Reframing Kurtz’s Painting: Colonial Legacies and Minority Rights in Ethnically Divided Societies

Minority rights constitute some of the most normatively and economically important human rights. Although the political science and legal literatures have proffered a number of constitutional and institutional design solutions to address the protection of minority rights, these solutions are characterized by a noticeable neglect of, and lack of sensitivity to, historical processes. This Article addresses that gap in the literature by developing a causal argument that explains diverging practices of minority rights protections as functions of colonial governments’ variegated institutional practices with respect to particular ethnic groups. Specifically, this Article argues that in instances where colonial governments politicize and institutionalize ethnic hegemony in the pre-independence period, an institutional legacy is created that leads to lower levels of minority rights protections. Conversely, a uniform treatment and depoliticization of ethnicity prior to independence ultimately minimizes ethnic cleavages post-independence and consequently causes higher levels of minority rights protections. Through a highly structured comparative historical analysis of Botswana and Ghana, this Article builds on a new and exciting research agenda that focuses on the role of long-term historio-structural and institutional influences on human rights performance and makes important empirical contributions by eschewing traditional methodologies that focus on single case studies that are largely descriptive in their analyses. Ultimately, this Article highlights both the strength of a historical approach to understanding current variations in minority rights protections and the varied institutional responses within a specific colonial government

Delayed Interventions, Low Compliance, and Health Disparities Amplified the Early Spread of COVID-19

The United States (US) public health interventions were rigorous and rapid, yet failed to arrest the spread of the Coronavirus Disease 2019 (COVID-19) pandemic as infections spread throughout the US. Many factors have contributed to the spread of COVID-19, and the success of public health interventions depends on the level of community adherence to preventative measures. Public health professionals must also understand regional demographic variation in health disparities and determinants to target interventions more effectively. In this study, a systematic evaluation of three significant interventions employed in the US, and their effectiveness in slowing the early spread of COVID-19 was conducted. Next, community-level compliance with a state-level stay at home orders was assessed to determine COVID-19 spread behavior. Finally, health disparities that may have contributed to the disproportionate acceleration of early COVID-19 spread between certain counties were characterized. The contribution of these factors for the disproportionate spread of the disease was analyzed using both univariate and multivariate statistical analyses. Results of this investigation show that delayed implementation of public health interventions, a low level of compliance with the stay at home orders, in conjunction with health disparities, significantly contributed to the early spread of the COVID-19 pandemic

Telehealth for patients at high risk of cardiovascular disease: pragmatic randomised controlled trial

Objective: To assess whether non-clinical staff can effectively manage people at high risk of cardiovascular disease using digital health technologies. Design: Pragmatic, multicentre, randomised controlled trial. Setting: 42 general practices in three areas of England. Participants: Between 3 December 2012 and 23 July 2013 we recruited 641 adults aged 40 to 74 years with a 10 year cardiovascular disease risk of 20% or more, no previous cardiovascular event, at least one modifiable risk factor (systolic blood pressure ≥140 mm Hg, body mass index ≥30, current smoker), and access to a telephone, the internet, and email. Participants were individually allocated to intervention (n=325) or control (n=316) groups using automated randomisation stratified by site, minimised by practice and baseline risk score. Interventions: Intervention was the Healthlines service (alongside usual care), comprising regular telephone calls from trained lay health advisors following scripts generated by interactive software. Advisors facilitated self-management by supporting participants to use online resources to reduce risk factors, and sought to optimise drug use, improve treatment adherence, and encourage healthier lifestyles. The control group comprised usual care alone. Main outcome measures: The primary outcome was the proportion of participants responding to treatment, defined as maintaining or reducing their cardiovascular risk after 12 months. Outcomes were collected six and 12 months after randomisation and analysed masked. Participants were not masked. Results: 50% (148/295) of participants in the intervention group responded to treatment compared with 43% (124/291) in the control group (adjusted odds ratio 1.3, 95% confidence interval 1.0 to 1.9; number needed to treat=13); a difference possibly due to chance (P=0.08). The intervention was associated with reductions in blood pressure (difference in mean systolic −2.7 mm Hg (95% confidence interval −4.7 to −0.6 mm Hg), mean diastolic −2.8 (−4.0 to −1.6 mm Hg); weight −1.0 kg (−1.8 to −0.3 kg), and body mass index −0.4 (−0.6 to −0.1) but not cholesterol −0.1 (−0.2 to 0.0), smoking status (adjusted odds ratio 0.4, 0.2 to 1.0), or overall cardiovascular risk as a continuous measure (−0.4, −1.2 to 0.3)). The intervention was associated with improvements in diet, physical activity, drug adherence, and satisfaction with access to care, treatment received, and care coordination. One serious related adverse event occurred, when a participant was admitted to hospital with low blood pressure. Conclusions: This evidence based telehealth approach was associated with small clinical benefits for a minority of people with high cardiovascular risk, and there was no overall improvement in average risk. The Healthlines service was, however, associated with improvements in some risk behaviours, and in perceptions of support and access to care

