Category: Covid-19

Its been four years since Covid-19 emerged, igniting a pandemic that killed millions of people and brought the world to its knees. A key factor in taming the pandemic was the creation of effective vaccines, which have saved millions of lives.

Youd think developing a successful vaccine would be an unmitigated win, from a financial perspective. And, indeed, for Pfizer and its partner BioNTech, as well as for Moderna whose vaccines were the most widely used in the United States and much of the world the revenues generated were absolutely staggering. But investors have shrugged at those sales as gains that will not be repeated.

Total sales of the Pfizer/BioNTech vaccine surpassed $80 billion, and more than 400 million doses of the shot and subsequent boosters have been administered in the U.S. alone. But the companys stock price fell 32% over the past five years. Meanwhile, AstraZeneca, which told STAT it has not booked sales from its vaccine since last April and does not expect future sales, has seen its share price rise 64%. Merck, which saw its vaccine efforts fail twice, is up 56%.

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Covid vaccine financial winners and losers, from Pfizer to Novavax - STAT

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Posted: March 25, 2024 Last Updated: 10 Hours Ago

Elon Musk's X said it's funding legal bills for a Canadian doctor previously chastised by regulators for her tweets about COVID-19.

In a post to the X News account on Sunday morning, the company formerly known as Twitter wrote that it's "proud to defend" Dr. Kulvinder Kaur Gill against what it calls "government-supported efforts to cancel her speech."

In 2021, the College of Physicians and Surgeons of Ontario (CPSO) cautioned the Brampton, Ont.-based pediatrics specialist over her tweets, including one saying vaccination for COVID-19 was unnecessary.

The doctorhas an ongoing crowdfunding campaign asking for $300,000 to help pay for legal costs, including a cost order related to a lawsuit she launched against what she called a "malicious online smear campaign."

On March 17, Gill tagged Musk in a post asking him for help, saying she owedcosts that were due in four days.

"It's $300,000 I don't have, after nearly four years of being entangled in multiple legal battles trying to advocate for my patients,"Gill said in thevideo. "It's now looking quite grim."

Gill then issued another video post on X on Thursday, saying Musk has committed to paying the remainder of her crowdfunding campaign and helping her appeal the College's cautions from 2021 "til the very end."

"May Wahegurualways bless you, Elon," she said, using the Sikh term for God.

Publicly available legal filings show that Gill previously launched a lawsuit against 23 defendants. The claim was dismissed, awarding costs to the defendants totalling more than $1.1 million.

LISTEN |Why Elon Musk's X is paying for the legal bills of a Brampton doctor who tweeted against COVID vaccines:

Gill appealed the dismissal, though only regarding her claim against four of the defendants, and sought leave to appeal the related costs orders. The appeal was dismissed, and she was refused leave to appeal the costs orders.

Last August, Musk posted on X promising to fund the legal bills of anyone who was "unfairly treated" by their employers "due to posting or liking something on this platform."

"No limit," he wrote.

University of Toronto bioethicist Kerry BowmantoldCBC Radio's Metro Morning thatMusk is "pretty selective about what kind of freedom of speech he will fight for."

Gill's case is not justabout freedom of speechbut about her responsibility as a physician,hesaid, adding that a physiciansaying vaccination for COVID-19 wasunnecessary can cause"a lot of social harm in a crisis."

"When you have a physician, emphasis on physician, saying this, credibility erodes very, very quickly," Bowman said. "People will say this is controversial because a physician says vaccines don't work."

It's been almost a year and a half since Musk bought Twitter for US$44 billion, taking the formerly publicly traded company private.

He has since renamed the platform X and made sweeping changes, including dismantling its verification systemand getting rid of the majority of the workforce including engineers and moderators.

Experts have raised concern about the amount of misinformation being posted and algorithmically promoted on X, including about topics like the Israel-Hamas war.

