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At least 127 records · Page 7Linked to original sources
USGS2023

Characteristics of a sea louse (Caligus clemensi) epizootic in wild Pacific herring (Clupea pallasii)

We characterized a natural sea louse epizootic of Caligus clemensi and the effects of parasitism on Pacific herring Clupea pallasii in Port Angeles Harbor, WA, USA. Infestation prevalence on newly metamorphosed age 0 Pacific herring reached 100% prevalence by mid-August. At this time, the mean louse intensity was 4.6 lice/fish, and a positive correlation occurred between louse intensity and herring body length. The epizootic then waned, with infestation prevalence decreasing to less than 25% and the mean parasite intensity falling below 1 louse. While skin injuries were not detected, motile lice preferentially aggregated around head and anterior dorsal areas. However, louse tropism became evenly distributed over the body as the parasite intensity increased. Louse-induced mortality in herring was negligible in controlled experiments. These results indicate that Caligus clemensi epizootics reach high prevalence, but also fade from mid-summer to early fall. Due to the predominant presence of motile copepod stages, we suggest that the epizootic fades because lice complete their life cycle and dislodge from the host; however, multiple explanations for epidemic fading are possible.

Washington↗
USGS2025

Risk implications of Poisson assumptions and declustering inferred from a fully time-dependent earthquake forecast

We use the Third Uniform California Earthquake Rupture Forecast Epidemic Type Aftershock Sequence model, which is fully time-dependent in terms of including spatiotemporal clustering, to evaluate the effects of the Poisson assumption and declustering algorithms on statewide loss exceedance curves. The model is simulation based, meaning it produces synthetic catalogs that exhibit realistic behavior with respect to aftershocks and multi-fault earthquakes. A Poisson version of the model was constructed by randomizing event times, and the influence of two declustering algorithms was examined as well. We demonstrate that the probability of one-or-more loss exceedances (occurrence exceedance probability) is greater for the Poisson model because it has fewer seismically quiet time windows. The discrepancy between dollar loss estimates with a given exceedance probability is up to a factor of 32% but varies depending on the loss threshold (the x-axis value) and the forecast duration (we examined a range between 24 h and 50 years, with the discrepancy for the latter being negligible). We discuss how the one-or-more loss exceedance metric is questionable because it ignores all but the maximum loss experienced in each timeframe. An alternative metric based on total aggregate loss in each time window (aggregate exceedance probability) was therefore also examined, for which the Poisson model again implies higher risk at intermediate losses but lower risk at higher losses (because large, triggered events now contribute to total aggregate losses for the fully time-dependent model). We also argue that declustering is not a scientifically justifiable way to deal with full time dependence, in agreement with a chorus from other recent studies. It is difficult to draw generally applicable conclusions from our study, in part because application specific details will likely be important, but our results highlight how full time dependence can be reckoned with once authoritative forecast models are made available.

California↗
USGS2017

A prototype operational earthquake loss model for California based on UCERF3-ETAS – A first look at valuation

We present a prototype operational loss model based on UCERF3-ETAS, which is the third Uniform California Earthquake Rupture Forecast with an Epidemic Type Aftershock Sequence (ETAS) component. As such, UCERF3-ETAS represents the first earthquake forecast to relax fault segmentation assumptions and to include multi-fault ruptures, elastic-rebound, and spatiotemporal clustering, all of which seem important for generating realistic and useful aftershock statistics. UCERF3-ETAS is nevertheless an approximation of the system, however, so usefulness will vary and potential value needs to be ascertained in the context of each application. We examine this question with respect to statewide loss estimates, exemplifying how risk can be elevated by orders of magnitude due to triggered events following various scenario earthquakes. Two important considerations are the probability gains, relative to loss likelihoods in the absence of main shocks, and the rapid decay of gains with time. Significant uncertainties and model limitations remain, so we hope this paper will inspire similar analyses with respect to other risk metrics to help ascertain whether operationalization of UCERF3-ETAS would be worth the considerable resources required.

