Impacts of Public-Private School Choice on Public Schools in the St. Louis Area

St. Louis Public Schools was once a thriving school district, leading the way for cities west of the Mississippi, but since 1967 the district has been declining in enrollment and is less than 1/4th of its peak size (Feldmann and Watson 2012). This thesis has two main research questions: the first is how policy changes have affected enrollment and segregation of St. Louis area schools from 1991 to 2017. The second is how segregation and enrollment have impacted school district achievement. The primary study area includes St. Louis City Public Schools, which is located in St. Louis City County, and the more than twenty suburban public school districts surrounding the city. For the first research question, I used temporal GIS to see if segregation has increased in St. Louis area school districts from 1991 to 2017, and to see when inner-city school districts started losing enrollment to private, charter, or surrounding suburban schools. Then, using historical and political context, I explored how desegregation and school-choice efforts have affected enrollment and segregation. I found that the amount of segregated school districts increased from 63% of school districts in 1991 to 91% in 2017. Furthermore, non-segregated school districts lost enrollment from 1991 to 2017. For the second research question, I used geographically weighted regression of Missouri school districts to analyze the impact of district indicators-including enrollment and racial demographics-on student achievement. I found that enrollment had a positive correlation with school district achievement, and segregation had a negative correlation with school district achievement for school districts with a greater percentage of minorities. This thesis provides a comprehensive display of the changes in enrollment over time alongside the historical context, in order to provide a better understanding of the impacts of policy changes and school choice on St. Louis schools

The potential smoke-free dividend across local areas in England: A cross-sectional analysis

BackgroundThe value that might be added to local economies each year through the money that people who smoke tobacco would save if everyone quit smoking is called the “smoke-free dividend”. This study aimed to estimate the value of the smoke-free dividend across local areas in England, and how it relates to the average income in those areas.MethodsThe study was a cross-sectional descriptive analysis of tobacco expenditure from the Smoking Toolkit Study (STS) matched to income and smoking prevalence data for English local authorities. The STS sample was from 2014–2020 and comprised 18,721 adults who smoke cigarettes. Self-reported expenditure estimates from the STS were adjusted for under-reporting. This adjustment aimed to align the total expenditure estimate with figures derived from government tax receipts and national estimates of illicit tobacco use. The smoke-free dividend is calculated as 93% of spending on legal tobacco, which is the percentage estimated to leave the local economy, plus 100% of spending on illicit tobacco.ResultsThe total dividend in England is estimated to be £10.9 billion each year, which equates to£1,776 per person who smokes or £246 per adult regardless of smoking status. The estimated dividend is greater in areas with lower average income, with a correlation coefficient of -0.521(95% Confidence Interval: -0.629, -0.392) between the average income of local areas and the dividend per adult.ConclusionsThis study has estimated that local economies could gain a substantial dividend if everybody stopped smoking, which is larger in lower-income areas, meaning that geographic economic inequalities could be reduced

Community Engagement newsletter, Faculty of Veterinary Science, Spring 2013

Community Engagement Day for Public Health / Thandi Fourie ; photos by Nicole Epstein -- Some TLC for our canine friends / Alison Cook, Bevin Meyer, Tessa Morris, Kelsey Skinner and Olivia McMurray -- Dog bite awareness / Bob Maswanganye -- Performing to fight animal abuse / Nadine Strydom, Megan Naude, Lise-Marie Roux and Charney Sargent -- All eyes on ears / Carine du Toit.Originally published as HTML file, converted to PDF with Adobe Acrobat 9 Pro Version 9.0.0.News articles with colour photos about the various community engagement projects of the Faculty of Veterinary Science, University of Pretoria.ab201

Evidence of Histoplasma capsulatum seropositivity and exploration of risk factors for exposure in Busia county, western Kenya: analysis of the PAZ dataset

Despite recognition of histoplasmosis as a priority disease of public health concern in Kenya and an important AIDS-defining illness, there remains a paucity of research on this neglected fungal disease. Clinical and laboratory capacity for the diagnosis and treatment of histoplasmosis across Kenya is limited or unknown, and existing diagnostic and therapeutic techniques can be cost-prohibitive. In addition, the fragmentary nature of histoplasmosis research groups worldwide and the under- or over-representation of specific sociodemographic groups and geographic regions in outbreak reports and hospital-based case series have been acknowledged. This study provides a first look at Histoplasma capsulatum seroprevalence in rural western Kenya and explores risk factors for exposure at this human-animal-environment interface. More broadly, these outcomes will help quantify the burden of H. capsulatum in household and community environments, which may direct further research efforts and inform policy-makers on the prioritisation for clinical services and public health efforts with regards to histoplasmosis

