and zoonotic disease outbreaks present a major challenge to global health. To investigate drivers of virus spillover, we evaluated the number of viruses mammalian species have shared with humans. We discovered that the number of zoonotic viruses detected in mammalian species scales positively with global species abundance, suggesting that virus transmission risk has been highest from animal species that have increased in abundance and even expanded their range by adapting to human-dominated landscapes. Domesticated species, primates and bats were identified as having more zoonotic viruses than other species. Among threatened wildlife species, those with population reductions owing to exploitation and loss of habitat shared more viruses with humans. Exploitation of wildlife through hunting and trade facilitates close contact between wildlife and humans, and our findings provide further evidence that exploitation, as well as anthropogenic activities that have caused losses in wildlife habitat quality, have increased opportunities for animal-human interactions and facilitated zoonotic disease transmission. Our study provides new evidence for assessing spillover risk from mammalian species and highlights convergent processes whereby the causes of wildlife population declines have facilitated the transmission of animal viruses to humans.

Predicting wildlife reservoirs and global vulnerability to zoonotic Flaviviruses.

Flaviviruses continue to cause globally relevant epidemics and have emerged or re-emerged in regions that were previously unaffected. Factors determining emergence of flaviviruses and continuing circulation in sylvatic cycles are incompletely understood. Here we identify potential sylvatic reservoirs of flaviviruses and characterize the macro-ecological traits common to known wildlife hosts to predict the risk of sylvatic flavivirus transmission among wildlife and identify regions that could be vulnerable to outbreaks. We evaluate variability in wildlife hosts for zoonotic flaviviruses and find that flaviviruses group together in distinct clusters with similar hosts. Models incorporating ecological and climatic variables as well as life history traits shared by flaviviruses predict new host species with similar host characteristics. The combination of vector distribution data with models for flavivirus hosts allows for prediction of  global vulnerability to flaviviruses and provides potential targets for disease surveillance in animals and humans.

Optimizing Viral Discovery in Bats.

Viral discovery studies in bats have increased dramatically over the past decade, yet a rigorous synthesis of the published data is lacking. We extract and analyze data from 93 studies published between 2007-2013 to examine factors that increase success of viral discovery in bats, and specific trends and patterns of infection across host taxa and viral families. Over the study period, 248 novel viruses from 24 viral families have been described. Using generalized linear models, at a study level we show the number of host species and viral families tested best explained number of viruses detected. We demonstrate that prevalence varies significantly across viral family, specimen type, and host taxonomy, and calculate mean PCR prevalence by viral family and specimen type across all studies. Using a logistic model, we additionally identify factors most likely to increase viral detection at an individual level for the entire dataset and by viral families with sufficient sample sizes. Our analysis highlights major taxonomic gaps in recent bat viral discovery efforts and identifies ways to improve future viral pathogen detection through the design of more efficient and targeted sample collection and screening approaches.