COVID-19 and all-cause mortality in South Africa – the hidden deaths in the first four waves

Decision letter: COVID-19 pandemic dynamics in South Africa and epidemiological characteristics of three variants of concern (Beta, Delta, and Omicron)

Decision letter: Tracking excess mortality across countries during the COVID-19 pandemic with the World Mortality Dataset

Background. The impacts on mortality of both the SARS-CoV-2 epidemic and the interventions to manage it differ between countries. The Rapid Mortality Surveillance System set up by the South African Medical Research Council based on data from the National Population Register (NPR) provides a means of tracking this impact on mortality in South Africa. Objectives. To report on the change in key metrics of mortality (numbers of deaths, life expectancy at birth, life expectancy at age 60, and infant, under-5, older child and adolescent, young adult, and adult mortality) over the period 2015 - 2020. The key features of the impact are contrasted with those measured in other countries. Methods. The numbers of registered deaths by age and sex recorded on the NPR were increased to account for both registered deaths that are not captured by the NPR and an estimate of deaths not reported. The estimated numbers of deaths together with estimates of the numbers in the population in the middle of each of the years were used to produce life tables and calculate various indicators. Results. Between 2019 and 2020, the number of deaths increased by nearly 53 000 (65% female), and life expectancy at birth fell by 1 year for females and by only 2.5 months for males. Life expectancy at age 60 decreased by 1.6 years for females and 1.2 years for males. Infant mortality, under-5 mortality and mortality of children aged 5 - 14 decreased by 22%, 20% and 10%, respectively, while that for older children and adolescents decreased by 11% for males and 5% for females. Premature adult mortality, the probability of a 15-year-old dying before age 60, increased by 2% for males and 9% for females. Conclusions. COVID-19 and the interventions to manage it had differential impacts on mortality by age and sex. The impact of the epidemic on life expectancy in 2020 differs from that in most other, mainly developed, countries, both in the limited decline and also in the greater impact on females. These empirical estimates of life expectancy and mortality rates are not reflected by estimates from agencies, either because agency estimates have yet to be updated for the impact of the epidemic or because they have not allowed for the impact correctly. Trends in weekly excess deaths suggest that the drop in life expectancy in 2021 will be greater than that in 2020.

BackgroundMaternal respiratory syncytial virus (RSV) vaccine, RSV prefusion F protein vaccine (RSVpreF (Abrysvo)), was found to be safe and efficacious in the MATISSE trial. However, post-hoc stratified analyses identified an excess of preterm births in the intervention arm in two upper-middle-income countries, most prominently in South Africa. This study weighs the potential benefits and risks in mortality associated with maternal RSV vaccination in South Africa, assuming the increased risk of preterm births observed in the trial was caused by vaccination.Methods and findingsWe compared the estimated RSV-associated infant deaths averted by vaccination (benefits) and neonatal mortality potentially associated with vaccine-associated risk in preterm birth (risks) in South Africa. The benefit model estimated the South African RSV disease burden in 2011−2016 and waning vaccine protection during infancy. The risk model estimated excess neonatal mortality using gestational age (GA)-specific mortality data from the Drakenstein Child Health Study and the GA-specific birth distribution in South Africa in the MATISSE trial, but did not incorporate the mortality risk found in the MATISSE vaccine trial in which no excess deaths occurred.The benefit model estimated that vaccination would reduce RSV-associated infant deaths by 31 (95% credible interval (Crl): 27, 35) per 100,000 live births born to vaccinated mothers in South Africa. Using the number of infants born to mothers vaccinated at 24–36 GA weeks in the MATISSE trial, if the association in South Africa between vaccination and preterm birth is actually causal, the risk model suggested that neonatal deaths would increase by 44 (95%CrI: −43, 210), totaling 1.4 (95%CrI: −1.4, 6.9) excess neonatal deaths for every infant RSV death prevented. When this was changed to the number of infants born to mothers vaccinated at 27–36 GA weeks in the MATISSE trial, the predicted risks dropped and in 97% of the simulations the benefits outweighed the risks. The outcome was sensitive to the GA window that we used to determine which infants to include in the analysis. The study was limited by only considering mortality associated with RSV disease and preterm birth.ConclusionsIf RSVpreF increases preterm birth risk, and if this increases neonatal mortality, then the benefit-risk analysis failed to show that the direct benefits of vaccination in reducing RSV-associated infant mortality would substantially outweigh the risks of preterm birth-associated neonatal mortality in South Africa with vaccination from 24 GA to 36 GA weeks. There was large uncertainty in the analyses due to small numbers of preterm births. With vaccination from 27 GA weeks, the benefit-risk analysis favored vaccination. RSVpreF vaccination has the potential to be safe and effective when used from the third trimester.