Earthquake Spectra↗
USGS2018

Global Earthquake Model (GEM) Risk Map

The Global Earthquake Risk Map (v2018.1) comprises four global maps. The main map presents the geographic distribution of average annual loss (USD) normalized by the average construction costs of the respective country (USD/m2 due to ground shaking in the residential, commercial and industrial building stock, considering contents, structural and non-structural components. The normalized metric allows a direct comparison of the risk between countries with widely different construction costs. It does not consider the effects of tsunamis, liquefaction, landslides, and fires following earthquakes. The loss estimates are from direct physical damage to buildings due to shaking, and thus damage to infrastructure or indirect losses due to business interruption are not included. The Global Earthquake Hazard Map depicts the geographic distribution of the Peak Ground Acceleration (PGA) with a 10% probability of being exceeded in 50 years, computed for reference rock conditions (shear wave velocity of 760-800 m/s). The Global Exposure Map depicts the geographic distribution of residential, commercial and industrial buildings. The Global Seismic Fatalities Map depicts an estimate of average annual human losses due to earthquake-induced structural collapse of buildings. The results for human losses do not consider indirect fatalities such as those from post­ earthquake epidemics. The average annual losses and number of buildings are presented on a hexagonal grid, with a spacing of 0.30 x 0.34 decimal degrees (approximately 1,000 km2 at the equator). The average annual losses were computed using the event-based calculator of the OpenQuake engine, an open-source software for seismic hazard and risk analysis developed by the GEM Foundation. The seismic hazard, exposure and vulnerability models employed in these calculations were provided by national institutions, or developed within the scope of regional programs or bilateral collaborations. These global maps and the underlying databases are based on best available and publicly accessible datasets and models. Due to possible limitations in the model, regions portrayed with low risk may experience potentially damaging earthquakes. The GEM Risk Map is intended to be a dynamic product, which will be updated when new datasets and models become available. Updated versions of the hazard, exposure, and average annual losses will be released on a regular basis. Additional metrics for each country can be explored at globalquakemodel.org/gem.

Report↗
USGS2021

Strategic testing approaches for targeted disease monitoring can be used to inform pandemic decision-making

More than 1.6 million Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) tests were administered daily in the United States at the peak of the epidemic, with a significant focus on individual treatment. Here, we show that objective-driven, strategic sampling designs and analyses can maximize information gain at the population level, which is necessary to increase situational awareness and predict, prepare for, and respond to a pandemic, while also continuing to inform individual treatment. By focusing on specific objectives such as individual treatment or disease prediction and control (e.g., via the collection of population-level statistics to inform lockdown measures or vaccine rollout) and drawing from the literature on capture–recapture methods to deal with nonrandom sampling and testing errors, we illustrate how public health objectives can be achieved even with limited test availability when testing programs are designed a priori to meet those objectives.

PLoS Biology↗
USGS2021

Synergistic interventions to control COVID-19: Mass testing and isolation mitigates reliance on distancing

Stay-at-home orders and shutdowns of non-essential businesses are powerful, but socially costly, tools to control the pandemic spread of SARS-CoV-2. Mass testing strategies, which rely on widely administered frequent and rapid diagnostics to identify and isolate infected individuals, could be a potentially less disruptive management strategy, particularly where vaccine access is limited. In this paper, we assess the extent to which mass testing and isolation strategies can reduce reliance on socially costly non-pharmaceutical interventions, such as distancing and shutdowns. We develop a multi-compartmental model of SARS-CoV-2 transmission incorporating both preventative non-pharmaceutical interventions (NPIs) and testing and isolation to evaluate their combined effect on public health outcomes. Our model is designed to be a policy-guiding tool that captures important realities of the testing system, including constraints on test administration and non-random testing allocation. We show how strategic changes in the characteristics of the testing system, including test administration, test delays, and test sensitivity, can reduce reliance on preventative NPIs without compromising public health outcomes in the future. The lowest NPI levels are possible only when many tests are administered and test delays are short, given limited immunity in the population. Reducing reliance on NPIs is highly dependent on the ability of a testing program to identify and isolate unreported, asymptomatic infections. Changes in NPIs, including the intensity of lockdowns and stay at home orders, should be coordinated with increases in testing to ensure epidemic control; otherwise small additional lifting of these NPIs can lead to dramatic increases in infections, hospitalizations and deaths. Importantly, our results can be used to guide ramp-up of testing capacity in outbreak settings, allow for the flexible design of combined interventions based on social context, and inform future cost-benefit analyses to identify efficient pandemic management strategies.

