publications

2024

1. 

   Periodic Vaccination for Post-Pandemic Management: Insights From and Planning Beyond COVID-19

   Jade Xiao, Turgay Ayer, and Jagpreet Chhatwal

   IISE Transactions on Healthcare Systems Engineering

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   Waning immunity to the SARS-CoV-2 virus and the inevitability of viral mutations necessitate a large-scale periodic revaccination program. Rapid mass vaccination may quickly suppress an epidemic, but it may have an unintended downstream effect of creating a surge in population susceptibility later when vaccinated people lose their immunity all at the same time. To test this hypothesis, we conducted a simulation study comparing pulse vaccination, the repeated administration of “booster” vaccines in large pulses occurring at fixed intervals, and constant vaccination, the continuous administration of booster vaccines at a slower, constant pace. We showed that constant vaccination can maintain population susceptibility and therefore incident deaths at a constant, manageable level; while pulse vaccination can induce large recurrent epidemics. The advantage of constant vaccination is only realized, however, in a post-pandemic scenario when a high level of population immunity has already been attained through a combination of vaccination and natural infection. At the beginning of a novel pandemic, aggressive vaccination is recommended to prioritize immediate protection over long-term protection. In a counterfactual analysis, we showed that prematurely switching to constant vaccination would have significantly increased the disease burden during the Delta variant wave in August 2021.

2. 

   Semaglutide vs Endoscopic Sleeve Gastroplasty for Weight Loss

   Muhammad Haseeb, Jagpreet Chhatwal, Jade Xiao, and 2 more authors

   JAMA Network Open

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   Importance: Obesity is a disease with a large socioeconomic burden. Endoscopic sleeve gastroplasty (ESG) is a minimally invasive endoscopic bariatric procedure with wide global adoption. More recently, new weight-loss medications, such as glucagon-like peptide-1 receptor agonists (eg, semaglutide), have attracted increased attention due to their efficacy. However, their cost-effectiveness over an extended period compared with ESG is a critical gap that needs to be better explored for informed health care decision-making. Objective: To assess the cost-effectiveness of semaglutide compared with ESG over 5 years for individuals with class II obesity. Design, Setting, and Participants: This economic evaluation study, conducted from September 1, 2022, to May 31, 2023, used a Markov cohort model to compare ESG and semaglutide, with a no-treatment baseline strategy. The study comprised adult patients in the US health care system with class II obesity (body mass index [BMI] of 35-39.9). The base case was a 45-year-old patient with class II obesity (BMI of 37). Patients undergoing ESG were subjected to risks of perioperative mortality and adverse events with resultant costs and decrement in quality of life. Interventions: Strategies included treatment with semaglutide and ESG. Main Outcomes and Measures: Costs (2022 US dollars), quality-adjusted life-years (QALYs), and incremental cost-effectiveness ratio (ICER) with a willingness-to-pay threshold of 100 000/QALY. A 5-year time horizon with a cycle length of 1 month with a 3% discount rate was used. Probabilities, costs, and quality-of-life estimates of the model were derived from published literature. One-way, 2-way, and probabilistic sensitivity analyses were also performed. Results: The model found that ESG was more cost-effective than semaglutide over a 5-year time horizon, with an ICER of –595 532/QALY. Endoscopic sleeve gastroplasty added 0.06 QALYs and reduced total cost by 33 583 relative to semaglutide. The results remained robust on 1-way and probabilistic sensitivity analyses. Endoscopic sleeve gastroplasty sustained greater weight loss over 5 years vs semaglutide (BMI of 31.7 vs 33.0). To achieve nondominance, the annual price of semaglutide, currently 13 618, would need to be $3591. Conclusions and Relevance: This study suggests that ESG is cost saving compared with semaglutide in the treatment of class II obesity. On price threshold analyses, a 3-fold decrease in the price of semaglutide is needed to achieve nondominance.

2023

1. 

   HTA2 Cost-Effectiveness of a Clinical Care Pathway for the Screening of Nonalcoholic Fatty Liver Disease in Patients with Type 2 Diabetes Mellitus

   Jade Xiao, Muhammad Haseeb, Fasiha Kanwal, and 7 more authors

   Value in Health

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   The American Gastroenterological Association (AGA) recently published a Clinical Care Pathway for the management of nonalcoholic fatty liver disease (NAFLD) with the aim of facilitating efficient, value-based care. Development of the Pathway was based on the expertise of a multidisciplinary task force. However, it has thus far not been evaluated in terms of cost-effectiveness. Our objective was to assess the cost-effectiveness of the Pathway for managing NAFLD in “high risk” patients, specifically, those with type 2 diabetes mellitus (T2DM).

