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What Economists Can Teach Epidemiologists

What Economists Can Teach Epidemiologists



What Economists Can Teach Epidemiologists Tyler Durden Sun, 07/12/2020 - 15:40

Authored by Peter Earle via The American Institute for Economic Research,

As data accrues on both a national and state-by-state basis, the parameters of COVID-19’s lethality is firming up. Two new papers from Dr. John Ioannidis point to the growing shortfall between apocalyptic pandemic predictions and the vastly more destructive policies implemented in observance of them.

The first, entitled “Population-level COVID-19 mortality risk for non-elderly individuals overall and for non-elderly individuals without underlying diseases in pandemic epicenters” offers more evidence supporting the assertion that the government reaction to the virus has been vastly overwrought. 

Using data from 11 European countries, 12 US states, and Canada, Ioannidis and his team show that the infection rate is much higher than previously thought, which suggests that both the incidence of asymptomatic and mildly symptomatic cases is higher than thought, and the fatality rate much lower than previously estimated

As regards the age of victims,

People [under] 65 years old have very small risks of COVID-19 death even in pandemic epicenters and deaths for people [under] 65 years without underlying predisposing conditions are remarkably uncommon. Strategies focusing specifically on protecting high-risk elderly individuals should be considered in managing the pandemic. 

In the other paper, “Forecasting for COVID-19 has failed,” Ioanndis and co-authors take aim at the reasons for which the predictions were so incredibly inaccurate. Early predictions included that New York needed up to 140,000 hospital beds for stricken COVID-19 victims; the total number of individuals hospitalized was 18,569. In California on March 17th, 2020, it was predicted that “at least 1.2 million people over the age of 18 [would] need hospitalization from the disease,” which would require 50,000 additional hospital beds. In fact, “COVID-19 patients [ultimately] occupied fewer than two in 10 beds.” On March 27th 2020, Vice Provost for Global Initiatives at the University of Pennsylvania, Ezekiel Emanuel’s prediction of 100,000,000 COVID-19 cases in the United States in the four subsequent weeks — slightly less than one in three of all Americans — has since been taken down.

Divination, accurate or not, is harmless in and of itself: that’s obvious. But when made by scientific dignitaries, in particular in the process of informing politicians amid crisis circumstances, it often leads to knee jerk reactions at all levels. The causative factors cited are, or should be, well known to economists: they include use of poor data or the wrong use of high quality data; improper or incorrect assumptions; wrongful estimates of sensitivity; wrongly interpreted past results or evidence; problems of dimensionality; and groupthink/bandwagon effects.

From a high level, epidemiological forecasts failed for the very reason that econometric predictions often flounder: the uncritical importation of modeling techniques from physics or applied mathematics into social science realms. This should not be especially revelatory. In “The Counter-revolution of Science” (1956), F. A. Hayek noted the pernicious effects of applying rigidly quantitative concepts where human action is at work, attributing them to “an ambition to imitate science in its methods rather than its spirit.”

Using Ioannidis’ guidelines, a subset of the elements which lead to predictive failures in epidemiology can not only be examined, but analogized directly with economic and econometric counterparts.

Data Problems

The issue of data quality and application in economics is one which arose from the growing quantification of the social sciences. Data which is either erroneously recorded, speciously accurate, or completely fabricated has been a problem of legendary proportions in econometrics and in the crafting of economic policy.

Although first identified as a serious issue 70 years ago (less than three years after the publication of this pivotal work), the mathematization of economics has proceeded apace with virtually no embracing of Oskar Morgenstern’s cautions. (While not waxing conspiratorially, it bears mentioning that low-quality data can be as much a political tool as a source of imprecision in both epidemiology and economics.) 

Similarly, there is growing evidence that some COVID-19 related data has been problematic: erroneous or miscalculated. Where testing is concerned, even a 1% error in the tens of millions of coronavirus tests being conducted would amount to hundreds of thousands of misdiagnoses, with the knock-on effects that such results give rise to. 