PLOS Computational Biology↗
USGS2024

Potential impact of annual vaccination with reformulated COVID-19 vaccines: Lessons from the US COVID-19 scenario modeling hub

Background Coronavirus Disease 2019 (COVID-19) continues to cause significant hospitalizations and deaths in the United States. Its continued burden and the impact of annually reformulated vaccines remain unclear. Here, we present projections of COVID-19 hospitalizations and deaths in the United States for the next 2 years under 2 plausible assumptions about immune escape (20% per year and 50% per year) and 3 possible CDC recommendations for the use of annually reformulated vaccines (no recommendation, vaccination for those aged 65 years and over, vaccination for all eligible age groups based on FDA approval). Methods and findings The COVID-19 Scenario Modeling Hub solicited projections of COVID-19 hospitalization and deaths between April 15, 2023 and April 15, 2025 under 6 scenarios representing the intersection of considered levels of immune escape and vaccination. Annually reformulated vaccines are assumed to be 65% effective against symptomatic infection with strains circulating on June 15 of each year and to become available on September 1. Age- and state-specific coverage in recommended groups was assumed to match that seen for the first (fall 2021) COVID-19 booster. State and national projections from 8 modeling teams were ensembled to produce projections for each scenario and expected reductions in disease outcomes due to vaccination over the projection period. From April 15, 2023 to April 15, 2025, COVID-19 is projected to cause annual epidemics peaking November to January. In the most pessimistic scenario (high immune escape, no vaccination recommendation), we project 2.1 million (90% projection interval (PI) [1,438,000, 4,270,000]) hospitalizations and 209,000 (90% PI [139,000, 461,000]) deaths, exceeding pre-pandemic mortality of influenza and pneumonia. In high immune escape scenarios, vaccination of those aged 65+ results in 230,000 (95% confidence interval (CI) [104,000, 355,000]) fewer hospitalizations and 33,000 (95% CI [12,000, 54,000]) fewer deaths, while vaccination of all eligible individuals results in 431,000 (95% CI: 264,000–598,000) fewer hospitalizations and 49,000 (95% CI [29,000, 69,000]) fewer deaths. Conclusions COVID-19 is projected to be a significant public health threat over the coming 2 years. Broad vaccination has the potential to substantially reduce the burden of this disease, saving tens of thousands of lives each year.

PLOS Medicine↗
USGS2013

Use of exposure history to identify patterns of immunity to pneumonia in bighorn sheep (Ovis canadensis)

Individual host immune responses to infectious agents drive epidemic behavior and are therefore central to understanding and controlling infectious diseases. However, important features of individual immune responses, such as the strength and longevity of immunity, can be challenging to characterize, particularly if they cannot be replicated or controlled in captive environments. Our research on bighorn sheep pneumonia elucidates how individual bighorn sheep respond to infection with pneumonia pathogens by examining the relationship between exposure history and survival in situ. Pneumonia is a poorly understood disease that has impeded the recovery of bighorn sheep (Ovis canadensis) following their widespread extirpation in the 1900s. We analyzed the effects of pneumonia-exposure history on survival of 388 radio-collared adults and 753 ewe-lamb pairs. Results from Cox proportional hazards models suggested that surviving ewes develop protective immunity after exposure, but previous exposure in ewes does not protect their lambs during pneumonia outbreaks. Paradoxically, multiple exposures of ewes to pneumonia were associated with diminished survival of their offspring during pneumonia outbreaks. Although there was support for waning and boosting immunity in ewes, models with consistent immunizing exposure were similarly supported. Translocated animals that had not previously been exposed were more likely to die of pneumonia than residents. These results suggest that pneumonia in bighorn sheep can lead to aging populations of immune adults with limited recruitment. Recovery is unlikely to be enhanced by translocating nai¨ve healthy animals into or near populations infected with pneumonia pathogens.

Idaho↗
USGS1935

The protozoan diseases of hatchery fish

Following the somewhat bleak picture painted in the consideration of the bacterial diseases of hatchery fish in the last number of The Progressive Fish Culturist, it is a relief to turn to another large group of fish diseases caused by small, single-celled parasitic animals known as the protozoa. To the hatcheryman, the protozoan diseases of fish are just as important as the bacterial diseases for they are equally destructive if allowed to run unchecked. The protozoan diseases are just as common as those caused by bacteria, particularly at those hatcheries which depend upon lakes or streams for their water supplies. However, a very cheery point of difference exists between these two groups of diseases—the protozoan diseases are easier to recognize and, for the most part, they are exceedingly easy to eradicate. To the hatcheryman who has struggled day and night for weeks in an attempt to combat an epidemic wherein he is rewarded immediately by the satisfying sight of a complete recovery of his infected fish as the direct result of his labors.

