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At least 109 records · Page 6Linked to original sources
USGS2025

Vibrio pectenicida strain FHCF-3 is a causative agent of sea star wasting disease

More than 10 years following the onset of the sea star wasting disease (SSWD) epidemic, affecting over 20 asteroid species from Mexico to Alaska, the causative agent has been elusive. SSWD killed billions of the most susceptible species, sunflower sea stars ( Pycnopodia helianthoides ), initiating a trophic cascade involving unchecked urchin population growth and the widespread loss of kelp forests. Identifying the causative agent underpins the development of recovery strategies. Here we induced disease and subsequent mortality in exposure experiments using tissue extracts, coelomic fluid and effluent water from wasting sunflower sea stars, with no mortality in controls. Deep sequencing of diseased sea star coelomic fluid samples from experiments and field outbreaks revealed a dominant proportion of reads assigned to the bacterium Vibrio pectenicida . Fulfilling Koch’s postulates, V. pectenicida strain FHCF-3, cultured from the coelomic fluid of a diseased sunflower sea star, caused disease and mortality in exposed sunflower sea stars, demonstrating that it is a causative agent of SSWD. This discovery will enable recovery efforts for sea stars and the ecosystems affected by their decline by facilitating culture-based experimental research and broad-scale screening for pathogen presence and abundance in the laboratory and field.

Nature Ecology & Evolution↗
USGS2020

Models with environmental drivers offer a plausible mechanism for the rapid spread of infectious disease outbreaks in marine organisms

The first signs of sea star wasting disease (SSWD) epidemic occurred in just few months in 2013 along the entire North American Pacific coast. Disease dynamics did not manifest as the typical travelling wave of reaction-diffusion epidemiological model, suggesting that other environmental factors might have played some role. To help explore how external factors might trigger disease, we built a coupled oceanographic-epidemiological model and contrasted three hypotheses on the influence of temperature on disease transmission and pathogenicity. Models that linked mortality to sea surface temperature gave patterns more consistent with observed data on sea star wasting disease, which suggests that environmental stress could explain why some marine diseases seem to spread so fast and have region-wide impacts on host populations.

Baja California, British Columbia, California, Ore↗
USGS2020

Mass mortality in freshwater mussels (Actinonaias pectorosa) in the Clinch River, USA, linked to a novel densovirus

Freshwater mussels (order Unionida) are among the world’s most biodiverse but imperiled taxa. Recent unionid mass mortality events around the world threaten ecosystem services such as water filtration, nutrient cycling, habitat stabilization, and food web enhancement, but causes have remained elusive. To examine potential infectious causes of these declines, we studied mussels in Clinch River, Virginia and Tennessee, USA, where the endemic and once-predominant pheasantshell ( Actinonaias pectorosa ) has suffered precipitous declines since approximately 2016. Using metagenomics, we identified 17 novel viruses in Clinch River pheasantshells. However, only one virus, a novel densovirus ( Parvoviridae ; Densovirinae ), was epidemiologically linked to morbidity. Clinch densovirus 1 was 11.2 times more likely to be found in cases (moribund mussels) than controls (apparently healthy mussels from the same or matched sites), and cases had 2.7 (log 10 ) times higher viral loads than controls. Densoviruses cause lethal epidemic disease in invertebrates, including shrimp, cockroaches, crickets, moths, crayfish, and sea stars. Viral infection warrants consideration as a factor in unionid mass mortality events either as a direct cause, an indirect consequence of physiological compromise, or a factor interacting with other biological and ecological stressors to precipitate mortality.

Virginia, Tennessee↗
USGS2014

Avian influenza H5N1 viral and bird migration networks in Asia

The spatial spread of the highly pathogenic avian influenza virus H5N1 and its long-term persistence in Asia have resulted in avian influenza panzootics and enormous economic losses in the poultry sector. However, an understanding of the regional long-distance transmission and seasonal patterns of the virus is still lacking. In this study, we present a phylogeographic approach to reconstruct the viral migration network. We show that within each wild fowl migratory flyway, the timing of H5N1 outbreaks and viral migrations are closely associated, but little viral transmission was observed between the flyways. The bird migration network is shown to better reflect the observed viral gene sequence data than other networks and contributes to seasonal H5N1 epidemics in local regions and its large-scale transmission along flyways. These findings have potentially far-reaching consequences, improving our understanding of how bird migration drives the periodic reemergence of H5N1 in Asia.

