PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
June 3, 20260 citationsOpen Access

A Deterministic Kinetic Framework for Modelling Pathogen Persistence and Recurrence in Zoonotic Reservoirs

View Full Paper
UKUrvashi Kankran

Key Points

  • This research aims to model the persistence and recurrence of zoonotic pathogens using a deterministic kinetic framework.
  • Integrated deterministic chemical reaction dynamics with ecological observations of Hantavirus vector systems.
  • Developed a mathematical framework mapping decay patterns to pathogen persistence in reservoir populations.
  • Modelled climatic and environmental shifts as factors influencing transmission rates.
  • Identified environmental shifts as significant catalysts in accelerating the rate of pathogen transmission.
  • Demonstrated a strong relationship between first-order reaction dynamics and the long-term persistence of zoonotic pathogens.
  • Provided a new methodology for predicting potential spillover events by analyzing ecological triggers.

Abstract

This paper explores the conceptual relationship between first-order chemical kinetics and the persistence of zoonotic viral outbreaks. By integrating the mathematical principles of deterministic chemical reaction dynamics with ecological observations of Hantavirus vector systems, this study establishes a deterministic framework mapping the asymptotic decay patterns of first-order reactions onto the long-term enzootic persistence of pathogens within reservoir populations. Climatic and environmental shifts are modelled as catalytic modulators that lower the ecological activation barriers to transmission, thereby accelerating the rate constant and triggering recurrent epidemic waves from a low-level baseline. This cross-disciplinary approach demonstrates the utility of reaction kinetics in modelling pathogen reservoirs, providing a novel, intuitive methodology for identifying environmental triggers prior to spillover events.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Urvashi Kankran (2026) studied this question.

synapsesocial.com/papers/6a1fc42cdee9eb8c0dce5c1bhttps://doi.org/10.5281/zenodo.20492903
Ask AI
Helpful
Bookmark
Share
View Full Paper