Progressive Fish-Culturist↗
USGS1939

Simplified methods for the prolonged treatment of fish diseases

The prevention or control of epidemics of fish diseases by applying a disinfecting solution in a uniform concentration directly to the water supply of a fish pond or trough for a definite period of time has been exceedingly slow in development. In so far as can be determined, the original idea should be credited to. Marsh and Robinson (1910). In their work on the control of algae in fish ponds by the continuous application of dilute copper sulphate solution, administered to the inflowing water supply by means of a floating syphon, they suggested this method as a possibility in the treatment of fish diseases. Following their work, this commendable idea seems to have remained quite dormant and apparently forgotten until Hess (1930) revived it twenty or more years later. This worker found that a prolonged immersion in a dilute disinfecting bath was more efficacious in remowng fluke parasites from goldfish than was the customary short "hand dip" method. Kingsbury and Embody (1932) later adapted the idea of a prolonged treatment to running water by the use of a float valve for maintaining a constant level in a reservoir, resulting in a constant flow to the pond or trough to be treated. Shortly thereafter, Fish (1933) modified the floating syphon of Marsh and Robinson, as it was a simpler apparatus than that of Kingsbury and Embody.

Transactions of the American Fisheries Society↗
USGS2004

West Nile Virus and wildlife

West Nile virus (WNV) has spread rapidly across North America, resulting in human deaths and in the deaths of untold numbers of birds, mammals, and reptiles. The virus has reached Central America and the Caribbean and may spread to Hawaii and South America. Although tens of thousands of birds have died, and studies of some bird species show local declines, few regionwide declines can be attributed to WNV. Predicting future impacts of WNV on wildlife, and pinpointing what drives epidemics, will require substantial additional research into host susceptibility, reservoir competency, and linkages between climate, mosquitoes, and disease. Such work will entail a collaborative effort between scientists in governmental research groups, in surveillance and control programs, and in nongovernmental organizations. West Nile virus was not the first, and it will not be the last, exotic disease to be introduced to the New World. Its spread in North America highlights the need to strengthen animal monitoring programs and to integrate them with research on disease ecology.

BioScience↗
USGS2013

Modeling earthquake rate changes in Oklahoma and Arkansas: possible signatures of induced seismicity

The rate of ML≥3 earthquakes in the central and eastern United States increased beginning in 2009, particularly in Oklahoma and central Arkansas, where fluid injection has occurred. We find evidence that suggests these rate increases are man‐made by examining the rate changes in a catalog of ML≥3 earthquakes in Oklahoma, which had a low background seismicity rate before 2009, as well as rate changes in a catalog of ML≥2.2 earthquakes in central Arkansas, which had a history of earthquake swarms prior to the start of injection in 2009. In both cases, stochastic epidemic‐type aftershock sequence models and statistical tests demonstrate that the earthquake rate change is statistically significant, and both the background rate of independent earthquakes and the aftershock productivity must increase in 2009 to explain the observed increase in seismicity. This suggests that a significant change in the underlying triggering process occurred. Both parameters vary, even when comparing natural to potentially induced swarms in Arkansas, which suggests that changes in both the background rate and the aftershock productivity may provide a way to distinguish man‐made from natural earthquake rate changes. In Arkansas we also compare earthquake and injection well locations, finding that earthquakes within 6 km of an active injection well tend to occur closer together than those that occur before, after, or far from active injection. Thus, like a change in productivity, a change in interevent distance distribution may also be an indicator of induced seismicity.

