The emergence and spread of antimicrobial-resistant bacteria (ARB) is one of the most serious public health threats. Patients admitted to healthcare institutions are the main reservoirs of ARB. It is estimated that 5-10% of patients develop an infection directly related to their hospitalization, resulting in over 90,000 deaths per year in the US. Approximately 70% of the causative pathogens implicated in these infections are resistant to one or more antimicrobials. Infections caused by ARB are associated with up to 5-times higher mortality rates than infections caused by antimicrobial-susceptible bacteria. To gain a complete understanding of the numerous interrelated variables that contribute to the spread of ARB, integration of individual-level and population-level data is necessary. Biological studies provide essential data to understand behavior at the single patient-level, but the spread of (ARB) requires an understanding of the complex transmission dynamics of ARB between patients and healthcare workers. The goal of this interdisciplinary proposal is to integrate individual-patient data with mathematical modeling to provide population-level analysis of the spread of ARB. Models will be created to characterize the superspreaders of ARB, the subgroup of patients responsible for the majority of ARB spread. Individual-level patient data will be obtained from an extensive integrated on-line medical record system of over one million hospitalized patients. Patient data of bacterial loads of ARB and its correlation with antibiotic exposure, the main risk factor for ARB spread, will be obtained from previous prospective clinical studies. Simulations of the models will be used to predict the effectiveness of preventative strategies. This proposal will enhance the partnership between medicine, public health and mathematics in both research and education. The results will be disseminated broadly through conferences, publications, undergraduate, graduate, and post-graduate education, medical students, nurses and physicians. The proposed work will lead to a better understanding of the factors which contribute to the spread of ARB, and will allow the development and implementation of effective public health policies. ? ? ?

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
5R01GM083607-02
Application #
7500273
Study Section
Special Emphasis Panel (ZGM1-CBCB-5 (BM))
Program Officer
Anderson, James J
Project Start
2007-09-21
Project End
2011-07-31
Budget Start
2008-08-01
Budget End
2009-07-31
Support Year
2
Fiscal Year
2008
Total Cost
$352,257
Indirect Cost
Name
University of Miami Coral Gables
Department
Biostatistics & Other Math Sci
Type
Schools of Arts and Sciences
DUNS #
625174149
City
Coral Gables
State
FL
Country
United States
Zip Code
33146
Chamchod, Farida; Ruan, Shigui (2012) Modeling methicillin-resistant Staphylococcus aureus in hospitals: transmission dynamics, antibiotic usage and its history. Theor Biol Med Model 9:25
D'Agata, Erika M C; Horn, Mary Ann; Ruan, Shigui et al. (2012) Efficacy of infection control interventions in reducing the spread of multidrug-resistant organisms in the hospital setting. PLoS One 7:e30170
Chamchod, Farida; Ruan, Shigui (2012) Modeling the spread of methicillin-resistant Staphylococcus aureus in nursing homes for elderly. PLoS One 7:e29757
Zhao, Guangyu; Ruan, Shigui (2011) Existence, Uniqueness and Asymptotic Stability of Time Periodic Traveling Waves for a Periodic Lotka-Volterra Competition System with Diffusion. J Math Pures Appl 96:627-671
Zou, Lan; Chen, Xingwu; Ruan, Shigui et al. (2011) Dynamics of a Model of Allelopathy and Bacteriocin with a Single Mutation. Nonlinear Anal Real World Appl 12:658-670
Wang, J; Wang, L; Magal, P et al. (2011) Modelling the transmission dynamics of meticillin-resistant Staphylococcus aureus in Beijing Tongren hospital. J Hosp Infect 79:302-8
Sun, Hong-Rui; Lu, Xinxin; Ruan, Shigui (2010) Qualitative analysis of models with different treatment protocols to prevent antibiotic resistance. Math Biosci 227:56-67
D'Agata, E M C; Webb, G F; Pressley, J (2010) Rapid Emergence of Co-colonization with Community-acquired and Hospital-Acquired Methicillin-Resistant Staphylococcus aureus Strains in the Hospital Setting. Math Model Nat Phenom 5:76-73
Webb, Glenn F; Horn, Mary Ann; D'Agata, Erika M C et al. (2010) Competition of hospital-acquired and community-acquired methicillin-resistant Staphylococcus aureus strains in hospitals. J Biol Dyn 4:115-29
Pressley, Joanna; D'Agata, Erika M C; Webb, Glenn F (2010) The effect of co-colonization with community-acquired and hospital-acquired methicillin-resistant Staphylococcus aureus strains on competitive exclusion. J Theor Biol 264:645-56

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