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Results for “Epidemics”

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At least 91 records · Page 5Linked to original sources

USGS2001

Decline of disjunct green salamander (Aneides aeneus) populations in the southern appalachians

Coincident with other amphibians around the world Aneides aeneus, a terrestrial plethodontid salamander, suffered a population collapse in a disjunct portion of its range in the mid-late 1970s. Long-term monitoring of seven historical green salamander populations throughout the 1990s showed a 98% decline in relative abundance since 1970. Three out of six populations first discovered in 1991 also crashed in 1996-1997. The synchronized suddenness of the declines, their region-wide impact, and effects on both small and larger populations, suggest the role of a novel agent of mortality beginning in the mid-late 1970s. Acting alone, but more likely in concert, habitat loss, overcollecting, epidemic disease and climate change could account for this region-wide decline.

Biological Conservation↗

USGS2016

A synthetic review of notoedres species mites and mange

Notoedric mange, caused by obligately parasitic sarcoptiform Notoedres mites, is associated with potentially fatal dermatitis with secondary systemic disease in small mammals, felids and procyonids among others, as well as an occasional zoonosis. We describe clinical spectra in non-chiropteran hosts, review risk factors and summarize ecological and epidemiological studies. The genus is disproportionately represented on rodents. Disease in felids and procyonids ranges from very mild to death. Knowledge of the geographical distribution of the mites is highly inadequate, with focal hot spots known for Notoedres cati in domestic cats and bobcats. Predisposing genetic and immunological factors are not known, except that co-infection with other parasites and anticoagulant rodenticide toxicoses may contribute to severe disease. Treatment of individual animals is typically successful with macrocytic lactones such as selamectin, but herd or wildlife population treatment has not been undertaken. Transmission requires close contact and typically is within a host species. Notoedric mange can kill half all individuals in a population and regulate host population below non-diseased density for decades, consistent with frequency-dependent transmission or spillover from other hosts. Epidemics are increasingly identified in various hosts, suggesting global change in suitable environmental conditions or increased reporting bias.

Parasitology↗

USGS2001

How are climate and marine biological outbreaks functionally linked?

Since the mid-1970s, large-scale episodic events such as disease epidemics, mass mortalities, harmful algal blooms and other population explosions have been occurring in marine environments at an historically unprecedented rate. The variety of organisms involved (host, pathogens and other opportunists) and the absolute number of episodes have also increased during this period. Are these changes coincidental? Between 1972 and 1976, a global climate regime shift took place, and it is manifest most clearly by a change in strength of the North Pacific and North Atlantic pressure systems. Consequences of this regime shift are: (1) prolonged drought conditions in the Sahel region of Africa; (2) increased dust supply to the global atmosphere, by a factor of approximately four; (3) increased easterly trade winds across the Atlantic; (4) increased eolian transport of dust to the Atlantic and Caribbean basins; and (5) increased deposition of iron-rich eolian dust to typically iron-poor marine regions. On the basis of well-documented climate and dust observations and the widely accepted increase in marine outbreak rates, this paper proposes that the increased iron supply has altered the micronutrient factors limiting growth of opportunistic organisms and virulence of pathogenic microbes, particularly in macronutrient-rich coastal systems.

Hydrobiologia↗

USGS2002

A public health issue related to collateral seismic hazards: The valley fever outbreak triggered by the 1994 Northridge, California earthquake

Following the 17 January 1994 Northridge. California earthquake (M = 6.7), Ventura County, California, experienced a major outbreak of coccidioidomycosis (CM), commonly known as valley fever, a respiratory disease contracted by inhaling airborne fungal spores. In the 8 weeks following the earthquake (24 January through 15 March), 203 outbreak-associated cases were reported, which is about an order of magnitude more than the expected number of cases, and three of these cases were fatal. Simi Valley, in easternmost Ventura County, had the highest attack rate in the county, and the attack rate decreased westward across the county. The temporal and spatial distribution of CM cases indicates that the outbreak resulted from inhalation of spore-contaminated dust generated by earthquake-triggered landslides. Canyons North East of Simi Valley produced many highly disrupted, dust-generating landslides during the earthquake and its aftershocks. Winds after the earthquake were from the North East, which transported dust into Simi Valley and beyond to communities to the West. The three fatalities from the CM epidemic accounted for 4 percent of the total earthquake-related fatalities.

Surveys in Geophysics↗

USGS2011

Detecting aseismic strain transients from seismicity data

Aseismic deformation transients such as fluid flow, magma migration, and slow slip can trigger changes in seismicity rate. We present a method that can detect these seismicity rate variations and utilize these anomalies to constrain the underlying variations in stressing rate. Because ordinary aftershock sequences often obscure changes in the background seismicity caused by aseismic processes, we combine the stochastic Epidemic Type Aftershock Sequence model that describes aftershock sequences well and the physically based rate‐ and state‐dependent friction seismicity model into a single seismicity rate model that models both aftershock activity and changes in background seismicity rate. We implement this model into a data assimilation algorithm that inverts seismicity catalogs to estimate space‐time variations in stressing rate. We evaluate the method using a synthetic catalog, and then apply it to a catalog of M ≥ 1.5 events that occurred in the Salton Trough from 1990 to 2009. We validate our stressing rate estimates by comparing them to estimates from a geodetically derived slip model for a large creep event on the Obsidian Buttes fault. The results demonstrate that our approach can identify large aseismic deformation transients in a multidecade long earthquake catalog and roughly constrain the absolute magnitude of the stressing rate transients. Our method can therefore provide a way to detect aseismic transients in regions where geodetic resolution in space or time is poor.