Erroneous Assumptions

Untenable and oversimplifying assumptions in economic formulations are often defended as pragmatic or unavoidable. These are problematic even when methodologies are appropriate, the data sound, and the calculations correct

Many [epidemiological] models assume homogeneity, i.e.all people having equal chances of mixing with each other and infecting each other. This is an untenable assumption and in reality, tremendous heterogeneity of exposures and mixing is likely to be the norm. Unless this heterogeneity is recognized, estimates of the proportion of people eventually infected before reaching her immunity can be markedly inflated.  

Epidemiologically, the homogeneity oversight is seen at its starkest and most tragically in comparing the outcome of insufficiently protecting the most vulnerable populations while simultaneously closing schools and excoriating teenagers/college students — among the least affected groups — for their social inclinations.   

Sensitivity of Estimates

Determining how an independent variable or groups of independent variables affect dependent variables is the focus of sensitivity analysis. Depending upon the regression (or other operation) being performed, and in particular the presence of exponents, a small error in independent factors can lead to huge variances in outcomes. (This is one of the characteristics of a chaotic system: the so-called butterfly effect refers to systems where ultimate outcomes or states show a tremendous degree of sensitivity to initial conditions.) 

There are techniques which can be used to determine where, when, and to what degree estimates have a disproportionate impact on the outcome of simulations or calculations, whether that comes in the form of wildly overblown or unrealistically diminished outcomes. Often, though, sensitivity is seen not in models, but in the real world events they are designed to approximate. 

Ioannidis cited the “inherent impossibility” of fixing such models, as the ubiquity of models employing “exponentiated variables [lead to] small errors [that] result in major deviations from reality.” Morgenstern evinced similar concerns in 1950 regarding the curve-fitting propensities of the new wave of economic practice; here in production functions, but the criticism is certainly extendable:

Consider, for example, the important problem of whether linear or nonlinear production functions should be considered in economic models. Non-linearity is a great complication and is, therefore, best avoided as much as possible. True non-linearity in the strict mathematical sense is avoided in physics as far as possible. Even quantum mechanics is treated as linear on a higher level. Many apparently nonlinear phenomena, upon closer investigation, can well be treated as linear . . . The distinction is largely a matter of the precision of measurement, which is exactly where the weakness is strongest in economics. It is astonishing that economists seem to hesitate far less to introduce non-linearity than physical scientists, where the tradition of mathematical exploration is so much older and the experience with observation and measurement so much firmer.

I would not deign to correct such a luminary as Dr. Morgenstern, but I would add that the weakness is not strongest in economics alone, but in all undertakings which quantitatively rigidify human action, whether individual or en masse

Poor past evidence on effects of available interventions

Unbeknownst to the vast majority of people who are or will suffer from the effects of the lockdowns, the “flatten-the-curve” efforts were informed by information from the Spanish Flu of 1918. Thus data of impeachable quality, from a pandemic event which occurred over one century ago, involving a different pathogen — as a major world war was ending, and when living conditions, longevity, the state of medical science, the tenor of social interactions, and countless other variables were immeasurably different — were applied to sculpt the government response to the outbreak of the novel coronavirus. 

 Ioannidis and his co-authors comment that “[w]hile some interventions . . . are likely to have beneficial effects, assuming huge benefits is incongruent with the past (weak) evidence and should be avoided. Large benefits may be feasible from precise, focused measures.” 

The idea that a single (or even a small handful) of studies might be used to buttress indefensible arguments or to support questionable plans is occasionally seen in economic policymaking as well.


“Almost all models that had a prominent role in [pandemic] decision-making,” Ioannidis continues, “focused on COVID-19 outcomes, often just a single outcome or a few outcomes (e.g., deaths or hospital needs). Models prime for decision making need to take into account the impact on multiple fronts (e.g. other aspects of healthcare, other diseases, dimensions of the economy, etc.).” Some remedies to this include interdisciplinary scrutiny of model outcomes and a look at past implementations in the face of pandemics — including those to which there was no response at all. 

While dimensionality as a specific problem afflicts economic modeling as well, general comments in this regard closely echo the battered-but-unmoved screeds against one of the earliest fixtures of economic education: ceteris paribus, by which one considers causal or empirical relations while holding other influences equal. While a useful tool for educational purposes, when it creeps into crafting policies the results can be costly. 

