Follow the Scientists? How Beliefs about the Practice of Science Shaped COVID-19 Views

“Follow the science” became the mantra for responding to COVID-19 pandemic. However, for the public this also meant “follow the scientists,” and this led to uneasiness as some viewed scientists as not credible. We investigate how beliefs about the way scientists develop their findings affect pandemic-related views. Our analysis shows that beliefs about scientists’ objectivity predict views regrading coronavirus-related risks, behavioral changes, and policy priorities. While political party identity also predicts views about COVID-19-related concerns, these vary by political leaders whose approaches embraced versus dismissed science based strategies, highlighting the importance of perceptions of scientists in shaping pandemic related attitudes and beliefs

The Zika Virus Threat

Shocking images of infants with severe birth defects in Brazil introduced the world to the devastating effects of the Zika virus. This mosquito-borne illness spread rapidly across Latin America and into the United States. News stories highlighting locally transmitted cases of Zika in Florida, and most recently in Texas, created a sense of urgency among public health officials. They stepped up efforts to inform the public about the transmission of the virus as well as the health risks associated with Zika. Public polling shows that Americans are becoming increasingly concerned about the threat of Zika, and they question the government's ability to limit its spread. What is less clear are the factors influencing perceptions of the Zika pandemic and support for governmental efforts to curb the spread of the virus

Multiple uncontrolled conditions and blood pressure medication intensification: an observational study

Abstract Background Multiple uncontrolled medical conditions may act as competing demands for clinical decision making. We hypothesized that multiple uncontrolled cardiovascular risk factors would decrease blood pressure (BP) medication intensification among uncontrolled hypertensive patients. Methods We observed 946 encounters at two VA primary care clinics from May through August 2006. After each encounter, clinicians recorded BP medication intensification (BP medication was added or titrated). Demographic, clinical, and laboratory information were collected from the medical record. We examined BP medication intensification by presence and control of diabetes and/or hyperlipidemia. 'Uncontrolled' was defined as hemoglobin A1c ≥ for diabetes, BP ≥ 140/90 mmHg (≥ 130/80 mmHg if diabetes present) for hypertension, and low density lipoprotein cholesterol (LDL-c) ≥ 130 mg/dl (≥ 100 mg/dl if diabetes present) for hyperlipidemia. Hierarchical regression models accounted for patient clustering and adjusted medication intensification for age, systolic BP, and number of medications. Results Among 387 patients with uncontrolled hypertension, 51.4% had diabetes (25.3% were uncontrolled) and 73.4% had hyperlipidemia (22.7% were uncontrolled). The BP medication intensification rate was 34.9% overall, but higher in individuals with uncontrolled diabetes and uncontrolled hyperlipidemia: 52.8% overall and 70.6% if systolic BP ≥ 10 mmHg above goal. Intensification rates were lowest if diabetes or hyperlipidemia were controlled, lower than if diabetes or hyperlipidemia were not present. Multivariable adjustment yielded similar results. Conclusions The presence of uncontrolled diabetes and hyperlipidemia was associated with more guideline-concordant hypertension care, particularly if BP was far from goal. Efforts to understand and improve BP medication intensification in patients with controlled diabetes and/or hyperlipidemia are warranted.http://deepblue.lib.umich.edu/bitstream/2027.42/78266/1/1748-5908-5-55.xmlhttp://deepblue.lib.umich.edu/bitstream/2027.42/78266/2/1748-5908-5-55.pdfPeer Reviewe

Changing forest structure across the landscape of the Sierra Nevada, CA, USA, since the 1930s

