Serving Synergy: A Service-Learning Capstone

For my capstone project I chose to work with the non-profit organization Women’s and Children\u27s Alliance in Boise, Idaho. I worked with the community to provide much needed items. In order to collect donations I reached out to the community and received so much support that we were able to provide help to two other non-profit organizations the City of Lights, and Dress for Success. I was able to help organize my community to come together and provide a service to the more vulnerable in our community

Adopting a Financial Capability and Asset Building Curriculum at Historically Black Colleges and Universities

Social workers currently engage in financial capability practice with low-income and financially vulnerable individuals and families in diverse practice settings but typically lack professional preparation for this work. In response, several schools of social work have begun developing curriculum. Using an in-depth interview methodology, this study explores the experiences of faculty and administrators (N=19) at four Historically Black Colleges and Universities (HBCUs) that adopted a curriculum in financial capability and asset building. Findings show that key reasons for adopting are the relevance of the content to student and community needs, faculty interest, and alignment with program, institutional, and professional goals. Additional findings show that relationship building and trust helped create the environment for adoption

Applying cusum-based methods for the detection of outbreaks of Ross River virus disease in Western Australia

<p>Abstract</p> <p>Background</p> <p>The automated monitoring of routinely collected disease surveillance data has the potential to ensure that important changes in disease incidence are promptly recognised. However, few studies have established whether the signals produced by automated monitoring methods correspond with events considered by epidemiologists to be of public health importance. This study investigates the correspondence between retrospective epidemiological evaluation of notifications of Ross River virus (RRv) disease in Western Australia, and the signals produced by two cumulative sum (cusum)-based automated monitoring methods.</p> <p>Methods</p> <p>RRv disease case notification data between 1991 and 2004 were assessed retrospectively by two experienced epidemiologists, and the timing of identified outbreaks was compared with signals generated from two different types of cusum-based automated monitoring algorithms; the three Early Aberration Reporting System (EARS) cusum algorithms (C1, C2 and C3), and a negative binomial cusum.</p> <p>Results</p> <p>We found the negative binomial cusum to have a significantly greater area under the receiver operator characteristic curve when compared with the EARS algorithms, suggesting that the negative binomial cusum has a greater level of agreement with epidemiological opinion than the EARS algorithms with respect to the existence of outbreaks of RRv disease, particularly at low false alarm rates. However, the performance of individual EARS and negative binomial cusum algorithms were not significantly different when timeliness was also incorporated into the area under the curve analyses.</p> <p>Conclusion</p> <p>Our retrospective analysis of historical data suggests that, compared with the EARS algorithms, the negative binomial cusum provides greater sensitivity for the detection of outbreaks of RRv disease at low false alarm levels, and decreased timeliness early in the outbreak period. Prospective studies are required to investigate the potential usefulness of these algorithms in practice.</p

Participatory mental health interventions in low-income and middle-income countries: a realist review protocol

INTRODUCTION: The launch of the Movement for Global Mental Health brought long-standing calls for improved mental health interventions in low-and middle-income countries (LMICs) to centre stage. Within the movement, the participation of communities and people with lived experience of mental health problems is argued as essential to successful interventions. However, there remains a lack of conceptual clarity around ‘participation’ in mental health interventions with the specific elements of participation rarely articulated. Our review responds to this gap by exploring how ‘participation’ is applied, what it means and what key mechanisms contribute to change in participatory interventions for mental health in LMICs. METHODS AND ANALYSIS: A realist review methodology will be used to identify the different contexts that trigger mechanisms of change, and the resulting outcomes related to the development and implementation of participatory mental health interventions, that is: what makes participation work in mental health interventions in LMICs and why? We augment our search with primary data collection in communities who are the targets of global mental health initiatives to inform the production of a programme theory on participation for mental health in LMICs. ETHICS AND DISSEMINATION: Ethical approval for focus group discussions (FGDs) was obtained in each country involved. FGDs will be conducted in line with WHO safety guidance during the COVID-19 crisis. The full review will be published in an academic journal, with further papers providing an in-depth analysis on community perspectives on participation in mental health. The project findings will also be shared on a website, in webinars and an online workshop

Participatory mental health interventions in low-income and middle-income countries:A realist review protocol

INTRODUCTION: The launch of the Movement for Global Mental Health brought long-standing calls for improved mental health interventions in low-and middle-income countries (LMICs) to centre stage. Within the movement, the participation of communities and people with lived experience of mental health problems is argued as essential to successful interventions. However, there remains a lack of conceptual clarity around 'participation' in mental health interventions with the specific elements of participation rarely articulated. Our review responds to this gap by exploring how 'participation' is applied, what it means and what key mechanisms contribute to change in participatory interventions for mental health in LMICs. METHODS AND ANALYSIS: A realist review methodology will be used to identify the different contexts that trigger mechanisms of change, and the resulting outcomes related to the development and implementation of participatory mental health interventions, that is: what makes participation work in mental health interventions in LMICs and why? We augment our search with primary data collection in communities who are the targets of global mental health initiatives to inform the production of a programme theory on participation for mental health in LMICs. ETHICS AND DISSEMINATION: Ethical approval for focus group discussions (FGDs) was obtained in each country involved. FGDs will be conducted in line with WHO safety guidance during the COVID-19 crisis. The full review will be published in an academic journal, with further papers providing an in-depth analysis on community perspectives on participation in mental health. The project findings will also be shared on a website, in webinars and an online workshop