(At times, the ceteris paribus approach is defended by econometricians who liken it to the practice of ignoring air resistance in gravity experiments. It’s a shamefully underhanded argument that immingles physical with social science phenomena.)

Groupthink and Bandwagon Effects

Ioannidis cites groupthink among epidemiologists as a source of forecasting error. When a doomsday prediction is made — especially by celebrity scientists — the act of introducing a more mitigating prognosis may bring substantial risk to one’s career, and thus be suppressed. Alternately, the published or broadcast results of thought leaders may be a form of anchoring. As Ioannidis and his team write,

Models can be tuned to get desirable results and predictions, e.g. by changing the input of what are deemed to be the plausible values for key variables. This is true for models that depend upon theory and speculation, but even data-driven forecasting can do the same, depending upon how the modeling is performed. In the presence of strong groupthink and bandwagon effects, modelers may consciously fit their predictions to what the dominant thinking and expectations are – or they may be forced to do so. 

The economics profession is certainly not immune to this. It manifests in several ways, one of which is mainstream economists’ unwillingness to admit their errors (as the continued use of flawed models or bad data attests to). Many economists instinctively do not criticize theory or practices within their institution or school of thought owing to political expediency. The highly ‘siloed’ nature of journals and conferences attests to it, as do the veritable echo chambers in social media. This is not merely a personal observation; it and its effects have been cited elsewhere. Here, in no less prominent a place as the International Monetary Fund:  

Analytical weaknesses were at the core of some of the IMF’s most evident shortcomings in surveillance … [as a result of] … the tendency among homogeneous, cohesive groups to consider issues only within a certain paradigm and not challenge its basic premises.

Cognitive and confirmation biases are noted as well. 

The Media Amplifier

Farcical predictions, whether owing to one or all of the above elements, would nevertheless be innocuous if limited to circulating among small groups of scientists or within the rarified pages of peer-reviewed journals. But whether viewed as a vital democratic institution, a propagandistic organ of political parties, or somewhere in between, it’s far from a conspiracy theory to note that the dominant media outlets are massive businesses which fundamentally compete for revenue on the basis of attention. As with politicians, the loudest and scariest messages and interpretations garner the most attention and have the added perk of defensibility in the name of “vigilance.” 

And in the same manner in which tremendously negative predictions permit self-aggrandizing assessments of policy outcomes — such as in Neil Ferguson’s claim that the lockdowns saved lives — doomy economic projections are almost always associated with unprovably optimal outcomes. 

An example of that is found in President Obama’s assertion that without the bailouts and Fed programs administered in the wake of the 2008 financial crisis, the world might have fallen into a “permanent recession.” (The idea that a “permanent recession” would have been a recession which simply lapsed into a new, permanent low level of economic activity went predictably unchallenged.) The best (and least common) unprovable counterfactuals are good guesses; the majority are deceptive. 

Where Economists can Help Epidemiologists

Having said all of that, the paper concludes with a redemptory note, commending the efforts of epidemiology teams and warning that it would be “horrifically retrograde if this [modeling] debate ushers in a return to an era where predictions, on which huge decisions are made, are kept under lock and key (e.g. by the government – as is the case in Australia).”

The mundanity of letting individuals or localities assess and act in concert with proprietary risk appetites must, on some level, be frustrating when compared with creating vast artificial populations of agents or using big data to sift through colossal data repositories. It would no doubt seem a massive waste of time to expend energy writing code and poring over results only to recommend that citizens exercise their best judgment. 

Simply building and running computational models is not, of course, harmful in and of itself: it is in the leap from output to implementation where hazards emerge. Here’s Hayek, again, in “The Counter-Revolution of Science” (1956):

The universal demand for conscious control or direction of social processes is one of the most characteristic features of our generation. It expresses perhaps more clearly than any of its other cliches the peculiar spirit of the age. That anything is not consciously directed as a whole is regarded as itself a blemish, a proof of its irrationality and of the need completely to replace it by a deliberately designed mechanism . . . The belief that processes which are consciously directed are necessarily superior to any spontaneous process is an unfounded superstition. It would be truer to say [as Whitehead did] that on the contrary “civilization advances by extending the number of important operations we can perform without thinking about them.”

