Back to the Future: Trump’s History of Promising a Health Plan That Never Comes

Last night's Presidential Debate produced nothing....chaos and empty promises.

Victoria Knight August 13, 2020

Ever since he was a presidential candidate, President Donald Trump has been promising the American people a “terrific,” “phenomenal” and “fantastic” new health care plan to replace the Affordable Care Act.

But, in the 3½ years since he set up shop in the Oval Office, he has yet to deliver.

In his early days on the campaign trail, circa 2015, he said on CNN he would repeal Obamacare and replace it with “something terrific,” and on Sean Hannity’s radio show he said the replacement would be “something great.” Fast-forward to 2020. Trump has promised an Obamacare replacement plan five times so far this year. And the plan is always said to be just a few weeks away.

The United States is also in the grips of the COVID-19 pandemic, which has resulted in more than 163,000 U.S. deaths. KFF estimates that 27 million Americans could potentially lose their employer-sponsored insurance and become uninsured following their job loss due to the pandemic. (KHN is an editorially independent program of the Kaiser Family Foundation.) All of this makes health care a hot topic during the 2020 election.

This record is by no means a comprehensive list, but here are some of the many instances when Trump promised a new health plan was coming soon.

2016: The Campaign Trail

Trump tweeted in February that he would immediately repeal and replace Obamacare and that his plan would save money and result in better health care.

By March, a blueprint, “Healthcare Reform to Make America Great Again,” was posted on his campaign website. It echoed popular GOP talking points but was skimpy on details.

During his speech accepting the Republican nomination in July, Trump again promised to repeal Obamacare and alluded to ways his replacement would be better. And, by October, Trump promised that within his first 100 days in office he would repeal and replace Obamacare. During his final week of campaigning, he suggested asking Congress to come in for a special session to repeal the health care law quickly.

2017: The First Year in Office

January and February:

Trump told The Washington Post in a January interview that he was close to completing his health care plan and that he wanted to provide “insurance for everybody.”

He tweeted Feb. 17 that while Democrats were delaying Senate confirmation of Tom Price, his pick to lead the Department of Health and Human Services, the “repeal and replacement of ObamaCare is moving fast!”

And, on Feb. 28, in his joint address to Congress, Trump discussed his vision for replacing Obamacare. “The way to make health insurance available to everyone is to lower the cost of health insurance, and that is what we are going to do,” he said.

March: Eyes on Congress — And Twitter

House Republicans, with backing from the White House, were the ones to introduce new health legislation, the American Health Care Act (AHCA). The repeal-and-replace bill kept in place some of the more popular provisions of the ACA. Some conservative Republicans said the bill didn’t go far enough, deriding it as “Obamacare Lite” and refusing to vote on it.

On March 9, Trump tweeted, “Despite what you hear in the press, healthcare is coming along great. We are talking to many groups and it will end in a beautiful picture!”

Later that month, as efforts to pass the AHCA continued to stall, Trump updated his earlier promise.

“And I never said — I guess I’m here, what, 64 days? I never said repeal and replace Obamacare. You’ve all heard my speeches. I never said repeal it and replace it within 64 days. I have a long time,” said Trump in his remarks from the Oval Office on March 24. (Which was true; he had said within 100 days.) “But I want to have a great health care bill and plan, and we will. It will happen. And it won’t be in the very distant future.”

April and May: A Roller-Coaster Ride of Legislation and Celebration, Then …

After an intraparty dust-up, the House narrowly passed the AHCA on May 4. Despite tepid support in the Republican-controlled Senate, Trump convened a Rose Garden celebratory event to mark the House’s passage, saying he felt “so confident” about the measure. He also congratulated Republican lawmakers on what he termed “a great plan” and “incredibly well-crafted.”