Journal of Geophysical Research B: Solid Earth↗

USGS2020

The role of seismic and slow slip events in triggering the 2018 M7.1 Anchorage earthquake in the Southcentral Alaska subduction zone

The M 7.1 2018 Anchorage earthquake occurred in the bending part of the subducting North Pacific plate near the geometrical barrier formed by the underthrusting Yakutat terrane. We calculate the triggering potential related with stress redistribution from deformation sources including the M 9.2 1964 earthquake coseismic slip, postseismic deformation, slip from regional M > 5 earthquakes, and the cumulative slip of previously detected slow slip events over the past 55 years. We investigate the deeper shallow depth (20–60 km) seismicity response to these perturbations using an epidemic type aftershock sequence model to describe earthquake‐to‐earthquake interactions. The statistical forecast captures the triggered seismicity during the 1983 M 6+ aftershocks in Columbia Bay but performs poorly during the slow slip event period between 1992.0 and 2004.8 that presents a statistically significant rate change ( β , Z > 2; M < 4.0). We find that stress effects from the 1964 postseismic source and the 12‐year‐long slow slip event (~ M 7.8) contribute to the 2018 Anchorage earthquake occurrence and that slow slip events modulate the deeper shallow depth seismicity patterns in the region.

Alaska↗

USGS2021

Spatial clustering of aftershocks impacts the performance of physics‐based earthquake forecasting models

I explore why physics‐based models of earthquake triggering rarely outperform statistical models in prospective testing, outside of limited spatial‐temporal windows. Pseudo‐prospective tests on suites of synthetic aftershock sequences show that a major factor is the level of unmodeled spatial clustering of the direct aftershocks triggered by the mainshock. The synthetic sequences are generated from generalized “physical” triggering models, optionally superimposed on background heterogeneity that controls the level of clustering. The statistical Epidemic Type Aftershock Sequence (ETAS) model performs relatively better the more clustered the direct aftershocks, while the true generalized “physical” model performs relatively worse. Real aftershocks appear to be sufficiently clustered to allow ETAS to perform as well as or better than physical models such as Coulomb stress triggering. A likely cause of the spatial clustering of direct aftershocks is heterogeneity of the background physical conditions, which typically is not modeled in physics‐based forecasts. This implies that the forecast performance of physical models could be substantially improved through a better understanding of the interaction between earthquake stress changes and variable background physical conditions such as stress state, fault strength, and fluid pressure.

JGR Solid Earth↗

USGS2021

Alpine glacier reveals ecosystem impacts of Europe's prosperity and peril over the last millennium

Information about past ecosystem dynamics and human activities is stored in the ice of Colle Gnifetti glacier in the Swiss Alps. Adverse climatic intervals incurred crop failures and famines and triggered reestablishment of forest vegetation but also societal resilience through innovation. Historical documents and lake sediments record these changes at local—regional scales but often struggle to comprehensively document continental-scale impacts on ecosystems. Here, we provide unique multiproxy evidence of broad-scale ecosystem, land use, and climate dynamics over the past millennium from a Colle Gnifetti microfossil and oxygen isotope record. Microfossil data indicate that before 1750 CE forests and fallow land rapidly replaced crop cultivation during historically documented societal crises caused by climate shifts and epidemics. Subsequently, with technology and the introduction of more resilient crops, European societies adapted to the Little Ice Age cold period, but resource overexploitation and industrialization led to new regional to global-scale environmental challenges.

Geophysical Research Letters↗

USGS2022

On the use of high-resolution and deep-learning seismic catalogs for short-term earthquake forecasts: Potential benefits and current limitations

Enhanced earthquake catalogs provide detailed images of evolving seismic sequences. Currently, these data sets take some time to be released but will soon become available in real time. Here, we explore whether and how enhanced seismic catalogs feeding into established short-term earthquake forecasting protocols may result in higher predictive skill. We consider three enhanced catalogs for the 2016–2017 Central Italy sequence, featuring a bulk completeness lower by at least two magnitude units compared to the real-time catalog and an improved hypocentral resolution. We use them to inform a set of physical Coulomb Rate-and-State (CRS) and statistical Epidemic-Type Aftershock Sequence (ETAS) models to forecast the space-time occurrence of M3+ events during the first 6 months of the sequence. We track model performance using standard likelihood-based metrics and compare their skill against the best-performing CRS and ETAS models among those developed with the real-time catalog. We find that while the incorporation of the triggering contributions from new small magnitude detections of the enhanced catalogs is beneficial for both types of forecasts, these models do not significantly outperform their respective near real-time benchmarks. To explore the reasons behind this result, we perform targeted sensitivity tests that show how (a) the typical spatial discretizations of forecast experiments ( 2 km) hamper the ability of models to capture highly localized secondary triggering patterns and (b) differences in earthquake parameters (i.e., magnitude and hypocenters) reported in different catalogs can affect forecast evaluation. These findings will contribute toward improving forecast model design and evaluation strategies for next-generation seismic catalogs.

Journal of Geophysical Research--Solid Earth↗

USGS2025

Sea star wasting disease mystery finally solved

A decade after a marine epidemic killed off sea stars and triggered ecosystem-wide effects along the Pacific Coast of North America, researchers have identified the bacterial pathogen that is responsible for sea star wasting disease.

Nature Ecology and Evolution↗

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↗