Arkansas;Oklahoma↗
USGS2015

Southern San Andreas Fault seismicity is consistent with the Gutenberg-Richter magnitude-frequency distribution

The magnitudes of any collection of earthquakes nucleating in a region are generally observed to follow the Gutenberg-Richter (G-R) distribution. On some major faults, however, paleoseismic rates are higher than a G-R extrapolation from the modern rate of small earthquakes would predict. This, along with other observations, led to formulation of the characteristic earthquake hypothesis, which holds that the rate of small to moderate earthquakes is permanently low on large faults relative to the large-earthquake rate (Wesnousky et al., 1983; Schwartz and Coppersmith, 1984). We examine the rate difference between recent small to moderate earthquakes on the southern San Andreas fault (SSAF) and the paleoseismic record, hypothesizing that the discrepancy can be explained as a rate change in time rather than a deviation from G-R statistics. We find that with reasonable assumptions, the rate changes necessary to bring the small and large earthquake rates into alignment agree with the size of rate changes seen in epidemic-type aftershock sequence (ETAS) modeling, where aftershock triggering of large earthquakes drives strong fluctuations in the seismicity rates for earthquakes of all magnitudes. The necessary rate changes are also comparable to rate changes observed for other faults worldwide. These results are consistent with paleoseismic observations of temporally clustered bursts of large earthquakes on the SSAF and the absence of M greater than or equal to 7 earthquakes on the SSAF since 1857.

California↗
USGS2016

Characterizing potentially induced earthquake rate changes in the Brawley Seismic Zone, southern California

The Brawley seismic zone (BSZ), in the Salton trough of southern California, has a history of earthquake swarms and geothermal energy exploitation. Some earthquake rate changes may have been induced by fluid extraction and injection activity at local geothermal fields, particularly at the North Brawley Geothermal Field (NBGF) and at the Salton Sea Geothermal Field (SSGF). We explore this issue by examining earthquake rate changes and interevent distance distributions in these fields. In Oklahoma and Arkansas, where considerable wastewater injection occurs, increases in background seismicity rate and aftershock productivity and decreases in interevent distance were indicative of fluid‐injection‐induced seismicity. Here, we test if similar changes occur that may be associated with fluid injection and extraction in geothermal areas. We use stochastic epidemic‐type aftershock sequence models to detect changes in the underlying seismogenic processes, shown by statistically significant changes in the model parameters. The most robust model changes in the SSGF roughly occur when large changes in net fluid production occur, but a similar correlation is not seen in the NBGF. Also, although both background seismicity rate and aftershock productivity increased for fluid‐injection‐induced earthquake rate changes in Oklahoma and Arkansas, the background rate increases significantly in the BSZ only, roughly corresponding with net fluid production rate increases. Moreover, in both fields the interevent spacing does not change significantly during active energy projects. This suggests that, although geothermal field activities in a tectonically active region may not significantly change the physics of earthquake interactions, earthquake rates may still be driven by fluid injection or extraction rates, particularly in the SSGF.

California↗
USGS2017

A spatiotemporal clustering model for the Third Uniform California Earthquake Rupture Forecast (UCERF3‐ETAS): Toward an operational earthquake forecast

We, the ongoing Working Group on California Earthquake Probabilities, present a spatiotemporal clustering model for the Third Uniform California Earthquake Rupture Forecast (UCERF3), with the goal being to represent aftershocks, induced seismicity, and otherwise triggered events as a potential basis for operational earthquake forecasting (OEF). Specifically, we add an epidemic‐type aftershock sequence (ETAS) component to the previously published time‐independent and long‐term time‐dependent forecasts. This combined model, referred to as UCERF3‐ETAS, collectively represents a relaxation of segmentation assumptions, the inclusion of multifault ruptures, an elastic‐rebound model for fault‐based ruptures, and a state‐of‐the‐art spatiotemporal clustering component. It also represents an attempt to merge fault‐based forecasts with statistical seismology models, such that information on fault proximity, activity rate, and time since last event are considered in OEF. We describe several unanticipated challenges that were encountered, including a need for elastic rebound and characteristic magnitude–frequency distributions (MFDs) on faults, both of which are required to get realistic triggering behavior. UCERF3‐ETAS produces synthetic catalogs of M ≥2.5 events, conditioned on any prior M ≥2.5 events that are input to the model. We evaluate results with respect to both long‐term (1000 year) simulations as well as for 10‐year time periods following a variety of hypothetical scenario mainshocks. Although the results are very plausible, they are not always consistent with the simple notion that triggering probabilities should be greater if a mainshock is located near a fault. Important factors include whether the MFD near faults includes a significant characteristic earthquake component, as well as whether large triggered events can nucleate from within the rupture zone of the mainshock. Because UCERF3‐ETAS has many sources of uncertainty, as will any subsequent version or competing model, potential usefulness needs to be considered in the context of actual applications.