Nonetheless, Senate Republicans first advanced their own replacement bill, the Better Care Reconciliation Act, but ultimately voted on a “skinny repeal” that would have eliminated the employer mandate and given broad authority to states to repeal sections of the ACA. It failed to gain passage when Sen. John McCain (R-Ariz.) gave it a historic thumbs-down in the wee hours of July 28.

September and October: Moving On … But Not

Trump began September by signaling in a series of tweets that he was moving on from health reform.

But on Oct. 12, he signed an executive order allowing for health care plans to be sold that don’t meet the regulatory standards set up in the Affordable Care Act. The next day, Trump tweeted, “ObamaCare is a broken mess. Piece by piece we will now begin the process of giving America the great HealthCare it deserves!”

Roughly two weeks later, on Oct. 29, Trump got back to the promise with this tweet: “… we will … have great Healthcare soon after Tax Cuts!”

2019: More Talk, More Tweets

March and April: A Moving Target

It seems that 2018 was a quiet time — at least for presidential promises regarding a soon-to-be-unveiled health plan. It was reported that conservative groups were working on an Obamacare replacement plan. But in 2019, Trump again took up the health plan mantle with this March 26 tweet: “The Republican Party will become ‘The Party of Healthcare!’” Two days later, in remarks to reporters before boarding Marine One, Trump said that “we’re working on a plan now,” but again updated the timeline, saying, “There’s no very great rush from the standpoint” because he was waiting on the court decision for Obamacare. This was a reference to Texas v. U.S., the lawsuit brought by a group of Republican governors to overturn the ACA. It is currently pending before the Supreme Court.

Backtracking from his earlier promises to repeal and replace Obamacare within his first 100 days in office, Trump on April 3 tweeted: “I was never planning a vote prior to the 2020 Election on the wonderful HealthCare package that some very talented people are now developing for me & the Republican Party. It will be on full display during the Election as a much better & less expensive alternative to ObamaCare…”

June 16:

In an interview with ABC News, Trump again said a health care plan would be coming shortly.

“We’re going to produce phenomenal health care. And we already have the concept of the plan. And it’ll be much better health care,” Trump told George Stephanopoulos. When Stephanopoulos asked if he was going to tell people what the plan was, Trump responded: “Yeah, we’ll be announcing that in two months, maybe less.”

June 26:

But then, timing again changed as Trump promised a sweeping health plan after the 2020 election. “If we win the House back, keep the Senate and keep the presidency, we’ll have a plan that blows away ObamaCare,” Trump said in a speech to the Faith and Freedom Coalition’s Road to the Majority conference.

Oct. 3:

He reiterated this post-2020 election pledge in a speech to Florida retirees. “If the Republicans take back the House, keep the Senate, keep the presidency — we’re gonna have a fantastic plan,” Trump said.

Oct. 25:

Trump told reporters that Republicans have a “great” health care plan. “You’ll have health care the likes of which you’ve never seen,” he said.

2020: ‘Two Weeks’

Feb. 10:

During a White House business session with governors, Trump commented on the Republican governors’ lawsuit to undo the ACA and whether protections for preexisting conditions would be lost: “If a law is overturned, that’s OK, because the new law’s going to have it in.”

May 6:

During the signing of a proclamation to honor National Nurses Day, Trump again said Obamacare would be replaced “with great healthcare at a lesser price, and preexisting conditions will be included and you won’t have the individual mandate.”

July 19:

Trump told Chris Wallace in a Fox News interview that a health care plan would be unveiled within two weeks: “We’re signing a health care plan within two weeks, a full and complete health care plan that the Supreme Court decision on DACA gave me the right to do.”

July 31:

With no sign of a plan yet, reporters asked Trump about it at a Florida event. Trump responded that a “very inclusive” health care plan was coming and “I’ll be signing it sometime very soon.”

Aug. 3:

Pushing the timeline once again, Trump said during a press briefing that the health care plan would be introduced “hopefully, prior to the end of the month.”

