In 2021, the leading causes of death in Africa were lower respiratory infections, malaria, and stroke. That year, lower respiratory infections resulted in around 65 deaths per 100,000 population in Africa. Leading causes of death in Africa vs the world Worldwide, the top three leading causes of death in 2021 were heart disease, COVID-19, and stroke. At that time, some of the leading causes of death in Africa, such as lower respiratory infections and stroke, were among the leading causes worldwide, but there were also stark differences in the leading causes of death in Africa compared to the leading causes worldwide. For example, malaria, diarrheal disease, and preterm birth complications were among the top ten leading causes of death in Africa, but not worldwide. Furthermore, HIV/AIDS was the eighth leading cause of death in Africa at that time, but was not among the top ten leading causes worldwide. HIV/AIDS in Africa Although HIV/AIDS impacts every region of the world, Africa is still the region most impacted by this deadly virus. Worldwide, there are around 40 million people currently living with HIV, with about 20.8 million found in Eastern and Southern Africa and 5.1 million in Western and Central Africa. The countries with the highest HIV prevalence worldwide include Eswatini, Lesotho, and South Africa, with the leading 20 countries by HIV prevalence all found in Africa. However, due in part to improvements in education and awareness, the prevalence of HIV in many African countries has decreased. For example, in Botswana, the prevalence of HIV decreased from 26.1 percent to 16.6 percent in the period from 2000 to 2023.

Lower respiratory infections were the leading cause of death in Africa in 2021. Lower respiratory infections accounted for 8.6 percent of all deaths in Africa that year, followed by malaria, which was responsible for 6.5 percent of deaths. Although HIV is not one of the leading causes of death worldwide, it remains within the top 10 leading causes of death in Africa. As of 2023, the top 15 countries with the highest prevalence of new HIV infections are all found in Africa. HIV/AIDS HIV (human immunodeficiency virus) is an infectious sexually transmitted disease that is transmitted via exposure to infected semen, blood, vaginal and anal fluids and breast milk. HIV weakens the human immune system, resulting in the affected person being unable to fight off opportunistic infections. HIV/AIDS was the eighth leading cause of death in Africa in 2021, accounting for around 4.6 percent of all deaths, or around 405,790 total deaths. HIV Treatment Although there is currently no effective cure for HIV, death can be prevented by taking HIV antiretroviral therapy (ART). Access to ART worldwide has increased greatly over the last decade; however, there are still barriers to access in some of the countries most impacted by HIV. The African countries with the highest percentage of HIV infected children who were receiving antiretroviral treatment were Eswatini, Lesotho, and Uganda.

Latest data from 2017 show that Tuberculosis was with approximately ****** cases the leading cause of death in South Africa. Diabetes mellitus caused ** thousand casualties and was the second highest underlying cause of death, whereas ****** people passed away due to Cerebrovascular diseases (e.g. stroke, carotid stenosis). HIV/AIDS was the fifth ranked disease, causing ****** casualties. In total, roughly **** million people in East and Southern Africa lived with HIV in 2018, causing over ******* AIDS-related deaths.

The leading causes of death among Black residents in the United States in 2023 included diseases of the heart, cancer, unintentional injuries, and stroke. The leading causes of death for African Americans generally reflect the leading causes of death for the entire United States population. However, a major exception is that death from assault or homicide is the seventh leading cause of death among African Americans but is not among the ten leading causes for the general population. Homicide among African Americans The homicide rate among African Americans has been higher than that of other races and ethnicities for many years. In 2023, around 9,284 Black people were murdered in the United States, compared to 7,289 white people. A majority of these homicides are committed with firearms, which are easily accessible in the United States. In 2023, around 13,350 Black people died by firearms. Cancer disparities There are also major disparities in access to health care and the impact of various diseases. For example, the incidence rate of cancer among African American males is the greatest among all ethnicities and races. Furthermore, although the incidence rate of cancer is lower among African American women than it is among white women, cancer death rates are still higher among African American women.

