Engineering responses to pandemics

Abstract

Focusing on pandemic influenza, this chapter approaches the planning for and response to such a major worldwide health event as a complex engineering systems problem. Action-oriented analysis of pandemics requires a broad inclusion of academic disciplines since no one domain can cover a significant fraction of the problem. Numerous research papers and action plans have treated pandemics as purely medical happenings, focusing on hospitals, health care professionals, creation and distribution of vaccines and anti-virals, etc. But human behavior with regard to hygiene and social distancing constitutes a first-order partial brake or control of the spread and intensity of infection. Such behavioral options are "non-pharmaceutical interventions." (NPIs) The chapter employs simple mathematical models to study alternative controls of infection, addressing a well-known parameter in epidemiology, R0, the "reproductive number," defined as the mean number of new infections generated by an index case. Values of R0 greater than 1.0 usually indicate that the infection begins with exponential growth, the generation-to-generation growth rate being R0. R0 is broken down into constituent parts related to the frequency and intensity of human contacts, both partially under our control. It is suggested that any numerical value for R0 has little meaning outside the social context to which it pertains. Difference equation models are then employed to study the effects of heterogeneity of population social contact rates, the analysis showing that the disease tends to be driven by high frequency individuals. Related analyses show the futility of trying geographically to isolate the disease. Finally, the models are operated under a variety of assumptions related to social distancing and changes in hygienic behavior. The results are promising in terms of potentially reducing the total impact of the pandemic.1389-1995/09/$17.00  2009 -IOS Press and the authors. All rights reserved 312 R.C. Larson and K.R. Nigmatulina / Engineering responses to pandemicsglobal economy [28]. It is for these reasons, and more -discussed below -that we select influenza pandemics as our focus in a chapter entitled, Engineering Responses to Pandemics.A common definition of "engineering' is as follows: "The application of scientific and mathematical principles to practical ends such as the design, manufacture, and operation of efficient and economical structures, machines, processes, and systems." 1 In engineering the response to a pandemic, we need to use "scientific and mathematical principles" to design processes and systems to mitigate the seriousness and consequences of the flu and to create a total system response to it.A standard engineering approach towards pandemic flu has been to tackle obvious more traditional engineering problems. These problems range from "optimizing" vaccine and anti-viral distribution and stockpiling strategies, to hospital surge capacity analysis, to developing solutions to supply chain 1 http://www.answers.com/topic/engineering Cit...

Science knowledge and trust in medicine affect individuals’ behavior in pandemic crises

“…Individuals’ behavior has a strong impact on epidemiological processes during pandemics (Anderson et al 2020 ; Bish and Michie 2010 ). On the one hand, compliance with preventive measures is critical to avoid further spreading an infectious disease or to slow down its spread (Larson and Nigmatulina 2009 ). On the other hand, avoiding panic behavior is important to ensure public order and prevent dangerous self-medication (Mowbray 2020 ).…”

“…To date, no vaccine is available to protect individuals from COVID-19 and no drugs can cure COVID-19 (Anderson et al 2020 ). In light of this situation, individual behavior will be crucial to controlling the spread of COVID­19 (Anderson et al 2020 ; Chen et al 2020 ; Larson and Nigmatulina 2009 ), as it has a strong impact on epidemiological processes during critical stages of the outbreak (Anderson et al 2020 ).…”

Science knowledge and trust in medicine affect individuals’ behavior in pandemic crises

“…Individuals' behavior has a strong impact on epidemiological processes during pandemics (Anderson et al, 2020;Bish & Michie, 2010). On the one hand, engaging in reasonable behavior is critical to avoid further spreading an infectious disease or to slow down its spread (Larson & Nigmatulina, 2009). On the other hand, avoiding unreasonable behavior is important to ensure public order and prevent dangerous self-medication (Mowbray, 2020).…”

Simulating influenza pandemic dynamics with public risk communication and individual responsive behavior

“…Individuals in these models are assumed to reduce their overall contacts with other people due to a pandemic, and the degree of reduction depends on the epidemic's propagation condition. This assumption is also called the mass action incidence assumption (Larson and Nigmatulina 2010). For example, both Larson and Nigmatulina (2009) and Yoo et al (2010) make the parameter of daily contact rate in their models a variable instead of a constant.…”