Aug. 7:

Citing his two-week timeline once again, Trump said during a press briefing that he would pursue a major executive order in the next two weeks “requiring health insurance companies to cover all preexisting conditions for all customers.” Trump also said that covering preexisting conditions had “never been done before,” despite the ACA provisions outlining protections for people who have preexisting conditions being among the law’s most popular components. The Trump administration has backed the effort to overturn the ACA — including these protections — now pending before the Supreme Court.

Aug. 10:

In response to a reporter’s question about why he was planning to issue an executive order when the ACA already protects those with preexisting conditions, Trump said: “Just a double safety net, and just to let people know that the Republicans are totally strongly in favor of … taking care of people with preexisting conditions. It’s a second platform. We have: Preexisting conditions will be taken care of 100% by Republicans and the Republican Party.”

Just before publication, we asked the White House for more information regarding when exactly the plan might be unveiled. The press office did not respond to our request for comment.

Subscribe to KHN's free Morning Briefing.

Apple Watch's abnormal pulse feature driving many unnecessary healthcare visits, Mayo Clinic researchers say |

 Apple Smart Watch 4 Pulse oximetry, EKG, GPS, Cell 

                              Apple Watch Rear Sensors

"Only one in seven self-referrals to physicians confirm a cardiac irregularity alert with an Apple Watch. The Apple Watch is not a diagnostic monitor and serves only as a screening device.

"The observation that new clinically actionable cardiovascular diagnoses of interest were diagnosed in only 11.4% of patients following medical evaluation as directed by the treating provider suggests a high false-positive rate as a screening tool for undiagnosed cardiovascular disease," Mayo Clinic researchers wrote in the Journal of the American Medical Informatics Association. "False-positive screening results have the potential to lead to excessive healthcare resource utilization and anxiety among the 'worried well.'”

The retrospective look at clinical documentation also suggests that a sizable portion of those presenting used the Apple Watch's feature "in a manner inconsistent with FDA guidance." The abnormal pulse detection feature is accessible across all generations of Apple Watch devices and is not to be confused with the ECG atrial fibrillation tool introduced with the Series 4 Apple Watch.

Among 264 patients whose clinical documentation was included in the study, 15.5% had records explicitly noting an abnormal pulse alert generated by the feature. The remainder included a reference to the watch and detection of abnormal pulse but did not explicitly mention that the user had received a generated alert, which the researchers noted could be a result of either incomplete documentation or the patient's manual use of the Apple Watch's heart monitoring application.

Patients who experienced symptoms were more likely to undergo diagnostic testing as part of their evaluation (78.5% versus 60.9%; p = .004). There was no significant difference in the proportion of patients with or without a documented abnormal pulse alert from the watch who underwent diagnostic testing.

Overall, 11.4% of patients received clinically actionable diagnoses. This diagnosis rate rose slightly to 15% among those documented to have received the alert.

"Therefore, for patients who experienced an abnormal pulse alert and presented for medical evaluation, 7 (95% confidence interval, 3.5-14.5) patients needed to be evaluated to establish [one] diagnosis of clinically actionable cardiovascular disease," the researchers wrote. "Among the 15 asymptomatic patients who presented following an abnormal pulse alert, only one was diagnosed with a clinically actionable cardiovascular diagnosis, yielding a number needed to diagnose of 15 (95% confidence interval, 2.9-286.5)."

Also of note were the patient populations included in the analysis. Twenty-two percent had pre-existing atrial fibrillation and 8.7% were younger than 22 years – both of which would exclude these patients from the FDA's guidance for this feature."

Author's note:

Regardless of the Mayo Clinic's FDA's guidance for use of the Apple watch physicians must make the evaluation and determination for each patient.  The data reveals that the information must be taken with historical information.  Physical examination is also part of the mandatory evacuation. The comments about the increase in utilization may affect health plan coverage.

