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How an SAMRC Study Found that HIV Deaths in SA May be Massively Undercounted

On By ModernMedia
Photo by Sergey Mikheev on Unsplash

By Chris Bateman

It is widely acknowledged among health and demographic experts that relying solely on what is written on death certificates does not paint an accurate picture of what people in South Africa are actually dying of. Now, an SAMRC study has provided evidence that the undercounting of deaths due to HIV might be even greater than previously thought.

Many in health circles were surprised by a recent South African Medical Research Council (SAMRC) study that found that 23% of deaths in a nationally representative sample drawn from 2017/2018 were due to HIV. By comparison, Stats SA data for roughly the same period puts the figure at only 5.7%.

That Stats SA’s HIV mortality figures differs from other sources is not new and not in itself surprising. This is because Stats SA reports a relatively straight-forward count of what is written on death certificates – where it is known HIV is often not indicated, even if it is the underlying cause of death. By contrast, the new SAMRC study looked at autopsy reports, death certificates, medical records, and interviews with next of kin to come up with its much higher estimate.

The thing that did come as a surprise, is just how much higher the SAMRC figures were than anticipated. Previously, the real number of HIV deaths were thought to be around double the Stats SA number, rather than four times as much. For example, according to Thembisa, the leading model of HIV in South Africa and the basis for UNAIDS’s estimates for the country, around 12% of deaths in the country in 2018 were due to HIV.

“Accurate mortality data are essential for informed public health policies and targeted interventions; however, this study highlights critical gaps in our cause-of-death data, particularly in the underreporting of HIV/AIDS and suicides,” says Professor Debbie Bradshaw, study co-author and Chief Specialist Scientist at the SAMRC Burden of Disease Research Unit, in a media statement. (The study also found substantial under-reporting of suicide on death certificates.)

Multiple data sources

The study was conducted in three phases, examining deaths that were registered in 27 randomly selected health sub-districts between 1 September 2017 and 13 April 2018.

In addition to the examination of autopsy reports, death certificates, and medical records, trained fieldworkers interviewed next of kin to conduct verbal autopsies using a World Health Organization (WHO) questionnaire that had been translated into the country’s nine official languages.

Based on these various sources of data, the cause of each death was categorised into one or more of 44 categories and then compared to the cause of death indicated on the person’s death certificate. (The process for ensuring accuracy, including a review shared by a team of 49 medical doctors, is described in detail in this report.)

The researchers collected data for over 26 000 deaths, although not all types of data were available for each death. Medical records were available for over 17 600 cases, forensic pathology (autopsy) records for 5 700, and about 5 400 verbal autopsies were conducted. In the end, “to save costs”, not all medical records were reviewed.

Overall, for just over 15 000 deaths, the researchers could link and compare their assessment of why a person died to what was written on death certificates.

‘Poor agreement’

The researchers found that “there was poor agreement between the underlying cause of death obtained from the study and the official cause of death data”. The cause of death was the same in only 37% of cases. In addition to the under-reporting of HIV, the researchers also identified “severe under-reporting” of suicide as a cause of death.

A strong link between TB and HIV was observed, with TB responsible for 46% of deaths among people with HIV and 63% of TB deaths occurring in individuals with HIV. Together, these two diseases accounted for almost 30% of deaths.

Some question marks

As noted earlier, the new numbers are substantially higher than estimates from the highly respected Thembisa model. According to their data only 12% of deaths from mid-2017 to mid-2018 were due to HIV-related causes, with a further 9% of deaths occurring in persons with HIV but due to other causes.

Dr Pam Groenewald, a co-author of the new study and also with the SAMRC, describes Thembisa as “an excellent source”. She tells Spotlight they had a long discussion with the Thembisa researchers, “but we weren’t able to fully explain the differences”.

The study authors cite several factors that might contribute to a higher proportion of HIV deaths in their study. Firstly, the weighted national causes of death validation sample aimed to represent the registered deaths in the country, and it was known that deaths in rural areas and child deaths were under-represented. Secondly, deaths that occurred in private sector hospitals were not represented. Groenewald says the HIV-linked deaths in private hospitals are “definitely lower”, but doubts they would have had a significant impact on their findings.

One thing in favour of the study numbers is the fact that the cases they identified with HIV/AIDS as the underlying cause of death were independently reviewed by clinicians. As Groenewald points out, they looked at medical records of people admitted to and who died in hospital, including CD4 cell counts and HIV viral loads. The suggestion is that if someone had a very low CD4 count and a very high HIV viral load at the time of death, then it is very likely HIV played a role in their death, unless of course they died of a clearly non-associated cause like injuries from a car accident.

On the other hand, it might be argued that since HIV is very widely tested for in South Africa, it is more likely to appear on medical records than other less tested for diseases.