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X to pay legal bills for doctor warned over COVID tweets - CBC.ca

'4 years is too long' Nursing home families, lawmakers call for release of pandemic report

by Ashley Cusicanqui

WRGB

On this day four years ago, the Department of Health and former Governor Andrew Cuomo's administration informed nursing homes No resident shall be denied re-admission or admission to the nursing home solely based on confirmed and suspected COVID-19."

A controversial decision blamed for thousands of deaths, a yet to be released independent report on the state's COVID-19 response could offer new insight.

On Monday, Republican lawmakers and nursing home advocates, many who lost family close to them during the pandemic, called for the release of the report.

"We will seek justice," said Voices For Seniors Co-Founder Vivian Zayas. "They are not forgotten because I am here."

With a pin on her shirt of Anna Martinez, Vivian Zayas tells the story of how her mother lost her life in a nursing home during the COVID-19 pandemic.

A story, far too familiar.

"We were not told she had a collapsed lunge, we were not told she caught COVID," said Zayas. "We were not told there was COVID-19 in her facility, we did not know the facility was accepting COVID positive patients."

At least 15,000 New Yorkers in nursing homes died from COVID-19.

Since, Governor Kathy Hochul contracted the Olsen Group out of Virginia at the rate of $4.3 million dollars for a year-long study on decisions made in New York throughout the pandemic, including in nursing homes.

That study began in November of 2022.

Im very frustrated by the pace, Ive wanted this before, but absolutely will be released to the public when its done. We're staying on top of it, we're pushing, and I'm told it's going to be, I won't even give a date, but we're told it shouldn't be too far out, but I keep asking all the time, the same question.

The review has still yet to be announced if it's completed, causing frustration and calls for answers.

"4 years is too long to wait for answers and to wait for accountability," said Voices For Seniors Director Tracey Alvino. "Grieving nursing home families were promised an independent investigation into the state's COVID response and here it is 16 months and 3 weeks since the Olsen group was hired to do this review and nothing but silence."

"New Yorkers need answers," said New York Assembly Minority Leader (R, C-Pulaski) Will Barclay. "Us in state government need answers so we can put protocols in place to ensure this tragedy doesn't happen again."

"4 years later we have a degree of perspective but what we don't have is the detail that an analysis should have presented."

Last Tuesday, reporters asked New York State Department of Health Commissioner James McDonald if he thinks the state legislature should approve a separate commission for an additional report. McDonald said he would read the Olsen report when it comes out and "for a lot of us in public health though we know what's happened and a lot of us are trying to never forget certain parts of it, and there's other parts we want to never remember. For us in public health, the pandemic is still very real for us though. As far as what needs to be reviewed, I think what's the question? What are you trying to do? Are you trying to learn something, or trying to blame somebody? I've already learned a lot. I'm always open to new ideas but I'm not blaming anybody anymore for anything."

We did reach out to the Governor's office for an update, the executive chamber referred us back to comments Governor Hochul made in January where she expressed frustration over the pace of the report release.

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'4 years is too long' Nursing home families, lawmakers call for release of pandemic report - WRGB

A cross-sectional observational study was performed in our department after obtaining prior approval from the Institute Ethics Committee. We initially reviewed CT thorax scans of 250 patients with RT-PCR-positive COVID-19 infection over one year as detailed in Fig. 1a. Lung nodules were present in 24 patients with COVID-19 infection of which four patients were eliminated from our study as their CT images were not suitable for radiomics analysis. Only patients in whom no other synchronous lung pathology was identified were included. The imaging features of COVID-19 lung nodules were studied in the remaining 20 patients and were assessed for size, type, margins, location, and the lobe and segment involved, Digital imaging and communications in medicine (DICOM) images of these 20 patients were thereafter subjected to segmentation analysis and radiomics post-processing.

(a) Flow diagram of the study of COVID-19-infected cases. (b) Flow diagram of the study of non-COVID-19-infected cases.