Apple Watch's abnormal pulse feature driving many unnecessary healthcare visits, Mayo Clinic researchers say | MobiHealthNews

FDA-approved medical devices and algorithms: an online database | Digital Medicine

Credits:  Stan Benjamens, Pranavsingh Dhunnoo & Bertalan Meskó

Introduction

The 2010s has brought a rise in the number of studies and papers discussing the role of artificial intelligence (AI) and machine learning (ML) in medicine and healthcare (AI/ML). The number of life science papers describing AI/ML rose from 596 in 2010 to 12,422 in 2019. While we are at the beginning of the AI/ML era, the expectations are high and experts foresee that AI/ML shows potential for diagnosing, managing and treating a wide variety of medical conditions1.

Indeed, AI/ML-based technologies have been shown to support several medical specialties from radiology2 and oncology3 to ophthalmology4 and general medical decision-making5. ML models have been shown to reduce waiting times6; improve medication adherence7; customize insulin dosages8; or help interpret magnetic resonance images9, among others. AI/ML- based technologies are coming to electronic health record systems and AI based notifications and messaging systems.

We classify technology like AI/ML-based if official FDA announcements, communications by the company or other publicly available information resources used the expressions ‘deep learning,’ ‘machine learning,’ ‘deep neural networks,’ ‘artificial intelligence,’ and/or ‘AI’ to describe the technology11. For simplicity, we use the term “AI/ML-based” to denote these technologies in this paper. With the increasing expertise and attention on AI/ML in the medical field, the opportunities and possible implications of its use are the topics of an ongoing debate12. A crucial element in this implementation debate is regulating such technologies.Because of the high-risk nature of these medical devices and the unknown consequences of using AI/ML for medical decision-making and data analysis, the FDA has stringent regulatory requirements for medical device licensing. Developers of AI/ML-based medical devices and algorithms have to go through rigorous processes that are time and resource consuming. This can be considered pivotal as a barrier for the introduction of AI/ML in medicine.

Before medical hardware or software is legally made available in the US market, the parent company has to submit it to the FDA for evaluation. For medically oriented AI/ML-based algorithms, the regulatory body has three levels of clearance, namely, 510(k)14, premarket approval15, and the de novo pathway16, each of which needs specific criteria to be fulfilled in order to be granted (Table 1). This process is similar to drug approvals.  

Table 1 Descriptions of the types of FDA approvals for AI/ML-based medical technologies.

From: The state of artificial intelligence-based FDA-approved medical devices and algorithms: an online database

Level of FDA clearance Description

510(k) clearance A 510(k) clearance for an algorithm is granted when it has been shown to be at least as safe and effective as another similar, legally marketed algorithm. The submitter seeking this clearance must provide substantial proof of equivalence in their application. Without approval of being substantially equivalent to the other algorithm, the one pending approval cannot be legally marketed.

Premarket approval Premarket approval is issued to algorithms for Class III medical devices. The latter are those that can have a large impact on human health and as such, their evaluation undergoes more thorough scientific and regulatory processes to determine their safety and effectiveness. In order to approve an application, the FDA determines that the device’s safety and effectiveness is supported by satisfactory scientific evidence. Upon approval, the applicant can proceed with marketing the product. de novo pathway Regarding the de novo classification, it is used to classify those novel medical devices for which there are no legally marketed counterparts, but which offer adequate safety and effectiveness with general controls. The FDA performs a risk-based assessment of the device in question before approval and allowing the device to be marketed.

Table 1 Descriptions of the types of FDA approvals for AI/ML-based medical technologies.

From: The state of artificial intelligence-based FDA-approved medical devices and algorithms: an online database

TABLE  Descriptions of the types of FDA approvals for AI/ML-based medical technologies. 

An infographic about the 29 FDA-approved, AI/ML-based medical technologies.

The two main medical specialties with AI/ML-based medical innovations are Radiology and Cardiology, with 21 (72.4%) and 4 (13.8%) FDA approved medical devices and algorithms respectively. The remaining medical devices and algorithms can be grouped as focusing on internal medicine/endocrinology, neurology, ophthalmology, emergency medicine, and oncology.