PNAS↗
USGS2015

Reduced transmission of human schistosomiasis after restoration of a native river prawn that preys on the snail intermediate host

Eliminating human parasitic disease often requires interrupting complex transmission pathways. Even when drugs to treat people are available, disease control can be difficult if the parasite can persist in nonhuman hosts. Here, we show that restoration of a natural predator of a parasite’s intermediate hosts may enhance drug-based schistosomiasis control. Our study site was the Senegal River Basin, where villagers suffered a massive outbreak and persistent epidemic after the 1986 completion of the Diama Dam. The dam blocked the annual migration of native river prawns ( Macrobrachium vollenhoveni ) that are voracious predators of the snail intermediate hosts for schistosomiasis. We tested schistosomiasis control by reintroduced river prawns in a before-after-control-impact field experiment that tracked parasitism in snails and people at two matched villages after prawns were stocked at one village’s river access point. The abundance of infected snails was 80% lower at that village, presumably because prawn predation reduced the abundance and average life span of latently infected snails. As expected from a reduction in infected snails, human schistosomiasis prevalence was 18 ± 5% lower and egg burden was 50 ± 8% lower at the prawn-stocking village compared with the control village. In a mathematical model of the system, stocking prawns, coupled with infrequent mass drug treatment, eliminates schistosomiasis from high-transmission sites. We conclude that restoring river prawns could be a novel contribution to controlling, or eliminating, schistosomiasis.

PNAS↗
USGS2017

Unraveling the disease consequences and mechanisms of modular structure in animal social networks

Disease risk is a potential cost of group living. Although modular organization is thought to reduce this cost in animal societies, empirical evidence toward this hypothesis has been conflicting. We analyzed empirical social networks from 43 animal species to motivate our study of the epidemiological consequences of modular structure in animal societies. From these empirical studies, we identified the features of interaction patterns associated with network modularity and developed a theoretical network model to investigate when and how subdivisions in social networks influence disease dynamics. Contrary to prior work, we found that disease risk is largely unaffected by modular structure, although social networks beyond a modular threshold experience smaller disease burden and longer disease duration. Our results illustrate that the lowering of disease burden in highly modular social networks is driven by two mechanisms of modular organization: network fragmentation and subgroup cohesion. Highly fragmented social networks with cohesive subgroups are able to structurally trap infections within a few subgroups and also cause a structural delay to the spread of disease outbreaks. Finally, we show that network models incorporating modular structure are necessary only when prior knowledge suggests that interactions within the population are highly subdivided. Otherwise, null networks based on basic knowledge about group size and local contact heterogeneity may be sufficient when data-limited estimates of epidemic consequences are necessary. Overall, our work does not support the hypothesis that modular structure universally mitigates the disease impact of group living.

PNAS↗
USGS2017

Essential information: Uncertainty and optimal control of Ebola outbreaks

Early resolution of uncertainty during an epidemic outbreak can lead to rapid and efficient decision making, provided that the uncertainty affects prioritization of actions. The wide range in caseload projections for the 2014 Ebola outbreak caused great concern and debate about the utility of models. By coding and running 37 published Ebola models with five candidate interventions, we found that, despite this large variation in caseload projection, the ranking of management options was relatively consistent. Reducing funeral transmission and reducing community transmission were generally ranked as the two best options. Value of information (VoI) analyses show that caseloads could be reduced by 11% by resolving all model-specific uncertainties, with information about model structure accounting for 82% of this reduction and uncertainty about caseload only accounting for 12%. Our study shows that the uncertainty that is of most interest epidemiologically may not be the same as the uncertainty that is most relevant for management. If the goal is to improve management outcomes, then the focus of study should be to identify and resolve those uncertainties that most hinder the choice of an optimal intervention. Our study further shows that simplifying multiple alternative models into a smaller number of relevant groups (here, with shared structure) could streamline the decision-making process and may allow for a better integration of epidemiological modeling and decision making for policy.

