Cecilia A. Sánchez

Authorship on academic publications is consequential for researchers in science fields. One’s position in a list of authors is typically used to signal information about author contributions and status, with the first and last author positions regarded as the most prestigious and important for career advancement. Therefore, any inequities that exist in the allocation of authorship (e.g., associated with gender or geography) could affect researchers’ career progression. We assessed patterns in authorship at EcoHealth Alliance, a non-profit organization that conducted One Health and conservation research. We compiled a corpus of 451 peer-reviewed journal articles published from 2011–2022, each of which had at least one EcoHealth Alliance-affiliated author, and gathered information on the gender and country affiliation of authors in first and last author positions. Within the corpus, we found that gendered male researchers and researchers with high-income country (HIC) affiliations were often in prestigious author positions. Specifically, we found that gendered male authors represented 60% of first and last authors, 65% of first and last authorships (FLAs), and 91% of highly productive authors (those with ≥ 10 FLAs). Last authorships were particularly male-dominated, with 2.7 times as many last authorships by gendered male authors as by gendered female authors. Our network analysis revealed that gendered male authors were more structurally important to the author network on average and comprised 65% of highly “powerful” authors in the network. HICs were also overrepresented in the corpus, with 72% of FLAs listing an HIC affiliation. Though our analysis was based on articles with at least one EcoHealth Alliance-affiliated author, authorship affiliations in the corpus extended to nearly 250 institutions across 43 countries, suggesting broader applicability of our findings. We conclude by offering recommendations—informed by the patterns observed in our data and based on our personal experiences as researchers—that we believe would help address the gender and geography disparities in authorship patterns we observed.

Coinfection is common in wild animals, and can profoundly influence disease outcomes and transmission. However, most coinfection research is based on laboratory experiments or a few well-studied wildlife systems. Here, we use data from the PREDICT project – the largest standardized wildlife disease surveillance project ever conducted – to describe patterns of viral coinfection and evaluate their association with host and virus factors. Within the viruses prioritized for testing, we find that coinfection is rare (detected in just 223 of 65,662 animals), but still more common than expected by chance – especially coinfections of coronaviruses, paramyxoviruses, and influenza A virus. We further find that coinfection is associated with host age, but bats and rodents exhibit opposing relationships. We find that captive wild animals (specifically rats and mallards) exhibit higher coinfection than free-ranging wild animals, highlighting potential risks to wildlife and human health from the wildlife trade. Finally, we find that biases in sampling and testing can shape observed patterns of coinfection. Our results characterize associations among viruses in the largest relevant dataset currently available. Factors associated with coinfection in this dataset such as host-level variation, virus-virus interactions, and human interference should be further tested via surveillance and laboratory approaches to better resolve the role of coinfection as an important and likely overlooked driver of viral dynamics in nature.

Bats are the reservoir hosts of emerging coronaviruses (CoVs) affecting human and livestock health. We assessed the diversity, evolution, and geographic distribution of two alphacoronaviruses (subgenus Rhinacovirus ) with considerable potential for emergence: swine acute diarrhea syndrome coronavirus (SADS-CoV), which has caused large outbreaks in pigs in China and can infect primary human airway epithelial cells in vitro ; and the related Rhinolophus bat coronavirus HKU2 (HKU2-CoV). Phylogenetic analyses of 523 rhinacovirus sequences from bats in China and Southeast Asia suggest these viruses should be reclassified into at least two distinct CoV species representing two well-supported monophyletic clades. Stronger phylogenetic clustering by sampling location than by host species suggests infrequent long-distance transmission of rhinacoviruses in southern China. Ancestral state reconstruction analysis indicates that R. sinicus/thomasi and R. affinis have played an important role in rhinacovirus evolution in southern China and that R. affinis is the likely reservoir host of SADS-CoV that spilled over into pigs. We used species distribution modeling of Rhinolophus spp. bat hosts of rhinacoviruses, combined with pig and human density data, to identify potential geographic rhinacovirus spillover risk in Southeast Asia. Areas of high pig density within suitable bat habitat exist primarily in southern China and northern Vietnam, and hotspots of the highest human density within suitable bat habitat are primarily along the southern coast of China, Java, and central Thailand. Targeted surveillance of pigs and people in these regions may facilitate the timely detection of bat CoV spillover events and mitigate the risk of future outbreaks. IMPORTANCE: Bats are the reservoir or ancestral hosts of important emerging coronaviruses affecting people (e.g., SARS-CoV and SARS-CoV-2) and livestock (e.g., PEDV, SADS-CoV). Here, we analyzed 523 genetic sequences of SADS-CoV that caused large-scale die-offs of pigs in China, which is known to be able to infect human cells and related HKU2-CoVs. We used this information to identify the horseshoe bat Rhinolophus affinis as the likely spillover host for the outbreak in pigs, and identified the bat species within which these viruses evolved. We then modeled the distribution of these host species and their overlap with dense human and pig populations to identify the regions where surveillance programs can help identify spillover events and prevent future outbreaks.

