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Modeling dynamics of an influenza pandemic with heterogeneous coping behaviors: case study of a 2009 H1N1 outbreak in Arizona

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Abstract

This paper aims to improve the accuracy of standard compartment models in modeling the dynamics of an influenza pandemic. Standard compartment models, which are commonly used in influenza simulations, make unrealistic assumptions about human behavioral responses during a pandemic outbreak. Existing simulation models with public avoidance also make a rigid assumption regarding the human behavioral response to influenza. This paper incorporates realistic assumptions regarding individuals’ avoidance behaviors in a standard compartment model. Both the standard and modified models are parameterized, implemented, and compared in the research context of the 2009 H1N1 influenza outbreak in Arizona. The modified model with heterogeneous coping behaviors forecasts influenza spread dynamics better than the standard model when evaluated against the empirical data, especially for the beginning of the 2009–2010 normal influenza season starting in October 2009 (i.e., the beginning of the second wave of 2009 H1N1). We end the paper with a discussion of the use of simulation models in efforts to help communities effectively prepare for and respond to influenza pandemics.

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Notes

  1. An influenza pandemic is “a global outbreak of disease that occurs when a new influenza virus appears or “emerges” in the human population, causes serious illness, and then spreads easily from person to person worldwide” (CDC 2012). It is different from pandemic influenza, which refers to the influenza that causes a global outbreak of the disease.

  2. Note that these are the laboratory confirmed cases. On August 30, 2009, the CDC stopped reporting laboratory-confirmed 2009 H1N1 influenza cases because such data tends to underestimate the true number of cases (CDC 2010b), whereas ADHS continued to report weekly laboratory-confirmed cases in Arizona. Given the difficulty in determining the true number of infected cases or the true case detection rate, a previous study (an der Heiden et al. 2009) used the number of laboratory-confirmed cases and an assumed case detection rate to estimate the actual number of cases. In this paper, the actual number of infected cases is calculated based on the number of laboratory-confirmed cases in Arizona reported by ADHS and a 10 % detection rate of 2009 H1N1 influenza cases as in the study by an der Heiden et al. (2009).

  3. Previous researchers have found that self-protective action is a family-level decision, and the whole household usually acts as one respondent (Ekberg et al. 2009; Vaughan and Tinker 2009). Here we assumed that the proportion of households in Arizona taking avoidance actions might be equivalent to the proportion of (susceptible) people taking avoidance actions.

  4. The modified model has one stochastic variable, the avoidance behavior effect. We run the model 20 and 100 times separately for each scenario shown in Figs. 3, 4 and 5. The results for 100 runs are very similar to those from 20 runs. In each scenario shown in Fig. 3, for example, the results from 20 and 100 runs are not much different, and the curve of cumulative morbidity (Fig. 4) produced from 100 runs is almost identical to that from 20 runs. In this paper we report the simulation results from 20 runs.

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Acknowledgements

This study was funded by the Arizona Department of Health Services (ADHS) through a Health and Human Services (HHS) preparedness grant, Arizona State University College of Public Program’s research seed grant, and the National Research Foundation of Korea Grant (NRF-2010-330-B00262). The authors thank Diane Reed and Andrew Lawless at ADHS, and Ken Anderson at Maricopa County Research & Reporting. We also thank Deborah Schumacher, Tanida Rojchanakasetchai, Barrie Bradley and Tim Lant, who helped conduct this research.

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  1. School of Public Administration and Policy, Renmin University of China, No. 59 Zhongguancun Street, Haidian District, Beijing, 100872, China

    Wei Zhong

  2. School of Public Affairs, Arizona State University, 411 N. Central Ave., Phoenix, AZ, 85004, USA

    Yushim Kim

  3. School of Human Evolution and Social Change, Arizona State University, P.O. Box 872402, Tempe, AZ, 85287, USA

    Megan Jehn

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Zhong, W., Kim, Y. & Jehn, M. Modeling dynamics of an influenza pandemic with heterogeneous coping behaviors: case study of a 2009 H1N1 outbreak in Arizona. Comput Math Organ Theory 19, 622–645 (2013). https://doi.org/10.1007/s10588-012-9146-6

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