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A Data-Driven Mathematical Model of CA-MRSA Transmission among Age Groups: Evaluating the Effect of Control Interventions

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  • Xiaoxia Wang
  • Sarada Panchanathan
  • Gerardo Chowell

Abstract

Community associated methicillin-resistant Staphylococcus aureus (CA-MRSA) has become a major cause of skin and soft tissue infections (SSTIs) in the US. We developed an age-structured compartmental model to study the spread of CA-MRSA at the population level and assess the effect of control intervention strategies. We used Monte-Carlo Markov Chain (MCMC) techniques to parameterize our model using monthly time series data on SSTIs incidence in children (≤19 years) during January 2004 -December 2006 in Maricopa County, Arizona. Our model-based forecast for the period January 2007–December 2008 also provided a good fit to data. We also carried out an uncertainty and sensitivity analysis on the control reproduction number, which we estimated at 1.3 (95% CI [1.2,1.4]) based on the model fit to data. Using our calibrated model, we evaluated the effect of typical intervention strategies namely reducing the contact rate of infected individuals owing to awareness of infection and decolonization strategies targeting symptomatic infected individuals on both and the long-term disease dynamics. We also evaluated the impact of hypothetical decolonization strategies targeting asymptomatic colonized individuals. We found that strategies focused on infected individuals were not capable of achieving disease control when implemented alone or in combination. In contrast, our results suggest that decolonization strategies targeting the pediatric population colonized with CA-MRSA have the potential of achieving disease elimination.Author Summary: Community associated methicillin-resistant Staphylococcus aureus (CA-MRSA) is a bacteria that causes skin infections in the US. We developed a mathematical model of CA-MRSA transmission among different age groups at the population level. We parameterized the model using monthly time series data on number of SSTIs in children during the period January 2004–December 2006 in Maricopa County, Arizona. Our model-based forecast to additional time series data covering the period 2007–2008 yielded a good fit to data. Using our calibrated model, we calculated that an infected individual generates on average 1.3 infected people in a totally susceptible population in the study area. We assessed the impact of intervention strategies including reductions in contact rates between infected and non-infected individuals and the effect of decolonization strategies aimed at infected individuals by drug treatment, and found that neither of the two strategies when implemented alone or in combination were able to control the disease. In contrast, we found that decolonization strategies targeting the pediatric population colonized with CA-MRSA have the potential of achieving disease elimination.

Suggested Citation

  • Xiaoxia Wang & Sarada Panchanathan & Gerardo Chowell, 2013. "A Data-Driven Mathematical Model of CA-MRSA Transmission among Age Groups: Evaluating the Effect of Control Interventions," PLOS Computational Biology, Public Library of Science, vol. 9(11), pages 1-13, November.
    • Handle: RePEc:plo:pcbi00:1003328
    DOI: 10.1371/journal.pcbi.1003328
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    References listed on IDEAS

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    1. Vanja M Dukic & Diane S Lauderdale & Jocelyn Wilder & Robert S Daum & Michael Z David, 2013. "Epidemics of Community-Associated Methicillin-Resistant Staphylococcus aureus in the United States: A Meta-Analysis," PLOS ONE, Public Library of Science, vol. 8(1), pages 1-9, January.
    2. Marjan W M Wassenberg & G Ardine de Wit & Ben A van Hout & Marc J M Bonten, 2010. "Quantifying Cost-Effectiveness of Controlling Nosocomial Spread of Antibiotic-Resistant Bacteria: The Case of MRSA," PLOS ONE, Public Library of Science, vol. 5(7), pages 1-7, July.
    3. Farida Chamchod & Shigui Ruan, 2012. "Modeling the Spread of Methicillin-Resistant Staphylococcus aureus in Nursing Homes for Elderly," PLOS ONE, Public Library of Science, vol. 7(1), pages 1-9, January.
    4. Joël Mossong & Niel Hens & Mark Jit & Philippe Beutels & Kari Auranen & Rafael Mikolajczyk & Marco Massari & Stefania Salmaso & Gianpaolo Scalia Tomba & Jacco Wallinga & Janneke Heijne & Malgorzata Sa, 2008. "Social Contacts and Mixing Patterns Relevant to the Spread of Infectious Diseases," PLOS Medicine, Public Library of Science, vol. 5(3), pages 1-1, March.
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