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Simple Summary: The spread of invasive wild pigs across the United States has been successfully slowed due to the establishment of a national management program. In this paper, we study the effectiveness of the national program by modeling the spread of wild pigs in the absence of intervention. Further, we use the models to assess the value of resources safeguarded from the threat of wild pigs. Our findings indicate that, on average, invasive wild pigs were prevented from spreading to 724 counties, and USD 40.2 billion in resource value was safeguarded over the first eight years of the program. Continuation of the program will deliver additional benefits and further research is critical to understand its comprehensive economic effects. Wild pigs (Sus scrofa) are one of the most destructive invasive species in the US, known for causing extensive damage to agricultural commodities, natural resources, and property, and for transmitting diseases to livestock. Following the establishment of the National Feral Swine Damage Management Program (NFSDMP) in 2014, the expansion of wild pig populations has been successfully slowed. This paper combines two modeling approaches across eight separate models to characterize the expansion of wild pig populations in the absence of intervention by the NFSDMP and forecasts the value of a subset of resources safeguarded from the threat of wild pigs. The results indicate that if wild pigs had continued spreading at pre-program levels, they would have spread extensively across the US, with significant geographic variation across modeling scenarios. Further, by averting the threat of wild pigs, a substantial amount of crops, land, property, and livestock was safeguarded by the NFSDMP. Cumulatively, between 2014 and 2021, wild pig populations were prevented from spreading to an average of 724 counties and an average of USD 40.2 billion in field crops, pasture, grasses, and hay was safeguarded. The results demonstrate that intervention by the NFSDMP has delivered significant ecological and economic benefits that were not previously known. [ABSTRACT FROM AUTHOR]

Through compelling examples from various continents, Reidinger effectively illustrates the far-reaching consequences of invasive species on native ecosystems and local communities, and the complexities of mitigating damage. In Chapter 6, Communities, Ecosystems, and Landscapes, Reidinger equates ecosystems to communities - all organisms living in an area at a given time interacting with their abiotic components. Russell Reidinger's revised book, I Human-Wildlife Conflict Management: Prevention and Problem Solving i , provides a comprehensive and practical guide to understanding human-wildlife conflict, and offers a variety of effective strategies in prevention and resolution. [Extracted from the article]

African swine fever (ASF), classical swine fever (CSF) and foot‐and‐mouth disease (FMD) are considered to be three of the most detrimental animal diseases and are currently foreign to the U.S. Emerging and re‐emerging pathogens can have tremendous impacts in terms of livestock morbidity and mortality events, production losses, forced trade restrictions, and costs associated with treatment and control. The United States is the world's top producer of beef for domestic and export use and the world's third‐largest producer and consumer of pork and pork products; it has also recently been either the world's largest or second largest exporter of pork and pork products. Understanding the routes of introduction into the United States and the potential economic impact of each pathogen are crucial to (a) allocate resources to prevent routes of introduction that are believed to be more probable, (b) evaluate cost and efficacy of control methods and (c) ensure that protections are enacted to minimize impact to the most vulnerable industries. With two scoping literature reviews, pulled from global data, this study assesses the risk posed by each disease in the event of a viral introduction into the United States and illustrates what is known about the economic costs and losses associated with an outbreak. [ABSTRACT FROM AUTHOR]

BACKGROUND Wildlife damage to crops is a persistent and costly problem for many farmers in the USA. Most existing estimates of crop damage have relied on direct assessment methods such as field studies conducted by trained biologists or surveys distributed to farmers. In this paper, we describe a new method of estimating wildlife damage that exploits federal crop insurance data. We focused our study on four crops: corn, soybean, wheat, and cotton, chosen because of their economic importance and their vulnerability to wildlife damage. RESULTS: We determined crop‐raiding hot spots across the USA over the 2015–2019 period and identified the eastern and southern regions of the USA as being the most susceptible to wildlife damage. We estimated lower bounds for dollar and percent losses attributable to wildlife to these four crops. The combined loss across four crops was estimated at $592.6 million. The highest total estimated losses to wildlife were incurred by soybeans ($323.9 million) and corn ($194.0 million) and the highest percentage losses were estimated for soybeans (0.87%) and cotton (0.72%). CONCLUSION: We believe the proposed method is a reliable way to evaluate geographic and temporal heterogeneity in damages for the coming years. Accurate information on damages benefits various management agencies by allowing them to allocate management resources to crops and regions where the problem is relatively severe. A better understanding of damage heterogeneity can also help guide research and development of new management techniques. [ABSTRACT FROM AUTHOR]

