Mortality variability and differentials by age and causes of death in rural South Africa, 1994-2018.

INTRODUCTION: Understanding mortality variability by age and cause is critical to identifying intervention and prevention actions to support disadvantaged populations. We assessed mortality changes in two rural South African populations over 25 years covering pre-AIDS and peak AIDS epidemic and subsequent antiretroviral therapy (ART) availability. METHODS: Using population surveillance data from the Agincourt Health and Socio-Demographic Surveillance System (AHDSS; 1994-2018) and Africa Health Research Institute (AHRI; 2000-2018) for 5-year periods, we calculated life expectancy from birth to age 85, mortality age distributions and variation, and life-years lost (LYL) decomposed into four cause-of-death groups. RESULTS: The AIDS epidemic shifted the age-at-death distribution to younger ages and increased LYL. For AHDSS, between 1994-1998 and 1999-2003 LYL increased for females from 13.6 years (95% CI 12.7 to 14.4) to 22.1 (95% CI 21.2 to 23.0) and for males from 19.9 (95% CI 18.8 to 20.8) to 27.1 (95% CI 26.2 to 28.0). AHRI LYL in 2000-2003 was extremely high (females=40.7 years (95% CI 39.8 to 41.5), males=44.8 years (95% CI 44.1 to 45.5)). Subsequent widespread ART availability reduced LYL (2014-2018) for women (AHDSS=15.7 (95% CI 15.0 to 16.3); AHRI=22.4 (95% CI 21.7 to 23.1)) and men (AHDSS=21.2 (95% CI 20.5 to 22.0); AHRI=27.4 (95% CI 26.7 to 28.2)), primarily due to reduced HIV/AIDS/TB deaths in mid-life and other communicable disease deaths in children. External causes increased as a proportion of LYL for men (2014-2018: AHRI=25%, AHDSS=17%). The share of AHDSS LYL 2014-2018 due to non-communicable diseases exceeded pre-HIV levels: females=43%; males=40%. CONCLUSIONS: Our findings highlight shifting burdens in cause-specific LYL and persistent mortality differentials in two populations experiencing complex epidemiological transitions. Results show high contributions of child deaths to LYL at the height of the AIDS epidemic. Reductions in LYL were primarily driven by lowered HIV/AIDS/TB and other communicable disease mortality during the ART periods. LYL differentials persist despite widespread ART availability, highlighting the contributions of other communicable diseases in children, HIV/AIDS/TB and external causes in mid-life and non-communicable diseases in older ages.

Understanding Household Dynamics From the Ground Up: A Longitudinal Study From a Rural South African Setting.

Investigations into household structure in low- and middle-income countries (LMICs) provide important insight into how families manage domestic life in response to resource allocation and caregiving needs during periods of rapid sociopolitical and health-related challenges. Recent evidence on household structure in many LMICs contrasts with long-standing viewpoints of worldwide convergence to a Western nuclearized household model. Here, we adopt a household-centered theoretical and methodological framework to investigate longitudinal patterns and dynamics of household structure in a rural South African setting during a period of high AIDS-related mortality and socioeconomic change. Data come from the Agincourt Health and Socio-Demographic Surveillance System (2003-2015). Using latent transition models, we derived six distinct household types by examining conditional interdependency between household heads' characteristics, members' age composition, and migration status. More than half of households were characterized by their complex and multigenerational profiles, with considerable within-typology variation in household size and dependency structure. Transition analyses showed stability of household types under female headship, while higher proportions of nuclearized household types dissolved over time. Household dissolution was closely linked to prior mortality experiences-particularly, following death of a male head. Our findings highlight the need to better conceptualize and contextualize household changes across populations and over time.

Agreement between cause of death assignment by computer-coded verbal autopsy methods and physician coding of verbal autopsy interviews in South Africa.

