Challenges of COVID-19 Case Forecasting in the US, 2020-2021.

During the COVID-19 pandemic, forecasting COVID-19 trends to support planning and response was a priority for scientists and decision makers alike. In the United States, COVID-19 forecasting was coordinated by a large group of universities, companies, and government entities led by the Centers for Disease Control and Prevention and the US COVID-19 Forecast Hub (https://covid19forecasthub.org). We evaluated approximately 9.7 million forecasts of weekly state-level COVID-19 cases for predictions 1-4 weeks into the future submitted by 24 teams from August 2020 to December 2021. We assessed coverage of central prediction intervals and weighted interval scores (WIS), adjusting for missing forecasts relative to a baseline forecast, and used a Gaussian generalized estimating equation (GEE) model to evaluate differences in skill across epidemic phases that were defined by the effective reproduction number. Overall, we found high variation in skill across individual models, with ensemble-based forecasts outperforming other approaches. Forecast skill relative to the baseline was generally higher for larger jurisdictions (e.g., states compared to counties). Over time, forecasts generally performed worst in periods of rapid changes in reported cases (either in increasing or decreasing epidemic phases) with 95% prediction interval coverage dropping below 50% during the growth phases of the winter 2020, Delta, and Omicron waves. Ideally, case forecasts could serve as a leading indicator of changes in transmission dynamics. However, while most COVID-19 case forecasts outperformed a naïve baseline model, even the most accurate case forecasts were unreliable in key phases. Further research could improve forecasts of leading indicators, like COVID-19 cases, by leveraging additional real-time data, addressing performance across phases, improving the characterization of forecast confidence, and ensuring that forecasts were coherent across spatial scales. In the meantime, it is critical for forecast users to appreciate current limitations and use a broad set of indicators to inform pandemic-related decision making.

Semaglutide vs Endoscopic Sleeve Gastroplasty for Weight Loss.

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.

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

Importance: 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. Objective: 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. Design, Setting, and Participants: 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. Exposure: Simulated natural history of NAFLD. Main Outcomes and Measures: Main outcomes were life expectancy; all cause, liver-related, and non-liver-related mortality; and cumulative incidence of decompensated cirrhosis and/or HCC. Results: 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%). Conclusions and Relevance: 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.

Projecting COVID-19 Mortality as States Relax Nonpharmacologic Interventions.

Importance: 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. Objective: 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. Design Setting and Participants: 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. Exposures: Date of lifting statewide NPI mandates as March 1, April 1, May 1, June 1, or July 1, 2022. Main Outcomes and Measures: Projected COVID-19 incident deaths from March to December 2022. Results: 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. Conclusions and Relevance: 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.