title: Modeling immune response and its effect on infectious disease outbreak dynamics.
abstract: BACKGROUND
  In recent epidemiological models, immunity is incorporated as a simplified value that determines the capacity of an individual to become infected or to transmit the disease. Moreover, the quality of the immune response determines the chances of infection and the length of time an individual is capable to infect others. We present a model that incorporates individuals' immune responses to, further, examine the role of the collective immune response of individuals in a population during an infectious outbreak.
  
  
  METHODS
  We constructed a contagion model that incorporates the collective immune response of individuals represented by the superposition of individual immune responses (PIR). Multiple probability distributions are used to represent the immunocompetence of different age groups, thereby modeling the concept of Population Immune Response (PIR). Multiple experiments were conducted in which the population is divided in different age groups for which each group has a unique immune response quality and thus a different length for its immune periods. Finally, we explored the effects of implementing different vaccination strategies in the population.
  
  
  RESULTS
  The experiments displayed important variations in the outbreak dynamics as a consequence of incorporating PIR in homogeneous and mixed populations. The experiments showed that individuals with weak immune responses and those who are immune to the pathogen play a significant role in shaping the outbreak dynamics. Finally, after implementing different vaccination strategies, the results suggest that if vaccination resources are limited, the vaccination should be targeted towards individuals that spread the disease for a longer period of time.
  
  
  CONCLUSIONS
  Our results suggest that it is essential for the public health establishment to increase their understanding of the characteristics of regional demographics that could impact the quality of the immune response of the individuals. The results indicate that it is necessary to further investigate mitigation strategies to limit the capacity to transmit the disease by individuals that spread the pathogen for extended periods of time. Ultimately, this study suggests that it is crucial for public health researchers to identify appropriate targeted vaccination regimes and to explore the link between PIR and outbreak dynamics to improve the monitoring and mitigating efforts of ongoing and future epidemics.
authors.affiliation: Center for Computational Epidemiology and Response Analysis, University of North Texas, 1155 Union Circle 311277, Denton, 76203, TX, USA. reyessja@plu.edu.|Department of Computer Science and Computer Engineering, Pacific Lutheran University, 1010 S 122nd St, Tacoma, 98447, WA, USA. reyessja@plu.edu.
authors.forename: Jorge
authors.initials: J
authors.lastname: Reyes-Silveyra
authors.affiliation: Center for Computational Epidemiology and Response Analysis, University of North Texas, 1155 Union Circle 311277, Denton, 76203, TX, USA. mikler@cs.unt.edu.
authors.forename: Armin R
authors.initials: AR
authors.lastname: Mikler
mesh_terms: D000293:Adolescent; D000328:Adult; D000367:Age Factors; D000368:Aged; D003141:Communicable Diseases / Q000276:immunology* / Q000503:physiopathology*; D003198:Computer Simulation; D004196:Disease Outbreaks; D004813:Epidemiology; D006801:Humans; D007107:Immune System; D007121:Immunocompetence; D008875:Middle Aged; D008962:Models, Theoretical; D011336:Probability; D014611:Vaccination; D019562:Viral Load; D055815:Young Adult