BACKGROUND: The South African national cause of death validation (NCODV 2017/18) project collected a national sample of verbal autopsies (VA) with cause of death (COD) assignment by physician-coded VA (PCVA) and computer-coded VA (CCVA). OBJECTIVE: The performance of three CCVA algorithms (InterVA-5, InSilicoVA and Tariff 2.0) in assigning a COD was compared with PCVA (reference standard). METHODS: Seven performance metrics assessed individual and population level agreement of COD assignment by age, sex and place of death subgroups. Positive predictive value (PPV), sensitivity, overall agreement, kappa, and chance corrected concordance (CCC) assessed individual level agreement. Cause-specific mortality fraction (CSMF) accuracy and Spearman's rank correlation assessed population level agreement. RESULTS: A total of 5386 VA records were analysed. PCVA and CCVAs all identified HIV/AIDS as the leading COD. CCVA PPV and sensitivity, based on confidence intervals, were comparable except for HIV/AIDS, TB, maternal, diabetes mellitus, other cancers, and some injuries. CCVAs performed well for identifying perinatal deaths, road traffic accidents, suicide and homicide but poorly for pneumonia, other infectious diseases and renal failure. Overall agreement between CCVAs and PCVA for the top single cause (48.2-51.6) indicated comparable weak agreement between methods. Overall agreement, for the top three causes showed moderate agreement for InterVA (70.9) and InSilicoVA (73.8). Agreement based on kappa (-0.05-0.49)and CCC (0.06-0.43) was weak to none for all algorithms and groups. CCVAs had moderate to strong agreement for CSMF accuracy, with InterVA-5 highest for neonates (0.90), Tariff 2.0 highest for adults (0.89) and males (0.84), and InSilicoVA highest for females (0.88), elders (0.83) and out-of-facility deaths (0.85). Rank correlation indicated moderate agreement for adults (0.75-0.79). CONCLUSIONS: Whilst CCVAs identified HIV/AIDS as the leading COD, consistent with PCVA, there is scope for improving the algorithms for use in South Africa.

Dynamics of oil-water interface at the beginning of the ultrasonic emulsification process.

A lot of effort has been dedicated in recent years towards understanding the basics of cavitation induced emulsification, mainly in the form of single cavitation bubbles. Regarding bulk acoustic emulsification, a lot less research has been done. In our here presented work we utilize advanced high-speed observation techniques in visible light and X-Rays to build upon that knowledge and advance the understanding of bulk emulsion preparation. During research we discovered that emulsion formation has an acute impact on the behavior of the interface and more importantly on its position relative to the horn, hence their interdependence must be carefully studied. We did this by observing bulk emulsification with 2 cameras simultaneously and corroborating these measurements with observation under X-Rays. Since the ultrasonic horns location also influences interface behavior, we shifted its initial position to different locations nearer to and further away from the oil-water interface in both phases. We found that a few millimeters distance between the horn and interface is not enough for fine emulsion formation, but that they must be completely adjacent to each other, with the horn being located inside the oil-water interface. We also observed some previously undiscovered phenomena, such as the splitting of the interface to preserve continuous emulsion formation, climbing of the interface up the horn and circular interface protrusions towards the horn forming vertical emulsion streams. Interestingly, no visible W/O emulsion was ever formed during our experiments, only O/W regardless of initial horn position.

The effects of HIV and systolic blood pressure on mortality risk in rural South Africa, 2010-2019: a data note.

OBJECTIVES: South Africa is experiencing both HIV and hypertension epidemics. Data were compiled for a study to identify effects of HIV and high systolic blood pressure on mortality risk among people aged 40-plus in a rural South African area experiencing high prevalence of both conditions. We aim to release the replication data set for this study. DATA DESCRIPTION: The research data comes from the 2010-11 Ha Nakekela (We Care) population-based survey nested in the Agincourt Health and socio-Demographic Surveillance System (AHDSS) located in the northeast region of South Africa. An age-sex-stratified probability sample was drawn from the AHDSS. The public data set includes information on individual socioeconomic characteristics and measures of HIV status and blood pressure for participants aged 40-plus by 2019. The AHDSS, through its annual surveillance, provided mortality data for nine years subsequent to the survey. These data were converted to person-year observations and linked to the individual-level survey data using participants' AHDSS census identifier. The data can be used to replicate Houle et al. (2022) - which used discrete-time event history models stratified by sex to assess differential mortality risks according to Ha Nakekela measures of HIV-infection, HIV-1 RNA viral load, and systolic blood pressure.