The medical field of radiology is the trendsetter regarding FDA-approved medical devices and algorithms, with the introduction of AI/ML-based solutions for worldwide applied image reading software. Examples are the three algorithms for Arterys Inc., Arterys Cardio DL, Arterys Oncology DL and Arterys MICA, which are connected to the workflow Picture Archiving and Communication Systems from main vendors as Siemens Healthineers AG (Germany) and GE Healthcare (USA)20. Six out of these 21 algorithms can be applied in the field of oncology, with three focusing on mammography analyses (ProFound™ AI Software V2.1, cmTriage and TransparaTM) and three others on CT-based lesion detection (Arterys Oncology DL, Arterys MICA and QuantX). This is followed by two algorithms focusing on brain image analyses, with innovations for stroke and hemorrhage detection (ContaCT, Accipiolx, and icobrain), and six algorithms to improve image processing, with noise and radiation dosage reduction (SubtlePET, Deep Learning Image Reconstruction, Advanced Intelligent Clear-IQ Engine, SubtleMR, AI-Rad Companion (Pulmonary) and AI-Rad Companion (Cardiovascular)). Another four algorithms focusing on acute care, with two algorithms for the assessment of pneumothorax (HealthPNX and Critical Care Suite), one focusing on wrist fracture diagnosis (OsteoDetect) and the Aidoc Medical BriefCase system for triage of head, spine, and chest injuries. The final two algorithms in this specialty can be applied for cardiovascular assessments, focusing on the assessment of the heart ejection fraction (EchoMD AEF Software and EchoGo Core).

During the past decade, the use of AI/ML-based medical innovations has become ubiquitous driven by specialty needs in the clinical process from diagnosis to remote monitoring and treatment.  Despite FDA approvals, end-users such as physicians, nurse practitioners must have the final word. Algorithms are continuously updated, and the FDA uses a "locked" or "adaptive" classification in order to monitor algorithms that 'learn' and change with time and use.

The authors clearly state the limitations for the FDA to accomplish this process, explaining that other organizations assess the accuracy of AI/ML-based devices.

eMurmer ID, CSD Labs GmbH), Apple Inc, being the ECG App and Apple Irregular Rhythm Notification Feature, Excel Medical Electronics, Spry Health, and Current Health, Stratoscientific, Inc. introduced the Steth IO device to analyze heart and lung sounds. BrainScope Company Inc. has introduced AI/ML for the evaluation of brain injuries. MindMotion GO (MindMaze SA), (Cantab Mobile, Cambridge Cognition Ltd), and seizure monitoring (Embrace, Empatica Srl.). 

QbCheck (QbTech AB) and ReSET-O (Pear Therapeutics Inc.). With QbCheck, healthcare workers can substantiate their diagnosis or rule out attention deficit hyperactivity disorder (ADHD), enhancing objective medical decisions in psychiatry29, whereas ReSET-O can be applied for patients with Opioid Use Disorder, providing cognitive behavioral therapy as a mobile medical application for prescription use only. As a next step, the ReSET-O algorithm will be used in a randomized controlled trial, which is scheduled to start this year (April 2020)30.

The FDA has a clinical trial protocol for drugs, which may also be applied to devices and AI/ML-based devices and software.

A challenge has developed for the FDAs search algorithm, which itself will require an AI/ML-based search-based method beyond its current version.

Users of AI/ML-based software need (CME) Continuing Medical Education in each specialty.

The ACMGE as the accrediting body for medical education should supervise this as a requirement for the training of physicians

Reference source:

The state of artificial intelligence-based FDA-approved medical devices and algorithms: an online database | npj Digital Medicine

Stressors Take Toll on Students’ Mental Health -

Xenia Shih Bion, MPH

Back to school time of year brings anxiety to some students while others are anxious to return to a routine discipline, friends, and sports.  The new routine of remote learning will cause new challenges for some, while some students will thrive in an independent environment.  In some cases, it will be better.