Hysterical, wildly off-the-mark forecasts about COVID-19 will ultimately cause more harm than good, and find their origins in the same set of snags which regularly trip up econometric forecasts. In the epidemiological version, instead of predicting a new Great Depression, they brought an artificial depression, a growing spate of coercive masking initiatives, school closures, and the lockdowns — which quite possibly filled the powderkeg that was ignited by the killing of George Floyd. And that’s what we can see, directly in front of us: the ultimate cost of surgeries foregone, rising rates of drug abusealcoholism, and suicides, and other knock-on effects of the ridiculous government responses to the novel coronavirus outbreak will be unfolding for a generation. 

What can economists teach epidemiologists? When it comes to forecasting, humility is key and discretion is the better part of valor. If in a position of power or influence, don’t be afraid to bore politicians to death. Be aware, and remain aware, of the utter unpredictability of human action. And always, above all, remain mindful that the presence of even one human being (and more realistically, millions) introduces complexities which are difficult to predict and virtually impossible to simulate. 

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“Extreme Events”: US Cancer Deaths Spiked In 2021 And 2022 In “Large Excess Over Trend”

"Extreme Events": US Cancer Deaths Spiked In 2021 And 2022 In "Large Excess Over Trend"

Cancer deaths in the United States spiked in 2021…



"Extreme Events": US Cancer Deaths Spiked In 2021 And 2022 In "Large Excess Over Trend"

Cancer deaths in the United States spiked in 2021 and 2022 among 15-44 year-olds "in large excess over trend," marking jumps of 5.6% and 7.9% respectively vs. a rise of 1.7% in 2020, according to a new preprint study from deep-dive research firm, Phinance Technologies.

Algeria, Carlos et. al "US -Death Trends for Neoplasms ICD codes: C00-D48, Ages 15-44", ResearchGate, March. 2024 P. 7

Extreme Events

The report, which relies on data from the CDC, paints a troubling picture.

"We show a rise in excess mortality from neoplasms reported as underlying cause of death, which started in 2020 (1.7%) and accelerated substantially in 2021 (5.6%) and 2022 (7.9%). The increase in excess mortality in both 2021 (Z-score of 11.8) and 2022 (Z-score of 16.5) are highly statistically significant (extreme events)," according to the authors.

That said, co-author, David Wiseman, PhD (who has 86 publications to his name), leaves the cause an open question - suggesting it could either be a "novel phenomenon," Covid-19, or the Covid-19 vaccine.

"The results indicate that from 2021 a novel phenomenon leading to increased neoplasm deaths appears to be present in individuals aged 15 to 44 in the US," reads the report.

The authors suggest that the cause may be the result of "an unexpected rise in the incidence of rapidly growing fatal cancers," and/or "a reduction in survival in existing cancer cases."

They also address the possibility that "access to utilization of cancer screening and treatment" may be a factor - the notion that pandemic-era lockdowns resulted in fewer visits to the doctor. Also noted is that "Cancers tend to be slowly-developing diseases with remarkably stable death rates and only small variations over time," which makes "any temporal association between a possible explanatory factor (such as COVID-19, the novel COVID-19 vaccines, or other factor(s)) difficult to establish."

That said, a ZeroHedge review of the CDC data reveals that it does not provide information on duration of illness prior to death - so while it's not mentioned in the preprint, it can't rule out so-called 'turbo cancers' - reportedly rapidly developing cancers, the existence of which has been largely anecdotal (and widely refuted by the usual suspects).

While the Phinance report is extremely careful not to draw conclusions, researcher "Ethical Skeptic" kicked the barn door open in a Thursday post on X - showing a strong correlation between "cancer incidence & mortality" coinciding with the rollout of the Covid mRNA vaccine.

Phinance principal Ed Dowd commented on the post, noting that "Cancer is suddenly an accelerating growth industry!"


Bottom line - hard data is showing alarming trends, which the CDC and other agencies have a requirement to explore and answer truthfully - and people are asking #WhereIsTheCDC.