Another interesting wrinkle is that the proportion of deaths from HIV/AIDS from this study was higher than anticipated based on observed declines in adult mortality. It is widely accepted that the decline in adult mortality and the increase in life-expectancy over the last two decades was driven by antiretroviral therapy keeping more people with HIV alive. While the new findings do not challenge this narrative, it does suggest the effect may be less pronounced than previously thought.

What to do?

The researchers suggest their study has immediate implications for the country’s response to HIV and TB.

“The study recommends strengthening case finding, follow-up, prevention, and treatment for HIV, AIDS and TB to reduce mortality rates, and underlines the importance of government’s rapid response to counter the recent abrupt withdrawal of Pepfar funding,” Bradshaw comments in the media release.

But more broadly, the findings put the spotlight on major problems in the country’s death certification systems.

“Our findings highlight the need for improved record quality and adherence to testing guidelines within the medical community. Poor record keeping included incomplete documentation of clinical findings and results,” the study authors write.

“A lot of doctors’ report HIV as ‘retroviral disease’, for example, and it’s not coded as HIV,” Groenewald explains to Spotlight.

Urging doctors to record the actual underlying cause of death when writing up death certificates, she also called for improved training in death certification at medical schools.

Doctors’ reluctance to report HIV on death certificates likely has various reasons, including stigma related to HIV and the fact that some medical insurance policies used to exclude HIV, though policies now treat HIV like any other chronic condition.

Overall, Groenewald says, we need to step back and probe the rationale of compiling underlying cause of death statistics.

“The public health aim of the medical certificate of cause of death, (MCCD), is to prevent premature deaths. We therefore need to record the cascade of events or causal sequence of medical conditions leading to death and target our interventions at the underlying cause of death. The coding rules focus on the underlying cause of death, (UCOD), to compile the mortality statistics,” she says.

Groenewald stresses that the law requires doctors to provide accurate information on death causation. The Health Professions Council of SA’s ethical rules also recognised that a statute requiring disclosure about a deceased person’s health must be complied with and is not considered unethical. Contrary to common physician misconception, Groenewald says all this combined to show “it is completely ethical to disclose on a death certificate that a person has died from an AIDS related illness”.

In the meantime, routine mortality data from Stats SA should clearly be taken with a pinch of salt. As Groenewald points out, vital registration data should not be accepted at face value but should be interrogated and cross-checked with other data sources to get coherent and consistent estimates that fit within an envelope of all causes of mortality.

– Additional reporting by Marcus Low.

Republished from Spotlight under a Creative Commons licence.

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Categories : Gender Medical Research & TechnologyTags :

Biological Research Often Incorrectly Reports Sex Differences

On By ModernMedia
Photo by Tim Mossholder on Unsplash

An analysis of published studies from a range of biological specialties shows that when data are reported by sex, critical statistical analyses are often missing and the findings are likely to be reported in misleading ways.

The analysis was published in the journal eLife.

“We found that when researchers report that males and females respond differently to a manipulation such as a drug treatment, 70% of the time the researchers have not actually compared those responses statistically at all,” said senior author Donna Maney, a professor of neuroscience in Emory’s Department of Psychology. “In other words, an alarming percentage of claims of sex differences are not backed by sufficient evidence.”

In the articles lacking the proper evidence, she added, sex-specific effects were claimed almost 90% of the time. In contrast, authors that tested statistically for sex-specific effects only reported them 63% of the time.

”Our results suggest that researchers are predisposed to finding sex differences and that sex-specific effects are likely over-reported in the literature,” Prof Maney said.

The problem is so pervasive not even her own work was safe. “Once I realised how prevalent it is, I went back and checked my own published articles and there it was,” she said. “I myself have claimed a sex difference without comparing males and females statistically.”

Prof Maney stressed that the problem should not be discounted; it is becoming increasingly serious, she said, because of mounting pressure from funding agencies and journals to study both sexes, and interest from the medical community to develop sex-specific treatments.

Better training and oversight are needed to ensure scientific rigor in research on sex differences, the authors wrote: “We call upon funding agencies, journal editors and our colleagues to raise the bar when it comes to testing for and reporting sex differences.”

Historically, biomedical research has often included just one sex, usually biased toward males. In recent decades, laws have been passed requiring US medical research to include females in clinical trials and report the sex of human participants or animal subjects.

“If you’re trying to model anything relevant to a general population, you should include both sexes,” Prof Maney explained. “There are a lot of ways that animals can vary, and sex is one of them. Leaving out half of the population makes a study less rigorous.”

As more studies consider sex-based differences, Maney adds, it is important to ensure that the methods underlying their analyses are sound.