Students will learn at their own pace. Some students will jump ahead, while some will lag behind, in much the same was in a normal school.

We also need to consider the teacher's needs and responsibilities. Teachers will not have physical responsibility for student safety. Social interaction and disruptive behavior will be lessened. Along with the technical challenges of video conferencing, new techniques will be learned. The new 'normalcy' will also prepare students for the new workplace of remote work.

As many predicted Covid 19 has transformed our lives, at work, at home, and in education.

Distance learning may not be appropriate for early elementary school where physical presence is important for developmental socialization.

Surveys of parents with school-age children reveal the mental health challenges faced by their young ones. A Gallup poll conducted in May found that among parents with children in kindergarten through grade 12, 29% said their child was “already experiencing harm” to their emotional or mental health because of physical distancing and pandemic-related closures of schools and businesses.

Classroom with Social Distancing

Typical Classroom, without social distancing

“Trauma on Top of Trauma”

Students from kindergarten through graduate school are already returning to their studies amid both the pandemic and widespread protests of racial injustice and police violence. Experts worry that these compounding stressors are taking a toll on the mental, emotional, and physical health of young people.

Finally, whatever happens, it is an opportunity to study the effects and make plans for a new future.

Stressors Take Toll on Students’ Mental Health - California Health Care Foundation

The Future Of Prosthetics Depends On A.I

Back in 2011, archeologists unearthed one of the oldest known prosthetic devices; a wooden toe buried with Egyptian mummies some 3,000 years ago. While aesthetically it packs a steampunk look, this artificial toe was far from being a cosmetic item. After testing replicas, researchers found that they were indeed practical devices that helped in walking. While throughout the millennia the materials have changed, prosthetics only evolved in recent decades with the advent of robotic prostheses.

Advance forward 5-6 millennia

From steampunk Egyptian mummies to cyberpunk brain-controlled prosthetics 

So, from bits and bytes of archeological digs, we move on to bits and bytes of technology to build anthropomorphic machines to attach to ourselves as we move toward biosynthetic human beings.

The technology is already here including material sciences, electronic, microchips, sensor technology, and human innovation, curiosity and goals.

The necessary steps to develop a self-sustaining business include already well-known startup implementation, venture capital funding, and committed leaders. The future prosthetic industry will require large amounts of capital which may include private, venture capital funding as well as existing companies in this field. A critical issue will be market demands and health payer reimbursements. Payer challenges may be met by different market segments. Military and Veterans Benefits will be the first to source this capability as many amputations result from battle.  It would seem the government will invest in R&D for prosthetics just as it has for military robotics, which includes augmented skeletons for load-carrying heavy supplies, as well as robotic mules. 

Autonomous robotic mule

The future has arrived. Want proof? Check out these amazing robotic exoskeletons

The Future Of Prosthetics Depends On A.I. | LinkedIn

Common class of drugs linked to onset of Alzheimer’s – Scientific Inquirer

As we age more and more people develop Alzheimer's disease.  This form of dementia is a specific one with 'tangles' and tau proteins infiltrating parts of the brain.  It is only one form of dementia.

Given the growing number of aged people and increasing life span, Alzheimer's Disorder has become a public health problem. People with Alzheimer's disease do not usually die from it and are victim to other disorders of aging, heart disease, hypertension, cancer, or kidney disease.  Sadly it robs them, family and friends of a loved one.

Researchers have searched for a "cause" suspecting toxins, drugs, environmental and immune disorders.  Alzheimer's disorder seems to have become more prevalent in a time when patients are subject to the use of many more drugs.  Could this be a factor in Alzheimer's Disorder?