We exclusively examined patients with COVID pneumonia who exhibited solid pulmonary nodules only, totaling 20 cases, to ensure similarity with benign and malignant nodules. Our study involved individuals who underwent chest CT scans between the 3rd and 6th day after the onset of symptoms (1st week of the disease) and who tested positive for COVID-19 infection through RT-PCR. Along with these pulmonary nodules, the other common CT findings in these patients typically included ground glass opacities, crazy paving, and consolidation. However, our focus for radiomics analysis was solely on these pulmonary nodules.

We reviewed CT thorax of 1200 non-COVID-19 patients as shown in Fig.1b. Lung nodules of compatible size were present in 133 cases. The final diagnosis was available in 97 patients, of whom 44 were benign and 53 were malignant nodules. The benign lesions were diagnosed based on histopathological diagnosis or correlation with clinical features and follow-up as per the Fleishers Society guidelines18. The final diagnosis in primary malignant lesions was arrived at based on histopathological diagnosis, and in metastasis based on the histopathological diagnosis of the lung nodule or primary tumor. The DICOM images of 40 benign nodules and 50 malignant nodules were subjected to segmentation analysis. Radiomics post-processing was done in 39 benign nodules and 49 malignant nodules. Radiomics analysis was not feasible in two patients. Subsequently, the radiomics texture analysis of COVID-19 lung nodules was compared separately with each radiomics analysis of benign non-COVID-19 benign lung nodules and malignant lung nodules.

The distribution of cases included in the final radiomics analysis included, n=24 (22%) metastatic pulmonary nodules, n=25 (23%) primary malignancies, n=39 (36%) non-COVID benign nodules, and n=20 (19%) COVID-related nodules (Fig.2). The final diagnosis was available in all these nodules. n=39 of the pulmonary nodules were found to be other benign, while n=49 were malignant. The benign lesions were diagnosed based on histopathological diagnosis or correlation with clinical features and follow-up as per the Fleishers Society guidelines. The final diagnosis in primary malignant lesions was arrived at based on histopathological diagnosis, and metastasis was based on the histopathological diagnosis of the lung nodule or primary tumor. Only patients in whom no other synchronous lung pathology was identified were included to prevent overlap of pathologies. Patients with subsolid pulmonary nodules and Nodules with calcification were excluded from the study to compare purely solid pulmonary nodules. Of the other benign lesions (n=39) analyzed using radiomics, 36% were septic emboli, 28%were benign lesions monitored long-term per Fleishner society guidelines, and the remainder comprised sarcoidosis, inflammatory conditions, pulmonary tuberculosis, benign carcinoid, hematoma, hydatid disease, Sjogrens syndrome, and Wegners granulomatosis cases, as shown in Supplementary Information (Fig. S1). Among the malignant nodules (n=49), there were 25 cases of primary lung malignancies and 24 cases of metastases. Primary lung malignancies consisted of adenocarcinoma (52%), squamous cell carcinoma (40%), and other types, as depicted in Supplementary Information (Fig. S2). The predominant source of metastases was breast carcinoma, with the remainder originating from various other primary organs, as depicted in Supplementary Information (Fig. S3).

Case distribution of the lung nodules included in the study.

HRCT examinations were performed using one of the following multidetector computed tomography (MDCT) scanners: Phillips-brilliance 16 (Philips medical systems, Cleveland); GE EVO evolution 128 slices (GE healthcare, Princeton); and Siemens biograph horizon (Siemens AG, Munich). HR-CT images were obtained during breath-holding with the following parameters: 120kV, 200mA. The section thickness and reconstruction intervals were 0.650.80mm. The CT images were sent to a picture archiving and communication system (PACS) to be interpreted at workstations.

