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Abstract BackgroundAedes (Stegomyia)-borne diseases are an expanding global threat, but gaps in surveillance make comprehensive and comparable risk assessments challenging. Geostatistical models combine data from multiple locations and use links with environmental and socioeconomic factors to make predictive risk maps. Here we systematically review past approaches to map risk for differentAedes-borne arboviruses from local to global scales, identifying differences and similarities in the data types, covariates, and modelling approaches used. MethodsWe searched on-line databases for predictive risk mapping studies for dengue, Zika, chikungunya, and yellow fever with no geographical or date restrictions. We included studies that needed to parameterise or fit their model to real-world epidemiological data and make predictions to new spatial locations of some measure of population-level risk of viral transmission (e.g. incidence, occurrence, suitability, etc.). ResultsWe found a growing number of arbovirus risk mapping studies across all endemic regions and arboviral diseases, with a total of 176 papers published 2002–2022 with the largest increases shortly following major epidemics. Three dominant use cases emerged: (i) global maps to identify limits of transmission, estimate burden and assess impacts of future global change, (ii) regional models used to predict the spread of major epidemics between countries and (iii) national and sub-national models that use local datasets to better understand transmission dynamics to improve outbreak detection and response. Temperature and rainfall were the most popular choice of covariates (included in 50% and 40% of studies respectively) but variables such as human mobility are increasingly being included. Surprisingly, few studies (22%, 31/144) robustly tested combinations of covariates from different domains (e.g. climatic, sociodemographic, ecological, etc.) and only 49% of studies assessed predictive performance via out-of-sample validation procedures. ConclusionsHere we show that approaches to map risk for different arboviruses have diversified in response to changing use cases, epidemiology and data availability. We identify key differences in mapping approaches between different arboviral diseases, discuss future research needs and outline specific recommendations for future arbovirus mapping. 

Abstract Pathogen evolution is one of the least predictable components of disease emergence, particularly in nature. Here, building on principles established by the geographic mosaic theory of coevolution, we develop a quantitative, spatially explicit framework for mapping the evolutionary risk of viral emergence. Driven by interest in diseases like Severe Acute Respiratory Syndrome (SARS), Middle East Respiratory Syndrome (MERS), and Coronavirus disease 2019 (COVID-19), we examine the global biogeography of bat-origin betacoronaviruses, and find that coevolutionary principles suggest geographies of risk that are distinct from the hotspots and coldspots of host richness. Further, our framework helps explain patterns like a unique pool of merbecoviruses in the Neotropics, a recently discovered lineage of divergent nobecoviruses in Madagascar, and—most importantly—hotspots of diversification in southeast Asia, sub-Saharan Africa, and the Middle East that correspond to the site of previous zoonotic emergence events. Our framework may help identify hotspots of future risk that have also been previously overlooked, like West Africa and the Indian subcontinent, and may more broadly help researchers understand how host ecology shapes the evolution and diversity of pandemic threats. 

Abstract Species distribution modeling (SDM) has become an increasingly common approach to explore questions about ecology, geography, outbreak risk, and global change as they relate to infectious disease vectors. Here, we conducted a systematic review of the scientific literature, screening 563 abstracts and identifying 204 studies that used SDMs to produce distribution estimates for mosquito species. While the number of studies employing SDM methods has increased markedly over the past decade, the overwhelming majority used a single method (maximum entropy modeling; MaxEnt) and focused on human infectious disease vectors or their close relatives. The majority of regional models were developed for areas in Africa and Asia, while more localized modeling efforts were most common for North America and Europe. Findings from this study highlight gaps in taxonomic, geographic, and methodological foci of current SDM literature for mosquitoes that can guide future efforts to study the geography of mosquito-borne disease risk. Graphical Abstract 

Abstract Species functional traits can influence pathogen transmission processes, and consequently affect species' host status, pathogen diversity, and community‐level infection risk. We here investigated, for 143 European waterbird species, effects of functional traits on host status and pathogen diversity (subtype richness) for avian influenza virus at species level. We then explored the association between functional diversity and HPAI H5Nx occurrence at the community level for 2016/17 and 2021/22 epidemics in Europe. We found that both host status and subtype richness were shaped by several traits, such as diet guild and dispersal ability, and that the community‐weighted means of these traits were also correlated with community‐level risk of H5Nx occurrence. Moreover, functional divergence was negatively associated with H5Nx occurrence, indicating that functional diversity can reduce infection risk. Our findings highlight the value of integrating trait‐based ecology into the framework of diversity–disease relationship, and provide new insights for HPAI prediction and prevention. 

Abstract Bats are exceptional among mammals for their powered flight, extended lifespans, and robust immune systems and therefore have been of particular interest in comparative genomics. Using the Oxford Nanopore Technologies long-read platform, we sequenced the genomes of two bat species with key phylogenetic positions, the Jamaican fruit bat (Artibeus jamaicensis) and the Mesoamerican mustached bat (Pteronotus mesoamericanus), and carried out a comprehensive comparative genomic analysis with a diverse collection of bats and other mammals. The high-quality, long-read genome assemblies revealed a contraction of interferon (IFN)-α at the immunity-related type I IFN locus in bats, resulting in a shift in relative IFN-ω and IFN-α copy numbers. Contradicting previous hypotheses of constitutive expression of IFN-α being a feature of the bat immune system, three bat species lost all IFN-α genes. This shift to IFN-ω could contribute to the increased viral tolerance that has made bats a common reservoir for viruses that can be transmitted to humans. Antiviral genes stimulated by type I IFNs also showed evidence of rapid evolution, including a lineage-specific duplication of IFN-induced transmembrane genes and positive selection in IFIT2. In addition, 33 tumor suppressors and 6 DNA-repair genes showed signs of positive selection, perhaps contributing to increased longevity and reduced cancer rates in bats. The robust immune systems of bats rely on both bat-wide and lineage-specific evolution in the immune gene repertoire, suggesting diverse immune strategies. Our study provides new genomic resources for bats and sheds new light on the extraordinary molecular evolution in this critically important group of mammals. 