2022

1. 

   Analysis of a Simulation Model to Estimate Long-term Outcomes in Patients with Nonalcoholic Fatty Liver Disease

   Jagpreet Chhatwal, Ozden O. Dalgic, Wanyi Chen, and 6 more authors

   JAMA Network Open

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   Quantitative assessment of disease progression in patients with nonalcoholic fatty liver disease (NAFLD) has not been systematically examined using competing liver-related and non–liver-related mortality.To estimate long-term outcomes in NAFLD, accounting for competing liver-related and non–liver-related mortality associated with the different fibrosis stages of NAFLD using a simulated patient population.This decision analytical modeling study used individual-level state-transition simulation analysis and was conducted from September 1, 2017, to September 1, 2021. A publicly available interactive tool, dubbed NAFLD Simulator, was developed that simulates the natural history of NAFLD by age and fibrosis stage at the time of (hypothetical) diagnosis defined by liver biopsy. Model health states were defined by fibrosis states F0 to F4, decompensated cirrhosis, hepatocellular carcinoma (HCC), and liver transplant. Simulated patients could experience nonalcoholic steatohepatitis resolution, and their fibrosis stage could progress or regress. Transition probabilities between states were estimated from the literature as well as calibration, and the model reproduced the outcomes of a large observational study.Simulated natural history of NAFLD.Main outcomes were life expectancy; all cause, liver-related, and non–liver-related mortality; and cumulative incidence of decompensated cirrhosis and/or HCC.The model included 1 000 000 simulated patients with a mean (range) age of 49 (18-75) years at baseline, including 66% women. The life expectancy of patients aged 49 years was 25.3 (95% CI, 20.1-29.8) years for those with F0, 25.1 (95% CI, 20.1-29.4) years for those with F1, 23.6 (95% CI, 18.3-28.2) years for those with F2, 21.1 (95% CI, 15.6-26.3) years for those with F3, and 13.8 (95% CI, 10.3-17.6) years for those with F4 at the time of diagnosis. The estimated 10-year liver-related mortality was 0.1% (95% uncertainty interval [UI], <0.1%-0.2%) in F0, 0.2% (95% UI, 0.1%-0.4%) in F1, 1.0% (95% UI, 0.6%-1.7%) in F2, 4.0% (95% UI, 2.5%-5.9%) in F3, and 29.3% (95% UI, 21.8%-35.9%) in F4. The corresponding 10-year non–liver-related mortality was 1.8% (95% UI, 0.6%-5.0%) in F0, 2.4% (95% UI, 0.8%-6.3%) in F1, 5.2% (95% UI, 2.0%-11.9%) in F2, 9.7% (95% UI, 4.3%-18.1%) in F3, and 15.6% (95% UI, 10.1%-21.7%) in F4. Among patients aged 65 years, estimated 10-year non–liver-related mortality was higher than liver-related mortality in all fibrosis stages (eg, F2: 16.7% vs 0.8%; F3: 28.8% vs 3.0%; F4: 40.8% vs 21.9%).This decision analytic model study simulated stage-specific long-term outcomes, including liver- and non–liver-related mortality in patients with NAFLD. Depending on age and fibrosis stage, non–liver-related mortality was higher than liver-related mortality in patients with NAFLD. By translating surrogate markers into clinical outcomes, the NAFLD Simulator could be used as an educational tool among patients and clinicians to increase awareness of the health consequences of NAFLD.

2. 

   The United States COVID-19 Forecast Hub dataset

   Estee Y. Cramer, Yuxin Huang, Yijin Wang, and 19 more authors

   Scientific Data

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   Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages.

3. 

