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In the ever-evolving field of public health, statistical analysis serves as a cornerstone for understanding and managing disease outbreaks. By leveraging various statistical tools, health professionals can predict potential outbreaks, analyze ongoing situations, and devise effective responses to mitigate impact. For that to happen, there are a few possible stages of the analysis:
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Mpox outbreak: Time series analysis with multifractal and deep learning network.

T M C Priyanka1, A Gowrisankar1, Santo Banerjee2

  • 1Department of Mathematics, School of Advanced Sciences, Vellore Institute of Technology, Vellore 632 014, Tamil Nadu, India.

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This summary is machine-generated.

This study reveals fractal patterns in mpox transmission across Africa, the Americas, and Europe. Advanced modeling forecasts future mpox spread, aiding global epidemic preparedness.

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Area of Science:

  • Epidemiology
  • Data Science
  • Public Health

Background:

  • The mpox outbreak presents a significant global public health challenge.
  • Understanding the transmission dynamics of mpox is crucial for effective control strategies.

Purpose of the Study:

  • To analyze the epidemiological situation of mpox in key affected regions.
  • To explore the fractal and multifractal nature of mpox transmission patterns.
  • To forecast future mpox spread using advanced computational models.

Main Methods:

  • Fractal interpolation was used for pre-processing mpox case data.
  • Multifractal analysis was applied to investigate heterogeneity in mpox cases.
  • A bidirectional long-short term memory (BiLSTM) neural network was employed for forecasting.

Main Results:

  • Irregular and fractal patterns were identified in mpox transmission trends.
  • Multifractality effectively characterized the heterogeneity of mpox case distribution.
  • The study demonstrated the utility of BiLSTM networks for predicting mpox outbreaks.

Conclusions:

  • Mpox transmission exhibits complex, fractal characteristics.
  • Multifractal analysis provides valuable insights into disease spread.
  • Forecasting mpox spread is essential for early warning systems and global health security.