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

Characteristics and Outcomes for Secondary Breast Cancer in Childhood, Adolescent, and Young Adult Cancer Survivors Treated with Radiation.

BackgroundRadiotherapy is used to treat many adolescent and young adult (AYA) and childhood cancer patients and is a risk factor for secondary breast cancer. While premenopausal breast cancer is inherently more aggressive, no studies to date have evaluated the characteristics and breast cancer-specific survival (BCSS) of premenopausal secondary breast cancer after radiotherapy in AYA and childhood cancer survivors.MethodsFemale patients ages 12 to 50 diagnosed with primary breast cancer from 1988 to 2014 (n = 107,751) were obtained from the California Cancer Registry and compared with similar aged patients with secondary breast cancer who were treated with radiotherapy for their primary tumor (n = 1,147) from ages 12 to 39. We examined BCSS using multivariable Cox proportional hazards regression.ResultsThe secondary breast cancer cohort was more likely to be Hispanic or Black, be 35 to 45 years of age, have earlier stage tumors, be higher grade, have no lymph node involvement, and be hormone receptor negative. All women showed worse BCSS for large tumor size, lymph node involvement, and hormone receptor-negative status. BCSS was worse for women with secondary breast cancer both overall (hazard ratio, 1.98; 95% confidence interval, 1.77-2.23) and in all subgroups considered. Associations were most pronounced in Hispanics, Asian/Pacific Islanders, and younger women, as well as those with earlier stage, lymph node-negative, and hormone receptor-positive disease.ConclusionsBCSS is significantly decreased among all survivors of childhood and AYA cancer treated with radiotherapy that develop a secondary breast cancer, including women with good prognostic features.ImpactTherefore, we may need to consider alternative and even more aggressive treatment in what were considered low-risk populations previously

The Green Wave: Reviewing the Environmental Impacts of the Invasive European Green Crab (Carcinus maenas) and Potential Management Approaches

The European green crab (Carcinus maenas), native to northwestern Europe and Africa, is among the top 100 most damaging invasive species globally. In some regions, including the Atlantic coast of North America, C. maenas has caused long-term degradation of eelgrass habitats and bivalve, crab, and finfish populations, while areas are near the beginning of the invasion cycle. Due to high persistence and reproductive potential of C. maenas populations, most local and regional mitigation efforts no longer strive for extirpation and instead focus on population control. Long-term monitoring and rapid response protocols can facilitate early detection of introductions that is critical to inform management decisions related to green crab control or extirpation. Once C. maenas are detected, local area managers will need to decide on management actions, including whether and what green crab control measures will be implemented, if local invasion might be prevented or extirpated, and if population reduction to achieve functional eradication is achievable. Due to the immense operational demands likely required to extirpate C. maenas populations, combined with limited resources for monitoring and removal, it is unlikely that any single government, conservation and/or academic organization would be positioned to adequately control or extirpate populations in local areas, highlighting the importance of collaborative efforts. Community-based monitoring, and emerging methods such as environmental DNA (eDNA), may help expand the spatial and temporal extent of monitoring, facilitating early detection and removal of C. maenas. While several C. maenas removal programs have succeeded in reducing their populations, to our knowledge, no program has yet successfully extirpated the invader; and the cost of any such program would likely be immense and unsustainable over the long-term. An alternative approach is functional eradication, whereby C. maenas populations are reduced below threshold levels such that ecosystem impacts are minimized. Less funding and effort would likely be required to achieve and maintain functional eradication compared to extirpation. In either case, continual control efforts will be required as C. maenas populations can quickly increase from low densities and larval re-introductions.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author

The Southern-sky MWA Rapid Two-metre (SMART) pulsar survey - II. : survey status, pulsar census, and first pulsar discoveries

In Paper I, we presented an overview of the Southern-sky MWA Rapid Two-metre (SMART) survey, including the survey design and search pipeline. While the combination of MWA's large field-of-view and the voltage capture system brings a survey speed of, the progression of the survey relies on the availability of compact configuration of the Phase II array. Over the past few years, by taking advantage of multiple windows of opportunity when the compact configuration was available, we have advanced the survey to 75% of the planned sky coverage. To date, about 10% of the data collected thus far have been processed for a first-pass search, where 10 min of observation is processed for dispersion measures out to 250, to realise a shallow survey that is largely sensitive to long-period pulsars. The ongoing analysis has led to two new pulsar discoveries, as well as an independent discovery and a rediscovery of a previously incorrectly characterised pulsar, all from of the data for which candidate scrutiny is completed. In this sequel to Paper I, we describe the strategies for further detailed follow-up including improved sky localisation and convergence to timing solution, and illustrate them using example pulsar discoveries. The processing has also led to re-detection of 120 pulsars in the SMART observing band, bringing the total number of pulsars detected to date with the MWA to 180, and these are used to assess the search sensitivity of current processing pipelines. The planned second-pass (deep survey) processing is expected to yield a three-fold increase in sensitivity for long-period pulsars, and a substantial improvement to millisecond pulsars by adopting optimal de-dispersion plans. The SMART survey will complement the highly successful Parkes High Time Resolution Universe survey at 1.2-1.5 GHz, and inform future large survey efforts such as those planned with the low-frequency Square Kilometre Array (SKA-Low)

The Southern-sky MWA Rapid Two-metre (SMART) pulsar survey - I. : survey design and processing pipeline

We present an overview of the Southern-sky MWA Rapid Two-metre (SMART) pulsar survey that exploits the Murchison Widefield Array's large field of view and voltage-capture system to survey the sky south of 30 in declination for pulsars and fast transients in the 140-170 MHz band. The survey is enabled by the advent of the Phase II MWA's compact configuration, which offers an enormous efficiency in beam-forming and processing costs, thereby making an all-sky survey of this magnitude tractable with the MWA. Even with the long dwell times employed for the survey (4800 s), data collection can be completed in <![CDATA[ $100 h of telescope time, while still retaining the ability to reach a limiting sensitivity of 2-3 mJy (at 150 MHz, near zenith), which is effectively 3-5 times deeper than the previous-generation low-frequency southern-sky pulsar survey, completed in the 1990s. Each observation is processed to generate 5000-8000 tied-array beams that tessellate the full field of view (at 155 MHz), which are then processed to search for pulsars. The voltage-capture recording of the survey also allows a multitude of post hoc processing options including the reprocessing of data for higher time resolution and even exploring image-based techniques for pulsar candidate identification. Due to the substantial computational cost in pulsar searches at low frequencies, the survey data processing is undertaken in multiple passes: in the first pass, a shallow survey is performed, where 10 min of each observation is processed, reaching about one-third of the full-search sensitivity. Here we present the system overview including details of ongoing processing and initial results. Further details including first pulsar discoveries and a census of low-frequency detections are presented in a companion paper. Future plans include deeper searches to reach the full sensitivity and acceleration searches to target binary and millisecond pulsars. Our simulation analysis forecasts 300 new pulsars upon the completion of full processing. The SMART survey will also generate a complete digital record of the low-frequency sky, which will serve as a valuable reference for future pulsar searches planned with the low-frequency Square Kilometre Array