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Looking back on forward-looking COVID models

ABSTRACT: Summary Covid Act Now (CAN) developed an epidemiological model that takes various non-pharmaceutical interventions (NPIs) into account and predicts viral spread and subsequent health outcomes. In this study, the projections of the model developed by CAN were back-tested against real-world data, and it was found that the model consistently overestimated hospitalizations and deaths by 25%–100% and 70%–170%, respectively, due in part to an underestimation of the efficacy of NPIs. Other COVID models were also back-tested against historical data, and it was found that all models generally captured the potential magnitude and directionality of the pandemic in the short term. There are limitations to epidemiological models, but understanding these limitations enables these models to be utilized as tools for data-driven decision-making in viral outbreaks. Further, it can be valuable to have multiple, independently developed models to mitigate the inaccuracies of or to correct for the incorrect assumptions made by a particular model. Highlights • An epidemiological model was developed by Covid Act Now (CAN)• The performance of the model by CAN was evaluated against historical data• The performances of several COVID models were similarly evaluated and compared• Models were found to capture the short-term magnitude and directionality of COVID The bigger picture Development of an epidemiological model by Covid Act Now (CAN) and evaluation of performance by back-testing against historical data was performed. Similar analysis was performed for several other COVID models and results compared. It was found that all models generally captured the potential magnitude and directionality of the pandemic in the short term. There are limitations to epidemiological models, but understanding these limitations enables these models to be utilized as tools for data-driven decision-making in viral outbreaks. Further, it can be valuable to have multiple, independently developed models to mitigate the inaccuracies of or to correct for the incorrect assumptions made by a particular model. An epidemiological model was developed by Covid Act Now (CAN), and its performance was evaluated against historical data along with several other COVID models. It was found that all models generally captured the potential magnitude and directionality of the pandemic in the short term. There are limitations to epidemiological models, but understanding these limitations enables these models to be utilized as tools for data-driven decision-making in viral outbreaks.

SUBMITTER: Chong P

PROVIDER: S-EPMC9278499 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Recent studies have found substantial variation in hospital resource use by expired Medicare beneficiaries with chronic illnesses. By analyzing only expired patients, these studies cannot identify differences across hospitals in health outcomes like mortality. This study examines the association between mortality and resource use at the hospital level, when all Medicare beneficiaries hospitalized for heart failure are examined.A total of 3999 individuals hospitalized with a principal diagnosis of heart failure at 6 California teaching hospitals between January 1, 2001, and June 30, 2005, were analyzed with multivariate risk-adjustment models for total hospital days, total hospital direct costs, and mortality within 180-days after initial admission ("Looking Forward"). A subset of 1639 individuals who died during the study period were analyzed with multivariate risk-adjustment models for total hospital days and total hospital direct costs within 180-days before death ("Looking Back"). "Looking Forward" risk-adjusted hospital means ranged from 17.0% to 26.0% for mortality, 7.8 to 14.9 days for total hospital days, and 0.66 to 1.30 times the mean value for indexed total direct costs. Spearman rank correlation coefficients were -0.68 between mortality and hospital days, and -0.93 between mortality and indexed total direct costs. "Looking Back" risk-adjusted hospital means ranged from 9.1 to 21.7 days for total hospital days and 0.91 to 1.79 times the mean value for indexed total direct costs. Variation in resource use site ranks between expired and all individuals were attributable to insignificant differences.California teaching hospitals that used more resources caring for patients hospitalized for heart failure had lower mortality rates. Focusing only on expired individuals may overlook mortality variation as well as associations between greater resource use and lower mortality. Reporting values without identifying significant differences may result in incorrect assumption of true differences.

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Looking back on forward-looking COVID models

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