We aren't holding our breath.

Wiseman, meanwhile, points out that Pfizer and several other companies are making "significant investments in cancer drugs, post COVID."


We've featured several of Phinance's self-funded deep dives into pandemic data that nobody else is doing. If you'd like to support them, click here.


Tyler Durden Sat, 03/16/2024 - 16:55

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“I Can’t Even Save”: Americans Are Getting Absolutely Crushed Under Enormous Debt Load

"I Can’t Even Save": Americans Are Getting Absolutely Crushed Under Enormous Debt Load

While Joe Biden insists that Americans are doing great…



"I Can't Even Save": Americans Are Getting Absolutely Crushed Under Enormous Debt Load

While Joe Biden insists that Americans are doing great - suggesting in his State of the Union Address last week that "our economy is the envy of the world," Americans are being absolutely crushed by inflation (which the Biden admin blames on 'shrinkflation' and 'corporate greed'), and of course - crippling debt.

The signs are obvious. Last week we noted that banks' charge-offs are accelerating, and are now above pre-pandemic levels.

...and leading this increase are credit card loans - with delinquencies that haven't been this high since Q3 2011.

On top of that, while credit cards and nonfarm, nonresidential commercial real estate loans drove the quarterly increase in the noncurrent rate, residential mortgages drove the quarterly increase in the share of loans 30-89 days past due.

And while Biden and crew can spin all they want, an average of polls from RealClear Politics shows that just 40% of people approve of Biden's handling of the economy.


On Friday, Bloomberg dug deeper into the effects of Biden's "envious" economy on Americans - specifically, how massive debt loads (credit cards and auto loans especially) are absolutely crushing people.

Two years after the Federal Reserve began hiking interest rates to tame prices, delinquency rates on credit cards and auto loans are the highest in more than a decade. For the first time on record, interest payments on those and other non-mortgage debts are as big a financial burden for US households as mortgage interest payments.

According to the report, this presents a difficult reality for millions of consumers who drive the US economy - "The era of high borrowing costs — however necessary to slow price increases — has a sting of its own that many families may feel for years to come, especially the ones that haven’t locked in cheap home loans."

The Fed, meanwhile, doesn't appear poised to cut rates until later this year.

According to a February paper from IMF and Harvard, the recent high cost of borrowing - something which isn't reflected in inflation figures, is at the heart of lackluster consumer sentiment despite inflation having moderated and a job market which has recovered (thanks to job gains almost entirely enjoyed by immigrants).

In short, the debt burden has made life under President Biden a constant struggle throughout America.

"I’m making the most money I've ever made, and I’m still living paycheck to paycheck," 40-year-old Denver resident Nikki Cimino told Bloomberg. Cimino is carrying a monthly mortgage of $1,650, and has $4,000 in credit card debt following a 2020 divorce.

Nikki CiminoPhotographer: Rachel Woolf/Bloomberg

"There's this wild disconnect between what people are experiencing and what economists are experiencing."

What's more, according to Wells Fargo, families have taken on debt at a comparatively fast rate - no doubt to sustain the same lifestyle as low rates and pandemic-era stimmies provided. In fact, it only took four years for households to set a record new debt level after paying down borrowings in 2021 when interest rates were near zero. 

Meanwhile, that increased debt load is exacerbated by credit card interest rates that have climbed to a record 22%, according to the Fed.

[P]art of the reason some Americans were able to take on a substantial load of non-mortgage debt is because they’d locked in home loans at ultra-low rates, leaving room on their balance sheets for other types of borrowing. The effective rate of interest on US mortgage debt was just 3.8% at the end of last year.

Yet the loans and interest payments can be a significant strain that shapes families’ spending choices. -Bloomberg

And of course, the highest-interest debt (credit cards) is hurting lower-income households the most, as tends to be the case.

The lowest earners also understandably had the biggest increase in credit card delinquencies.

"Many consumers are levered to the hilt — maxed out on debt and barely keeping their heads above water," Allan Schweitzer, a portfolio manager at credit-focused investment firm Beach Point Capital Management told Bloomberg. "They can dog paddle, if you will, but any uptick in unemployment or worsening of the economy could drive a pretty significant spike in defaults."