The leading cause of death in low-income countries worldwide in 2021 was lower respiratory infections, followed by stroke and ischemic heart disease. The death rate from lower respiratory infections that year was 59.4 deaths per 100,000 people. While the death rate from stroke was around 51.6 per 100,000 people. Many low-income countries suffer from health issues not seen in high-income countries, including infectious diseases, malnutrition and neonatal deaths, to name a few. Low-income countries worldwide Low-income countries are defined as those with per gross national incomes (GNI) per capita of 1,045 U.S. dollars or less. A majority of the world’s low-income countries are located in sub-Saharan Africa and South East Asia. Some of the lowest-income countries as of 2023 include Burundi, Sierra Leone, and South Sudan. Low-income countries have different health problems that lead to worse health outcomes. For example, Chad, Lesotho, and Nigeria have some of the lowest life expectancies on the planet. Health issues in low-income countries Low-income countries also tend to have higher rates of HIV/AIDS and other infectious diseases as a consequence of poor health infrastructure and a lack of qualified health workers. Eswatini, Lesotho, and South Africa have some of the highest rates of new HIV infections worldwide. Likewise, tuberculosis, a treatable condition that affects the respiratory system, has high incident rates in lower income countries. Other health issues can be affected by the income of a country as well, including maternal and infant mortality. In 2023, Afghanistan had one of the highest rates of infant mortality rates in the world.

Abstract

This cumulative dataset contains statistics on mortality and causes of death in South Africa covering the period 1997-2020. The mortality and causes of death dataset is part of a regular series published by Stats SA, based on data collected through the civil registration system. This dataset is the most recent cumulative round in the series which began with the separately available dataset Recorded Deaths 1996.

The main objective of this dataset is to outline emerging trends and differentials in mortality by selected socio-demographic and geographic characteristics for deaths that occurred in the registered year and over time. Reliable mortality statistics, are the cornerstone of national health information systems, and are necessary for population health assessment, health policy and service planning; and programme evaluation. They are essential for studying the occurrence and distribution of health-related events, their determinants and management of related health problems. These data are particularly critical for monitoring the Sustainable Development Goals (SDGs) and Agenda 2063 which share the same goal for a high standard of living and quality of life, sound health and well-being for all and at all ages. Mortality statistics are also required for assessing the impact of non-communicable diseases (NCD's), emerging infectious diseases, injuries and natural disasters.

Geographic coverage

The survey has national coverage.

Analysis unit

Individuals

Universe

This dataset is based on information on mortality and causes of death from the South African civil registration system. It covers all death notification forms from the Department of Home Affairs for deaths that occurred in 1997-2020, that reached Stats SA during the 2021/2022 processing phase.

Kind of data

Administrative records

Mode of data collection

Other

Research instrument

The registration of deaths is captured using two instruments: form BI-1663 and form DHA-1663 (Notification/Register of death/stillbirth).

Data appraisal

This cumulative dataset is part of a regular series published by Stats SA and includes all previous rounds in the series (excluding Recorded Deaths 1996). Stats SA only includes one variable to classify the occupation group of the deceased (OccupationGrp) in the current round (1997-2020). Prior to 2016, Stats SA included both occupation group (OccupationGrp) and industry classifcation (Industry) in all previous rounds. Therefore, DataFirst has made the 1997-2015 cumulative round available as a separately downloadable dataset which includes both occupation group and industry classification of the deceased spanning the years 1997-2015.

A database detailing the top twenty single underlying causes of death in South Africa, with separate rankings for males and females.

In 2021, the leading cause of death in South Africa was COVID-19, with a distribution of 15.1 percent. Diabetes mellitus and hypertensive diseases followed, with a share of six percent and around five percent, respectively.

Two datasets that explore causes of death due to cancer in South Africa, drawing on data from the Revised Burden of Disease estimates for the Comparative Risk Factor Assessment for South Africa, 2000.

The number and percentage of deaths due to cancer by cause are ranked for persons, males and females in the tables below.

Lung cancer is the leading cause of cancer in SA accounting for 17% of all cancer deaths. This is followed by oesophagus Ca which accounts for 13%, cervix cancer accounting for 8%, breast cancer accounting for 8% and liver cancer which accounts for 6% of all cancers. Many more males suffer from lung and oesophagus cancer than females.

