A Class of Their Own: A Correlational Study on Household Composition, Chronic Absenteeism, and Graduation among African American Males

The purpose of this study was to investigate the relationship between household compositions of African American male students, chronic absenteeism, and graduation. Chronic absenteeism is missing 10% or more of the academic school year. Using Bowen family systems theory as the theoretical framework helped examine if household composition is related to chronic absenteeism and graduation in African American males. In addition, this study explored the factors that best differentiated single-mother households from two-parent households. This study was conducted in order to develop paternal involvement programs, mentoring programs, attendance programs, and academic programs to increase graduation rates and decrease chronic absenteeism for African American males. The sample included African American males who were enrolled in high school in South Carolina between 2013 and 2018. Archival data were collected from the South Carolina Department of Education on graduation and chronic absenteeism and the U.S. Census Bureau on the household compositions of single-mother and two-parent households and the median household income. Results were analyzed using Classification Tree Analysis with a Chi-square Automatic Interaction Detection growth method and a Pearson’s correlation coefficient to determine the statistical relationship between the variables. The results of the study indicated a significant relationship between household composition: single-mother and two-parent, chronic absenteeism, and graduation for African American males. Additionally, race, income below $62,028, nongraduate, and not chronically absent were identified as factors that differentiated students with single mothers from students with two-parents

“The Pandemic is Just Happening on Top of a Pandemic for Us”. Unpaid Carers’ Experiences of Lockdown in the UK: A Thematic Analysis

Context: With reduced access to medical and social support during the COVID-19 pandemic, the level of support provided by unpaid carers over the lockdown period in the UK was higher than ever. However, the experience of unpaid carers during this period is often overlooked. Objective: The aim of this study was to explore the question ‘what has been the experience of unpaid carers during lockdown?’. Method: Eighteen unpaid carers, caring for a family member(s) with physical, learning, mental health, or behavioral disabilities, were interviewed about their experience of lockdown in the UK. Thematic analysis was utilized. Findings: Three overarching themes created: (a) The value of support, (b) Non-stop care, and (c) Risk to health. A central theme of mental health was also created and discussed across the three overarching themes, rather than individually, due to its extensivity. Support for unpaid carers during the lockdown became more important than ever due to the higher risk to physical and mental health (of both the carer and dependent) and the lack of respite available. Limitations: Due to volunteer sampling, the evidence in this report is largely based on the perspectives of female carers’, with all but two participants being female. Implications: Findings raise implications for prioritizing the return of in-person medical appointments post-pandemic and ensuring the continuation of support services for unpaid carers during a pandemic

Performance of differenced range data types in Voyager navigation

Voyager radio navigation made use of a differenced rage data type for both Saturn encounters because of the low declination singularity of Doppler data. Nearly simultaneous two-way range from two-station baselines was explicitly differenced to produce this data type. Concurrently, a differential VLBI data type (DDOR), utilizing doubly differenced quasar-spacecraft delays, with potentially higher precision was demonstrated. Performance of these data types is investigated on the Jupiter-to-Saturn leg of Voyager 2. The statistics of performance are presented in terms of actual data noise comparisons and sample orbit estimates. Use of DDOR as a primary data type for navigation to Uranus is discussed

Tracking mortality in near to real time provides essential information about the impact of the COVID-19 pandemic in South Africa in 2020

