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Nowcasting by Bayesian Smoothing: A flexible, generalizable model for real-time epidemic tracking.

Sarah F McGough1, Michael A Johansson2, Marc Lipsitch3,4

  • 1Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Harvard University, Boston, Massachusetts, United States of America.

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Summary

Accurate disease nowcasting is improved by NobBS, a Bayesian method that links future cases to past reports. This approach enhances real-time disease activity estimates, especially with time-varying reporting delays.

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Area of Science:

  • Epidemiology
  • Biostatistics
  • Computational Biology

Background:

  • Real-time disease activity estimation is hindered by delayed case reporting.
  • Current nowcasting methods often overlook the temporal relationship between past and future infectious disease cases.
  • Existing nowcasting approaches may lack generalizability due to narrow optimization.

Purpose of the Study:

  • To introduce NobBS (Nowcasting by Bayesian Smoothing), a novel Bayesian approach for disease nowcasting.
  • To evaluate NobBS's performance and robustness across diverse disease settings and reporting delay characteristics.
  • To compare NobBS with existing nowcasting software and identify key performance-enhancing features.

Main Methods:

  • Developed a Bayesian smoothing approach (NobBS) to model infectious disease transmission.
  • Applied NobBS to dengue and influenza-like illness (ILI) data from Puerto Rico and the US, respectively.
  • Compared NobBS performance against a published nowcasting software package, analyzing reporting delay dynamics.

Main Results:

  • NobBS demonstrated smooth and accurate nowcasting capabilities in multiple disease settings.
  • Incorporating a temporal relationship between cases significantly improved nowcasting accuracy with time-varying reporting delays.
  • Analysis revealed trade-offs in using moving windows for capturing reporting delay variations.

Conclusions:

  • NobBS offers a robust and generalizable approach to real-time disease activity estimation.
  • The temporal linkage of cases is crucial for accurate nowcasting, particularly when reporting delays fluctuate.
  • The R package "NobBS" is available for broader application, aiding public health surveillance.