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Alternative SIAR models for infectious diseases and applications in the study of non-compliance

Journal Article · · Mathematical Models and Methods in Applied Sciences
 [1];  [2];  [3];  [4];  [5];  [6];  [4]
  1. Weierstrass Institute for Applied Analysis and Stochastics, Mohrenstraße 39, 10117 Berlin, Germany
  2. Department of Mathematics, University of Texas, Austin, 2515 Speedway, Austin, TX 78712, USA
  3. Department of Mathematics, Indiana University Bloomington, 831 East 3rd Street, Bloomington, IN 47405, USA
  4. Department of Mathematics, University of California, Los Angeles, 520 Portola Plaza, Los Angeles, CA 90095, USA
  5. Department of Mathematics, University of Arizona, 617 North Santa Rita Avenue, Tucson, AZ 85721, USA
  6. Department of Mathematics, University of Alabama, 505 Hackberry Lane, Tuscaloosa, AL 35401, USA
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In this paper, we use modified versions of the SIAR model for epidemics to propose two ways of understanding and quantifying the effect of non-compliance to non-pharmaceutical intervention measures on the spread of an infectious disease. The SIAR model distinguishes between symptomatic infected (I) and asymptomatic infected (A) populations. One modification, which is simpler, assumes a known proportion of the population does not comply with government mandates such as quarantining and social-distancing. In a more sophisticated approach, the modified model treats non-compliant behavior as a social contagion. We theoretically explore different scenarios such as the occurrence of multiple waves of infections. Local and asymptotic analyses for both models are also provided.

Research Organization:
Oak Ridge Inst. for Science and Education (ORISE), Oak Ridge, TN (United States)
Sponsoring Organization:
USDOE Office of Science (SC)
DOE Contract Number:
SC0014664
OSTI ID:
1983002
Journal Information:
Mathematical Models and Methods in Applied Sciences, Vol. 32, Issue 10; ISSN 0218-2025
Publisher:
World Scientific
Country of Publication:
United States
Language:
English

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