A team of scientists, led by researchers at the University of California San Diego School of Medicine, report that a class of drugs used for a broad array of conditions, from allergies and colds to hypertension and urinary incontinence, may be associated with an increased risk of cognitive decline, particularly in older adults at greater risk for Alzheimer’s disease (AD)

The study done at the University of California San Diego is published in Neurology found that patients taking anticholernigic drugs (AD) and who had genetic markers for AD were four times more likely to develop MCI (mild cognitive impairment) a term which is inclusive of AD)

Anticholinergics can treat a variety of conditions, including:

Urinary incontinence, overactive bladder (OAB), chronic obstructive pulmonary disorder (COPD), certain types of poisoning

They also help block involuntary muscle movements associated with certain diseases such as Parkinson’s disease. Sometimes, they’re used before surgery to help maintain body functions while a person is treated with anesthesia.

List of anticholinergics

Anticholinergics are only available with a doctor’s prescription. Examples of these drugs include:

atropine (Atropine)
belladonna alkaloids
benztropine mesylate (Cogentin)
aclidinium
cyclopentolate (Cyclogyl)
darifenacin (Enablex)
dicyclomine
fesoterodine (Toviaz)
flavoxate (Urispas)
glycopyrrolate
homatropine hydrobromide
hyoscyamine (Levsinex)
ipratropium (Atrovent)
orphenadrine
oxybutynin (Ditropan XL)
propantheline (Pro-banthine)
scopolamine
methscopolamine
solifenacin (VESIcare)
tiotropium (Spiriva)
tolterodine (Detrol)
trihexyphenidyl
trospium

All of these drugs are very commonly used in elderly patients.

To add to this list we must also include certain other drug classes that are used for other purposes and have anticholernigic properties, such as Benadryl  (diphenhydramine (commonly used for allergy.

Many of these drugs are used and coexist with patients with Alzheimer's disorder. Add to this as we age are metabolic changes. Dosage may be a factor for elderly patients.  Doses should be adjusted appropriately.



There is conflicting information regarding the role of tau proteins, neurofibrillary tangle in AD. Are they cause, or effect?

Some information examines the role of gum disease, specifically the presence of the bacterium, p.gingivales.

There are many confounding factors for investigators to tease out in their search for a cause.





















Common class of drugs linked to onset of Alzheimer’s – Scientific Inquirer

COVID-19 Vaccine Research Is Facing a Monkey Shortage - The Atlantic

In the past seven months, more than 100 COVID-19 vaccines, therapies, and drugs have been pushed into development. But for any of these treatments to make it to humans, they usually have to face another animal first: a monkey. And here, scientists in the United States say they are facing a bottleneck. There just aren’t enough monkeys to go around.

“Nationally, there is basically a big shortage,” says Koen Van Rompay, an infectious-disease scientist at the California National Primate Research Center. Primate research in the U.S. is expensive and often controversial, making it challenging even in normal circumstances. The pandemic has made acquiring monkeys even harder. “We can’t find any rhesus any longer. They’ve completely disappeared,” says Mark Lewis, the CEO of Bioqual, a contract research organization that specializes in animal testing. Scientists in academia and industry alike are all competing for a limited pool of monkeys.

The reasons for the shortage are threefold. First, COVID-19 has created extraordinary demand for monkeys. Second, this coincided with a massive drop in supply from China, which provided 60 percent of the nearly 35,000 monkeys imported to the U.S. last year and which shut off exports after COVID-19 hit. And third, these pandemic-related events are exacerbating preexisting monkey shortfalls. A 2018 National Institutes of Health report had found that NIH-funded national primate centers would be unable to meet future demand and specifically discussed a “strategic monkey reserve” to provide “surge capability for unpredictable disease outbreaks.” A disease outbreak is upon us; the strategic monkey reserve was never created. Furthermore, monkeys infected with COVID-19 have to be kept in Animal Biosafety Level 3 labs, which have specific design and ventilation requirements to prevent the spread of pathogens. The U.S. has a limited number of ABSL-3 labs.