Exploring the eligibility criteria of the child support grant and its impact on poverty

One of the most important policy objectives in the post-apartheid South African economy is to reduce poverty. Although economic growth and job creation are the preferred sources of alleviating poverty and inequality, social grant spending has contributed significantly to reduce poverty (Van der Berg et al. in Poverty trends since the transition: what we know. Stellenbosch Economic Working Papers: 19/09. Stellenbosch: Stellenbosch University, 2009). Recently proposals were tabled by the Department of Social Development of South Africa (Fin24 in R3.3bn plan to extend child support grant to 21. www.fin24.com/Economy/R33bn-child-care-grant-extension-to-21-on-cards-20150316. Accessed August 7, 2015, 2015) to extend the age eligibility of the child support grant (CSG) to 21 years (at the time of writing children aged up to 18 years are eligible). This sparked an interest to investigate the impact on poverty of changes to the eligibility criteria of CSG, as well as its fiscal implications. Using person and household data from the 2010/2011 Income and Expenditure Survey, various simulations are performed to assess the impact on poverty rates and changes to social spending, given the following changes: (1) if all age-eligible children applied; (2) if all beneficiaries received the grant amount for the full 12-month duration; (3) if the age eligibility criterion is extended; and (4) if the monthly child grant income amount is revised upwards. We also examine how changes in the eligibility criteria affect the income distribution.IS

Using GIS to create synthetic disease outbreaks

BACKGROUND: The ability to detect disease outbreaks in their early stages is a key component of efficient disease control and prevention. With the increased availability of electronic health-care data and spatio-temporal analysis techniques, there is great potential to develop algorithms to enable more effective disease surveillance. However, to ensure that the algorithms are effective they need to be evaluated. The objective of this research was to develop a transparent user-friendly method to simulate spatial-temporal disease outbreak data for outbreak detection algorithm evaluation. A state-transition model which simulates disease outbreaks in daily time steps using specified disease-specific parameters was developed to model the spread of infectious diseases transmitted by person-to-person contact. The software was developed using the MapBasic programming language for the MapInfo Professional geographic information system environment. RESULTS: The simulation model developed is a generalised and flexible model which utilises the underlying distribution of the population and incorporates patterns of disease spread that can be customised to represent a range of infectious diseases and geographic locations. This model provides a means to explore the ability of outbreak detection algorithms to detect a variety of events across a large number of stochastic replications where the influence of uncertainty can be controlled. The software also allows historical data which is free from known outbreaks to be combined with simulated outbreak data to produce files for algorithm performance assessment. CONCLUSION: This simulation model provides a flexible method to generate data which may be useful for the evaluation and comparison of outbreak detection algorithm performance

Disease surveillance using a hidden Markov model

<p>Abstract</p> <p>Background</p> <p>Routine surveillance of disease notification data can enable the early detection of localised disease outbreaks. Although hidden Markov models (HMMs) have been recognised as an appropriate method to model disease surveillance data, they have been rarely applied in public health practice. We aimed to develop and evaluate a simple flexible HMM for disease surveillance which is suitable for use with sparse small area count data and requires little baseline data.</p> <p>Methods</p> <p>A Bayesian HMM was designed to monitor routinely collected notifiable disease data that are aggregated by residential postcode. Semi-synthetic data were used to evaluate the algorithm and compare outbreak detection performance with the established Early Aberration Reporting System (EARS) algorithms and a negative binomial cusum.</p> <p>Results</p> <p>Algorithm performance varied according to the desired false alarm rate for surveillance. At false alarm rates around 0.05, the cusum-based algorithms provided the best overall outbreak detection performance, having similar sensitivity to the HMMs and a shorter average time to detection. At false alarm rates around 0.01, the HMM algorithms provided the best overall outbreak detection performance, having higher sensitivity than the cusum-based Methods and a generally shorter time to detection for larger outbreaks. Overall, the 14-day HMM had a significantly greater area under the receiver operator characteristic curve than the EARS C3 and 7-day negative binomial cusum algorithms.</p> <p>Conclusion</p> <p>Our findings suggest that the HMM provides an effective method for the surveillance of sparse small area notifiable disease data at low false alarm rates. Further investigations are required to evaluation algorithm performance across other diseases and surveillance contexts.</p

Rapid HIV testing program implementation: lessons from the emergency department

Background: The US Centers for Disease Control and Prevention (CDC) guidelines and the World Health Organization (WHO) both recommend HIV testing in health-care settings. However, neither organization provides prescriptive details regarding how these recommendations should be adapted into clinical practice in an emergency department. Methods: We have implemented an HIV-testing program in the ED of a major academic medical center within the scope of the Universal Screening for HIV Infection in the Emergency Room (USHER) Trial—a randomized clinical trial evaluating the feasibility and cost-effectiveness of HIV screening in this setting. Results and conclusion: Drawing on our collective experiences in establishing programs domestically and internationally, we offer a practical framework of lessons learned so that others poised to embark on such HIV testing programs may benefit from our experiences