"We had more money when Trump was president," said Denise Nierzwicki, 69. She and her 72-year-old husband Paul have around $20,000 in debt spread across multiple cards - all of which have interest rates above 20%.

Denise and Paul Nierzwicki blame Biden for what they see as a gloomy economy and plan to vote for the Republican candidate in November.
Photographer: Jon Cherry/Bloomberg

During the pandemic, Denise lost her job and a business deal for a bar they owned in their hometown of Lexington, Kentucky. While they applied for Social Security to ease the pain, Denise is now working 50 hours a week at a restaurant. Despite this, they're barely scraping enough money together to service their debt.

The couple blames Biden for what they see as a gloomy economy and plans to vote for the Republican candidate in November. Denise routinely voted for Democrats up until about 2010, when she grew dissatisfied with Barack Obama’s economic stances, she said. Now, she supports Donald Trump because he lowered taxes and because of his policies on immigration. -Bloomberg

Meanwhile there's student loans - which are not able to be discharged in bankruptcy.

"I can't even save, I don't have a savings account," said 29-year-old in Columbus, Ohio resident Brittany Walling - who has around $80,000 in federal student loans, $20,000 in private debt from her undergraduate and graduate degrees, and $6,000 in credit card debt she accumulated over a six-month stretch in 2022 while she was unemployed.

"I just know that a lot of people are struggling, and things need to change," she told the outlet.

The only silver lining of note, according to Bloomberg, is that broad wage gains resulting in large paychecks has made it easier for people to throw money at credit card bills.

Yet, according to Wells Fargo economist Shannon Grein, "As rates rose in 2023, we avoided a slowdown due to spending that was very much tied to easy access to credit ... Now, credit has become harder to come by and more expensive."

According to Grein, the change has posed "a significant headwind to consumption."

Then there's the election

"Maybe the Fed is done hiking, but as long as rates stay on hold, you still have a passive tightening effect flowing down to the consumer and being exerted on the economy," she continued. "Those household dynamics are going to be a factor in the election this year."

Meanwhile, swing-state voters in a February Bloomberg/Morning Consult poll said they trust Trump more than Biden on interest rates and personal debt.


These 'headwinds' have M3 Partners' Moshin Meghji concerned.

"Any tightening there immediately hits the top line of companies," he said, noting that for heavily indebted companies that took on debt during years of easy borrowing, "there's no easy fix."

Tyler Durden Fri, 03/15/2024 - 18:00

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Sylvester researchers, collaborators call for greater investment in bereavement care

MIAMI, FLORIDA (March 15, 2024) – The public health toll from bereavement is well-documented in the medical literature, with bereaved persons at greater…



MIAMI, FLORIDA (March 15, 2024) – The public health toll from bereavement is well-documented in the medical literature, with bereaved persons at greater risk for many adverse outcomes, including mental health challenges, decreased quality of life, health care neglect, cancer, heart disease, suicide, and death. Now, in a paper published in The Lancet Public Health, researchers sound a clarion call for greater investment, at both the community and institutional level, in establishing support for grief-related suffering.

Credit: Photo courtesy of Memorial Sloan Kettering Comprehensive Cancer Center

MIAMI, FLORIDA (March 15, 2024) – The public health toll from bereavement is well-documented in the medical literature, with bereaved persons at greater risk for many adverse outcomes, including mental health challenges, decreased quality of life, health care neglect, cancer, heart disease, suicide, and death. Now, in a paper published in The Lancet Public Health, researchers sound a clarion call for greater investment, at both the community and institutional level, in establishing support for grief-related suffering.

The authors emphasized that increased mortality worldwide caused by the COVID-19 pandemic, suicide, drug overdose, homicide, armed conflict, and terrorism have accelerated the urgency for national- and global-level frameworks to strengthen the provision of sustainable and accessible bereavement care. Unfortunately, current national and global investment in bereavement support services is woefully inadequate to address this growing public health crisis, said researchers with Sylvester Comprehensive Cancer Center at the University of Miami Miller School of Medicine and collaborating organizations.  

