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Threshold dynamics of the Transmission of Antibiotic-Resistant Infections

Zinabu Teka Melese1, S M Mwalili2, G O Orwa2

  • 1Pan African University Institute for Basic Sciences, Technology and Innovation, Nairobi, Kenya.

Bio Systems
|June 29, 2018
PubMed

Insights

Mathematical modeling reveals how hospital-acquired (HA-MRSA) and community-acquired (CA-MRSA) methicillin-resistant Staphylococcus aureus strains compete. This analysis identifies key factors influencing transmission and guides effective control strategies against these multidrug-resistant infections.

Area of Science:

  • Epidemiology
  • Mathematical Biology
  • Infectious Diseases

Background:

  • Multidrug-resistant infections, including methicillin-resistant Staphylococcus aureus (MRSA) and vancomycin-resistant enterococci (VRE), pose significant global health challenges.
  • Hospital-acquired infections (HAIs) represent a critical area of concern due to increasing resistance rates.

Purpose of the Study:

  • To formulate and analyze a mathematical model characterizing the transmission co-dynamics of hospital-acquired MRSA (HA-MRSA) and community-acquired MRSA (CA-MRSA).
  • To investigate the long-term competitiveness and dominance of these two MRSA strains within hospital settings.
  • To identify effective intervention strategies for controlling MRSA transmission and spread in hospitals.

Main Methods:

  • Development of a mathematical model to simulate MRSA strain dynamics.
  • Numerical simulations to calculate basic and invasion reproduction numbers for each strain.
  • Sensitivity analysis to assess the impact of various parameters on transmission and spread.
  • Graphical representations to support theoretical findings.

Main Results:

  • The study determines the conditions under which one MRSA strain may dominate over the other.
  • Invasion reproduction numbers are used to predict the uniform persistence of both HA-MRSA and CA-MRSA.
  • Sensitivity analysis highlights critical parameters influencing MRSA transmission dynamics.

Conclusions:

  • Mathematical modeling provides valuable insights for policy and decision-making in controlling MRSA spread.
  • Understanding strain competitiveness is crucial for developing targeted and effective intervention strategies.
  • The findings aid in reducing the burden of MRSA infections in hospital environments.
Keywords:
Basic reproduction numberDisease transmission dynamicsDrug-resistanceForward bifurcationInvasion reproduction numberMRSE co-infectionSensitivity indicesStability analysis

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