A simple SI-type model for HIV/AIDS with media and self-imposed psychological fear

Indrajit Ghosh, Pankaj Kumar Tiwari, Sudip Samanta, Ibrahim M. Elmojtaba, Nasser Al-Salti, Joydev Chattopadhyay*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

50 Citations (Scopus)


Infectious diseases can have a large impact on society, as they cause morbidity, mortality, unemployment, inequality and other adverse effects. Mathematical models are invaluable tools in understanding and describing disease dynamics with preventive measures for controlling the disease. The roles of media coverage and behavioral changes due to externally imposed factors on the disease dynamics are well studied. However, the effect of self-imposed psychological fear on the disease transmission has not been considered in extant research, and this gap is addressed in the present investigation. We propose a simple SI-type model for HIV/AIDS to assess the effects of media and self-imposed psychological fear on the disease dynamics. Local and global dynamics of the system are studied. Global sensitivity analysis is performed to identify the most influential parameters that have significant impact on the basic reproduction number. After calibrating our model using HIV case data-sets for Uganda and Tanzania, we calculate the basic reproduction numbers in the study period using the estimated parameters. Furthermore, a comparison of the effects of awareness and self-imposed psychological fear effects reveals that awareness is more effective in eliminating the burden of HIV infection.

Original languageEnglish
Pages (from-to)160-169
Number of pages10
JournalMathematical Biosciences
Publication statusPublished - Dec 2018


  • Awareness
  • Epidemic model
  • Global sensitivity analysis
  • Parameter estimation
  • Self-imposed psychological fear
  • Stability analysis

ASJC Scopus subject areas

  • Statistics and Probability
  • Modelling and Simulation
  • General Biochemistry,Genetics and Molecular Biology
  • General Immunology and Microbiology
  • General Agricultural and Biological Sciences
  • Applied Mathematics


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