Proceedings of the National Academy of Sciences of↗
USGS2019

Precision mapping of snail habitat provides a powerful indicator of human schistosomiasis transmission

Recently, the World Health Organization recognized that efforts to interrupt schistosomiasis transmission through mass drug administration have been ineffective in some regions; one of their new recommended strategies for global schistosomiasis control emphasizes targeting the freshwater snails that transmit schistosome parasites. We sought to identify robust indicators that would enable precision targeting of these snails. At the site of the world’s largest recorded schistosomiasis epidemic—the Lower Senegal River Basin in Senegal—intensive sampling revealed positive relationships between intermediate host snails (abundance, density, and prevalence) and human urogenital schistosomiasis reinfection (prevalence and intensity in schoolchildren after drug administration). However, we also found that snail distributions were so patchy in space and time that obtaining useful data required effort that exceeds what is feasible in standard monitoring and control campaigns. Instead, we identified several environmental proxies that were more effective than snail variables for predicting human infection: the area covered by suitable snail habitat (i.e., floating, nonemergent vegetation), the percent cover by suitable snail habitat, and size of the water contact area. Unlike snail surveys, which require hundreds of person-hours per site to conduct, habitat coverage and site area can be quickly estimated with drone or satellite imagery. This, in turn, makes possible large-scale, high-resolution estimation of human urogenital schistosomiasis risk to support targeting of both mass drug administration and snail control efforts.

PNAS↗
USGS2014

Susceptibility of Koi and Yellow Perch to infectious hematopoietic necrosis virus by experimental exposure

Infectious hematopoietic necrosis virus (IHNV) is a novirhabdoviral pathogen that originated in western North America among anadromous Pacific salmonids. Severe disease epidemics in the late 1970s resulting from IHNV's invasion into farmed Rainbow Trout Oncorhynchus mykiss in North America, Asia, and Europe emphasized IHNV's ability to adapt to new hosts under varying rearing conditions. Yellow Perch Perca flavescens and Koi Carp Cyprinus carpio (hereafter, “Koi”) are aquaculture-reared fish that are highly valued in sport fisheries and the ornamental fish trade, respectively, but it is unknown whether these fish species are vulnerable to IHNV infection. In this study, we exposed Yellow Perch, Koi, and steelhead (anadromous Rainbow Trout) to IHNV by intraperitoneal injection (10 6 PFU/fish) and by immersion (5.7×10 5 PFU/mL) for 7 h, and monitored fish for 28 d. The extended immersion exposure and high virus concentrations used in the challenges were to determine if the tested fish had any level of susceptibility. After experimental exposure, Yellow Perch and Koi experienced low mortality (<6%) compared with steelhead (>35%). Virus was found in dead fish of all species tested and in surviving Yellow Perch by plaque assay and quantitative reverse transcription polymerase chain reaction (qPCR), with a higher prevalence in Yellow Perch than Koi. Infectious virus was also detected in Yellow Perch out to 5 d after bath challenge. These findings indicate that Yellow Perch and Koi are highly resistant to IHNV disease under the conditions tested, but Yellow Perch are susceptible to infection and may serve as possible virus carriers.

Journal of Aquatic Animal Health↗
USGS2023

A decade of death and other dynamics: Deepening perspectives on the diversity and distribution of sea stars and wasting