Background. Producing timely and accurate estimates of the impact of COVID-19 on mortality is challenging for most countries, but impossible for South Africa (SA) from cause-of-death statistics. Objectives. To quantify the excess deaths and likely magnitude of COVID-19 in SA in 2020 and draw conclusions on monitoring the epidemic in 2021. Methods. Basic details of deaths registered on the National Population Register by the Department of Home Affairs (DoHA) are provided to the South African Medical Research Council weekly. Adjustments are made to the numbers of weekly deaths to account for non-registration on the population register, as well as late registration of death with the DoHA. The weekly number of deaths is compared with the number predicted based on the Holt-Winters time-series analysis of past deaths for provinces and metropolitan areas. Excess deaths were calculated for all-causes deaths and natural deaths, using the predicted deaths as a baseline. In addition, an adjustment was made to the baseline for natural deaths to account for the drop in natural deaths due to lockdown. Results. We estimated that just over 550 000 deaths occurred among persons aged ≥1 year during 2020, 13% higher than the 485 000 predicted before the pandemic. A pronounced increase in weekly deaths from natural causes peaked in the middle of July across all ages except <20 years, and across all provinces with slightly different timing. During December, it became clear that SA was experiencing a second wave of COVID-19 that would exceed the death toll of the first wave. In 2020, there were 70 000 - 76 000 excess deaths from natural causes, depending on the base. Using the adjusted base, the excess death rate from natural causes was 122 per 100 000 population, with a male-to-female ratio of 0.78. Deaths from unnatural causes halved for both males and females during the stringent lockdown level 5. The numbers reverted towards the predicted number with some fluctuations as lockdown restrictions varied. Just under 5 000 unnatural deaths were averted. Conclusions. Tracking the weekly numbers of deaths in near to real time has provided important information about the spatiotemporal impact of the pandemic and highlights that the ~28 000 reported COVID-19 deaths during 2020 substantially understate the death toll from COVID-19. There is an urgent need to re-engineer the system of collecting and processing cause-of-death information so that it can be accessed in a timely way to inform public health actions

Psychometric Evaluation and Design of Patient-Centered Communication Measures for Cancer Care Settings

Objective To evaluate the psychometric properties of questions that assess patient perceptions of patient-provider communication and design measures of patient-centered communication (PCC). Methods Participants (adults with colon or rectal cancer living in North Carolina) completed a survey at 2 to 3 months post-diagnosis. The survey included 87 questions in six PCC Functions: Exchanging Information, Fostering Health Relationships, Making Decisions, Responding to Emotions, Enabling Patient Self-Management, and Managing Uncertainty. For each Function we conducted factor analyses, item response theory modeling, and tests for differential item functioning, and assessed reliability and construct validity. Results Participants included 501 respondents; 46% had a high school education or less. Reliability within each Function ranged from 0.90 to 0.96. The PCC-Ca-36 (36-question survey; reliability=0.94) and PCC-Ca-6 (6-question survey; reliability=0.92) measures differentiated between individuals with poor and good health (i.e., known-groups validity) and were highly correlated with the HINTS communication scale (i.e., convergent validity). Conclusion This study provides theory-grounded PCC measures found to be reliable and valid in colorectal cancer patients in North Carolina. Future work should evaluate measure validity over time and in other cancer populations. Practice implications The PCC-Ca-36 and PCC-Ca-6 measures may be used for surveillance, intervention research, and quality improvement initiatives

Issues in public health: Unnatural deaths, alcohol bans and curfews: Evidence from a quasi-natural experiment during COVID-19

Background. Coronavirus disease-19 (COVID-19) restrictions, particularly relating to the sale of alcohol and hours of curfew, have had a marked effect on the temporal pattern of unnatural deaths in South Africa. Methods. Death data were collected over 68 weeks from January 2020 to April 2021, together with information on the nature of restrictions (if any) on the sale of alcohol, and hours of curfew. Data were analysed using a simple ordinary least square (OLS) regression model to estimate the relative contribution of restrictions on the sale of alcohol and hours of curfew to the pattern of excess unnatural deaths. Results. The complete restriction on the sale of alcohol resulted in a statistically significant reduction in unnatural deaths regardless of the length of curfew. To the contrary, periods where no or limited restrictions on alcohol were in force had no significant effect, or resulted in significantly increased unnatural deaths. Conclusion. The present study highlights an association between alcohol availability and the number of unnatural deaths and demonstrates the extent to which those deaths might be averted by disrupting the alcohol supply. While this is not a long-term solution to addressing alcohol-related harm, it further raises the importance of implementing evidence-based alcohol control measures

The role of modelling and analytics in South African COVID-19 planning and budgeting