BackgroundMajor changes in health policy, health service delivery, specific protocols, guidelines and recommendations for the management of common causes of maternal death have been developed in South Africa since the advent of the current democratic government. However, maternal mortality ratio remains high. The scientific community has conducted numerous studies on maternal mortality in South Africa; save for an analysis of the causes of maternal deaths, stratified by province. This study examines the geographic distribution of maternal causes of death in South Africa.MethodsA pooled cross-sectional dataset for the years 2002–2006 retrieved from the vital registration database of Statistics South Africa was used to analyse maternal causes of death. About 8773 maternal deaths between 10–55 years were analysed using frequency tables, cross-tabulations and logistic regression. Maternal mortality ratios (MMR), odds ratios (OR) and 95% confidence intervals (CI) were used to analyse provincial disparities.ResultsMMR was highest in the Free State (286/100 000) and lowest in the Western Cape (87/100 000). Tuberculosis (10.4%) was the leading single indirect cause of maternal deaths while hypertensive disorders (9.1%) were the leading direct cause of death. KwaZulu-Natal women had a significantly higher risk of dying from sepsis (aOR=3.1,95% CI=1.2-7.9). North West women had the lowest risk of dying from hypertensive disorders (aOR=0.4,95% CI=0.2-0.7). The risk of dying from complications of labour was lowest for Gauteng women (aOR=0.4,95% CI=0.1-0.9). The 30–34 years age group had a significantly high risk (aOR=2.5,95% CI=1.6-4.0) of dying from abortion while the 25–29 years age group had a significantly higher risk of dying from maternal infectious diseases (aOR=2.3,95% CI=1.3-3.9). The 40–44 years age group had a significantly higher risk of dying from haemorrhage (aOR=2.3,95% CI=1.3-3.9 and the 45+ age group from other maternal diseases (aOR=3.3,95% CI=1.2-8.5) and miscellaneous direct causes (aOR=4.1,95% CI=1.7-9.9) respectively.ConclusionsThe study shows great variations in the distribution and causes of maternal deaths by age and provincial level. Poorer provinces had lower MMR than the better off provinces. The provincial variations in the leading causes of death indicate the importance of targeted interventions at sub-national level.Electronic supplementary materialThe online version of this article (doi:10.1186/s12889-015-1597-5) contains supplementary material, which is available to authorized users.

Even though highly effective drugs are available in South Africa, multidrug resistant tuberculosis (MDR-TB) patients with HIV infection have higher mortality compared to HIV-uninfected MDR-TB patients. This trend has been observed in similar countries with high HIV prevalence. This study sought to determine excess mortality attributable to HIV among MDR-TB patients in South Africa using relative survival methods. Data available were from a cohort of 2079 MDR-TB patients enrolled in a Standardized Programmatic Management of MDR-TB from 2000 to 2004 in South Africa. A Poisson-based model adjusted for age, gender, year of diagnosis, TB history, and resistance to ethambutol, anti-TB injectable drugs and fluoroquinolones antibiotics was constructed to assess the excess mortality among HIV co-infected MDR-TB patients. Excess hazard ratios (EHRs) were used to describe the effect of the predictors on net mortality, controlling for the general mortality in the South African population. Death was recorded on 1619 patients, of whom 367 (22.7%) had died within 2 years. Out of the 1413 patients that tested for HIV infection, 554 (39.2%) tested positive. Excess mortality was higher in HIV infected, compared to HIV uninfected, MDR-TB patients (adjusted excess hazard ratio, 5.6 [95% CI, 3.2-9.7]); in patients whose TB isolates' resistance to ethambutol and kanamycin was unknown (3.7 [2.1-6.2] and 4.87 [1.9-13.3], respectively) vs. known. There were no differences in excess mortality between age and gender of the patient, year of diagnosis and TB history. Adjusting for some important predictors, MDR-TB patients with HIV infection experienced higher excess mortality compared to HIV-uninfected MDR-TB patients, after accounting for the general mortality in South Africa. An appropriate, though complex method has produced predictor effect estimates similar to those obtained from classical methods. Thus, the use of relative survival methods should be encouraged in the analysis of causespecific mortality, when ascertainment of cause of death is inaccurate or unknown.