The segmentation of the DICOM images of the pulmonary nodules, a critical initial step for accurate feature extraction, was performed manually by an expert radiologist using Insight Segmentation and Registration Toolkit (ITK-SNAP) software19 and was verified by three radiologists independently. The steps described above are shown in Figs.3 and 4. By relying on the expert radiologist, we could delineate the nodules with a high degree of precision, particularly in terms of their shape and texture characteristics, which are crucial for subsequent radiomic analysis. Following the segmentation, we extracted radiomic features from the 3D representations of the nodules. The extraction process focused on a comprehensive set of features, including but not limited to, shape, size, intensity, texture, and wavelet features. The emphasis was on capturing a broad spectrum of information that reflects the underlying pathology and can be correlated with clinical outcomes. By combining expert radiological input with radiomic feature extraction techniques, we aimed to mitigate some of the challenges associated with parametric texture feature extraction.

A 57year-old male patient with RTPCR has proven COVID-19 pneumonia. (a,b) The axial section of the CT thorax in the lung window and soft tissue window shows a subpleural soft tissue nodule in the posterior segment of the left lower lobe. (c) Creation of ROI for segmentation. (d) 2D-segmented nodule. (e) 3D-volumetric rendering of the nodule. (f) Follow-up chest CT after 6months revealed partial resolution of the nodule.

A 21year-old lady with cough and hemoptysis. HPE: benign carcinoid tumor. (a,b) Axial section of CT thorax in lung window and soft tissue window showing a mass lesion in the posterior segment of the right lower lobe. (c) Creation of ROI for segmentation. (d) 2D segmented mass lesion. (e) 3D volumetric rendering of the mass lesion.

Segmented lung nodules were used to extract different types of features. These features were classified into three categories: shape features (14), first-order features (18 features), and texture-based features (69 features). Texture-based features were of four types, namely gray level co-occurrence matrix (GLCM) features (24 features)20, gray-level run-length matrix (GLRLM) features (16 features)21, gray level size zone (GLSZM) features (16 features)15,22,23 and gray level dependence matrix (GLDM) features (13 features). Each radiomics feature was given a feature rank based on a random forest classifier. Out of 101, the top 10 features were selected for classification algorithms according to Anand et al.24. Figures 5 and 6 show the top 10 selected radiomics features with rank, and Tables 1 and 2 summarize their feature importance values. Several classification algorithms, such as SUPPORT VECTOR MACHine (SVM)25, multi-layer perceptron (MLP), naive Bayes, discriminant analysis, and decision tree26, were applied to selected feature matrices to classify benign and malignant nodules. SVM with the linear kernel (L-SVM) and radial basis function kernel (RBFSVM) were used as SVM variants. Linear discriminant analysis (LDA) and quadratic discriminant analysis (QDA) were used in the category of discriminant analysis. We have also experimented with MLP classifiers for different hyperparameters which include activation, layers/number of neurons, and learning rate. To evaluate the performance of classifiers, confusion matrices were drawn on the test set. Accuracy, sensitivity, specificity, precision, and F1-measure were calculated for each classifier.

(a) Ten important features used for the classification of COVID-19 and non-COVID-19 benign lung nodules. (b) Comparison plot of the most prominent feature.

While many state-of-the-art approaches in medical image analysis today do use deep learning methods, in our experiments they showed poor performance with an accuracy of at most 55%. We evaluated models such as ResNet, DenseNet, and Vision Transformer for the same but due to the limited data available, the models showed poor performance27. The radiomic features provide a more robust basis for training on limited data as compared to the deep learning approaches.

The study was performed after obtaining prior approval from the Institutional Research Ethics CommitteeSri Ramachandra Institute of Higher Education and Research (CSPMED/19/SEP/56/122) and all methods were performed by relevant guidelines and regulations.

Informed consent was obtained from all subjects and/or their legal guardians involved in the study.

Excerpt from:

Radiomics analysis for distinctive identification of COVID-19 pulmonary nodules from other benign and malignant ... - Nature.com

CINCINNATI, Ohio A new artificial intelligence tool developed at the University of Cincinnati can accurately predict whether someone is willing to be vaccinated against COVID-19 with only a little bit of information.

Such accurate assessments of perceptions about vaccines and other medical treatments is information that may one day be useful in designing more effective public health campaigns beyond COVID-19, say the creators of the technology.

