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Hot-spots detection in count data by Poisson assisted smooth sparse tensor decomposition.

Yujie Zhao1, Xiaoming Huo2, Yajun Mei2

  • 1Biostatistics and Research Decision Sciences Department, Merck & Co., Inc, North Wales, PA, USA.

Journal of Applied Statistics
|October 9, 2023
PubMed
Summary
This summary is machine-generated.

We developed Poisson assisted Smooth Sparse Tensor Decomposition (PoSSTenD) to detect and locate infectious disease hot-spots. This method analyzes spatial, temporal, and categorical count data for timely public health interventions.

Keywords:
CUSUMHot-spots detectionPoisson regressionspatio-temporal modeltensor decomposition

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Area of Science:

  • Public Health Surveillance
  • Biostatistics
  • Data Science

Background:

  • Count data from bio-surveillance and healthcare applications are crucial for monitoring infectious diseases.
  • Timely detection and localization of infectious disease hot-spots are essential for effective public health responses.

Purpose of the Study:

  • To introduce a novel method, Poisson assisted Smooth Sparse Tensor Decomposition (PoSSTenD), for detecting and localizing infectious disease hot-spots.
  • To provide a robust framework for analyzing spatio-temporal-categorical count data in disease surveillance.

Main Methods:

  • Representing count data as a three-dimensional tensor (spatial, temporal, categorical).
  • Fitting the tensor into a Poisson regression model to decompose infectious rates into global trends and local hot-spots.
  • Utilizing cumulative sum (CUSUM) control charts for hot-spot detection and LASSO-type sparse estimation for localization.

Main Results:

  • The PoSSTenD method successfully detects and localizes infectious disease hot-spots.
  • Validation through numerical simulations and a real-world dataset of infectious diseases in the United States demonstrates the method's effectiveness.

Conclusions:

  • PoSSTenD offers a powerful tool for enhancing infectious disease surveillance systems.
  • The methodology enables rapid identification of unusual infectious rates, facilitating targeted public health interventions.