BackgroundStroke in adults is a critical clinical condition and a leading cause of death and disability globally. Epidemiological data on stroke in sub-Saharan Africa are limited. This study describes incidence rates, stroke types and antecedent factors among patients hospitalized with stroke in Zanzibar.MethodsThis was a prospective, observational study of stroke patients at hospitals in Unguja, Zanzibar. Socioeconomic and demographic data were recorded alongside relevant past medical history, medicine use and risk factors. The modified National Institute of Health Stroke Scale (mNIHSS) was used to assess admission stroke severity and, when possible, stroke was confirmed by neuroimaging.ResultsA total of 869 stroke admissions were observed from 1st October 2019 through 30th September 2020. Age-standardized to the World Health Organization global population, the yearly incidence was 286.8 per 100,000 adult population (95%CI: 272.4–301.9). Among these patients, 720 (82.9%) gave consent to participate in the study. Median age of participants was 62 years (53–70), 377 (52.2%) were women, and 463 (64.3%) had a first-ever stroke. Known stroke risk factors included hypertension in 503 (72.3%) patients, of whom 279 (55.5%) reported regularly using antihypertensive medication, of whom 161 (57.7%) had used this medication within the last week before stroke onset. A total of 460 (63.9%) participants had neuroimaging performed; among these there was evidence of intracerebral hemorrhage (ICH) in 140 (30.4%). Median stroke severity score using mNIHSS was 19 (10–27).ConclusionZanzibar has high incidence of hospitalization for stroke, indicating a very high population incidence of stroke. The proportion of strokes due to ICH is substantially higher than in high-income countries. Most stroke patients had been in contact with health care providers prior to stroke onset and been diagnosed with hypertension. However, few were using antihypertensive medication at the time of stroke onset.www.ClinicalTrial.gov registration NCT04095806.

Globally, there are 1.35 million road fatalities every year, which are estimated to cost governments approximately US$ 518 billion, making road fatalities the eighth leading cause of death across all age groups and the leading cause of death of children and young adults. In South Africa, despite tremendous governmental efforts to curb the soaring trajectory of road crashes, the annual number of road fatalities has increased by 26% in recent years. By fitting a structural equation model (SEM) and a GARCH Model (Generalized Auto-Regressive Conditional Heteroskedasticity) to analyze and predict future trend of road crashes (number of road crashes, number of casualties, number of fatal crashes and number of persons killed) in South Africa, we propose and test a complex metamodel that integrates multiple causality relationships. We show an increasing trend of road crashes over time, a trend that is predictable by number of vehicles in the country, the population of the country and the total distance travelled by vehicles. We further show that death rate linked to road crashes is on average 23.14 deaths per 100,000 persons. Finally, in the next decade, the number of road crashes is predicted to be roughly constant at 617,253 crashes but can reach 1,896,667 crashes in the worst-case scenario. The number of casualties was also predicted to be roughly constant at 93,531 over time, although this number may reach 661,531 in the worst-case scenario. However, although the number of fatal crashes may decrease in the next decade, it is forecasted to reach 11,241 within the next 10 years with the worse scenario estimated at 19,034 within the same period. At the same time, the number of persons killed in fatal crashes is also predicted to be roughly constant at 14,739 but may also reach 172,784 in the worse scenario. Overall, the present study reveals perhaps the positive effects of government initiatives to curb road crashes and their consequences; we call for more stronger actions for a drastic reduction in road accident events in South Africa.

BackgroundAround 8.8 million children under-five die each year, mostly due to infectious diseases, including malaria that accounts for 16% of deaths in Africa, but the impact of international financing of malaria control on under-five mortality in sub-Saharan Africa has not been examined. Methods and FindingsWe combined multiple data sources and used panel data regression analysis to study the relationship among investment, service delivery/intervention coverage, and impact on child health by observing changes in 34 sub-Saharan African countries over 2002–2008. We used Lives Saved Tool to estimate the number of lives saved from coverage increase of insecticide-treated nets (ITNs)/indoor residual spraying (IRS). As an indicator of outcome, we also used under-five mortality rate. Global Fund investments comprised more than 70% of the Official Development Assistance (ODA) for malaria control in 34 countries. Each $1 million ODA for malaria enabled distribution of 50,478 ITNs [95%CI: 37,774–63,182] in the disbursement year. 1,000 additional ITNs distributed saved 0.625 lives [95%CI: 0.369–0.881]. Cumulatively Global Fund investments that increased ITN/IRS coverage in 2002–2008 prevented an estimated 240,000 deaths. Countries with higher malaria burden received less ODA disbursement per person-at-risk compared to lower-burden countries ($3.90 vs. $7.05). Increased ITN/IRS coverage in high-burden countries led to 3,575 lives saved per 1 million children, as compared with 914 lives in lower-burden countries. Impact of ITN/IRS coverage on under-five mortality was significant among major child health interventions such as immunisation showing that 10% increase in households with ITN/IRS would reduce 1.5 [95%CI: 0.3–2.8] child deaths per 1000 live births. ConclusionsAlong with other key child survival interventions, increased ITNs/IRS coverage has significantly contributed to child mortality reduction since 2002. ITN/IRS scale-up can be more efficiently prioritized to countries where malaria is a major cause of child deaths to save greater number of lives with available resources.