Mass mortality events provide valuable insight into biological extremes and also ecological interactions more generally. The sea star wasting epidemic that began in 2013 catalyzed study of the microbiome, genetics, population dynamics, and community ecology of several high-profile species inhabiting the northeastern Pacific but exposed a dearth of information on the diversity, distributions, and impacts of sea star wasting for many lesser-known sea stars and a need for integration across scales. Here, we combine datasets from single-site to coast-wide studies, across time lines from weeks to decades, for 65 species. We evaluated the impacts of abiotic characteristics hypothetically associated with sea star wasting (sea surface temperature, pelagic primary productivity, upwelling wind forcing, wave exposure, freshwater runoff) and species characteristics (depth distribution, developmental mode, diet, habitat, reproductive period). We find that the 2010s sea star wasting outbreak clearly affected a little over a dozen species, primarily intertidal and shallow subtidal taxa, causing instantaneous wasting prevalence rates of 5%–80%. Despite the collapse of some populations within weeks, environmental and species variation protracted the outbreak, which lasted 2–3 years from onset until declining to chronic background rates of ∼2% sea star wasting prevalence. Recruitment began immediately in many species, and in general, sea star assemblages trended toward recovery; however, recovery was heterogeneous, and a marine heatwave in 2019 raised concerns of a second decline. The abiotic stressors most associated with the 2010s sea star wasting outbreak were elevated sea surface temperature and low wave exposure, as well as freshwater discharge in the north. However, detailed data speaking directly to the biological, ecological, and environmental cause(s) and consequences of the sea star wasting outbreak remain limited in scope, unavoidably retrospective, and perhaps always indeterminate. Redressing this shortfall for the future will require a broad spectrum of monitoring studies not less than the taxonomically broad cross-scale framework we have modeled in this synthesis.

Biological Bulletin↗
USGS2005

Rural cases of equine West Nile virus encephalomyelitis and the normalized difference vegetation index

Data from an outbreak (August to October, 2002) of West Nile virus (WNV) encephalomyelitis in a population of horses located in northern Indiana was scanned for clusters in time and space. One significant (p = 0.04) cluster of case premises was detected, occurring between September 4 and 10 in the south-west part of the study area (85.70??N, 45.50??W). It included 10 case premises (3.67 case premises expected) within a radius of 2264 m. Image data were acquired by the Advanced Very High Resolution Radiometer (AVHRR) sensor onboard a National Oceanic and Atmospheric Administration polar-orbiting satellite. The Normalized Difference Vegetation Index (NDVI) was calculated from visible and near-infrared data of daily observations, which were composited to produce a weekly-1km2 resolution raster image product. During the epidemic, a significant (p<0.01) decrease (0.025 per week) in estimated NDVI was observed at all case and control premise sites. The median estimated NDVI (0.659) for case premises within the cluster identified was significantly (p<0.01) greater than the median estimated NDVI for other case (0.571) and control (0.596) premises during the same period. The difference in median estimated NDVI for case premises within this cluster, compared to cases not included in this cluster, was greatest (5.3% and 5.1%, respectively) at 1 and 5 weeks preceding occurrence of the cluster. The NDVI may be useful for identifying foci of WNV transmission. ?? Mary Ann Liebert, Inc.

Vector-Borne and Zoonotic Diseases↗
USGS2008

Cancer mortality in a Chinese population exposed to hexavalent chromium in drinking water

BACKGROUND: In 1987, investigators in Liaoning Province, China, reported that mortality rates for all cancer, stomach cancer, and lung cancer in 1970-1978 were higher in villages with hexavalent chromium (Cr)-contaminated drinking water than in the general population. The investigators reported rates, but did not report statistical measures of association or precision. METHODS: Using reports and other communications from investigators at the local Jinzhou Health and Anti-Epidemic Station, we obtained data on Cr contamination of groundwater and cancer mortality in 9 study regions near a ferrochromium factory. We estimated:(1) person-years at risk in the study regions, based on census and population growth rate data, (2) mortality counts, based on estimated person-years at risk and previously reported mortality rates, and (3) rate ratios and 95% confidence intervals. RESULTS: The all-cancer mortality rate in the combined 5 study regions with Cr-contaminated water was negligibly elevated in comparison with the rate in the 4 combined study regions without contaminated water (rate ratio = 1.13; 95% confidence interval = 0.86-1.46), but was somewhat more elevated in comparison with the whole province (1.23; 0.97-1.53). Stomach cancer mortality in the regions with contaminated water was more substantially elevated in comparison with the regions without contaminated water (1.82; 1.11-2.91) and the whole province (1.69; 1.12-2.44). Lung cancer mortality was slightly elevated in comparison with the unexposed study regions (1.15; 0.62-2.07), and more strongly elevated in comparison with the whole province (1.78; 1.03-2.87). Mortality from other cancers combined was not elevated in comparison with either the unexposed study regions (0.86; 0.53-1.36) or the whole province (0.92; 0.58-1.38). CONCLUSIONS: While these data are limited, they are consistent with increased stomach cancer risk in a population exposed to Cr in drinking water. ?? 2008 Lippincott Williams & Wilkins, Inc.