Most studies on mortality focus on under-five children and adults (18+). However between these ages lie an important population of adolescents, aged between 10 and 19 years old. A study on the causes of adolescent mortality from 1984 to 1986 found racial and gendered differences (Fischer, et al, 1992). However, this study admits to under-representing the African population and is out-dated. Although overall, the levels and numbers of adolescent mortality are not very high in South Africa, it is noted here that it is increasing over time. Research and measures need to be put into place now to avert the increasing adolescent mortality rates. This study uses descriptive statistics, age-specific mortality rates, proportional mortality ratios, a direct estimation of mortality, cause- specific mortality rates and associated single decrement life tables to examine the levels and causes of adolescent mortality in contemporary South Africa. Data from the 2001 Census and 2007 Community Survey are used. Findings from this paper show that adolescent mortality was highest in 2007at 54,046 adolescent deaths compared to the 41,443 deaths in 2001. Further, this paper shows that in 2007, life expectancy in the absence of unnatural causes of death would increase to 56 years among younger adolescents (10-14 years old) and 51 years for older adolescents (15-19 years old). In addition, the absence of certain infectious diseases including HIV/ AIDS and Tuberculosis, would increase life expectancy to an additional 57 years for younger adolescents according to 2007 data. Thus the prevention of these causes of death is of vital importance to national youth programmes and policies.

Although essential to guide control measures, published estimates of influenza-related seasonal mortality for low- and middle-income countries are few. We aimed to compare influenza-related mortality among individuals aged ≥65 years in South Africa and the United States. We estimated influenza-related excess mortality due to all causes, pneumonia and influenza, and other influenza-associated diagnoses from monthly age-specific mortality data for 1998-2005 using a Serfling regression model. We controlled for between-country differences in population age structure and nondemographic factors (baseline mortality and coding practices) by generating age-standardized estimates and by estimating the percentage excess mortality attributable to influenza. Age-standardized excess mortality rates were higher in South Africa than in the United States: 545 versus 133 deaths per 100,000 population for all causes (P<.001) and 63 vs 21 deaths per 100,000 population for pneumonia and influenza (P=.03). Standardization for nondemographic factors decreased but did not eliminate between-country differences; for example, the mean percentage of winter deaths attributable to influenza was 16% in South Africa and 6% in the United States (P<.001). For all respiratory causes, cerebrovascular disease, and diabetes, age-standardized excess death rates were 4-8-fold greater in South Africa than in the United States, and the percentage increase in winter deaths attributable to influenza was 2-4-fold higher. These data suggest that the impact of seasonal influenza on mortality among elderly individuals may be substantially higher in an African setting, compared with in the United States, and highlight the potential for influenza vaccination programs to decrease mortality.

Mortality during the COVID-19 pandemic: the blind spots in statistics

Conflicting COVID-19 excess mortality estimates

Amenable mortality comprises causes of death that should not occur with timely and effective healthcare. It is commonly used to assess healthcare performance. It could also be used to assess the effectiveness of the pending National Health Insurance (NHI) in South Africa (SA), but to do this, the level and distribution of amenable mortality are required using a local list of amenable causes. To establish an amenable cause-of-death list appropriate for SA and to determine the levels, trends, geographical distribution, population group differences and international comparisons of mortality amenable to healthcare. A local list of amenable causes of death was developed with input from public health and disease-specific medical experts. The Second SA National Burden of Disease estimates were reclassified into amenable mortality. Analyses of age-standardised death rates (ASDRs) and amenable mortality proportions were conducted by province and population group between 1997 and 2012. Excess mortality in relation to the best- performing province and population group was also analysed. ASDRs for SA were compared with those of European Union (EU) and Organisation for Economic Co-operation and Development (OECD) countries. The local list of amenable conditions contained 45 causes of death. There were large disparities in amenable mortality between provinces and population groups, which did not attenuate over time. There was an average annual percentage increase in amenable ASDRs, but when HIV/AIDS was excluded from the analysis there was an average annual decrease of 1.12%. In the post-peak HIV/AIDS period between 2008 and 2012, an annual average of 207 810 amenable deaths could have been saved if all provinces had the same ASDR as the Western Cape. SA's ASDR was 2.6 and 2.2 times higher than that of the worst-performing EU and OECD country, respectively. This is the first study known to the authors that has established a local amenable mortality list and described the epidemiology of amenable mortality in SA. Amenable mortality could be used as an indicator of the performance of the pending NHI over time and, in combination with other indicators, could identify areas of the health system that require improvement. Benchmarking could also quantify gaps in health system performance between geographical regions and indicate whether these are reduced with time.