   Projecting COVID-19 Mortality as States Relax Nonpharmacologic Interventions

   Benjamin P. Linas, Jade Xiao, Ozden O. Dalgic, and 5 more authors

   JAMA Health Forum

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   A key question for policy makers and the public is what to expect from the COVID-19 pandemic going forward as states lift nonpharmacologic interventions (NPIs), such as indoor mask mandates, to prevent COVID-19 transmission.To project COVID-19 deaths between March 1, 2022, and December 31, 2022, in each of the 50 US states, District of Columbia, and Puerto Rico assuming different dates of lifting of mask mandates and NPIs.This simulation modeling study used the COVID-19 Policy Simulator compartmental model to project COVID-19 deaths from March 1, 2022, to December 31, 2022, using simulated populations in the 50 US states, District of Columbia, and Puerto Rico. Projected current epidemiologic trends for each state until December 31, 2022, assuming the current pace of vaccination is maintained into the future and modeling different dates of lifting NPIs.Date of lifting statewide NPI mandates as March 1, April 1, May 1, June 1, or July 1, 2022.Projected COVID-19 incident deaths from March to December 2022.With the high transmissibility of current circulating SARS-CoV-2 variants, the simulated lifting of NPIs in March 2022 was associated with resurgences of COVID-19 deaths in nearly every state. In comparison, delaying by even 1 month to lift NPIs in April 2022 was estimated to mitigate the amplitude of the surge. For most states, however, no amount of delay was estimated to be sufficient to prevent a surge in deaths completely. The primary factor associated with recurrent epidemics in the simulation was the assumed high effective reproduction number of unmitigated viral transmission. With a lower level of transmissibility similar to those of the ancestral strains, the model estimated that most states could remove NPIs in March 2022 and likely not see recurrent surges.This simulation study estimated that the SARS-CoV-2 virus would likely continue to take a major toll in the US, even as cases continued to decrease. Because of the high transmissibility of the recent Delta and Omicron variants, premature lifting of NPIs could pose a substantial threat of rebounding surges in morbidity and mortality. At the same time, continued delay in lifting NPIs may not prevent future surges.

4. 

   Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

   Estee Y. Cramer, Evan L. Ray, Velma K. Lopez, and 292 more authors

   Proceedings of the National Academy of Sciences

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   Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks.

2021

1. 

   Changing Dynamics of COVID-19 in the U.S. with the Emergence of the Delta Variant: Projections of the COVID-19 Simulator

   Jagpreet Chhatwal, Jade Xiao, Peter Mueller, and 5 more authors

   medRxiv

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   With the recent emergence of the B.1.617.2 (Delta) variant of SARS-CoV-2 in the U.S., many states are seeing rising cases and hospitalizations after a period of steady decline. As We used the COVID-19 Simulator, an interactive online tool that utilizes a validated mathematical model, to simulate the trajectory of COVID-19 at the state level in the U.S. COVID-19 Simulator’s forecasts are updated weekly and included in the Centers for Disease Control and Prevention (CDC) ensemble model. We employed our model to analyze scenarios where the Delta variant becomes dominant in every state. The combination of high transmissibility of the Delta variant, low vaccination coverage in several regions, and more relaxed attitude towards social distancing is expected to result in as surge in COVID-19 deaths in at least 40 states. In several states – including Idaho, Maine, Montana, Nebraska, North Carolina, Oregon, Puerto Rico, Washington, and West Virginia – the projected daily deaths in 2021 could exceed the prior peak daily deaths under current social distancing behavior and vaccination rate. The number of COVID-19 deaths across the U.S. could exceed 1600 per day. Between August 1, 2021, and December 31, 2021, there could be additional 157,000 COVID-19 deaths across the U.S. Of note, our model projected approximately 20,700 COVID-19 deaths in Texas, 16,000 in California, 12,400 in Florida, 12,000 in North Carolina, and 9,300 in Georgia during this period. In contrast, the projected number of COVID-19 deaths would remain below 200 in New Jersey, Massachusetts, Connecticut, Vermont, and Rhode Island. We project COVID-19 deaths based on the current vaccination rates and social distancing behavior. Our hope is that the findings of this report serve a warning sign and people revert to wearing masks and maintain social distancing to reduce COVID-19 associated deaths in the U.S. Our projections are updated weekly by incorporating vaccination rates and social distancing measures in each state; the latest results can be found at the COVID-19 Simulator website.

2020

1. 

   PIN68 COVID-19 Simulator: An Interactive Tool to Inform COVID-19 Intervention Policy Decisions in the United States

   Jagpreet Chhatwal, Ozden O. Dalgic, Peter Mueller, and 5 more authors

   Value in Health

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   Dynamic and fast actions are needed to suppress the coronavirus disease 2019 (COVID-19) pandemic, which has affected every sector of human life. Our objective was to develop an open-access, interactive tool for policy makers to inform timely decisions and evaluate the impact of different non-pharmaceutical interventions (of varied intensity and timing) on reducing the spread of COVID-19 in the U.S.