COVID-19 is unlikely to be the last pandemic we see in the next decades, said lead author Nicole Vike, a senior research associate in UCs College of Engineering and Applied Science. Having a new form of AI for prediction in public health provides a valuable tool that could help prepare hospitals for predicting vaccination rates and consequential infection rates.

The predictive artificial intelligence system uses a small set of data from demographics along with information about a persons personal judgments. Then using some patterns about how one responds to rewards and aversion to risk, it comes up with its answer.

The framework by which we judge what is rewarding or aversive is fundamental to how we make medical decisions, explained co-senior author Hans Breiter, a professor of computer science at UC.

Breiter, Vike and the other researchers developed and tested the accuracy of their model by surveying nearly 4,000 adults across the United States in 2021 during the COVID-19 pandemic. At the time of the survey, the first vaccines had been available for more than a year.

Respondents provided information such as where they live, income, highest education level completed, ethnicity and access to the internet.

They were also asked if they had received either of the available COVID-19 vaccines and if they routinely followed four recommendations designed to prevent the spread of the virus: wearing a mask, social distancing, washing their hands and not gathering in large groups.

Participants were then shown a set of 48 color photographs in six categories: sports, disasters, cute animals, aggressive animals, nature and food and asked to rate how much they liked or disliked each of them on a seven-point scale.

The pictures were designed to evoke some mild emotion. The way a person responds to the pictures tells behavioral scientists how a person makes judgements about taking risks and protecting themselves from loss.

The judgment variables and demographics were compared between respondents who were vaccinated and those who were not. What they found was that AI could make accurate predictions about human attitudes with surprisingly little data or reliance on expensive and time-consuming clinical assessments.

We found that a small set of demographic variables and 15 judgment variables predict vaccine uptake with moderate to high accuracy and high precision, the authors wrote.

In terms of computing power, the whole thing is pretty easy too.

And in age of big-data, the team says their work provides evidence that sometimes less information is better.

The study is anti-big-data, said co-senior author Aggelos Katsaggelos, an endowed professor of electrical engineering and computer science at Northwestern University.

It can work very simply. It doesnt need super-computation, its inexpensive and can be applied with anyone who has a smartphone. We refer to it as computational cognition AI. It is likely you will be seeing other applications regarding alterations in judgment in the very near future.

The study was published in the Journal of Medical Internet Research Public Health and Surveillance.

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Are you willing to get the COVID-19 vaccine? AI says it knows the answer - cleveland.com

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Shaken by Covid-19, countries decided to build a framework of binding commitments to stop such trauma from ... - mycouriertribune.com

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Four years later, we look at the day Minnesota shut down as the COVID-19 pandemic spread across the nation.

ST. PAUL, Minn. (FOX 9) - At a time when the nation was seeing rising cases of COVID-19 that ultimately led to the deaths of thousands of people, four years ago Monday, Minnesota Gov. Tim Walz signed an executive order telling people to stay home.

All people within the State of Minnesota were, "ordered to stay at home or in their place of residence except to engage in the Activities and Critical Sector," according to Executive Order 2020, which began on Friday, March 27, 2020, at 11:59 p.m. through Friday, April 10, 2020 at 5:00 p.m. It would later be extended, and the definition of what was and was not a "critical employee" would become heavily debated.

As of March 24, 2020, Minnesota had 287 confirmed COVID-19 cases including the states first confirmed death plus 35 hospitalizations, according to the executive order.

At the time, it wasnt the first executive order that Gov. Walz issued for the pandemic. On March 13, Walz issued Executive Order 2001, declaring a "peacetime emergency" due to the pandemic threatening the lives of Minnesotans.

On March 15, Executive Order 2002 ordered the temporary closure of public schools.

The following day, Executive Order 2004 ordered the closure of bars, restaurants, and other places of public accommodation. President Donald Trump issued guidelines to limit gatherings of more than 10 people that same day, March 16.

As the pandemic waned and spiked, so did policies to shift the needs of both public safety and economic stability.

