A Scaling Analysis of Influenza Transmission in Nepal

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Authors: Gokul Saha*
Cited by: 0

Abstract

This research provides a detailed scaling analysis of Influenza transmission in Nepal by applying time series methods and the Hurst exponent. Examining monthly incidence across the most impacted districts from July 2022 to June 2024, the study evaluates the fractal characteristics—specifically self-similarity and self-affinity—of the data. By distinguishing between long-term and short-term memory patterns, the analysis determines whether the disease spread is persistent or anti-persistent. These insights offer a robust framework for public health officials to refine forecasting models and optimize intervention strategies.

Fields of Study & Subjects

COVID-19 epidemiological studies Data-Driven Disease Surveillance Complex Systems and Time Series Analysis

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
2 January 2026