Background The South African COVID-19 Modelling Consortium (SACMC) was established in late March 2020 to support planning and budgeting for COVID-19 related healthcare in South Africa. We developed several tools in response to the needs of decision makers in the different stages of the epidemic, allowing the South African government to plan several months ahead. Methods Our tools included epidemic projection models, several cost and budget impact models, and online dashboards to help government and the public visualise our projections, track case development and forecast hospital admissions. Information on new variants, including Delta and Omicron, were incorporated in real time to allow the shifting of scarce resources when necessary. Results Given the rapidly changing nature of the outbreak globally and in South Africa, the model projections were updated regularly. The updates reflected 1) the changing policy priorities over the course of the epidemic; 2) the availability of new data from South African data systems; and 3) the evolving response to COVID-19 in South Africa, such as changes in lockdown levels and ensuing mobility and contact rates, testing and contact tracing strategies and hospitalisation criteria. Insights into population behaviour required updates by incorporating notions of behavioural heterogeneity and behavioural responses to observed changes in mortality. We incorporated these aspects into developing scenarios for the third wave and developed additional methodology that allowed us to forecast required inpatient capacity. Finally, real-time analyses of the most important characteristics of the Omicron variant first identified in South Africa in November 2021 allowed us to advise policymakers early in the fourth wave that a relatively lower admission rate was likely. Conclusion The SACMC’s models, developed rapidly in an emergency setting and regularly updated with local data, supported national and provincial government to plan several months ahead, expand hospital capacity when needed, allocate budgets and procure additional resources where possible. Across four waves of COVID-19 cases, the SACMC continued to serve the planning needs of the government, tracking waves and supporting the national vaccine rollout

Need for timely paediatric HIV treatment within primary health care in rural South Africa

<p>Background: In areas where adult HIV prevalence has reached hyperendemic levels, many infants remain at risk of acquiring HIV infection. Timely access to care and treatment for HIV-infected infants and young children remains an important challenge. We explore the extent to which public sector roll-out has met the estimated need for paediatric treatment in a rural South African setting.</p> <p>Methods: Local facility and population-based data were used to compare the number of HIV infected children accessing HAART before 2008, with estimates of those in need of treatment from a deterministic modeling approach. The impact of programmatic improvements on estimated numbers of children in need of treatment was assessed in sensitivity analyses.</p> <p>Findings: In the primary health care programme of HIV treatment 346 children <16 years of age initiated HAART by 2008; 245(70.8%) were aged 10 years or younger, and only 2(<1%) under one year of age. Deterministic modeling predicted 2,561 HIV infected children aged 10 or younger to be alive within the area, of whom at least 521(20.3%) would have required immediate treatment. Were extended PMTCT uptake to reach 100% coverage, the annual number of infected infants could be reduced by 49.2%.</p> <p>Conclusion: Despite progress in delivering decentralized HIV services to a rural sub-district in South Africa, substantial unmet need for treatment remains. In a local setting, very few children were initiated on treatment under 1 year of age and steps have now been taken to successfully improve early diagnosis and referral of infected infants.</p&gt

Rapid mortality surveillance using a national population register to monitor excess deaths during SARS-CoV-2 pandemic in South Africa

This paper describes how an up-to-date national population register recording deaths by age and sex, whether deaths were due to natural or unnatural causes, and the offices at which the deaths were recorded can be used to monitor excess death during the SARS-CoV-2 pandemic, both nationally, and sub-nationally, in a country with a vital registration system that is neither up to date nor complete. Apart from suggesting an approach for estimating completeness of reporting at a sub-national level, the application produces estimates of the number of deaths in excess of those expected in the absence of the SARS-CoV-2 epidemic that are highly correlated with the confirmed number of COVID-19 deaths over time, but at a level 2.5 to 3 times higher than the official numbers of COVID-19 deaths. Apportioning the observed excess deaths more precisely to COVID, COVID-related and collateral deaths, and non-COVID deaths averted by interventions with reduced mobility and gatherings, etc., requires access to real-time cause-of-death information. It is suggested that the transition from ICD-10 to ICD-11 should be used as an opportunity to change from a paper-based system to electronic capture of the medical cause-of-death information