Following the wave of shutdowns, both businesses and cities continue to grapple with a new normal of a lack of foot traffic and remote work.

Concerns about government spending and potentially fraudulent programs have also been reported.

Signed four years ago Monday, the lives of Minnesotans and politicians tasked with crafting policy resulting from its impact are undoubtedly forever changed.

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Gov. Walz signed stay at home' order 4 years ago Monday: COVID-19 - FOX 9 Minneapolis-St. Paul

PATRICK WHITTLE Associated Press

31 mins ago

FILE - A cod is seen on a trawler April 23, 2016, off the coast of Hampton Beach, N.H. Maine fishermen bucked yearslong, industrywide trends last year and caught more fish in a development regulators said shows the impact of COVID-19 relief funds. (AP Photo/Robert F. Bukaty, File)

PORTLAND, Maine (AP) Maine fishermen bucked yearslong, industrywide trends last year and caught more fish, a development regulators and industry members said shows the impact of COVID-19 relief funds.

Maine has long been a leader in catching groundfish, which are bottom-dwelling species of fish such as cod and flounder that are often used in seafood staples such as fish and chips. The New England groundfishing industryhas been in decline for decadesdue in part to past overfishing of key species and difficulty rebuilding those stocks.

But Maines groundfishermen had a stronger year than most in 2023, according to state data released earlier this month. The catch of haddock more than doubled to more than 500,000 pounds (226,796 kilograms), and the catches of Atlantic cod, witch flounder and Atlantic halibut were all up significantly.

The increase in catch, as well as a more stable price, reflects investments the state made in critical infrastructure such as the Portland Fish Exchange, an auction house, said Patrick Keliher, the commissioner of the Maine Department of Marine Resources. The state received COVID-19 relief funds via the National Oceanic and Atmospheric Administration for that work and other improvements, he said.

Federal money also supported the Fishermen Feeding Mainers program, which buys fish to support food banks and schools.

Its important work and a positive story; fishermen were able to keep working, critical infrastructure has been maintained, and fresh, healthy Maine seafood went to schools and families in need, Keliher said in a statement.

Maine Coast Fishermens Association, an industry nonprofit group, launched the Fishermen Feeding Mainers program in part to help the groundfish industry survive the COVID-19 pandemic. The program began with a goal of donating 100,000 meals and is now over 1.3 million, said Ben Martens, executive director of the association.

The success of the program has helped buoy the groundfish industry through a challenging time, Martens said.

What we have been able to do is provide a little bit of stability on the market side with Fishermen Feeding Mainers, Martens said. We are connecting these fishermen and these fish into our food system.

The long-term trends for the American groundfish industry are still dire. The nationwide catch of Atlantic cod has fallen from more than 28 million pounds (12.7 million kilograms) in 2002 to just over a million pounds (453,592 kilograms) in 2022.

The industry mustcontend with warming oceans, changing ecosystems,tight fishing quotasand foreign competition in the marketplace. As American catch of cod and haddock have fallen, imports from countries such as Iceland and Norway have become more common in U.S. fish markets.

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Maine fishermen caught more fish in 2023, thanks to a hunger relief program and COVID funds - WPRI.com

Even as Germany's BioNTech deals with ongoing declines of its revenue and share price, it's facing another serious concern: U.S. officials are pressing the company to pay royalties linked to the commercialization of its lucrative Pfizer-partnered COVID-19 vaccine.

In a Monday filing, BioNTech said the U.S. National Institutes of Health (NIH) has sent a "notice of default" on funds that BioNTech allegedly owes the U.S. agency under their prior licensing agreement.

BioNTech says it "disagrees with the positions being taken by the NIH, and intends to vigorously defend against all allegations of breach."

In an annual filinga few days earlier, on March 20, BioNTech said it was in "ongoing discussions" with the NIH "concerning royalties and other related amounts allegedly owed on sales of our COVID-19 vaccine since commercialization."

At that point, the NIH had only threatened to send a notice of default, according to BioNTech.