Household structure, composition and child mortality in the unfolding antiretroviral therapy era in rural South Africa: comparative evidence from population surveillance, 2000-2015.

OBJECTIVES: The structure and composition of the household has important influences on child mortality. However, little is known about these factors in HIV-endemic areas and how associations may change with the introduction and widespread availability of antiretroviral treatment (ART). We use comparative, longitudinal data from two demographic surveillance sites in rural South Africa (2000-2015) on mortality of children younger than 5 years (n=101 105). DESIGN: We use multilevel discrete time event history analysis to estimate children's probability of dying by their matrilineal residential arrangements. We also test if associations have changed over time with ART availability. SETTING: Rural South Africa. PARTICIPANTS: Children younger than 5 years (n=101 105). RESULTS: 3603 children died between 2000 and 2015. Mortality risks differed by co-residence patterns along with different types of kin present in the household. Children in nuclear households with both parents had the lowest risk of dying compared with all other household types. Associations with kin and child mortality were moderated by parental status. Having older siblings lowered the probability of dying only for children in a household with both parents (relative risk ratio (RRR)=0.736, 95% CI (0.633 to 0.855)). Only in the later ART period was there evidence that older adult kin lowered the probability of dying for children in single parent households (RRR=0.753, 95% CI (0.664 to 0.853)). CONCLUSIONS: Our findings provide comparative evidence of how differential household profiles may place children at higher mortality risk. Formative research is needed to understand the role of other household kin in promoting child well-being, particularly in one-parent households that are increasingly prevalent.

Machine learning-aided real-time detection of keyhole pore generation in laser powder bed fusion.

Porosity defects are currently a major factor that hinders the widespread adoption of laser-based metal additive manufacturing technologies. One common porosity occurs when an unstable vapor depression zone (keyhole) forms because of excess laser energy input. With simultaneous high-speed synchrotron x-ray imaging and thermal imaging, coupled with multiphysics simulations, we discovered two types of keyhole oscillation in laser powder bed fusion of Ti-6Al-4V. Amplifying this understanding with machine learning, we developed an approach for detecting the stochastic keyhole porosity generation events with submillisecond temporal resolution and near-perfect prediction rate. The highly accurate data labeling enabled by operando x-ray imaging allowed us to demonstrate a facile and practical way to adopt our approach in commercial systems.

Time resolved in-situ multi-contrast X-ray imaging of melting in metals.

In this work, the application of a time resolved multi-contrast beam tracking technique to the investigation of the melting and solidification process in metals is presented. The use of such a technique allows retrieval of three contrast channels, transmission, refraction and dark-field, with millisecond time resolution. We investigated different melting conditions to characterize, at a proof-of-concept level, the features visible in each of the contrast channels. We found that the phase contrast channel provides a superior visibility of the density variations, allowing the liquid metal pool to be clearly distinguished. Refraction and dark-field were found to highlight surface roughness formed during solidification. This work demonstrates that the availability of the additional contrast channels provided by multi-contrast X-ray imaging delivers additional information, also when imaging high atomic number specimens with a significant absorption.

Keyhole fluctuation and pore formation mechanisms during laser powder bed fusion additive manufacturing.