California↗
USGS2018

Turing-style tests for UCERF3 synthetic catalogs

Epidemic-Type Aftershock Sequence (ETAS) catalogs generated from the 3rd Uniform California Earthquake Rupture Forecast (UCERF3) model are unique in that they are the first to combine a complex, fault-based long-term forecast with short-term earthquake clustering statistics. We present Turing-style tests to examine whether these synthetic catalogs can successfully imitate observed earthquake behavior in California. We find that UCERF3-ETAS is more spatially diffuse than the observed historic catalog in California and that it is lacking quiet periods that are present in the real catalog. While mean aftershock productivity of the observed catalog is matched closely by UCERF3-ETAS, the real catalog has more inter-sequence productivity variability and small mainshocks have more foreshocks. In sum, we find that UCERF3-ETAS differs from the observed catalog in ways that are foreseeable from its modeling simplifications. The tests we present here can be used on any model which produces suites of synthetic catalogs; as such, in addition to providing avenues for future improvements to the model, they could also be incorporated into testing platforms such as Collaboratory for the Study of Earthquake Predictability (CSEP).

Bulletin of the Seismological Society of America↗
USGS2019

Ensembles of ETAS models provide optimal operational earthquake forecasting during swarms: Insights from the 2015 San Ramon, California swarm

Earthquake swarms, typically modeled as time-varying changes in background seismicity that are driven by external processes such as fluid flow or aseismic creep, present challenges for operational earthquake forecasting. While the time decay of aftershock sequences can be estimated with the modified Omori law, it is difficult to forecast the temporal behavior of seismicity rates during a swarm. To explore these issues, we apply the Epidemic-Type Aftershock Sequence (ETAS) model (Ogata, JASA, 1988) to the 2015 San Ramon, California swarm, which lasted several weeks and had almost 100 2≤M≤3.6 earthquakes. We develop 3-day forecasts during the swarm based on an ETAS model fit to all prior seismicity in the region as well as an ETAS model fit only to previous swarms in the region, which is better at capturing the higher background rate during the swarm. We also explore forecasts where the background rate is updated periodically during the swarm using data over different lookback windows and find that generally these models perform better than the models where the background rate is fixed. Finally, we construct ensemble forecasts by combining the different models weighted according to their performance. The ensemble forecasts outperform all of the individual models and allow us to avoid making arbitrary choices at the outset of a swarm as to which single model will perform the best.

California↗
USGS2020

Regionally Optimized Background Earthquake Rates from ETAS (ROBERE) for probabilistic seismic hazard assessment

We use an epidemic‐type aftershock sequence (ETAS) based approach to develop a regionally optimized background earthquake rates from ETAS (ROBERE) method for probabilistic seismic hazard assessment. ROBERE fits parameters to the full seismicity catalog for a region with maximum‐likelihood estimation, including uncertainty. It then averages the earthquake rates over a suite of catalogs from which foreshocks and aftershocks have been removed using stochastic declustering while maintaining the same Gaussian smoothing currently used for the U.S. Geological Survey National Seismic Hazard Model (NSHM). The NSHM currently determines these rates by smoothing a single catalog from which foreshocks and aftershocks have been removed using the method of Gardner and Knopoff (1974 ; hereafter, GK74). The parameters used in GK74 were determined from subjectively identified aftershock sequences, unlike ROBERE, in which both background rate and aftershock triggering parameters are objectively fitted. A major difference between the impacts of the two methods is GK74 significantly reduces the b "> b ‐value, a critical value for seismic hazard analysis, whereas ROBERE maintains the original b "> b ‐value from the full catalog. We apply these methods to the induced seismicity in Oklahoma and Kansas and tectonic activity in the San Francisco Bay Region. Using GK74 gives lower overall earthquake rates but estimates higher hazard due to the reduction in the b "> b ‐value. ROBERE provides higher earthquake rates, at the magnitude of completeness, but lower hazard because it does not alter the b "> b ‐value. We test two other declustering methods that produce results closer to ROBERE but do not use objectively fit parameters, include uncertainty, and may not work as well in other areas. We suggest adopting ROBERE for the NSHM so that our hazard estimates are based on an objective analysis, including uncertainty, and do not depend strongly on potentially biased b "> b ‐values, which was never the goal of the existing methodology.

Bulletin of the Seismological Society of America↗