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A statistical tool for comparing seasonal ILI surveillance data.

René Ferland1, Sorana Froda2

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This study introduces a new method to compare yearly influenza epidemics using CDC surveillance data across ten Health and Human Services (HHS) regions. The approach uses predicted incidence data to highlight regional variations in flu activity.

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Area of Science:

  • Epidemiology
  • Biostatistics
  • Public Health Surveillance

Background:

  • Yearly influenza epidemics pose a significant public health challenge.
  • Seasonal surveillance data from the Center for Disease Control and Prevention (CDC) provides insights into influenza trends.
  • Comparing influenza incidence across different geographical regions is crucial for targeted interventions.

Purpose of the Study:

  • To develop and apply a novel methodology for comparing influenza epidemic features across ten Health and Human Services (HHS) regions.
  • To analyze the evolution of influenza incidence data within these regions.
  • To facilitate effective comparison of regional influenza surveillance data.

Main Methods:

  • Utilized seasonal influenza surveillance data from the CDC.
  • Developed a method comparing the relative distribution of weekly new cases.
  • Employed a negative binomial regression model to predict incidence, controlling for covariates.
  • Calculated predictions using a standardized set of covariate values, accounting for regional population size.

Main Results:

  • Presented main findings through graphical representations for clear emphasis.
  • The methodology facilitates rapid identification of relevant features in seasonal influenza data.
  • Enabled effective comparison of influenza incidence patterns across the ten HHS regions.

Conclusions:

  • The proposed methodology offers a robust approach for comparing regional influenza surveillance data.
  • Predicted values, adjusted for population, provide a standardized basis for inter-regional comparisons.
  • Graphical presentation enhances the understanding of influenza epidemic dynamics and regional differences.