Keyhole porosity is a key concern in laser powder-bed fusion (LPBF), potentially impacting component fatigue life. However, some keyhole porosity formation mechanisms, e.g., keyhole fluctuation, collapse and bubble growth and shrinkage, remain unclear. Using synchrotron X-ray imaging we reveal keyhole and bubble behaviour, quantifying their formation dynamics. The findings support the hypotheses that: (i) keyhole porosity can initiate not only in unstable, but also in the transition keyhole regimes created by high laser power-velocity conditions, causing fast radial keyhole fluctuations (2.5-10 kHz); (ii) transition regime collapse tends to occur part way up the rear-wall; and (iii) immediately after keyhole collapse, bubbles undergo rapid growth due to pressure equilibration, then shrink due to metal-vapour condensation. Concurrent with condensation, hydrogen diffusion into the bubble slows the shrinkage and stabilises the bubble size. The keyhole fluctuation and bubble evolution mechanisms revealed here may guide the development of control systems for minimising porosity.

Twin epidemics: the effects of HIV and systolic blood pressure on mortality risk in rural South Africa, 2010-2019.

BACKGROUND: Sub-Saharan African settings are experiencing dual epidemics of HIV and hypertension. We investigate effects of each condition on mortality and examine whether HIV and hypertension interact in determining mortality. METHODS: Data come from the 2010 Ha Nakekela population-based survey of individuals ages 40 and older (1,802 women; 1,107 men) nested in the Agincourt Health and socio-Demographic Surveillance System in rural South Africa, which provides mortality follow-up from population surveillance until mid-2019. Using discrete-time event history models stratified by sex, we assessed differential mortality risks according to baseline measures of HIV infection, HIV-1 RNA viral load, and systolic blood pressure. RESULTS: During the 8-year follow-up period, mortality was high (477 deaths). Survey weighted estimates are that 37% of men (mortality rate 987.53/100,000, 95% CI: 986.26 to 988.79) and 25% of women (mortality rate 937.28/100,000, 95% CI: 899.7 to 974.88) died. Over a quarter of participants were living with HIV (PLWH) at baseline, over 50% of whom had unsuppressed viral loads. The share of the population with a systolic blood pressure of 140mm Hg or higher increased from 24% at ages 40-59 to 50% at ages 75-plus and was generally higher for those not living with HIV compared to PLWH. Men and women with unsuppressed viral load had elevated mortality risks (men: adjusted odds ratio (aOR) 3.23, 95% CI: 2.21 to 4.71, women: aOR 2.05, 95% CI: 1.27 to 3.30). There was a weak, non-linear relationship between systolic blood pressure and higher mortality risk. We found no significant interaction between systolic blood pressure and HIV status for either men or women (p>0.05). CONCLUSIONS: Our results indicate that HIV and elevated blood pressure are acting as separate, non-interacting epidemics affecting high proportions of the older adult population. PLWH with unsuppressed viral load were at higher mortality risk compared to those uninfected. Systolic blood pressure was a mortality risk factor independent of HIV status. As antiretroviral therapy becomes more widespread, further longitudinal follow-up is needed to understand how the dynamics of increased longevity and multimorbidity among people living with both HIV and high blood pressure, as well as the emergence of COVID-19, may alter these patterns.

The openVA Toolkit for Verbal Autopsies.

Verbal autopsy (VA) is a survey-based tool widely used to infer cause of death (COD) in regions without complete-coverage civil registration and vital statistics systems. In such settings, many deaths happen outside of medical facilities and are not officially documented by a medical professional. VA surveys, consisting of signs and symptoms reported by a person close to the decedent, are used to infer the COD for an individual, and to estimate and monitor the COD distribution in the population. Several classification algorithms have been developed and widely used to assign causes of death using VA data. However, the incompatibility between different idiosyncratic model implementations and required data structure makes it difficult to systematically apply and compare different methods. The openVA package provides the first standardized framework for analyzing VA data that is compatible with all openly available methods and data structure. It provides an open-source, R implementation of several most widely used VA methods. It supports different data input and output formats, and customizable information about the associations between causes and symptoms. The paper discusses the relevant algorithms, their implementations in R packages under the openVA suite, and demonstrates the pipeline of model fitting, summary, comparison, and visualization in the R environment.

