COVID-19 Mortality Rates were Higher in States that Limited Governments from Enacting Public Health Emergency Orders

State and local governments enacted various public health emergency policies during the COVID-19 pandemic that resulted in lower infection and death rates than would have occurred without these policies. However, some states limited emergency public health authority of state executives, state governors, and state and local officials during the pandemic. This brief summarizes the results of a study that used data from the Center for Public Health Law Research and Oxford COVID-19 Government Response Tracker to explore which states passed laws that limited emergency public health authority during the COVID-19 pandemic and the effects of those limitations on COVID-19 death rates. The study finds that states with unified Republican control were more likely to limit emergency authority during the COVID-19 pandemic and that limiting emergency public health authority was associated with higher COVID-19 death rates

COVID-19 Mortality Rates were Higher in States that Limited Governments from Enacting Public Health Emergency Orders

State and local governments enacted various public health emergency policies during the COVID-19 pandemic, resulting in lower infection and death rates than would have occurred without these policies. However, some states limited the emergency public health authority of state executives, state governors, and other state and local officials during the pandemic. This brief summarizes the results of a study that used data from the Center for Public Health Law Research and Oxford COVID-19 Government Response Tracker to explore which states passed laws that limited emergency public health authority during the COVID-19 pandemic and the effects of those limits on COVID-19 death rates. The study finds that states with unified Republican control were more likely to limit emergency authority during the COVID-19 pandemic and that limiting emergency public health authority was associated with higher COVID-19 death rates

Cross-cutting principles for planetary health education

Since the 2015 launch of the Rockefeller Foundation Lancet Commission on planetary health,1 an enormous groundswell of interest in planetary health education has emerged across many disciplines, institutions, and geographical regions. Advancing these global efforts in planetary health education will equip the next generation of scholars to address crucial questions in this emerging field and support the development of a community of practice. To provide a foundation for the growing interest and efforts in this field, the Planetary Health Alliance has facilitated the first attempt to create a set of principles for planetary health education that intersect education at all levels, across all scales, and in all regions of the world—ie, a set of cross-cutting principles

Common, low-frequency, rare, and ultra-rare coding variants contribute to COVID-19 severity

The combined impact of common and rare exonic variants in COVID-19 host genetics is currently insufficiently understood. Here, common and rare variants from whole-exome sequencing data of about 4000 SARS-CoV-2-positive individuals were used to define an interpretable machine-learning model for predicting COVID-19 severity. First, variants were converted into separate sets of Boolean features, depending on the absence or the presence of variants in each gene. An ensemble of LASSO logistic regression models was used to identify the most informative Boolean features with respect to the genetic bases of severity. The Boolean features selected by these logistic models were combined into an Integrated PolyGenic Score that offers a synthetic and interpretable index for describing the contribution of host genetics in COVID-19 severity, as demonstrated through testing in several independent cohorts. Selected features belong to ultra-rare, rare, low-frequency, and common variants, including those in linkage disequilibrium with known GWAS loci. Noteworthily, around one quarter of the selected genes are sex-specific. Pathway analysis of the selected genes associated with COVID-19 severity reflected the multi-organ nature of the disease. The proposed model might provide useful information for developing diagnostics and therapeutics, while also being able to guide bedside disease management. © 2021, The Author(s)

Joint analysis of three genome-wide association studies of esophageal squamous cell carcinoma in Chinese populations

We conducted a joint (pooled) analysis of three genome-wide association studies (GWAS) 1-3 of esophageal squamous cell carcinoma (ESCC) in ethnic Chinese (5,337 ESCC cases and 5,787 controls) with 9,654 ESCC cases and 10,058 controls for follow-up. In a logistic regression model adjusted for age, sex, study, and two eigenvectors, two new loci achieved genome-wide significance, marked by rs7447927 at 5q31.2 (per-allele odds ratio (OR) = 0.85, 95% CI 0.82-0.88; P=7.72x10−20) and rs1642764 at 17p13.1 (per-allele OR= 0.88, 95% CI 0.85-0.91; P=3.10x10−13). rs7447927 is a synonymous single nucleotide polymorphism (SNP) in TMEM173 and rs1642764 is an intronic SNP in ATP1B2, near TP53. Furthermore, a locus in the HLA class II region at 6p21.32 (rs35597309) achieved genome-wide significance in the two populations at highest risk for ESSC (OR=1.33, 95% CI 1.22-1.46; P=1.99x10−10). Our joint analysis identified new ESCC susceptibility loci overall as well as a new locus unique to the ESCC high risk Taihang Mountain region

Vector-Borne Disease Surveillance & Control Training Needs Assessment

A major goal of the Northeast Regional Center for Excellence in Vector Borne Diseases is to develop training and education tools for public health professionals. The purpose of this needs assessment survey was a first step in these education efforts. We sought to understand perceived gaps in training and workforce needs related to vector-borne disease and public health. Needs assessment content was targeted to public health practitioners, vector control districts and associations, integrated pest management researchers and educators, and state emergency preparedness staff working in the Northeast region of the US.The Northeast Regional Center for Excellence in Vector-Borne Diseases is supported through Cooperative Agreement Number 1U01CK000509-01 between the Centers for Disease Control and Prevention (CDC) and Cornell Universit

Design of scheduling algorithms: Applications

The accomplishment of a manufacturing company's objectives is strongly connected to the efficient solution of scheduling problems that are faced in the production environment. Numerous methods for the solution of these problems have been published. However, very few of them have been adopted by manufacturing companies. This chapter suggests that the basic reason behind this imbalance is the inadequate representation of the scheduling process when designing decision support systems. Hence, the algorithms that are designed and included in these systems might not reflect the problems that actually have to be solved. The relevance of algorithmic design can be improved by using a more complete representation of the scheduling process, which would be highly relevant for increasing the adoption rate of new support systems. The main contribution of the chapter concerns the development of a theoretical framework for the design of scheduling decision support systems. This framework is based on an interdisciplinary approach that integrates insights from cognitive psychology, computer science, and operations management. The use of this framework implies that the design of a decision support system should start with an examination of the human, organizational, and technical characteristics of the scheduling situation that has to be supported. This information can be obtained and analyzed using appropriate methodologies such as hierarchical task analysis, cognitive task analysis and cognitive work analysis as well as other methodologies, such as interviews, observations, context diagrams, and data flow diagrams. The designer of the decision support system can then match the results of the analysis to the guidelines of the theoretical framework and proceed accordingly.</p