South Africa (SA) is highly vulnerable to the effects of drought on the environment, economy, and society. However, its effect on human health remains unclear. Understanding the mortality risk associated with different types of droughts in different population groups and by specific causes would help clarify the potential mechanisms involved. The study aims to comprehensively assess the effect of droughts of varying time scales on cause-specific mortality (all; infectious and parasitic; endocrine, nutritional, and metabolic; cardiovascular; respiratory) in SA (from 2009–2016) and identify more vulnerable profiles based on sex and age. We also evaluated the urbanicity and district-level socioeconomic deprivation as potential risk modifiers. We used a two-stage time-series study design, with the weekly standardized precipitation-evapotranspiration index (SPEI) calculated at 1, 6, 12, and 15 months of accumulation to identify droughts of different duration (SPEI1, 6, 12, 15, respectively). We applied a quasi-Poisson regression adjusted by mean temperature to assess the association between each type of drought and weekly mortality in all district municipalities of SA, and then pooled the estimates in a meta-regression model. We reported relative risks (RRs) for one unit increase of drought severity. Overall, we found a positive association between droughts (regardless the time scale) and all causes of death analyzed. The strongest associations were found for the drought events more prolonged (RR [95%CI]: 1.027 [1.018, 1.036] (SPEI1); 1.035 [1.021, 1.050] (SPEI6); 1.033 [1.008, 1.058] (SPEI12); 1.098 [1.068, 1.129] (SPEI15)) and respiratory mortality (RRs varied from 1.037 [1.021, 1.053] (SPEI1) to 1.189 [1.14, 1.241] (SPEI15)). An indication of greater vulnerability was found in younger adults for the shortest droughts, in older adults for medium-term and long-term droughts, and children for very long-term droughts. However, differences were not significant. Further evidence of the relevance of urbanicity and demographic and socioeconomic conditions as potential risk modifiers is needed.

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

This chapter addresses a number of factors that complicate the effectiveness of law and policymaking on maternal mortality in South Africa and Nigeria. It discusses the data on maternal mortality in South Africa and Nigeria, including data on human immunodeficiency virus-related maternal deaths. The chapter also discusses summarily some of the factors that affect the effectiveness of law. It addresses the socio-cultural causes of maternal deaths generally, as well as the political, legal and economic problems associated with poor maternal health. The definition of maternal death is unsettled. However, all definitions acknowledge that maternal death relates to or arises from pregnancy. Statistics on maternal mortality are further divided by the specific cause of death. The data suggests that domestic laws and government policies in South Africa and Nigeria aimed at reducing rates of maternal mortality, either directly or indirectly, have not achieved projected results.

To identify the major causes of perinatal mortality in South Africa. Seventy-three state hospitals throughout South Africa representing metropolitan areas, cities and towns and rural areas. Users of the Perinatal Problem Identification Programme (PPIP) amalgamated their data to provide descriptive information on the causes of perinatal death and the avoidable factors, missed opportunities and substandard care in South Africa. A total of 8,085 perinatal deaths among babies weighing 1,000 g or more were reported from 232,718 births at the PPIP user sites. The perinatal mortality rates for the metropolitan, city and town, and rural groupings were 36.2, 38.6 and 26.7/1,000 births, respectively. The neonatal death rate was highest in the city and town group (14.5/1,000 live births) followed by the rural and metropolitan groups (11.3 and 10.0/1,000 live births respectively). The low birth weight rate was highest in the metropolitan group (19.6%), followed by the city and town group (16.5%) and the rural group (13.0%). The most common primary cause of perinatal death in the rural group was intrapartum asphyxia and birth trauma (rate 6.92/1,000 births) followed by spontaneous preterm delivery (5.37/1,000 births). The most common primary cause of death in the city and town group was spontaneous preterm delivery (6.79/1,000 births) followed by intrapartum asphyxia and birth trauma (6.21/1,000 births) and antepartum haemorrhage (5.7/1,000 births). The metropolitan group's most common primary causes were antepartum haemorrhage (7.14/1,000 births), complications of hypertension in pregnancy (5.09/1000 births) and spontaneous preterm labour (4.01/1,000 births). Unexplained intrauterine deaths were the most common recorded primary obstetric cause of death in all areas. Complications of prematurity and hypoxia were the most common final causes of neonatal death in all groups. Intrapartum asphyxia, birth trauma, antepartum haemorrhage, complications of hypertension in pregnancy and spontaneous preterm labour account for more than 80% of the primary obstetric causes of death.