Background: Multiple myeloma is a plasma cell tumour with approximately 5500 new cases in the UK each year. Ixazomib is a next generation inhibitor of the 20S proteasome and is thought to be an effective treatment for those who have relapsed from bortezomib. The combination of cyclophosphamide and dexamethasone (CD) is a recognised treatment option for patients with relapsed refractory multiple myeloma (RRMM) who have relapsed after treatment with bortezomib and lenalidomide, whilst also often being combined with newer proteasome inhibitors. The most apparent combination for ixazomib is therefore with CD.Methods: MUK eight is a randomised, controlled, open, parallel group, multi-centre phase II trial that will recruit patients with RRMM who have relapsed after treatment with thalidomide, lenalidomide, and a proteasome inhibitor. The primary objective of the trial is to evaluate whether ixazomib in combination with cyclophosphamide and dexamethasone (ICD) has improved clinical activity compared to CD in terms of progression-free survival (PFS). Secondary objectives include comparing toxicity profiles and the activity and cost-effectiveness of both treatments. Since opening, the trial has been amended to allow all participants who experience disease progression (as per the IMWG criteria) on the CD arm to subsequently switch to receive ICD treatment, once progression has been confirmed with two clinical members of the Trial Management Group (TMG). This 'switch' phase of the study is exploratory and will assess second progression-free survival measured from randomisation to second disease progression (PFS2) and progression-free survival from the point of switching to second disease progression (PFS Switch) in participants who switch from CD to ICD treatment.Discussion: Development of ixazomib offers the opportunity to further investigate the value of proteasome inhibition through oral administration in the treatment of RRMM. Previous studies investigating the safety and efficacy of ICD in patients with RRMM demonstrate a toxicity profile consistent with ixazomib in combination with lenalidomide and dexamethasone, whilst the combination showed possible activity in RRMM patients. Further investigation of the anti-tumour effect of this drug in RRMM patients is therefore warranted, especially since no trials comparing CD with ICD have been completed at present.Trial Registration: ISRCTN number: ISRCTN58227268 . Registered on 26 August 2015. [ABSTRACT FROM AUTHOR]

The establishment of interventions to maximize maternal health requires the identification of modifiable risk factors. Toward the identification of modifiable hospital‐based factors, we analyze over 2 million births from 2005 to 2010 in Texas, employing a series of quasi‐experimental tests involving hourly, daily, and monthly circumstances where medical service quality (or clinical capital) is known to vary exogenously. Motivated by a clinician's choice model, we investigate whether maternal delivery complications (1) vary by work shift, (2) increase by the hours worked within shifts, (3) increase on weekends and holidays when hospitals are typically understaffed, and (4) are higher in July when a new cohort of residents enter teaching hospitals. We find consistent evidence of a sizable statistical relationship between deliveries during nonstandard schedules and negative patient outcomes. Delivery complications are higher during night shifts (OR = 1.21, 95% CI: 1.18–1.25), and on weekends (OR = 1.09, 95% CI: 1.04–1.14) and holidays (OR = 1.29, 95% CI: 1.04–1.60), when hospitals are understaffed and less experienced doctors are more likely to work. Within shifts, we show deterioration of occupational performance per additional hour worked (OR = 1.02, 95% CI: 1.01–1.02). We observe substantial additional risk at teaching hospitals in July (OR = 1.28, 95% CI: 1.14–1.43), reflecting a cohort‐turnover effect. All results are robust to the exclusion of noninduced births and intuitively falsified with analyses of chromosomal disorders. Results from our multiple‐test strategy indicate that hospitals can meaningfully attenuate harm to maternal health through strategic scheduling of staff. [ABSTRACT FROM AUTHOR]

The establishment of interventions to maximize maternal health requires the identification of modifiable risk factors. Toward the identification of modifiable hospital-based factors, we analyze over 2 million births from 2005 to 2010 in Texas, employing a series of quasi-experimental tests involving hourly, daily, and monthly circumstances where medical service quality (or clinical capital) is known to vary exogenously. Motivated by a clinician's choice model, we investigate whether maternal delivery complications (1) vary by work shift, (2) increase by the hours worked within shifts, (3) increase on weekends and holidays when hospitals are typically understaffed, and (4) are higher in July when a new cohort of residents enter teaching hospitals. We find consistent evidence of a sizable statistical relationship between deliveries during nonstandard schedules and negative patient outcomes. Delivery complications are higher during night shifts (OR = 1.21, 95% CI: 1.18-1.25), and on weekends (OR = 1.09, 95% CI: 1.04-1.14) and holidays (OR = 1.29, 95% CI: 1.04-1.60), when hospitals are understaffed and less experienced doctors are more likely to work. Within shifts, we show deterioration of occupational performance per additional hour worked (OR = 1.02, 95% CI: 1.01-1.02). We observe substantial additional risk at teaching hospitals in July (OR = 1.28, 95% CI: 1.14-1.43), reflecting a cohort-turnover effect. All results are robust to the exclusion of noninduced births and intuitively falsified with analyses of chromosomal disorders. Results from our multiple-test strategy indicate that hospitals can meaningfully attenuate harm to maternal health through strategic scheduling of staff., (© 2019 Society for Risk Analysis.)