They proposed a model for transitional care that involves firmly establishing bereavement support services within healthcare organizations to ensure continuity of family-centered care while bolstering community-based support through development of “compassionate communities” and a grief-informed workforce. The model highlights the responsibility of the health system to build bridges to the community that can help grievers feel held as they transition.   

The Center for the Advancement of Bereavement Care at Sylvester is advocating for precisely this model of transitional care. Wendy G. Lichtenthal, PhD, FT, FAPOS, who is Founding Director of the new Center and associate professor of public health sciences at the Miller School, noted, “We need a paradigm shift in how healthcare professionals, institutions, and systems view bereavement care. Sylvester is leading the way by investing in the establishment of this Center, which is the first to focus on bringing the transitional bereavement care model to life.”

What further distinguishes the Center is its roots in bereavement science, advancing care approaches that are both grounded in research and community-engaged.  

The authors focused on palliative care, which strives to provide a holistic approach to minimize suffering for seriously ill patients and their families, as one area where improvements are critically needed. They referenced groundbreaking reports of the Lancet Commissions on the value of global access to palliative care and pain relief that highlighted the “undeniable need for improved bereavement care delivery infrastructure.” One of those reports acknowledged that bereavement has been overlooked and called for reprioritizing social determinants of death, dying, and grief.

“Palliative care should culminate with bereavement care, both in theory and in practice,” explained Lichtenthal, who is the article’s corresponding author. “Yet, bereavement care often is under-resourced and beset with access inequities.”

Transitional bereavement care model

So, how do health systems and communities prioritize bereavement services to ensure that no bereaved individual goes without needed support? The transitional bereavement care model offers a roadmap.

“We must reposition bereavement care from an afterthought to a public health priority. Transitional bereavement care is necessary to bridge the gap in offerings between healthcare organizations and community-based bereavement services,” Lichtenthal said. “Our model calls for health systems to shore up the quality and availability of their offerings, but also recognizes that resources for bereavement care within a given healthcare institution are finite, emphasizing the need to help build communities’ capacity to support grievers.”

Key to the model, she added, is the bolstering of community-based support through development of “compassionate communities” and “upskilling” of professional services to assist those with more substantial bereavement-support needs.

The model contains these pillars:

  • Preventive bereavement care –healthcare teams engage in bereavement-conscious practices, and compassionate communities are mindful of the emotional and practical needs of dying patients’ families.
  • Ownership of bereavement care – institutions provide bereavement education for staff, risk screenings for families, outreach and counseling or grief support. Communities establish bereavement centers and “champions” to provide bereavement care at workplaces, schools, places of worship or care facilities.
  • Resource allocation for bereavement care – dedicated personnel offer universal outreach, and bereaved stakeholders provide input to identify community barriers and needed resources.
  • Upskilling of support providers – Bereavement education is integrated into training programs for health professionals, and institutions offer dedicated grief specialists. Communities have trained, accessible bereavement specialists who provide support and are educated in how to best support bereaved individuals, increasing their grief literacy.
  • Evidence-based care – bereavement care is evidence-based and features effective grief assessments, interventions, and training programs. Compassionate communities remain mindful of bereavement care needs.

Lichtenthal said the new Center will strive to materialize these pillars and aims to serve as a global model for other health organizations. She hopes the paper’s recommendations “will cultivate a bereavement-conscious and grief-informed workforce as well as grief-literate, compassionate communities and health systems that prioritize bereavement as a vital part of ethical healthcare.”

“This paper is calling for healthcare institutions to respond to their duty to care for the family beyond patients’ deaths. By investing in the creation of the Center for the Advancement of Bereavement Care, Sylvester is answering this call,” Lichtenthal said.

Follow @SylvesterCancer on X for the latest news on Sylvester’s research and care.

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Article Title: Investing in bereavement care as a public health priority

DOI: 10.1016/S2468-2667(24)00030-6

Authors: The complete list of authors is included in the paper.

Funding: The authors received funding from the National Cancer Institute (P30 CA240139 Nimer) and P30 CA008748 Vickers).

Disclosures: The authors declared no competing interests.

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