BioNTech has generated around 40.5 billion euros ($43.9 billion) since starting its COVID-19 vaccine rolloutwith partner Pfizerin late 2020, so any amount owed could be quite substantial for the company.

Last week, BioNTech said it entered this year with cash, cash equivalents and security investments totaling 17.7 billion euros ($19.2 billion).

In a 2021 report (PDF), the NIH provided some background behindthe BioNTech arrangement. After government and academic researchers published an engineered version of the theSARS-CoV-2 spike protein in early 2020,theNational Institute of Allergy and Infectious Diseases began receiving a "significant amount of interest" from companies looking to incorporate the research into their vaccine development, the NIH said. Multiple government agencies worked together and determined that because of the urgency of the situation, they would allow for nonexclusive licenses.

A licensing deal with BioNTech in 2020, and the company's subsequent partnership with Pfizer, yielded the successful Comirnaty vaccine, the NIH said.

Besides the NIH alleging missed royalty payments, BioNTech is in similar discussionswith the University of Pennsylvania, according to the company's annual filing.

BioNTech'sCOVID-19 partner Pfizer didn't mention any ongoing NIH discussions in its own recent annual filing.

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BioNTech hit with 'notice of default' in COVID royalty dispute - FiercePharma

22 Investigates: Indiana Attorney General's analysis of COVID-19

by Julianna Furfari, WSBT 22 Evening Anchor

FILE- In this Aug. 9, 2017, file photo, Rep. Todd Rokita, R-Ind., speaks during a news conference outside of the Indiana Statehouse in Indianapolis. (AP Photo/Darron Cummings, File)

INDIANA (WSBT)

Indiana Attorney General Todd Rokita is calling into question data from the COVID-19 pandemic that contributed to decisions made about lockdowns and mitigation policies.

Rokita says he instructed his staff to prepare an analysis of the state's data following comments made on WSBT 22 more than 2 years ago.

In December of 2021, Rokita said "I don't believe any numbers anymore. I am sorry about that, but they are politicized." You can watch the full interview below.

FULL%20INTERVIEW:%20Indiana%20Attorney%20General%20Todd%20Rokita%20discusses%20the%20state's%20lawsuit%20aimed%20at%20COVID-19%20vaccine%20mandates%20requiring%20healthcare%20workers%20be%20vaccinated%20on%20Dec%2017,%202021.(WSBT%2022)

The analysis points out what Rokita's office outlines as flaws, including:

"We looked at nearly 145,000 death records, for example, to come up with the conclusions I'm going to share with you," Rokita said.

The report claims that the Indiana Department of Health's official Management Performance Hub over-reported COVID 19 deaths by 10.9 % in 2020, 7 % in 2021 and 12.5 % in 2022.

Rokita says they compared death counts reported on the MPH website to the number of death certificates listing COVID as cause of death from the vital records database maintained by IDOH.

JF: Is this a problem with any other illnesses, or just COVID? For example, if someone has the flu and dies from complications?

Rokita claims there are two major problems with positivity rate data, including the health department attributing multiple positive cases to the same person. He claims the state reported a positivity rate of 30% during several months of 2020, but his office's analysis believes that rate was less than 5% during every month of 2020.

Rokita also says decisions on restrictions were based on a sample group that were not representative of the whole population.

JF: The governor at the time said if there were such inaccuracies he would consider that fraud and it should be handed over the inspector general. At the time you said: "this isn't about fraud at this point it's about inaccurate numbers and political agendas causing doubt."

JF: Now that this research has been conducted, has your opinion changed?

On Saturday, WSBT22 News emailed the Governor's office for a response. They recommended we contact the Indiana State Health Department.

We emailed them twice and left a voicemail. We have not heard back. We also emailed the Press Person for the Governor again on Monday- listing several questions: including if the Governor has read this report.

So far, we have not received a response. When we do, we'll update this story.

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22 Investigates: Indiana Attorney General's analysis of COVID-19 - WSBT-TV