Epidemiology↗
USGS2019

Concurrent assessment of epidemiological and operational uncertainties for optimal outbreak control: Ebola as a case study

Determining how to best manage an epidemiological outbreak may be hindered by both epidemiological uncertainty (i.e. about epidemiological processes) and operational uncertainty (i.e. about the effectiveness of candidate interventions). These two uncertainties are rarely addressed concurrently in epidemic studies, impeding decision-making. We present an approach to simultaneously address both sources of uncertainty. Epidemiological uncertainty is represented by a large ensemble of models of the 2014 West African Ebola outbreak. Operational uncertainty about the effectiveness of three classes of intervention is assessed for a wide range of potential effectiveness for each intervention. We ranked each intervention in terms of caseload reduction in each model, initially assuming an unlimited budget. To explore the role of budget limitation, we assessed the influence of three candidate cost functions relating intervention effectiveness and cost for different budget levels. The Value of Information (VoI) to resolve uncertainty is generally high in this study; appropriate information gain could reduce expected caseload by more than 50%. The ranking of interventions is jointly determined by the underlying epidemiological process, the effectiveness of the interventions and the size of the budget available for the program. An epidemiologically effective intervention might not be optimal if its costs outweigh its epidemiological benefit. Under higher budget conditions, resolution of epidemiological uncertainty is most valuable. When budgets are tight, however, operational and epidemiological uncertainty are equally important. Overall, our study demonstrates that significant public health improvements could result from a careful examination of both epidemiological and operational uncertainties within the same modelling structure. This approach can be applied to decision-making for management of other diseases for which multiple models and multiple interventions are available.

Proceedings of the Royal Society B↗
USGS2025

Systematic shifts in the variation among host individuals must be considered in climate-disease theory

To make more informed predictions of host–pathogen interactions under climate change, studies have incorporated the thermal performance of host, vector and pathogen traits into disease models to quantify effects on average transmission rates. However, this body of work has omitted the fact that variation in susceptibility among individual hosts affects disease spread and long-term patterns of host population dynamics. Furthermore, and especially for ectothermic host species, variation in susceptibility is likely to be plastic, influenced by variables such as environmental temperature. For example, as host individuals respond idiosyncratically to temperature, this could affect the population-level variation in susceptibility, such that there may be predictable functional relationships between variation in susceptibility and temperature. Quantifying the relationship between temperature and among-host trait variation will therefore be critical for predicting how climate change and disease will interact to influence host–pathogen population dynamics. Here, we use a model to demonstrate how short-term effects of temperature on the distribution of host susceptibility can drive epidemic characteristics, fluctuations in host population sizes and probabilities of host extinction. Our results emphasize that more research is needed in disease ecology and climate biology to understand the mechanisms that shape individual trait variation, not just trait averages.

Proceedings of the Royal Society B: Biological Sci↗
USGS2026

Stochastic within-host dynamics and climate-sensitive traits generate predictable patterns of variation in disease outcomes

Understanding how climatic variables impact host-pathogen relationships in temperature-sensitive ectothermic host organisms is crucial under global change. Few studies have explored how temperature gradients generate inter-individual variation in epidemiological traits like host susceptibility or pathogen replication. Here, we develop a mathematical model to explore a novel hypothesis: stochastic within-host dynamics and simulated thermal mismatches between host and pathogen traits generate predictable variation in infection outcomes among hosts and across thermal gradients. Our model demonstrates that varying trait thermal optima in host immunity and pathogen replication, and stochastic within-host processes produced variation in infection outcomes. Variability was low when temperatures strongly favored host or pathogen traits, but high and diverse when their performance was similar across a broad thermal range. In contrast, when trait performance was equal across all temperatures (no mismatch) variability remained low at all temperatures. Further, the magnitude of variation, quantified by entropy, exhibited predictable patterns depending on host-pathogen thermal mismatches. We conclude that interactions between trait thermal mismatches and within-host stochasticity provide a theoretical framework to improve ectotherm disease models under climate change, providing a valuable tool for exploring the impacts of environmental change on epizootic or epidemic dynamics, particularly in vulnerable marine ecosystems.