Radiotherapy plus cisplatin or cetuximab in low-risk human papillomavirus-positive oropharyngeal cancer (De-ESCALaTE HPV):an open-label randomised controlled phase 3 trial

Background The incidence of human papillomavirus (HPV)-positive oropharyngeal cancer, a disease affecting younger patients, is rapidly increasing. Cetuximab, an epidermal growth factor receptor inhibitor, has been proposed for treatment de-escalation in this setting to reduce the toxicity of standard cisplatin treatment, but no randomised evidence exists for the efficacy of this strategy. Methods We did an open-label randomised controlled phase 3 trial at 32 head and neck treatment centres in Ireland, the Netherlands, and the UK, in patients aged 18 years or older with HPV-positive low-risk oropharyngeal cancer (non-smokers or lifetime smokers with a smoking history of <10 pack-years). Eligible patients were randomly assigned (1: 1) to receive, in addition to radiotherapy (70 Gy in 35 fractions), either intravenous cisplatin (100 mg/m(2) on days 1, 22, and 43 of radiotherapy) or intravenous cetuximab (400 mg/m(2) loading dose followed by seven weekly infusions of 250 mg/m(2)). The primary outcome was overall severe (grade 3-5) toxicity events at 24 months from the end of treatment. The primary outcome was assessed by intention-to-treat and per-protocol analyses. This trial is registered with the ISRCTN registry, number ISRCTN33522080. Findings Between Nov 12, 2012, and Oct 1, 2016, 334 patients were recruited (166 in the cisplatin group and 168 in the cetuximab group). Overall (acute and late) severe (grade 3-5) toxicity did not differ significantly between treatment groups at 24 months (mean number of events per patient 4.8 [95% CI 4.2-5.4] with cisplatin vs 4.8 [4.2-5.4] with cetuximab; p=0.98). At 24 months, overall all-grade toxicity did not differ significantly either (mean number of events per patient 29.2 [95% CI 27.3-31.0] with cisplatin vs 30.1 [28.3-31.9] with cetuximab; p=0.49). However, there was a significant difference between cisplatin and cetuximab in 2-year overall survival (97.5% vs 89.4%, hazard ratio 5.0 [95% CI 1.7-14.7]; p=0.001) and 2-year recurrence (6.0% vs 16.1%, 3.4 [1.6-7.2]; p=0.0007). Interpretation Compared with the standard cisplatin regimen, cetuximab showed no benefit in terms of reduced toxicity, but instead showed significant detriment in terms of tumour control. Cisplatin and radiotherapy should be used as the standard of care for HPV-positive low-risk patients who are able to tolerate cisplatin. Funding Cancer Research UK. Copyright (c) 2018 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license

Incremental value of the CT coronary calcium score for the prediction of coronary artery disease

Objectives:: To validate published prediction models for the presence of obstructive coronary artery disease (CAD) in patients with new onset stable typical or atypical angina pectoris and to assess the incremental value of the CT coronary calcium score (CTCS). Methods:: We searched the literature for clinical prediction rules for the diagnosis of obstructive CAD, defined as≥50% stenosis in at least one vessel on conventional coronary angiography. Significant variables were re-analysed in our dataset of 254 patients with logistic regression. CTCS was subsequently included in the models. The area under the receiver operating characteristic curve (AUC) was calculated to assess diagnostic performance. Results:: Re-analysing the variables used by Diamond & Forrester yielded an AUC of 0.798, which increased to 0.890 by adding CTCS. For Pryor, Morise 1994, Morise 1997 and Shaw the AUC increased from 0.838 to 0.901, 0.831 to 0.899, 0.840 to 0.898 and 0.833 to 0.899. CTCS significantly improved model performance in each model. Conclusions:: Validation demonstrated good diagnostic performance across all models. CTCS improves the prediction of the presence of obstructive CAD, independent of clinical predictors, and should be considered in its diagnostic work-up. © 2010 The Author(s)

Insecticide-Treated Nets and Protection against Insecticide-Resistant Malaria Vectors in Western Kenya

Insecticide resistance might reduce the efficacy of malaria vector control. In 2013 and 2014, malaria vectors from 50 villages, of varying pyrethroid resistance, in western Kenya were assayed for resistance to deltamethrin. Long-lasting insecticide-treated nets (LLIN) were distributed to households at universal coverage. Children were recruited into 2 cohorts, cleared of malaria-causing parasites, and tested every 2 weeks for reinfection. Infection incidence rates for the 2 cohorts were 2.2 (95% CI 1.9–2.5) infections/person-year and 2.8 (95% CI 2.5–3.0) infections/person-year. LLIN users had lower infection rates than non-LLIN users in both low-resistance (rate ratio 0.61, 95% CI 0.42–0.88) and high-resistance (rate ratio 0.55, 95% CI 0.35–0.87) villages (p = 0.63). The association between insecticide resistance and infection incidence was not significant (p = 0.99). Although the incidence of infection was high among net users, LLINs provided significant protection (p = 0.01) against infection with malaria parasite regardless of vector insecticide resistanc