The Personalized Acne Treatment Tool - Recommendations to facilitate a patient-centered approach to acne management from the Personalizing Acne: Consensus of Experts

BACKGROUND: Acne, a commonly treated skin disease, requires patient-centered management due to its varying presentations, chronicity, and impact on health-related quality of life. Despite this, evidence-based clinical guidelines focus primarily on clinical severity of facial acne, omitting important patient- and disease-related factors, including ongoing management. OBJECTIVES: To generate recommendations to support patient-centered acne management, which incorporate priority and prognostic factors beyond conventional clinical severity, traditionally defined by grading the appearance and extent of visible lesions. METHODS: The Personalizing Acne: Consensus of Experts consisted of 17 dermatologists who used a modified Delphi approach to reach consensus on statements regarding patient- and treatment-related factors pertaining to patient-centered acne management. Consensus was defined as ≥75% voting agree or strongly agree. RESULTS: Recommendations based on factors such as acne sequelae, location of acne, high burden of disease, and individual patient features were generated and incorporated into the Personalized Acne Treatment Tool. LIMITATIONS: Recommendations are based on expert opinion, which may differ from patients\u27 perspectives. Regional variations in healthcare systems may not be represented. CONCLUSIONS: The Personalizing Acne: Consensus of Experts panel provided practical recommendations to facilitate individualized management of acne, based on patient features, which can be implemented to improve treatment outcomes, adherence, and patient satisfaction

Investigating spatial error structures in continuous raster data

The objective of this study is to investigate spatial structures of error in the assessment of continuous raster data. The use of conventional diagnostics of error often overlooks the possible spatial variation in error because such diagnostics report only average error or deviation between predicted and reference values. In this respect, this work uses a moving window (kernel) approach to generate geographically weighted (GW) versions of the mean signed deviation, the mean absolute error and the root mean squared error and to quantify their spatial variations. Such approach computes local error diagnostics from data weighted by its distance to the centre of a moving kernel and allows to map spatial surfaces of each type of error. In addition, a GW correlation analysis between predicted and reference values provides an alternative view of local error. These diagnostics are applied to two earth observation case studies. The results reveal important spatial structures of error and unusual clusters of error can be identified through Monte Carlo permutation tests. The first case study demonstrates the use of GW diagnostics to fractional impervious surface area datasets generated by four different models for the Jakarta metropolitan area, Indonesia. The GW diagnostics reveal where the models perform differently and similarly, and found areas of under-prediction in the urban core, with larger errors in peri-urban areas. The second case study uses the GW diagnostics to four remotely sensed aboveground biomass datasets for the Yucatan Peninsula, Mexico. The mapping of GW diagnostics provides a means to compare the accuracy of these four continuous raster datasets locally. The discussion considers the relative nature of diagnostics of error, determining moving window size and issues around the interpretation of different error diagnostic measures. Investigating spatial structures of error hidden in conventional diagnostics of error provides informative descriptions of error in continuous raster data

The Impact of Contributor Confidence, Expertise and Distance on the Crowdsourced Land Cover Data Quality. GI_Forum 2014 – Geospatial Innovation for Society|

There is much interest in the opportunities for formal scientific investigations afforded by crowdsourcing and citizen sensing activities. However, one of the critical research issues relates to the ‘quality’ of the data collected in this way. This paper uses volunteer data on land cover collected under the Geo-Wiki system, where contributors label the land cover class at a series of locations, with expert labels at the same locations. It examines the statistical relationships between the accuracy of volunteer labels, their self assessed confidence in labelling, their ‘experiential distance’ to the location under consideration and the level of their domain expertise. The results show that distance has a minor effect on the reliability of land cover labelling, and that generally expertise has a greater effect, but not for all land cover classes

The Impact of Contributor Confidence, Expertise and Distance on the Crowdsourced Land Cover Data Quality. GI_Forum 2014 – Geospatial Innovation for Society|

There is much interest in the opportunities for formal scientific investigations afforded by crowdsourcing and citizen sensing activities. However, one of the critical research issues relates to the ‘quality’ of the data collected in this way. This paper uses volunteer data on land cover collected under the Geo-Wiki system, where contributors label the land cover class at a series of locations, with expert labels at the same locations. It examines the statistical relationships between the accuracy of volunteer labels, their self assessed confidence in labelling, their ‘experiential distance’ to the location under consideration and the level of their domain expertise. The results show that distance has a minor effect on the reliability of land cover labelling, and that generally expertise has a greater effect, but not for all land cover classes