Philosophical Transactions of the Royal Society, S↗
USGS2026

The impacts of co-circulating pathogens in Pacific herring depend on interactions between viral life-cycle traits and transmission parameters, highlighting interdependencies between pathogen epizootics

The average host susceptibility decreases as the epizootic progresses because easily infected hosts are first removed from the population. While host susceptibility is pathogen-specific, it is likely that host susceptibility is correlated between different pathogens, so that co-circulating pathogens may have reciprocal impacts on their epidemics. However, despite well-documented examples of concomitant infections in marine hosts, reciprocal epizootic effects have not been documented in wild marine organisms. We quantify reciprocal impacts between viral haemorrhagic septicaemia and viral erythrocytic necrosis in Pacific herring ( Clupea pallasii ) using field and laboratory work. We show that the causative viruses for both diseases circulate through herring populations and that infection with one pathogen has negative impacts on the epizootic and infection characteristics of the other pathogen, suggesting positive correlations in the susceptibility to infection between pathogens. We then use simulations of a two-strain pathogen model to show that the impact of the correlation is modulated by transmission parameters, such as the incubation period and the initial transmission rate. Our work shows that co-occurring epizootics pose a management challenge because single-pathogen management actions may amplify the epizootics of the non-targeted pathogen. This study provides a framework to evaluate the consequences of reciprocal epizootic impacts through field, experimental and modelling work.

Washington↗
USGS2003

Phylogeography of infectious haematopoietic necrosis virus in North America

Infectious hematopoietic necrosis virus (IHNV) is a rhabdoviral pathogen that infects wild and cultured salmonid fish throughout the Pacific Northwest of North America. IHNV causes severe epidemics in young fish and can cause disease or occur asymptomatically in adults. In a broad survey of 323 IHNV field isolates, sequence analysis of a 303 nucleotide variable region within the glycoprotein gene revealed a maximum nucleotide diversity of 8·6 %, indicating low genetic diversity overall for this virus. Phylogenetic analysis revealed three major virus genogroups, designated U, M and L, which varied in topography and geographical range. Intragenogroup genetic diversity measures indicated that the M genogroup had three- to fourfold more diversity than the other genogroups and suggested relatively rapid evolution of the M genogroup and stasis within the U genogroup. We speculate that factors influencing IHNV evolution may have included ocean migration ranges of their salmonid host populations and anthropogenic effects associated with fish culture.

Journal of General Virology↗
USGS2018

Decision making for mitigating wildlife diseases: From theory to practice for an emerging fungal pathogen of amphibians

Conservation science can be most effective in its decision‐support role when seeking answers to clearly formulated questions of direct management relevance. Emerging wildlife diseases, a driver of global biodiversity loss, illustrate the challenges of performing this role: in spite of considerable research, successful disease mitigation is uncommon. Decision analysis is increasingly advocated to guide mitigation planning, but its application remains rare. Using an integral projection model, we explored potential mitigation actions for avoiding population declines and the ongoing spatial spread of the fungus Batrachochytrium salamandrivorans ( Bsal ). This fungus has recently caused severe amphibian declines in north‐western Europe and currently threatens Palearctic salamander diversity. Available evidence suggests that a Bsal outbreak in a fire salamander ( Salamandra salamandra ) population will lead to its rapid extirpation. Treatments such as antifungals or probiotics would need to effectively interrupt transmission (reduce probability of infection by nearly 90%) in order to reduce the risk of host extirpation and successfully eradicate the pathogen. Improving the survival of infected hosts is most likely to be detrimental as it increases the potential for pathogen transmission and spread. Active removal of a large proportion of the host population has some potential to locally eradicate Bsal and interrupt its spread, depending on the presence of Bsal reservoirs and on the host's spatial dynamics, which should therefore represent research priorities. Synthesis and applications . Mitigation of Batrachochytrium salamandrivorans epidemics in susceptible host species is highly challenging, requiring effective interruption of transmission and radical removal of host individuals. More generally, our study illustrates the advantages of framing conservation science directly in the management decision context, rather than adapting to it a posteriori .

Journal of Applied Ecology↗