The result, Van Rompay says, is that he gets emails and calls weekly from companies looking to test COVID-19 treatments at the California research center, one of the seven NIH-funded primate centers that work with both academic and industry researchers. “I have to tell them, ‘I’m sorry, we are not allowed to start your research,’” he says. With so much demand for monkeys, the NIH is now centrally deciding which studies can use the national primate centers under a public-private initiative called Accelerating COVID-19 Therapeutic Interventions and Vaccines (ACTIV), creating a new bureaucratic bottleneck. Meanwhile, non-COVID-19 research is also getting pushed aside.

Monkeys account for just 0.5 percent of the animals used in U.S. biomedical research, but they typically represent the last step before human clinical trials. They are closely related to humans, after all—so closely related that scientists refer to the research animals as, technically, “nonhuman primates.” For example, monkey and human immune systems are so similar that vaccine studies can use the same tests to measure antibodies in both. “Literally the same test,” says Skip Bohm, the associate director of the Tulane National Primate Research Center. The similarity means that monkeys are also a good model for testing the agents that help boost the effectiveness of a vaccine, says JoAnne Flynn, a vaccine researcher at the University of Pittsburgh.

The rush to manufacture Covid 19 vaccines has caused biopharmaceutical companies to bypass simian testing with new vaccines. This was always an additional step in clinical trials for adjusting dosages and for safety in children, as juvenile monkeys were also tested.  The FDA protocols have been in existence for several decades.  Bypassing simian trials may be faster, but will it be as safe?
As COVID-19 vaccine development has moved forward at an unprecedented pace, though, some pharmaceutical companies have started human trials before monkey studies have concluded. And with monkeys so hard to come by, others are wondering if certain studies can be skipped altogether. Linda Marbán, the CEO of the biotech company Capricor Therapeutics, says her company originally tried to test its vaccine candidates at the California primate center. It couldn’t get in. She’s now exploring how to go straight into human-safety trials.

Scientists who work with primates, however, say that the animal research still offers certain advantages. Monkeys can be challenged—that is, deliberately infected with COVID-19 after being given an experimental vaccine. Researchers can then follow the animals’ exact progression of disease or lack thereof, tracking how quickly antibody levels shoot up or whether a vaccine reduces how long the monkey sheds the virus. These details are harder to get in human trials because people are naturally exposed to COVID-19 and aren’t being monitored every day. (Although some researchers have proposed human challenge trials for COVID-19, the idea is controversial and none has begun.)
Simians are used because they are also considered primates, the same family that human beings are a member.  The close genetic relationship sometimes allow researcher to test medications prior to actual human trials.

The relative scarcity of these monkeys is also due to activism several decades ago. PETA and other animal rights groups invaded and destroyed hundreds of monkeys by breaking into laboratories and destroying them.  This provoked national attention to the plight of research animals.  Many ongoing research studies were destroyed, cancelled or terminated outright. No one can argue with humane treatment of animals during test studies. 

PETA today remains quite active with celebrities advocating kindness to animals. These activities draw quite a bit of interest.  Many of their claims are half-truths and accusations of NIH being cruel to animals is untrue, bordering on libel.

Following the PETA protests in the 1980s Congress, the FDA and NIH reviewed their practices. and established new regulations.

The animals were bred in companies specifically tasked with breeding monkeys, mice (some) are genetically modified for specific diseases. Knock-out mice have been in use for several decades and are instrumental in treating, studying and modeling different kinds of cancer, obesity, heart disease, diabetes, arthritis, substance abuse, anxiety, aging and Parkinson disease.

Regulation and inspection by Animal Abuse Abundant in Spite of AAALAC Accreditation - USDA Data reveals repeated citations of animal laboratories.

Both sides have self-interest involved. Research laboratories and








-19 Vaccine Research Is Facing a Monkey Shortage - The Atlantic