For the analysis, Prof Maney and co-author Yesenia Garcia-Sifuentes, PhD candidate, looked at 147 studies published in 2019 to see what is used for evidence of sex differences. The studies ranged across nine different biological disciplines, including field studies on giraffes and immune responses in humans.

The studies that were analysed all included both males and females and separated the data by sex. Garcia-Sifuentes and Prof Maney found that the sexes were compared, either statistically or by assertion, in 80% of the articles. Of those articles, sex differences were reported in 70% of them and of those treated as a major finding in about half.

Statistical errors were seen in some studies, with a significant difference for one sex but not the other counted as a difference between them.  The problem with that approach is that the statistical tests conducted on each sex can’t give “yes” or “no” answers about whether the treatment had an effect.

“Comparing the outcome of two independent tests is like comparing a ‘maybe so’ with an ‘I don’t know’ or ‘too soon to tell,'” Maney explains. “You’re just guessing. To show actual evidence that the response to treatment differed between females and males, you need to show statistically that the effect of treatment depended on sex. That is, to claim a ‘sex-specific’ effect, you must demonstrate that the effect in one sex was statistically different from the effect in the other.”

Conversely, their analysis also encountered strategies that could mask sex differences, such as pooling data from males and females without testing for a difference.

“At this moment in history, the stakes are high,” Maney says. “Misreported findings may affect health care decisions in dangerous ways. Particularly in cases where sex-based differences may be used to determine what treatment someone gets for a particular condition, we need to proceed cautiously. We need to hold ourselves to a very high standard when it comes to scientific rigor.”

Source: EurekAlert!

Categories : Diseases, Syndromes and ConditionsTags :

Another COVID-scale Pandemic in 59 Years ‘Statistically Likely’

On By ModernMedia
Photo by Edwin Hooper on Unsplash

A new study based on 400 years of historical records asserts that extreme pandemic events such as COVID are more common than believed.

The Duke University study, published in Proceedings of the National Academy of Sciences, used records of past outbreaks to estimate the intensity of those events and the yearly probability of them recurring.

It found the probability of a pandemic with similar impact to COVID is about 2% in any year, meaning that someone born in the year 2000 by now would have about a 38% chance of experiencing one. That probability is only increasing, highlighting the need to adjust perceptions of pandemic risks and expectations for preparedness, the researchers said.

“The most important takeaway is that large pandemics like COVID and the Spanish flu are relatively likely,” said study co-author William Pan, PhD, associate professor of global environmental health at Duke. The understanding that pandemics are not so rare should raise the priority of future prevention and control efforts, he said.

The study employed new statistical methods to measure the scale and frequency of disease outbreaks for which there was no immediate medical intervention over the past four centuries. Their analysis, including deadly pathogens including plague, smallpox, cholera, typhus and novel influenza viruses, found pandemics occurred with great variability in the past. But they also identified patterns that allowed them to describe the probabilities of similar-scale events happening again.

In the case of a pandemic like the Spanish flu, which killed more than 30 million people between 1918 and 1920, the probability of a pandemic of similar magnitude occurring ranged from 0.3% to 1.9% per year over the time period studied. Taken together, it is statistically likely that such a massive pandemic would occur within the next 400 years.

However, the data also show that the risk of intense outbreaks is increasing rapidly. Based on the increasing rate at which novel pathogens such as SARS-CoV-2 have broken loose in human populations in the past 50 years, the study estimates that the probability of novel disease outbreaks will likely triple in the next few decades.

With this increased risk factor, the researchers estimate that a COVID-scale pandemic is likely within a span of 59 years (by the year 2090), a result they write is “much lower than intuitively expected.” Although not included in the paper, they also calculated the probability of a pandemic capable of eliminating all human life, finding it statistically likely within the next 12 000 years. 

That does not mean it will be 59 years before the next COVID-like pandemic, nor that the Spanish flu for another 300 years. Such events are equally probable in any year during the span, said Duke University Professor Gabriel Katul, another of the paper’s authors.

“When a 100-year flood occurs today, one may erroneously presume that one can afford to wait another 100 years before experiencing another such event. This impression is false. One can get another 100-year flood the next year,” explained Prof Katul.

Dr Pan noted that population growth, changes in food systems, environmental degradation and more frequent contact between humans and disease-harboring animals all may be significant factors for increasing frequency of pandemics. However, he stresses that the statistical techniques are not to explain the pandemics.

However, he hopes the study will spark deeper exploration of the factors that may be making devastating pandemics more likely – and how to counteract them.

“This points to the importance of early response to disease outbreaks and building capacity for pandemic surveillance at the local and global scales, as well as for setting a research agenda for understanding why large outbreaks are becoming more common,” Dr Pan said.

Source: Duke University