Background: Stroke is a leading cause of death and disability in sub-Saharan Africa with increasing incidence. In Kenya, it is a neglected condition with a paucity of evidence despite its need for urgent care and hefty economic burden. Therefore, we reviewed studies on stroke epidemiology, care, and outcomes in Kenya to highlight existing evidence and gaps on stroke in Kenya.Methods: We reviewed all published studies on epidemiology, care, and outcomes of stroke in Kenya between 1 January 1990 to 31 December 2020 from PubMed, Web of Science, EBSCOhost, Scopus, and African journal online. We excluded case reports, reviews, and commentaries. We used the Newcastle-Ottawa scale adapted for cross-sectional studies to assess the quality of included studies.Results: Twelve articles were reviewed after excluding 111 duplicates and 94 articles that did not meet the inclusion criteria. Five studies were of low quality, two of medium quality, and five of high quality. All studies were hospital-based and conducted between 2003 and 2017. Of the included studies, six were prospective and five were single-center. Stroke patients in the studies were predominantly female, in their seventh decade with systemic hypertension. The mortality rate ranged from 5 to 27% in-hospital and 23.4 to 26.7% in 1 month.Conclusions: Our study highlights that stroke is a significant problem in Kenya, but current evidence is of low quality and limited in guiding policy development and improving stroke care. There is thus a need for increased investment in hospital- and community-based stroke care and research.

This statistic presents the death rates for the five leading causes of deaths among adolescents aged 10 to 19 years in each WHO region in 2015 (per 100,000 population). In low- and middle-income countries in Africa the leading cause of death among those aged 10 to 19 years was lower respiratory infections with a death rate of **** per 100,000 population. In high income WHO countries road injury was the leading cause of death among adolescents with a rate of ***. Road injury was the only cause to be in the five leading causes of death among adolescents in every WHO region.

Age-standardized death rates of TB in 1990 and 2021, and annual rate of changes across countries in Eastern Africa.

BackgroundSevere maternal outcome (SMO) encompasses women who survive life-threatening conditions either by chance or due to treatment quality, or who die. This concept assumes that severe maternal morbidity predicts mortality risk, enabling the analysis of risk factors for life-threatening outcomes and improving our understanding on the causes of maternal death. This study aims to determine the incidence of SMO and its leading causes in East Gojjam during a period of regional conflict.MethodsA prospective follow-up study was conducted at Debre Markos Comprehensive Specialized Hospital in East Gojjam from July 1, 2023, to February 30, 2024. The study included 367 women admitted with potentially life-threatening conditions, including 8 maternal deaths, using sub-Saharan Africa (SSA) and WHO Maternal Near-Miss (MNM) criteria. Data were entered into Epi Data v.4.6 and analyzed using SPSS v.27. The WHO MNM approach assessed SMO indicators and maternal health care quality were utilized.ResultsDuring the eight-month period, there were 3,167 live births, 359 potentially life-threatening conditions (PLTC), and 188 SMO cases (180 MNM and 8 maternal deaths). The SMO ratio was 59.4 per 1,000 live births (95% CI: 51, 68 per 1,000 live births). The MNM to mortality ratio, mortality index, and maternal mortality ratio were 22.5:1, 4.2%, and 252.6 per 100,000 live births, respectively. Over 80% of women with SMO showed evidence of organ dysfunction upon arrival or within 12 h of hospitalization. The leading causes of SMO were hypertensive disorders of pregnancy (HDP) and obstetric hemorrhage, including uterine rupture, with uterine rupture contributing to half of the maternal deaths.ConclusionThis study found that the incidence of SMO was comparable to that reported in most other studies. HDP was the primary cause of SMO, followed by obstetrical hemorrhage, consistent with other studies in Ethiopia. Uterine rupture was identified as the leading cause of maternal death. As this study was conducted in a single institution and in the period of severe armed conflict, it may not fully capture the range of maternal health issues across populations with varying healthcare access and socio-economic backgrounds. Caution should be exercised when generalizing these findings to the wider population.

