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 28,700 cases the leading cause of death in South Africa. Diabetes mellitus caused 25 thousand casualties and was the second highest underlying cause of death, whereas 22,259 people passed away due to Cerebrovascular diseases (e.g. stroke, carotid stenosis). HIV/AIDS was the fifth ranked disease, causing 21,439 casualties. In total, roughly 20.6 million people in East and Southern Africa lived with HIV in 2018, causing over 300,000 AIDS-related deaths.

The leading causes of death among Black residents in the United States in 2022 included diseases of the heart, cancer, unintentional injuries, and stroke. The leading causes of death for African Americans generally reflects 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 2022, around 14,189 Black people died by firearms. However, suicide deaths account for over half of all deaths from firearms in the United States. 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.

Abstract

This cumulative dataset contains statistics on mortality and causes of death in South Africa covering the period 1997-2019. 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 1997-2019, that reached Stats SA during the 2020/2021 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 (1997-2018). 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.

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.

Excess mortality in Sierra Leone comparing weekly death rates (per 100,000 population) from HEAL-SL and monthly death counts from NCRA during COVID-19 peak and non-peak periods by age, sex, region, and residence type.

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.

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.

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 21.8 per 100,000 population. In high income WHO countries road injury was the leading cause of death among adolescents with a rate of 4.6. Road injury was the only cause to be in the five leading causes of death among adolescents in every WHO region.

South Africa ZA: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70: Male data was reported at 32.300 NA in 2016. This records a decrease from the previous number of 32.600 NA for 2015. South Africa ZA: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70: Male data is updated yearly, averaging 33.800 NA from Dec 2000 (Median) to 2016, with 5 observations. The data reached an all-time high of 34.400 NA in 2000 and a record low of 32.300 NA in 2016. South Africa ZA: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70: Male data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s South Africa – Table ZA.World Bank.WDI: Health Statistics. Mortality from CVD, cancer, diabetes or CRD is the percent of 30-year-old-people who would die before their 70th birthday from any of cardiovascular disease, cancer, diabetes, or chronic respiratory disease, assuming that s/he would experience current mortality rates at every age and s/he would not die from any other cause of death (e.g., injuries or HIV/AIDS).; ; World Health Organization, Global Health Observatory Data Repository (http://apps.who.int/ghodata/).; Weighted average;

South Africa ZA: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70: Female data was reported at 21.200 NA in 2016. This records a decrease from the previous number of 21.500 NA for 2015. South Africa ZA: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70: Female data is updated yearly, averaging 23.400 NA from Dec 2000 (Median) to 2016, with 5 observations. The data reached an all-time high of 25.000 NA in 2000 and a record low of 21.200 NA in 2016. South Africa ZA: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70: Female data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s South Africa – Table ZA.World Bank.WDI: Health Statistics. Mortality from CVD, cancer, diabetes or CRD is the percent of 30-year-old-people who would die before their 70th birthday from any of cardiovascular disease, cancer, diabetes, or chronic respiratory disease, assuming that s/he would experience current mortality rates at every age and s/he would not die from any other cause of death (e.g., injuries or HIV/AIDS).; ; World Health Organization, Global Health Observatory Data Repository (http://apps.who.int/ghodata/).; Weighted average;