Dynamic Multicontrast X-Ray Imaging Method Applied to Additive Manufacturing.

We present a dynamic implementation of the beam-tracking x-ray imaging method providing absorption, phase, and ultrasmall angle scattering signals with microscopic resolution and high frame rate. We demonstrate the method's ability to capture dynamic processes with 22-ms time resolution by investigating the melting of metals in laser additive manufacturing, which has so far been limited to single-modality synchrotron radiography. The simultaneous availability of three contrast channels enables earlier segmentation of droplets, tracking of powder dynamic, and estimation of unfused powder amounts, demonstrating that the method can provide additional information on melting processes.

Estimating seroprevalence of SARS-CoV-2 in Ohio: A Bayesian multilevel poststratification approach with multiple diagnostic tests.

Globally, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has infected more than 59 million people and killed more than 1.39 million. Designing and monitoring interventions to slow and stop the spread of the virus require knowledge of how many people have been and are currently infected, where they live, and how they interact. The first step is an accurate assessment of the population prevalence of past infections. There are very few population-representative prevalence studies of SARS-CoV-2 infections, and only two states in the United States-Indiana and Connecticut-have reported probability-based sample surveys that characterize statewide prevalence of SARS-CoV-2. One of the difficulties is the fact that tests to detect and characterize SARS-CoV-2 coronavirus antibodies are new, are not well characterized, and generally function poorly. During July 2020, a survey representing all adults in the state of Ohio in the United States collected serum samples and information on protective behavior related to SARS-CoV-2 and coronavirus disease 2019 (COVID-19). Several features of the survey make it difficult to estimate past prevalence: 1) a low response rate; 2) a very low number of positive cases; and 3) the fact that multiple poor-quality serological tests were used to detect SARS-CoV-2 antibodies. We describe a Bayesian approach for analyzing the biomarker data that simultaneously addresses these challenges and characterizes the potential effect of selective response. The model does not require survey sample weights; accounts for multiple imperfect antibody test results; and characterizes uncertainty related to the sample survey and the multiple imperfect, potentially correlated tests.

Should the SARS-CoV-2 vaccine be mandatory for nurses? An ethical debate.

The COVID-19 pandemic has had a devastating impact on the UK, as well as many other countries around the world, affecting all aspects of society. Nurses and other health and care professionals are a group particularly exposed to the virus through their work. Evidence suggests that vaccines form the most promising strategy for fighting this pandemic. Should vaccination against be mandatory for nurses and other health professionals? This article explores this question using an ethical framework.

Linking the timing of a mother's and child's death: Comparative evidence from two rural South African population-based surveillance studies, 2000-2015.

BACKGROUND: The effect of the period before a mother's death on child survival has been assessed in only a few studies. We conducted a comparative investigation of the effect of the timing of a mother's death on child survival up to age five years in rural South Africa. METHODS: We used discrete time survival analysis on data from two HIV-endemic population surveillance sites (2000-2015) to estimate a child's risk of dying before and after their mother's death. We tested if this relationship varied between sites and by availability of antiretroviral therapy (ART). We assessed if related adults in the household altered the effect of a mother's death on child survival. FINDINGS: 3,618 children died from 2000-2015. The probability of a child dying began to increase in the 7-11 months prior to the mother's death and increased markedly in the 3 months before (2000-2003 relative risk = 22.2, 95% CI = 14.2-34.6) and 3 months following her death (2000-2003 RR = 20.1; CI = 10.3-39.4). This increased risk pattern was evident at both sites. The pattern attenuated with ART availability but remained even with availability at both sites. The father and maternal grandmother in the household lowered children's mortality risk independent of the association between timing of mother and child mortality. CONCLUSIONS: The persistence of elevated mortality risk both before and after the mother's death for children of different ages suggests that absence of maternal care and abrupt breastfeeding cessation might be crucial risk factors. Formative research is needed to understand the circumstances for children when a mother is very ill or dies, and behavioral and other risk factors that increase both the mother and child's risk of dying. Identifying families when a mother is very ill and implementing training and support strategies for other members of the household are urgently needed to reduce preventable child mortality.