The impacts of high ambient temperatures on mortality in humans and domestic animals are well understood. However, much less is known about how hot weather affects mortality in wild animals. High ambient temperatures have been associated with African wild dog Lycaon pictus pup mortality, suggesting that high temperatures might also be linked to high adult mortality. We analysed mortality patterns in African wild dogs radio-collared in Kenya (0°N), Botswana (20°S), and Zimbabwe (20°S), to examine whether ambient temperature was associated with adult mortality. We found that high ambient temperatures were associated with increased adult wild dog mortality at the Kenya site, and there was some evidence for temperature associations with mortality at the Botswana and Zimbabwe sites. At the Kenya study site, which had the highest human impact, high ambient temperatures were associated with increased risks of wild dogs being killed by people, and by domestic dog diseases. In contrast, temperature was not associated with the risk of snare-related mortality at the Zimbabwe site, which had the second-highest human impact. Causes of death varied markedly between sites. Pack size was positively associated with survival at all three sites. These findings suggest that while climate change may not lead to new causes of mortality, rising temperatures may exacerbate existing anthropogenic threats to this endangered species, with implications for conservation. This evidence suggests that temperature-related mortality, including interactions between temperature and other anthropogenic threats, should be investigated in a greater number of species to understand and mitigate the likely impacts of climate change. Methods Study sites We analysed adult African wild dog mortality at three sites: the Ewaso ecosystem, Kenya; the Okavango Delta, Botswana; and Savé Valley Conservancy, Zimbabwe. All three study sites fall within semi-arid savanna ecosystems.

Field Data Collection At the Kenya study site 130 African wild dogs (56 female, 74 male) from 41 packs were monitored using either Vectronics GPS collars (GPS Plus, Vectronic Aerospace GmbH), Televilt GPS collars (GPS-Posrec, Televilt, Lindesberg, Sweden), Berlin, Germany), or VHF radio-collars (Telonics, Mesa AZ, USA). All three collar types included a mortality sensor programmed to emit a characteristic radio signal if stationary for ≥4h. At the Zimbabwe study site, 59 African wild dogs (22 female, 37 male) from 34 packs were monitored using either radio collars or GPS collars (African Wildlife Tracking, Rietondale, Pretoria, South Africa). Using radio-collars (Sirtrack, Havelock West, New Zealand) 31 African wild dogs (10 female, 21 male) from 16 packs were monitored at the Botswana site. Collars were fitted using the procedures outlined in McNutt (1996), Woodroffe (2011) and Jackson et al. (2017). At all three sites, packs were located every 1-2 weeks where possible. Any collared animal found dead was carefully examined with the aim of establishing a cause of death. At the Kenya site necropsies were carried out on all dead individuals located. At the Botswana site cause of death was only recorded in cases where the death was directly observed, or during disease outbreaks, and therefore the majority of causes of death were unconfirmed. Most deaths at the Botswana site are likely to be due to natural causes given the low human activity in this area. For all three sites, the date of first detection of a mortality signal from the collar was used to estimate the date of death when not observed directly, and where this was not possible an estimated date of mortality was made based on the date midway between the last sighting, or the last detection of the radio-collar without a mortality signal, and the discovery of the carcass or collar. If any study animal was not observed in its resident pack for over 30 days, no mortality signal was detected, and no carcass was found, it was considered lost from the study and censored from the day of the last observation (Kenya: n=51, Zimbabwe: n=34, Botswana: n=8). If a carcass or collar was discovered more than 30 days after the last sighting (n=2), the animal was considered lost from the study due to the inaccuracy of the date of death and was censored from the date of the last sighting. Group and individual characteristics were recorded at each site. At all three sites dispersal status of the individual was recorded. Individuals were defined as dispersing if they left their pack for multiple days and did not return, otherwise they were defined as resident (Woodroffe et al. 2019b). Group size – either the pack size for resident individuals or the dispersal group size for dispersing individuals – was recorded for each individual, and was defined as the number of adults (>12 months in age) in the group. African wild dog pup-rearing involves the pups being left at a den site for the first three months of life while the majority of the rest of the pack hunt daily, bringing food back to provision the pups. This pup rearing period is referred to as denning. For each pack, denning periods were identified using either direct observations or GPS-collar data. At the Kenya site a number of other individual and pack characteristics were also monitored. Individuals’ alpha status was inferred based on consistent close association with a specific individual of the opposite sex, coordinated scent marking, and reproductive activity; all animals not identified as alpha were considered subdominant. African wild dog age was known for many individuals, otherwise it was estimated from tooth wear when the individual was collared (Woodroffe et al. 2019b). Age range at collaring ranged from 1 to 7 years old (mean: 2.43 ±1.27). The age of the majority of individuals at the Zimbabwe and Botswana sites was not known. Weather data is from weather stations within the field site at Mpala research station at the Kenya site (detailed in Caylor K., Gitonga, J. and Martins 2016), 30km outside the study site at Maun airport for the Botswana site and the Middle Sabi Research Station, 12km from the study area boundary at the Zimbabwe research site.