Understanding the dynamics of forest structure aids inference regarding future forests and their distributions around the world. Over the last few decades, several papers have addressed changing forest structure in the Sierra Nevada, CA, USA, but these studies were limited in scope. We carried out a broad comparison of forest density and composition in the 1930s versus the 2000s for the west slope of the central and northern Sierra Nevada, using the two most extensive data sets available. Forests in this region have endured a long, complex history of human disturbance, and are now experiencing climatic shifts. We subdivided the landscape into elevation and latitude zones and compared historical and modern tree densities within each zone. We compared densities in historical plots to burned and unburned modern plots, as well as densities of individual tree species in historical vs. modern plots for their entire elevational distribution. Density of small trees (10.2-30.4 cm dbh) was significantly higher in the modern data set for all elevations and all latitudes, ranging from 20 to 148% higher. However, density of large trees (61.0 cm) was lower in the modern data set for most elevations and latitudes, ranging from 41% to 60% lower in most zones. Density difference of mid-sized trees (30.5-60.9 cm) was mixed, but was generally higher in modern plots. The pattern of more small trees but fewer large trees held for most individual species as well, but with notable exceptions. Our comparison of burned and unburned plots strongly implicates fire suppression as a driver of increased density of small trees in low- to mid-elevation forests. However, modern high-elevation (.2500 m) forests, where fire suppression impacts should be minimal, were also significantly denser than historical plots. Changing climatic conditions may be driving increased densities of small trees in high elevations, as well as decreased densities of large trees across the region

No evidence of suitability of prophylactic fluids for wildfire prevention at landscape scales

Yu et al. propose a viscoelastic fluid as a prophylactic fire-retardant treatment in landscapes at high risk of wildfires. We argue that, while the idea is worth exploring further, their data do not support its suitability for real landscape-scale applications.Peer reviewe

Implementing just climate adaptation policy: An analysis of recognition, framing, and advocacy coalitions in Boston, U.S.A.

Cities face intersectional challenges implementing climate adaptation policy. This research contributes to scholarship dedicated to understanding how policy implementation affects socially vulnerable groups, with the overarching goal of promoting justice and equity in climate policy implementation. We apply a novel framework that integrates social justice theory and the advocacy coalition framework to incrementally assess just climate adaptation in Boston, Massachusetts in the United States. Boston made an ambitious commitment to address equity as part of its climate planning and implementation efforts. In this paper, we evaluate the first implementation stage over the period 2016–2019 during which Boston developed coastal resilience plans for three neighborhoods. Despite Boston\u27s commitment to equity, we find injustice was nevertheless reproduced through representation and coalition dynamics, the framing of problems and solutions, and a failure to recognize the priorities and lived experiences of city residents. The assessment framework presented can be adapted to evaluate how other climate adaptation initiatives advance social justice and highlights the need for incremental evaluation over short time periods to inform ongoing implementation efforts

The impact of near-miss events on betting behavior: An examination of casino rapid roulette play

We examine how almost winning in roulette affects subsequent betting behavior. Our main finding is heterogeneity in gambler behavior with some gamblers less likely to bet on numbers that were near misses on the prior spin and other gamblers more likely to bet on near miss numbers. Using a unique data set from the game rapid roulette, we model the likelihood of a gambler betting on a near miss number while controlling for the favorite number bias and the likelihood of a number being a near miss. We also find no evidence that near misses in roulette leads to gamblers extending the time spent gambling or to the placing of more bets

Modeling plant ranges over 75 years of climate change in California, USA: temporal transferability and species traits

Species distribution model (SDM) projections under future climate scenarios are increasingly being used to inform resource management and conservation strategies. A critical assumption for projecting climate change responses is that SDMs are transferable through time, an assumption that is largely untested because investigators often lack temporally independent data for assessing transferability. Further, understanding how the ecology of species influences temporal transferability is critical yet almost wholly lacking. This raises two questions. (1) Are SDM projections transferable in time? (2) Does temporal transferability relate to species ecological traits? To address these questions we developed SDMs for 133 vascular plant species using data from the mountain ranges of California (USA) from two time periods: the 1930s and the present day. We forecast historical models over 75 years of measured climate change and assessed their projections against current distributions. Similarly, we hindcast contemporary models and compared their projections to historical data. We quantified transferability and related it to species ecological traits including physiognomy, endemism, dispersal capacity, fire adaptation, and commonness. We found that non-endemic species with greater dispersal capacity, intermediate levels of prevalence, and little fire adaptation had higher transferability than endemic species with limited dispersal capacity that rely on fire for reproduction. We demonstrate that variability in model performance was driven principally by differences among species as compared to model algorithms or time period of model calibration. Further, our results suggest that the traits correlated with prediction accuracy in a single time period may not be related to transferability between time periods. Our findings provide a priori guidance for the suitability of SDM as an approach for forecasting climate change responses for certain taxa