ABSTRACT Background : The Covid-19 pandemic associated with the SARS-CoV-2 has caused very high death tolls in many countries, while it has had less prevalence in other countries of Africa and Asia. Climate and geographic conditions, as well as other epidemiologic and demographic conditions, were a matter of debate on whether or not they could have an effect on the prevalence of Covid-19. Objective : In the present work, we sought a possible relevance of the geographic location of a given country on its Covid-19 prevalence. On the other hand, we sought a possible relation between the history of epidemiologic and demographic conditions of the populations and the prevalence of Covid-19 across four continents (America, Europe, Africa, and Asia). We also searched for a possible impact of pre-pandemic alcohol consumption in each country on the two year death tolls across the four continents. Methods : We have sought the death toll caused by Covid-19 in 39 countries and obtained the registered deaths from specialized web pages. For every country in the study, we have analysed the correlation of the Covid-19 death numbers with its geographic latitude, and its associated climate conditions, such as the mean annual temperature, the average annual sunshine hours, and the average annual UV index. We also analyzed the correlation of the Covid-19 death numbers with epidemiologic conditions such as cancer score and Alzheimer score, and with demographic parameters such as birth rate, mortality rate, fertility rate, and the percentage of people aged 65 and above. In regard to consumption habits, we searched for a possible relation between alcohol intake levels per capita and the Covid-19 death numbers in each country. Correlation factors and determination factors, as well as analyses by simple linear regression and polynomial regression, were calculated or obtained by Microsoft Exell software (2016). Results : In the present study, higher numbers of deaths related to Covid-19 pandemic were registered in many countries in Europe and America compared to other countries in Africa and Asia. The analysis by polynomial regression generated an inverted bell-shaped curve and a significant correlation between the Covid-19 death numbers and the geographic latitude of each country in our study. Higher death numbers were registered in the higher geographic latitudes of both hemispheres, while lower scores of deaths were registered in countries located around the equator line. In a bell shaped curve, the latitude levels were negatively correlated to the average annual levels (last 10 years) of temperatures, sunshine hours, and UV index of each country, with the highest scores of each climate parameter being registered around the equator line, while lower levels of temperature, sunshine hours, and UV index were registered in higher latitude countries. In addition, the linear regression analysis showed that the Covid-19 death numbers registered in the 39 countries of our study were negatively correlated with the three climate factors of our study, with the temperature as the main negatively correlated factor with Covid-19 deaths. On the other hand, cancer and Alzheimer's disease scores, as well as advanced age and alcohol intake, were positively correlated to Covid-19 deaths, and inverted bell-shaped curves were obtained when expressing the above parameters against a country’s latitude. Instead, the (birth rate/mortality rate) ratio and fertility rate were negatively correlated to Covid-19 deaths, and their values gave bell-shaped curves when expressed against a country’s latitude. Conclusion : The results of the present study prove that the climate parameters and history of epidemiologic and demographic conditions as well as nutrition habits are very correlated with Covid-19 prevalence. The results of the present study prove that low levels of temperature, sunshine hours, and UV index, as well as negative epidemiologic and demographic conditions and high scores of alcohol intake may worsen Covid-19 prevalence in many countries of the northern hemisphere, and this phenomenon could explain their high Covid-19 death tolls. Keywords : Covid-19, Coronavirus, SARS-CoV-2, climate, temperature, sunshine hours, UV index, cancer, Alzheimer disease, alcohol.

BackgroundMaternal immunization has gained traction as a strategy to diminish maternal and young infant mortality attributable to infectious diseases. Background rates of adverse pregnancy outcomes are crucial to interpret results of clinical trials in Sub-Saharan Africa. MethodsWe developed a mathematical model that calculates a clinical trial's expected number of neonatal and maternal deaths at an interim safety assessment based on the person-time observed during different risk windows. This model was compared to crude multiplication of the maternal mortality ratio and neonatal mortality rate by the number of live births. Systematic reviews of severe acute maternal morbidity (SAMM), low birth weight (LBW), prematurity, and major congenital malformations (MCM) in Sub-Saharan African countries were also performed. FindingsAccounting for the person-time observed during different risk periods yields lower, more conservative estimates of expected maternal and neonatal deaths, particularly at an interim safety evaluation soon after a large number of deliveries. Median incidence of SAMM in 16 reports was 40.7 (IQR: 10.6–73.3) per 1,000 total births, and the most common causes were hemorrhage (34%), dystocia (22%), and severe hypertensive disorders of pregnancy (22%). Proportions of liveborn infants who were LBW (median 13.3%, IQR: 9.9–16.4) or premature (median 15.4%, IQR: 10.6–19.1) were similar across geographic region, study design, and institutional setting. The median incidence of MCM per 1,000 live births was 14.4 (IQR: 5.5–17.6), with the musculoskeletal system comprising 30%. InterpretationSome clinical trials assessing whether maternal immunization can improve pregnancy and young infant outcomes in the developing world have made ethics-based decisions not to use a pure placebo control. Consequently, reliable background rates of adverse pregnancy outcomes are necessary to distinguish between vaccine benefits and safety concerns. Local studies that quantify population-based background rates of adverse pregnancy outcomes will improve safety assessment of interventions during pregnancy.

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...

This statistic shows the number of deaths per day by selected diseases in West African countries that are suffering from the Ebola outbreak in 2014. Malaria causes some 552 deaths per day in these countries, while Ebola causes around four deaths per day (as of August 2014).