Data Processing The average mean temperature was taken on a 90 day rolling average at the Kenya and Zimbabwe sites, and a 30 day rolling average at the Botswana site. Rainfall was summed over a 30 day rolling time period at the Kenya and Botswana sites and a 90 day rolling period at the Zimbabwe site.

The project, based at the University of Greenwich, UK and Stellenbosch University, South Africa, aimed to examine epidemiologic transitions by identifying and quantifying the drivers of change in CVD risk in the middle-income country of South Africa compared to the high-income nation of England. The project produced a harmonised dataset of national surveys measuring CVD risk factors in South Africa and England for others to use in future work. The harmonised dataset includes microdata from nationally-representative surveys in South Africa derived from the Demographic and Health Surveys, National Income Dynamics Study, South Africa National Health and Nutrition Examination Survey and Study on Global Ageing and Adult Health, covering 11 cross-sections and approximately 156,000 individuals aged 15+ years, representing South Africa’s adult population from 1998 to 2017.

Data for England come from 17 Health Surveys for England (HSE) over the same time period, covering over 168,000 individuals aged 16+ years, representing England’s adult population.

This study uses existing data to identify drivers of recent health transitions in South Africa compared to England. The global burden of non-communicable diseases (NCDs) on health is increasing. Cardiovascular diseases (CVD) in particular are the leading causes of death globally and often share characteristics with many major NCDs. Namely, they tend to increase with age and are influenced by behavioural factors such as diet, exercise and smoking. Risk factors for CVD are routinely measured in population surveys and thus provide an opportunity to study health transitions. Understanding the drivers of health transitions in countries that have not followed expected paths (eg, South Africa) compared to those that exemplified models of 'epidemiologic transition' (eg, England) can generate knowledge on where resources may best be directed to reduce the burden of disease. In the middle-income country of South Africa, CVD is the second leading cause of death after HIV/AIDS and tuberculosis (TB). Moreover, many of the known risk factors for NCDs like CVD are highly prevalent. Rates of hypertension are high, with recent estimates suggesting that over 40% of adults have high blood pressure. Around 60% of women and 30% of men over 15 are overweight in South Africa. In addition, excessive alcohol consumption, a risk factor for many chronic diseases, is high, with over 30% of men aged 15 and older having engaged in heavy episodic drinking within a 30-day period. Nevertheless, infectious diseases such as HIV/AIDS remain the leading cause of death, though many with HIV/AIDS and TB also have NCDs. In high-income countries like England, by contrast, NCDs such as CVD have been the leading causes of death since the mid-1900s. However, CVD and risk factors such as hypertension have been declining in recent decades due to increased prevention and treatment. The major drivers of change in disease burden have been attributed to factors including ageing, improved living standards, urbanisation, lifestyle change, and reduced infectious disease. Together, these changes are often referred to as the epidemiologic transition. However, recent research has questioned whether epidemiologic transition theory accurately describes the experience of many low- and middle-income countries or, in fact, of high-income nations such as England. Furthermore, few studies have empirically tested the relative contributions of demographic, behavioural, health and economic factors to trends in disease burden and risk, particularly on the African continent. In addition, many social and environmental factors are overlooked in this research. To address these gaps, our study will use population measurements of CVD risk derived from surveys in South Africa over nearly 20 years in order to examine whether and to what extent demographic, behavioural, environmental, medical, social and other factors contribute to recent health trends and transitions. We will compare these trends to those occurring in England over the same time period. Thus, this analysis seeks to illuminate the drivers of health transitions in a country which is assumed to still be 'transitioning' to a chronic disease profile but which continues to have a high infectious disease burden (South Africa) as compared to a country which is assumed to have already transitioned following epidemiological transition theory (England). The analysis will employ modelling techniques on pooled cross-sectional data to examine how various factors explain the variation in CVD risk over time in representative population samples from South Africa and England. The results of this analysis may help to identify some of the main contributors to recent changes in CVD risk in South Africa and England. Such information can be used to pinpoint potential areas for intervention, such as social policy and services, thereby helping to set priorities for governmental and nongovernmental action to control the CVD epidemic and improve health.