Consistency of impact assessment protocols for non-native species

Standardized tools are needed to identify and prioritize the most harmful non-native species (NNS). A plethora of assessment protocols have been developed to evaluate the current and potential impacts of non-native species, but consistency among them has received limited attention. To estimate the consistency across impact assessment protocols, 89 specialists in biological invasions used 11 protocols to screen 57 NNS (2614 assessments). We tested if the consistency in the impact scoring across assessors, quantified as the coefficient of variation (CV), was dependent on the characteristics of the protocol, the taxonomic group and the expertise of the assessor. Mean CV across assessors was 40%, with a maximum of 223%. CV was lower for protocols with a low number of score levels, which demanded high levels of expertise, and when the assessors had greater expertise on the assessed species. The similarity among protocols with respect to the final scores was higher when the protocols considered the same impact types. We conclude that all protocols led to considerable inconsistency among assessors. In order to improve consistency, we highlight the importance of selecting assessors with high expertise, providing clear guidelines and adequate training but also deriving final decisions collaboratively by consensus

Future-ai:International consensus guideline for trustworthy and deployable artificial intelligence in healthcare

Despite major advances in artificial intelligence (AI) for medicine and healthcare, the deployment and adoption of AI technologies remain limited in real-world clinical practice. In recent years, concerns have been raised about the technical, clinical, ethical and legal risks associated with medical AI. To increase real world adoption, it is essential that medical AI tools are trusted and accepted by patients, clinicians, health organisations and authorities. This work describes the FUTURE-AI guideline as the first international consensus framework for guiding the development and deployment of trustworthy AI tools in healthcare. The FUTURE-AI consortium was founded in 2021 and currently comprises 118 inter-disciplinary experts from 51 countries representing all continents, including AI scientists, clinicians, ethicists, and social scientists. Over a two-year period, the consortium defined guiding principles and best practices for trustworthy AI through an iterative process comprising an in-depth literature review, a modified Delphi survey, and online consensus meetings. The FUTURE-AI framework was established based on 6 guiding principles for trustworthy AI in healthcare, i.e. Fairness, Universality, Traceability, Usability, Robustness and Explainability. Through consensus, a set of 28 best practices were defined, addressing technical, clinical, legal and socio-ethical dimensions. The recommendations cover the entire lifecycle of medical AI, from design, development and validation to regulation, deployment, and monitoring. FUTURE-AI is a risk-informed, assumption-free guideline which provides a structured approach for constructing medical AI tools that will be trusted, deployed and adopted in real-world practice. Researchers are encouraged to take the recommendations into account in proof-of-concept stages to facilitate future translation towards clinical practice of medical AI

FUTURE-AI: International consensus guideline for trustworthy and deployable artificial intelligence in healthcare

Despite major advances in artificial intelligence (AI) for medicine and healthcare, the deployment and adoption of AI technologies remain limited in real-world clinical practice. In recent years, concerns have been raised about the technical, clinical, ethical and legal risks associated with medical AI. To increase real world adoption, it is essential that medical AI tools are trusted and accepted by patients, clinicians, health organisations and authorities. This work describes the FUTURE-AI guideline as the first international consensus framework for guiding the development and deployment of trustworthy AI tools in healthcare. The FUTURE-AI consortium was founded in 2021 and currently comprises 118 inter-disciplinary experts from 51 countries representing all continents, including AI scientists, clinicians, ethicists, and social scientists. Over a two-year period, the consortium defined guiding principles and best practices for trustworthy AI through an iterative process comprising an in-depth literature review, a modified Delphi survey, and online consensus meetings. The FUTURE-AI framework was established based on 6 guiding principles for trustworthy AI in healthcare, i.e. Fairness, Universality, Traceability, Usability, Robustness and Explainability. Through consensus, a set of 28 best practices were defined, addressing technical, clinical, legal and socio-ethical dimensions. The recommendations cover the entire lifecycle of medical AI, from design, development and validation to regulation, deployment, and monitoring. FUTURE-AI is a risk-informed, assumption-free guideline which provides a structured approach for constructing medical AI tools that will be trusted, deployed and adopted in real-world practice. Researchers are encouraged to take the recommendations into account in proof-of-concept stages to facilitate future translation towards clinical practice of medical AI