Ebola compared to other diseases

Ebola first emerged in 1976 in Sudan and the Democratic Republic of Congo. The 2014 outbreak in West Africa has proven difficult to control. Currently, there is no cure, however, treatment is available to maximize survival chances as well as minimize the potential for transmission. In August 2014, the World Health Organization has stated that the Ebola outbreak in West Africa had become an international health emergency. Ebola has caused four deaths per day in West Africa between December 2013 and August 11th, 2014. However, diseases such as malaria and HIV or AIDS have caused a significantly larger number of deaths daily in these countries, reaching 552 and 685 deaths per day in 2014, respectively. HIV/AIDS was responsible for some 1.5 million deaths in 2013 globally.

As of 2013, there have been over 77 million cases of malaria in Africa and almost 7 million cases in the Eastern Mediterranean. Worldwide, malaria accounted for just under 90 million cases in 2013. Malaria is caused by a parasite which can be carried by mosquitoes and transmitted to humans. The parasite is then able to multiply within the liver and proceed to infect red blood cells. Common symptoms are fever, headache, and vomiting. Malaria can cause death if blood supply to vital organs is inhibited. The U.S. National Institute of Health and the Bill & Melinda Gates Foundation are among the leading funders for malaria research and development worldwide, contributing to 27.9 percent and 21.2 percent, respectively, between 2007 and 2012.

BackgroundThyroid cancer is the leading cause of mortality and morbidity among cancers of the endocrine system. We aimed to describe the trends of thyroid cancer burden in North Africa and Middle East for 1990–2019.MethodsData on burden of thyroid cancer in North Africa and Middle East from 1990 to 2019 were obtained from the Global Burden of Disease (GBD) Study 2019. Decomposition analysis was used to estimate the effects of population growth, aging, and change in incident numbers on overall change of thyroid cancer incidence. Also, we used the comparative risk assessment framework of GBD to determine the burden of thyroid cancer attributable to a high body mass index (BMI).ResultsIn 2019, the age-standardized incidence rate (ASIR) and age-standardized mortality rate (ASMR) of thyroid cancer were 3.5 (2.9–4) and 0.5 (0.5–0.7) per 100,000, respectively. The highest age-standardized incidence, deaths, and disability-adjusted life year (DALY) rate were in Lebanon, Afghanistan, and United Arab Emirates, respectively. The ASIR of thyroid cancer in region was about 2.5 times higher among women, which had a positive association with increasing age. In 2019, the age-standardized deaths attributable to a high BMI was 16.7% of all deaths due to thyroid cancer. In 1990–2019, the overall change in thyroid cancer incident cases was a 396% increase which was mostly driven by the increase in disease-specific incidence rate (256.8%).ConclusionsWomen, the elderly above about 60 years old, and countries with a higher sociodemographic index showed higher incidence rates of thyroid cancer. Regarding our findings, it is recommended to establish preventive plans by modification in life style like weight reduction programs.

COVID-2019: No of Deaths: To Date: CC: Unallocated data was reported at 0.000 Person in 01 Feb 2023. This records a decrease from the previous number of 1.000 Person for 25 Jan 2023. COVID-2019: No of Deaths: To Date: CC: Unallocated data is updated daily, averaging 0.000 Person from Mar 2020 (Median) to 01 Feb 2023, with 866 observations. The data reached an all-time high of 2.000 Person in 31 Mar 2022 and a record low of 0.000 Person in 01 Feb 2023. COVID-2019: No of Deaths: To Date: CC: Unallocated data remains active status in CEIC and is reported by Department of Health. The data is categorized under High Frequency Database’s Disease Outbreaks – Table ZA.D001: South African Department of Health: Coronavirus Disease 2019 (COVID-2019).

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.

WHO: COVID-2019: Number of Patients: Death: New: South Africa data was reported at 0.000 Person in 24 Dec 2023. This stayed constant from the previous number of 0.000 Person for 23 Dec 2023. WHO: COVID-2019: Number of Patients: Death: New: South Africa data is updated daily, averaging 10.000 Person from Jan 2020 (Median) to 24 Dec 2023, with 1451 observations. The data reached an all-time high of 844.000 Person in 07 Jan 2021 and a record low of 0.000 Person in 24 Dec 2023. WHO: COVID-2019: Number of Patients: Death: New: South Africa data remains active status in CEIC and is reported by World Health Organization. The data is categorized under High Frequency Database’s Disease Outbreaks – Table WHO.D002: World Health Organization: Coronavirus Disease 2019 (COVID-2019): by Country and Region (Discontinued).