Insights from low‐temperature thermochronometry into transpressional deformation and crustal exhumation along the San Andreas fault in the western Transverse Ranges, California

The San Emigdio Mountains are an example of an archetypical, transpressional structural system, bounded to the south by the San Andreas strike‐slip fault, and to the north by the active Wheeler Ridge thrust. Apatite (U‐Th)/He and apatite and zircon fission track ages were obtained along transects across the range and from wells in and to the north of the range. Apatite (U‐Th)/He ages are 4–6 Ma adjacent to the San Andreas fault, and both (U‐Th)/He and fission track ages grow older with distance to the north from the San Andreas. The young ages north of the San Andreas fault contrast with early Miocene (U‐Th)/He ages from Mount Pinos on the south side of the fault. Restoration of sample paleodepths in the San Emigdio Mountains using a regional unconformity at the base of the Eocene Tejon Formation indicates that the San Emigdio Mountains represent a crustal fragment that has been exhumed more than 5 km along the San Andreas fault since late Miocene time. Marked differences in the timing and rate of exhumation between the northern and southern sides of the San Andreas fault are difficult to reconcile with existing structural models of the western Transverse Ranges as a thin‐skinned thrust system. Instead, these results suggest that rheologic heterogeneities may play a role in localizing deformation along the Big Bend of the San Andreas fault as the San Emigdio Mountains are compressed between the crystalline basement of Mount Pinos and oceanic crust that underlies the southern San Joaquin Valley. Key Points There is Pliocene exhumation of the western Transverse Ranges Localization of deformation may be controlled by lithospheric strength Strain is partitioned between the San Andreas and regional thrustsPeer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/102707/1/tect20096.pd

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the US

This article contains supporting information online at http://www.pnas.org/lookup/suppl/doi:10.1073/pnas.2113561119/-/DCSupplemental.Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multi-model ensemble forecast that combined predictions from dozens of different research groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-week horizon 3-5 times larger than when predicting at a 1-week horizon. This project underscores the role that collaboration and active coordination between governmental public health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks.Integrative Biolog

Adenovirus-5-Vectored P. falciparum Vaccine Expressing CSP and AMA1. Part B: Safety, Immunogenicity and Protective Efficacy of the CSP Component

Background: A protective malaria vaccine will likely need to elicit both cell-mediated and antibody responses. As adenovirus vaccine vectors induce both these responses in humans, a Phase 1/2a clinical trial was conducted to evaluate the efficacy of an adenovirus serotype 5-vectored malaria vaccine against sporozoite challenge.\ud \ud Methodology/Principal Findings: NMRC-MV-Ad-PfC is an adenovirus vector encoding the Plasmodium falciparum 3D7 circumsporozoite protein (CSP). It is one component of a two-component vaccine NMRC-M3V-Ad-PfCA consisting of one adenovector encoding CSP and one encoding apical membrane antigen-1 (AMA1) that was evaluated for safety and immunogenicity in an earlier study (see companion paper, Sedegah et al). Fourteen Ad5 seropositive or negative adults received two doses of NMRC-MV-Ad-PfC sixteen weeks apart, at 1x1010 particle units per dose. The vaccine was safe and well tolerated. All volunteers developed positive ELISpot responses by 28 days after the first immunization (geometric mean 272 spot forming cells/million[sfc/m]) that declined during the following 16 weeks and increased after the second dose to levels that in most cases were less than the initial peak (geometric mean 119 sfc/m). CD8+ predominated over CD4+ responses, as in the first clinical trial. Antibody responses were poor and like ELISpot responses increased after the second immunization but did not exceed the initial peak. Pre-existing neutralizing antibodies (NAb) to Ad5 did not affect the immunogenicity of the first dose, but the fold increase in NAb induced by the first dose was significantly associated with poorer antibody responses after the second dose, while ELISpot responses remained unaffected. When challenged by the bite of P. falciparum-infected mosquitoes, two of 11 volunteers showed a delay in the time to patency compared to infectivity controls, but no volunteers were sterilely protected.\ud \ud Significance: The NMRC-MV-Ad-PfC vaccine expressing CSP was safe and well tolerated given as two doses, but did not provide sterile protection

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages

In COVID-19 Health Messaging, Loss Framing Increases Anxiety with Little-to-No Concomitant Benefits: Experimental Evidence from 84 Countries

The COVID-19 pandemic (and its aftermath) highlights a critical need to communicate health information effectively to the global public. Given that subtle differences in information framing can have meaningful effects on behavior, behavioral science research highlights a pressing question: Is it more effective to frame COVID-19 health messages in terms of potential losses (e.g., "If you do not practice these steps, you can endanger yourself and others") or potential gains (e.g., "If you practice these steps, you can protect yourself and others")? Collecting data in 48 languages from 15,929 participants in 84 countries, we experimentally tested the effects of message framing on COVID-19-related judgments, intentions, and feelings. Loss- (vs. gain-) framed messages increased self-reported anxiety among participants cross-nationally with little-to-no impact on policy attitudes, behavioral intentions, or information seeking relevant to pandemic risks. These results were consistent across 84 countries, three variations of the message framing wording, and 560 data processing and analytic choices. Thus, results provide an empirical answer to a global communication question and highlight the emotional toll of loss-framed messages. Critically, this work demonstrates the importance of considering unintended affective consequences when evaluating nudge-style interventions

A global experiment on motivating social distancing during the COVID-19 pandemic

Finding communication strategies that effectively motivate social distancing continues to be a global public health priority during the COVID-19 pandemic. This cross-country, preregistered experiment (n = 25,718 from 89 countries) tested hypotheses concerning generalizable positive and negative outcomes of social distancing messages that promoted personal agency and reflective choices (i.e., an autonomy-supportive message) or were restrictive and shaming (i.e., a controlling message) compared with no message at all. Results partially supported experimental hypotheses in that the controlling message increased controlled motivation (a poorly internalized form of motivation relying on shame, guilt, and fear of social consequences) relative to no message. On the other hand, the autonomy-supportive message lowered feelings of defiance compared with the controlling message, but the controlling message did not differ from receiving no message at all. Unexpectedly, messages did not influence autonomous motivation (a highly internalized form of motivation relying on one’s core values) or behavioral intentions. Results supported hypothesized associations between people’s existing autonomous and controlled motivations and self-reported behavioral intentions to engage in social distancing. Controlled motivation was associated with more defiance and less long-term behavioral intention to engage in social distancing, whereas autonomous motivation was associated with less defiance and more short- and long-term intentions to social distance. Overall, this work highlights the potential harm of using shaming and pressuring language in public health communication, with implications for the current and future global health challenges

It’s Not Only Rents: Explaining the Persistence and Change of Neopatrimonialism in Indonesia

Indonesia has long been associated with neopatrimonialism, corruption, collusion, and nepotism as the main modi operandi of politics, economics and public administration. Despite various measures and initiatives to fight these practises, little evidence for a significant decline can be found over the years. Rather, longitudinal analysis points to changes in the character of neopatrimonialism. Based on more than 60 in-depth interviews, focus-group discussions, and the analysis of both primary and secondary data, the aim of this article is, first, to describe the changes that have taken place, and, second, to investigate what accounts for these changes. Political economy concepts posit the amount and development of economic rents as the explanatory factor for the persistence and change of neopatrimonialism. This study's findings, however, indicate that rents alone cannot explain what has taken place in Indonesia. Democratisation and decentralisation exert a stronger impact