Health and demographic surveillance systems in low- and middle-income countries: history, state of the art and future prospects.

Health and Demographic Surveillance Systems (HDSS) have been developed in several low- and middle-income countries (LMICs) in Africa and Asia. This paper reviews their history, state of the art and future potential and highlights substantial areas of contribution by the late Professor Peter Byass.Historically, HDSS appeared in the second half of the twentieth century, responding to a dearth of accurate population data in poorly resourced settings to contextualise the study of interventions to improve health and well-being. The progress of the development of this network is described starting with Pholela, and progressing through Gwembe, Balabgarh, Niakhar, Matlab, Navrongo, Agincourt, Farafenni, and Butajira, and the emergence of the INDEPTH Network in the early 1990'sThe paper describes the HDSS methodology, data, strengths, and limitations. The strengths are particularly their temporal coverage, detail, dense linkage, and the fact that they exist in chronically under-documented populations in LMICs where HDSS sites operate. The main limitations are generalisability to a national population and a potential Hawthorne effect, whereby the project itself may have changed characteristics of the population.The future will include advances in HDSS data harmonisation, accessibility, and protection. Key applications of the data are to validate and assess bias in other datasets. A strong collaboration between a national HDSS network and the national statistics office is modelled in South Africa and Sierra Leone, and it is possible that other low- to middle-income countries will see the benefit and take this approach.

Estimating causes of death where there is no medical certification: evolution and state of the art of verbal autopsy.

Over the past 70 years, significant advances have been made in determining the causes of death in populations not served by official medical certification of cause at the time of death using a technique known as Verbal Autopsy (VA). VA involves an interview of the family or caregivers of the deceased after a suitable bereavement interval about the circumstances, signs and symptoms of the deceased in the period leading to death. The VA interview data are then interpreted by physicians or, more recently, computer algorithms, to assign a probable cause of death. VA was originally developed and applied in field research settings. This paper traces the evolution of VA methods with special emphasis on the World Health Organization's (WHO)'s efforts to standardize VA instruments and methods for expanded use in routine health information and vital statistics systems in low- and middle-income countries (LMICs). These advances in VA methods are culminating this year with the release of the 2022 WHO Standard Verbal Autopsy (VA) Toolkit. This paper highlights the many contributions the late Professor Peter Byass made to the current VA standards and methods, most notably, the development of InterVA, the most commonly used automated computer algorithm for interpreting data collected in the WHO standard instruments, and the capacity building in low- and middle-income countries (LMICs) that he promoted. This paper also provides an overview of the methods used to improve the current WHO VA standards, a catalogue of the changes and improvements in the instruments, and a mapping of current applications of the WHO VA standard approach in LMICs. It also provides access to tools and guidance needed for VA implementation in Civil Registration and Vital Statistics Systems at scale.

Using Bayesian Latent Gaussian Graphical Models to Infer Symptom Associations in Verbal Autopsies.

Learning dependence relationships among variables of mixed types provides insights in a variety of scientific settings and is a well-studied problem in statistics. Existing methods, however, typically rely on copious, high quality data to accurately learn associations. In this paper, we develop a method for scientific settings where learning dependence structure is essential, but data are sparse and have a high fraction of missing values. Specifically, our work is motivated by survey-based cause of death assessments known as verbal autopsies (VAs). We propose a Bayesian approach to characterize dependence relationships using a latent Gaussian graphical model that incorporates informative priors on the marginal distributions of the variables. We demonstrate such information can improve estimation of the dependence structure, especially in settings with little training data. We show that our method can be integrated into existing probabilistic cause-of-death assignment algorithms and improves model performance while recovering dependence patterns between symptoms that can inform efficient questionnaire design in future data collection.