Powassan virus (POWV) is an emerging tick-borne encephalitic virus in Lyme disease-endemic sites in North America. Due to range expansion and local intensification of blacklegged tick vector (Ixodes scapularis) populations in the northeastern and upper midwestern U.S., human encephalitis cases are increasingly being reported. A better understanding of the transmission cycle between POWV and ticks is required in order to better predict and understand their public health burden. Recent phylogeographic analyses of POWV have identified geographical structuring, with well-defined northeastern and midwestern clades of the lineage II subtype. The extent that geographic and genetically defined sublineages differ in their ability to infect and be transmitted by blacklegged ticks is unclear. Accordingly, we determined whether there are strain-dependent differences in the transmission of POWV to ticks at multiple life stages. Five recent, low-passage POWV isolates were used to measure aspects of vector competence, using viremic and artificial infection methods. Infection rates in experimental ticks remained consistent between all five isolates tested, resulting in a 12–20% infection rate and some differences in viral load. We confirm that these differences are likely not due to differences in host viremia. Our results demonstrate that blacklegged ticks are susceptible to, and capable of transmitting, all tested strains and suggest that the tick–virus association is stable across diverse viral genotypes. 

Improved RNA virus understanding is critical to studying animal and plant health, and environmental processes. However, the continuous and rapid RNA virus evolution makes their identification and characterization challenging. While recent sequence-based advances have led to extensive RNA virus discovery, there is growing variation in how RNA viruses are identified, analyzed, characterized, and reported. To this end, an RdRp Summit was organized and a hybrid meeting took place in Valencia, Spain in May 2023 to convene leading experts with emphasis on early career researchers (ECRs) across diverse scientific communities. Here we synthesize key insights and recommendations and offer these as a first effort to establish a consensus framework for advancing RNA virus discovery. First, we need interoperability through standardized methodologies, data-sharing protocols, metadata provision and interdisciplinary collaborations and offer specific examples as starting points. Second, as an emergent field, we recognize the need to incorporate cutting-edge technologies and knowledge early and often to improve omic-based viral detection and annotation as novel capabilities reveal new biology. Third, we underscore the significance of ECRs in fostering international partnerships to promote inclusivity and equity in virus discovery efforts. The proposed consensus framework serves as a roadmap for the scientific community to collectively contribute to the tremendous challenge of unveiling the RNA virosphere. 

Mosquitoes are responsible for the transmission of numerous viruses of global health significance. The term “vector competence” describes the intrinsic ability of an arthropod vector to transmit an infectious agent. Prior to transmission, the mosquito itself presents a complex and hostile environment through which a virus must transit to ensure propagation and transmission to the next host. Viruses imbibed in an infectious blood meal must pass in and out of the mosquito midgut, traffic through the body cavity or hemocoel, invade the salivary glands, and be expelled with the saliva when the vector takes a subsequent blood meal. Viruses encounter physical, cellular, microbial, and immunological barriers, which are influenced by the genetic background of the mosquito vector as well as environmental conditions. Collectively, these factors place significant selective pressure on the virus that impact its evolution and transmission. Here, we provide an overview of the current state of the field in understanding the mosquito-specific factors that underpin vector competence and how each of these mechanisms may influence virus evolution. 

Habitat degradation can increase zoonotic disease risks by altering infection dynamics in wildlife and increasing wildlife–human interactions. Bats are an important taxonomic group to consider these effects, because they harbour many relevant zoonotic viruses and have species‐ and context‐dependent responses to degradation that could affect zoonotic virus dynamics. Yet our understanding of the associations between habitat degradation and bat virus prevalence and seroprevalence are limited to a small number of studies, which often differ in the bats or viruses sampled, the study region, and methodology. To develop a broad understanding of the associations between bat viruses and habitat degradation, we conducted an initial phylogenetic meta‐analysis that combines published prevalence and seroprevalence (‘(sero)prevalence') with remote‐sensing habitat degradation data. Our dataset includes 588 unique records of (sero)prevalence across 16 studies, 64 bat species, and five virus families. We quantified the overall strength and direction of the relationship between habitat degradation and bat virus outcomes and tested how this relationship is moderated by the time between habitat degradation and bat sampling and by ecological traits of bat hosts while controlling for phylogenetic non‐independence among bat species. We found no effect of degradation on prevalence overall, although a weak effect may exist when forest loss occurs the year prior to bat sampling. In contrast, we detected a negative but weak association between degradation and seroprevalence overall that was strengthened when forest loss occurred the year prior to bat sampling. No bat traits that we investigated interacted with habitat degradation to impact virus outcomes, suggesting observed trends are independent of these traits. Biases in our initial dataset highlight opportunities for future work; prevalence was highly zero‐inflated, and seroprevalence was dominated byDesmodus rotundusand rabies virus. These findings and subsequent analyses will improve our understanding of how global change affects host–pathogen dynamics.