A mathematical model of effects of environmental contamination and presence of volunteers on hospital infections in China.

Deterministic and stochastic mathematical models were formulated to investigate the roles that environmental contamination and the presence of volunteers played in the dynamics of hospital infections in China. Semi-stochastic simulation was used to estimate some of the parameters by fitting the observed data and investigating the impacts of interventions such as cleaning, hand hygiene and isolation of admitted MRSA (Methicillin-resistant Staphylococcus aureus) patients on mean prevalence of infection. The basic reproduction number was estimated to be 0.9753. Numerical simulations show that environmental contamination is a threat to hospital infection and free-living bacteria in the environment can promote transmission and initiate infection even if an infection has died out among HCWs (health-care workers) and patients. Sensitivity analysis indicates that a contaminated environment and volunteers contribute substantially to MRSA transmission in hospital infections, and hence effective control measures should be targeted. Hand hygiene of volunteers and cleaning are more effective in reducing the mean prevalence of colonized patients than isolation of newly admitted MRSA-positive patients and hand hygiene of HCWs. Hence volunteers, a cadre of semi-professional nurses, are beneficial to both disease control and supplementary treatment of HCWs if they are well trained. However, isolation of newly admitted MRSA-positive patients could be influential and dominant in reducing the prevalence of infection when the environment within a ward is sufficiently clean.

[1]  Sylvie Chevret,et al.  Modeling the spread of resistant nosocomial pathogens in an intensive-care unit. , 1997 .

[2]  J A P Heesterbeek,et al.  The type-reproduction number T in models for infectious disease control. , 2007, Mathematical biosciences.

[3]  B. Reboussin,et al.  Dispersal of Staphylococcus aureus Into the Air Associated With a Rhinovirus Infection , 2005, Infection Control & Hospital Epidemiology.

[4]  A. Pettitt,et al.  A stochastic mathematical model of methicillin resistant Staphylococcus aureus transmission in an intensive care unit: predicting the impact of interventions. , 2007, Journal of theoretical biology.

[5]  Xiao-Qiang Zhao,et al.  An epidemic model in a patchy environment. , 2004, Mathematical biosciences.

[6]  John M Boyce,et al.  Environmental contamination makes an important contribution to hospital infection. , 2007, The Journal of hospital infection.

[7]  J. Boyce,et al.  Environmental Contamination Due to Methicillin-Resistant Staphylococcus aureus Possible Infection Control Implications , 1997, Infection Control & Hospital Epidemiology.

[8]  D. Austin,et al.  Risk factors for the transmission of methicillin-resistant Staphylococcus aureus in an adult intensive care unit: fitting a model to the data. , 2002, The Journal of infectious diseases.

[9]  S. Dancer,et al.  Importance of the environment in meticillin-resistant Staphylococcus aureus acquisition: the case for hospital cleaning. , 2008, The Lancet. Infectious diseases.

[10]  S. Dancer,et al.  The role of environmental cleaning in the control of hospital-acquired infection. , 2009, The Journal of hospital infection.

[11]  G. Webb,et al.  A mathematical model quantifying the impact of antibiotic exposure and other interventions on the endemic prevalence of vancomycin-resistant enterococci. , 2005, The Journal of infectious diseases.

[12]  R. Bowers,et al.  A semi-stochastic model for Salmonella infection in a multi-group herd. , 2006, Mathematical biosciences.

[13]  M. Begon,et al.  A semi-stochastic model of the transmission of Escherichia coli O157 in a typical UK dairy herd: dynamics, sensitivity analysis and intervention/prevention strategies. , 2006, Journal of theoretical biology.

[14]  M.J.W. Jansen,et al.  Review of Saltelli, A. & Chan, K. & E.M.Scott (Eds) (2000), Sensitivity analysis. Wiley (2000) , 2001 .

[15]  B. Cooper,et al.  Preliminary analysis of the transmission dynamics of nosocomial infections: stochastic and management effects. , 1999, The Journal of hospital infection.

[16]  Damian Clancy,et al.  A stochastic SIS infection model incorporating indirect transmission , 2005 .

[17]  J. Watmough,et al.  Reproduction numbers and sub-threshold endemic equilibria for compartmental models of disease transmission. , 2002, Mathematical biosciences.

[18]  A J Valleron,et al.  A computer simulation model for the spread of nosocomial infections caused by multidrug-resistant pathogens. , 1997, Computers and biomedical research, an international journal.

[19]  M. G. Roberts,et al.  A new method for estimating the effort required to control an infectious disease , 2003, Proceedings of the Royal Society of London. Series B: Biological Sciences.

[20]  R. Anderson,et al.  Vancomycin-resistant enterococci in intensive-care hospital settings: transmission dynamics, persistence, and the impact of infection control programs. , 1999, Proceedings of the National Academy of Sciences of the United States of America.

[21]  W A Rutala,et al.  Role of Environmental Contamination in the Transmission of Vancomycin-Resistant Enterococci , 1997, Infection Control & Hospital Epidemiology.

[22]  D. Kirschner,et al.  A methodology for performing global uncertainty and sensitivity analysis in systems biology. , 2008, Journal of theoretical biology.

[23]  M. Loeb,et al.  Modeling Transmission of Methicillin-Resistant Staphylococcus Aureus Among Patients Admitted to a Hospital , 2005, Infection Control & Hospital Epidemiology.

[24]  A. Rampling,et al.  Evidence that hospital hygiene is important in the control of methicillin-resistant Staphylococcus aureus. , 2001, The Journal of hospital infection.

[25]  R. Bowers,et al.  Understanding the dynamics of Salmonella infections in dairy herds: a modelling approach. , 2005, Journal of theoretical biology.