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Join Value Analytics Labs at ISPOR US from May 5-8, 2024. At ISPOR 2024, attendees will delve into the latest methodologies, data analytics, and evidence-based approaches that drive transformative changes in health and well-being. This year’s meeting is themed HEOR: A Transformative Force for Whole Health

An episode on The Geo-Analyzer that Value Analytics Labs developed in collaboration with Seagen is posted on Gynecologic Oncology's website.

According to Chhatwal, this combination of lower vaccination and relaxed attitudes created ideal conditions for the Delta variant to spread in communities. "To get out of the wave sooner—or reduce the impact of the wave—we need higher vaccination rates and more social distancing, including indoor mask mandates in almost all states," he said.

In collaboration with Seagen, we developed Cervical Cancer Geo-Analyzer, an open access, web-based, interactive tool to visualize geographical areas in the US where cervical cancer education or healthcare resource needs are high. The tool was launched at the American Society of Clinical Oncology (ASCO) 2022 Annual Meeting.

“Look at Google Analytics, the prediction models, and waste water all pointing to the same trends,” Chhatwal said. “That tells us something about what’s happening in the state, which is trends should be going downwards from this point onwards.”

Dr. Jagpreet Chhatwal, an assistant professor at Harvard Medical School and the associate director of Massachusetts General Hospital’s Institute for Technology Assessment, which also projects COVID-19 metrics, cautioned that trying to predict what may happen with the virus in the weeks ahead is “highly uncertain.”

What is clear is that more variants will emerge if people remain susceptible to catching COVID-19 in the first place, said Jagpreet Chhatwal, an assistant professor at Harvard Medical School.

In this joint interview feature, following their workshop delivered at the International Society for Pharmacoeconomics and Outcomes Research’s 2020 Asia Pacific meeting (Virtual ISPOR Asia Pacific 2020; 14–16 September), Turgay Ayer (Georgia Tech, GA, USA), Jag Chhatwal (Massachusetts General Hospital, MA, USA) and Selin Merdan (Value Analytics Lab, GA, USA) discuss the practicalities of applying machine learning (ML) in the real-world evidence and health economics and outcomes research (HEOR) fields.

Jagpreet Chhatwal, a lead investigator of the COVID-19 simulator, which models the potential future of coronavirus infection and death based on behavior changes

Jag Chhatwal, Assistant Professor at Harvard Medical School, joined KUSI to discuss the new study’s findings.

"We were surprised because before conducting the study I would think that mass gatherings in large stadiums would have contributed significantly to increase in daily number of cases. But our findings show that this indeed was not the case." said Turgay Ayer from Georgia Institute of Technology.

Jagpreet Chhatwal, an assistant professor at Harvard Medical School, helped design a tool to detect COVID-19 outbreaks in counties that hosted professional football games. "We can essentially break a transmission chain — and prevent a super spreader event — by adhering to masking and 6-feet social distancing at Raymond James Stadium," he said.

Jagpreet Chhatwal, an assistant professor at Harvard Medical School who works on The COVID-19 Simulator forecasting project used for the CDC ensemble, sees a similar path. He told Newsweek: "Unfortunately, we can very likely hit 3,000 deaths per day by the end of the year if we continue at the current trajectory... it's just a matter of weeks that deaths per day will cross the previous peak seen in April."

Using our Covid-19 Simulator, we estimated that a lockdown of four to six weeks could substantially decrease Covid-19 in most states. Following such an intense period of sacrifice, it would be possible to reopen colleges and universities, and likely other schools and businesses, with firm masking and distancing policies to contain transmission.

According to Jagpreet Chhatwal, principal investigator of the COVID-19 Simulator Website and an assistant professor at Harvard Medical School, football games can also accelerate the spread of COVID-19 because fans often travel from neighboring counties to attend them.

The COVID-19 Policy Simulator — created by researchers at MGH, Harvard Medical School, Georgia Tech, and Boston Medical Center — predicts that with the current level of restrictions, there could be more than 800 new cases every day in Massachusetts. Under new stay-at-home orders, the computer model suggests the number of daily cases could be brought below 325.

There’s no crystal ball that can tell us what’s going to happen next with COVID-19, but there are computer models that provide some insight into the direction things are heading. Scientists at Boston Medical Center and Massachusetts General Hospital have developed a COVID-19 outbreak predictor computer model, and it’s showing that infection rates are increasing at an alarming rate in many Massachusetts counties. WGBH News Reporter Craig LeMoult spoke with Benjamin Linas, associate professor at the Boston University School of Medicine and an infectious disease physician at Boston Medical Center, who is one of the computer model’s developers. The transcript below has been edited for clarity.

Ever wondered what machine learning is and how it might be applied to health economics and outcomes research (HEOR)? This informative workshop presented a technical overview of machine learning techniques, examples of machine learning conducted in healthcare and relevant to health economics, and some potential uses for machine learning moving forward.

Project lead Jagpreet Chhatwal, a professor at Harvard Medical School, said the biggest challenge the researchers faced was accounting for unknown variables — considerations that are becoming more apparent as the pandemic continues.

According to the COVID-19 Simulator developed by researchers at Massachusetts General Hospital and Georgia Tech, the total deaths from the coronavirus in the six New England states could reach some 90,000 by the end of August if all restrictions were lifted.

For the past three years, various governments and patient advocacy groups have clamored for lower-cost hepatitis C medicines, given the high cure rate for these pricey new drugs. Now, a new study finds that upfront treatment with cheaper generic versions can offer a substantial payback.

Dr. Jagpreet Chhatwal, at Massachusetts General Hospital, calculates that the new, more effective therapy will cause the overall cost of treating patients with that leukemia to balloon by nearly six times. That's due to both the cost of the new drug and the growing number of patients who will live longer and thus will need continuous treatment.

Jagpreet Chhatwal of Mass General Hospital, who led the study, tells me the new treatment has tripled the cost of treating a patient with this one type of cancer. Chhatwal said, "We find that on average the lifetime cost of treatment with these new therapies would be $600,000."

“It’s a disturbing concern,” said one of the study authors, Jagpreet Chhatwal, who is an assistant professor at Harvard Medical School and a senior scientist at the Institute for Technology Assessment at Massachusetts General Hospital. “And it’s happening now in CLL… Drug prices have to come down to make them more effective and more affordable.”

Dr. Jagpreet Chhatwal, assistant professor of radiology at Harvard Medical School, has studied the economics of treating hepatitis C in prisons and said that while the drugs are expensive, liver transplants and treatment for patients with hepatitis C in its later stages are also costly.

“We have millions of people who need treatment for hepatitis C and payers obviously don’t have the budget to cover this tremendous expense,” Jagpreet Chhatwal, the study’s lead author and an assistant professor of health services research at the The University of Texas M.D. Anderson Cancer Center said.