Data is sourced from various health resources. Data is transformed into a BI format and quality assured. Data is consumed by a dashboard created in Power BI. Four reports exist for this dashboard:1. HIV Prevalence and TB Success RateHIV prevalence amongst women attending antenatal clinics in the Western Cape (2012-2015) by district and yearHIV prevalence amongst women attending antenatal clinics in the province (2012-2015) by province and yearTB Programme Success Rate (2013/14-2018/19) by TB Measure2. Births and Maternal MortalitiesNeonatal in facility (0-28 days) mortality rate (2015/16-2018/19); by years and neonatal death rate in facility and mortality rate by 1,000 live births Facility maternal mortality rate (2002, 2005, 2008, 2011, 2014); by triennia (3 years) deaths by 1,000 live births in WC (incl count of maternal deaths, count of live births, and infant maternal mortality ration)(Child (under 5) and Infant (under 1) mortality rate (2011, 2012, 2013); filter years, Infant/Child age band; Years, District, Births and Deaths by age bandDelivery rate in facility to women under 20 years (2013/14-2018/19); filter by financial year (FY); delivery rate by FY, delivery rate, numerator (births to women <20), denominator (total births)3. Deaths and Life ExpectancyLeading underlying causes of death in the Western Cape (2012-2016) by years and cause of deathYears of life lost (YLL) by cause of death in the WC (2012-2016) by years and YLL cause of deathAverage Life Expectency (LE) at birth (2006, 2011, 2016) by year, province, and gender4. Travel time to facilitiesTravel time taken to health facility by households with expenditure less than R1200-SA (2013-2018); by year, province, and travel time to health facilityTravel time taken to health facility by households with expenditure less than R1200-WC (2013-2018); by year, province, population group, and travel time to health facilityPublication Date2 September 2021LineageData from various sources transformed to a BI format and used to develop dynamic Power BI dashboards reflecting Outcome Indicators: HIV prevalence amongst women attending antenatal clinics in the provinceAll DS-TB (drug-susceptible tuberculosis) client treatment success rateNeonatal in facility (0-28 days) mortality rateFacility maternal mortality rateDelivery rate in facility to women under 20 yearsLife Expectancy (LE)Leading underlying causes of death in the Western CapeTravel time taken to health facility by households with expenditure less than R1200 (SA and WC)Data Source2019 National Antenatal Sentinel HIV Survey, National Department of Health 2021;Annual report 2014/15-2020/21, DOH;District Health Information Systems;Mid-year population estimates, Stats SA; Life Expectancy Stats SA calculations;Mortality and Causes of Death in South Africa 2018, June 2021, Stats SA

Non-communicable diseases (NCDs) constitute a major public health challenge globally. The increase in the prevalence of non-communicable diseases in South Africa continues to impact mortality and morbidity, necessitating the need to explore the growing burden of NCDs and their implications for public health. NCDs like cardiovascular diseases, cancer, diabetes, and respiratory diseases are leading causes of death and disability, with various factors ranging from modifiable lifestyle choices, environmental factors, and socioeconomic differences. Therefore, this review will explore and describe the prevalence of NCDs, associated risk factors, and the impact on the South African public healthcare system to inform the development of targeted public health policies and interventions for NCDs in South Africa to achieve a reduction in the burden of NCDs in South Africa. The five-step review described by the Joanna Briggs Institute (JBI) scoping review methodology: (1) determining the research question, (2) search strategy, (3) inclusion criteria, (4) data extraction, and (5) analysis and presentation of the results, will be used. The Preferred Reporting Items for Systematic Reviews and the Meta-Analysis for Scoping Reviews (PRISMA-ScR) will be used as a guide for this scoping review protocol. The selection of studies for the review is anticipated to be completed within 10 weeks, from 15 October to 31 December 2025. Literature search will be conducted across multiple electronic databases: PubMed, SCOPUS, and Google Scholar, reflecting empirical evidence as well as grey literature. The literature search timeline is between 2005 and 2025. The eligibility of articles will be determined using a two-stage screening process. All articles will be individually assessed for eligibility by two reviewers, while any disagreements will be resolved by a third reviewer. The extracted data from eligible articles will be synthesized and presented using tables, charts, graphs, and narrative summaries.