Rapid and comprehensive data sharing is vital to the transparency and actionability of wildlife infectious disease research and surveillance. Unfortunately, most best practices for publicly sharing these data are focused on pathogen determination and genetic sequence data. Other facets of wildlife disease data – particularly negative results – are often withheld or, at best, summarized in a descriptive table with limited metadata. Here, we propose a minimum data and metadata reporting standard for wildlife disease studies. Our data standard identifies a set of 40 data fields (9 required) and 24 metadata fields (7 required) sufficient to standardize and document a dataset consisting of records disaggregated to the finest possible spatial, temporal, and taxonomic scale. We illustrate how this standard is applied to an example study, which documented a novel alphacoronavirus found in bats in Belize. Finally, we outline best practices for how data should be formatted for optimal re-use, and how researchers can navigate potential safety concerns around data sharing.

Authorship on academic publications carries substantial weight for researchers in science fields. One’s position in a list of authors is typically used to signal information about author contributions and status, with the first and last authorship positions regarded as the most prestigious and important for career advancement. Therefore, any inequities that exist in the allocation of publication authorship (e.g. due to gender or geography) could affect researchers' career progression. We assessed patterns in publication authorship at EcoHealth Alliance, a non-profit organization that conducts One Health and conservation research. We compiled a corpus of 451 peer-reviewed journal articles published from 2011-2022, each of which had at least one EcoHealth Alliance-affiliated author, and gathered information on the gender and country affiliation of first and last authorships (FLAs). We found that gendered male authors represented ~60% of authors, 65% of FLAs, and 91% of highly productive authors. Last authorships were particularly male-dominated, with ~2.7 times as many last authorships by gendered male authors as by gendered female authors. Gendered male authors were more structurally important to the author network on average and comprised 65% of highly “powerful” authors in the network. High-income countries were also overrepresented in the corpus, with ~72% of FLAs listing a high-income country affiliation. We conclude by offering recommendations for researchers, organizations, and funders and publishers to improve equity in authorship practices.

Over the past two decades, research on bat-associated microbes such as viruses, bacteria and fungi has dramatically increased. Here, we synthesize themes from a conference symposium focused on advances in the research of bats and their microbes, including physiological, immunological, ecological and epidemiological research that has improved our understanding of bat infection dynamics at multiple biological scales. We first present metrics for measuring individual bat responses to infection and challenges associated with using these metrics. We next discuss infection dynamics within bat populations of the same species, before introducing complexities that arise in multi-species communities of bats, humans and/or livestock. Finally, we outline critical gaps and opportunities for future interdisciplinary work on topics involving bats and their microbes.

Bats are reservoirs for various pathogens, including SARS-like coronaviruses (CoVs). Understanding the distribution of bat species is crucial to identifying areas where viral spillover from bats to other animals or humans might occur. In this study, we performed species distribution modeling to predict suitable habitats within Thailand under current and predicted future climate conditions for Rhinolophus acuminatus, a bat species that has been found to host SARS-CoV-2-related viruses. Our assessment of current conditions revealed that temperature seasonality had the greatest impact on habitat suitability and that suitable habitats were primarily restricted to the southern and eastern regions of Thailand. Over time, the projections indicate a diminishing availability of suitable habitats, suggesting a potential trend toward migration into neighboring areas. We next combined modeled bat distribution with urbanization data to estimate regions in Thailand where bat–human interactions might occur. The resulting map highlighted regions of heightened interaction risk, encompassing approximately 46,053.94 km² across 58 provinces and representing approximately 9.24% of Thailand’s total area. These risk concentrations are prominently situated in the southern, central, and eastern Thai regions, with extensions into neighboring border areas. Our findings will significantly aid future risk surveillance efforts and enhance the effectiveness of monitoring and managing emerging diseases within the country and in contiguous regions.

Emerging diseases caused by coronaviruses of likely bat origin (e.g. SARS, MERS, SADS and COVID-19) have disrupted global health and economies for two decades. Evidence suggests that some bat SARS-related coronaviruses (SARSr-CoVs) could infect people directly, and that their spillover is more frequent than previously recognized. Each zoonotic spillover of a novel virus represents an opportunity for evolutionary adaptation and further spread; therefore, quantifying the extent of this “hidden” spillover may help target prevention programs. We derive biologically realistic range distributions for known bat SARSr-CoV hosts and quantify their overlap with human populations. We then use probabilistic risk assessment and data on human-bat contact, human SARSr-CoV seroprevalence, and antibody duration to estimate that ∼400,000 people (median: ∼50,000) are infected with SARSr-CoVs annually in South and Southeast Asia. These data on the geography and scale of spillover can be used to target surveillance and prevention programs for potential future bat-CoV emergence.

Anticoagulant rodenticides (ARs) deployed to control rodent pest populations can increase the risk of pathogen infection for some wildlife. However, it is unknown whether ARs also increase infection risk for target rodents, which are common hosts for zoonotic (animal-to-human transmitted) pathogens. In this study, we tested whether rats exposed to ARs were more likely to be infected with zoonotic pathogens, specifically Leptospira spp. or Escherichia coli , after controlling for known predictors of infection (i.e. sex, age, body condition). We collected biological samples from 99 rats trapped in Chicago alleys and tested these for Leptospira infection, E. coli shedding and AR exposure. We found that rats that had been exposed to ARs and survived until the time of trapping, as well as older rats, were significantly more likely to be infected with Leptospira spp. than other rats. We found no significant association between E. coli shedding and any predictors. Our results show that human actions to manage rats can affect rat disease ecology and public health risks in unintended ways, and more broadly, contribute to a growing awareness of bidirectional relationships between humans and natural systems in cities.