Transmission dynamics for Methicilin-resistant Staphalococous areus with injection drug user


Abstract

Background: Methicillin-resistant Staphylococcus aureus (MRSA) is a bacterial pathogen resistance to antibiotics including methicillin. The resistance first emerged in 1960 in a healthcare setting only after two years of using methicillin as a viable treatment for methicillin-susceptible Staphylococcus aureus. MRSA leads to infections in different parts of the body including the skin, bloodstream, lungs, or the urinary tract.

Methods: A deterministic model for methicillin-resistant Staphylococcus aureus (MRSA) with injection drug users is designed. The model incorporates transmission of MRSA among non-injection drug users and injection drug users (IDUs) who are both low-and high-risk users. A reduced MRSA transmission model with only non-IDUs is fitted to a 2008-2013 MRSA data from the Agency for Healthcare and Research and Quality (AHRQ). The parameter estimates obtained are projected onto the parameters for the low-and high-risk IDUs subgroups using risk factors obtained by constructing a risk assessment ethogram. Sensitivity analysis is carried out to determine parameters with the greatest impact on the reproduction number using the reduced non-IDUs model. Change in risk associated behaviors was studied using the full MRSA transmission model via the increase in risky behaviors and enrollment into rehabilitation programs or clean needle exchange programs. Three control effectiveness levels determined from the sensitivity analysis were used to study control of disease translation within the subgroups.

Results: The sensitivity analysis indicates that the transmission probability and recovery rates within the subgroup have the highest impact on the reproduction number of the reduced non-IDU model. Change in risk associated behaviors from non-IDUs to low-and high-risk IDUs lead to more MRSA cases among the subgroups. However, when more IDUs enroll into rehabilitation programs or clean needle exchange programs, there was a reduction in the number of MRSA cases in the community. Furthermore, MRSA burden within the subgroups can effectively be curtailed in the community by implementing moderate- and high-effectiveness control strategies.

Conclusions: MRSA burden can be curtailed among and within non-injection drug users and both low-and high-risk injection drug users by encouraging positive change in behaviors and by moderate- and high-effectiveness control strategies that effectively targets the transmission probability and recovery rates within the subgroups in the community.

Keywords: Control strategies; Injection drug users; Methicillin-resistant; Risk factors; Sensitivity analysis.

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Figures

Fig. 1
Fig. 1
Flow diagram of the MRSA model (1) with IDUs
Fig. 2
Fig. 2
Demographic data from three regional areas, large metro, large suburb, and rural. Red dots represent large metro areas, magenta correspond to the large suburb areas and turquoises blue represent the data for rural areas
Fig. 3
Fig. 3
Simulation of the non-IDUs reduced MRSA model (5) fitted to the ICD-9 MRSA data for: (a) Large metro area data and model simulation; (b) Large suburbs area data and model simulation; (c) Rural area data and model simulation. Turquoise solid lines represent model simulations, red dot in (a) represent large metro area data, magenta dot in (b) is the data for large suburb area and the black dot in (c) is the data for rural area
Fig. 4
Fig. 4
Simulation of the MRSA model (1) with varied risk factors εL and εH values. a Infected individuals with 6% lrf and 42% hrf. b Infected individuals with 21% lrf and 66% hrf. c Infected individuals with 36% lrf and 90% hrf. Parameter values used are as given in Tables?6 and 7. Blue lines correspond to non-IDUs, green represent the low-risk IDUs and red represent the high-risk IDUs
Fig. 5
Fig. 5
Simulation of the MRSA model using regional data with 21% low-risk factor and 66% high-risk factor. a Infected individuals in suburb area. b Infected individuals in rural area. Parameter values used are as given in Tables?6 and 7. Blue lines correspond to non-IDUs, green represent the low-risk IDUs and red represent the high-risk IDUs
Fig. 6
Fig. 6
MRSA model simulation with large metro demographics. Each simulation shows a restriction of individuals transition between sub-groups with the parameter values ωN=0,ωL=0,αL=0,αH=0 (a) Colonized individuals, (b) Infected individuals. Parameter values used are as given in Tables?6 and 7. Blue lines correspond to non-IDUs, green represent the low-risk IDUs and red represent the high-risk IDUs
Fig. 7
Fig. 7
MRSA model simulation with large metro demographics. Each simulation shows a restriction of individuals transition between sub-groups with the parameter values ωN=0.05825,ωL=0.116,αL=0,αH=0 (a) Colonized individuals, (b) Infected individuals. Parameter values used are given in Tables?6 and 7. Blue lines correspond to non-IDUs, green represent the low-risk IDUs and red represent the high-risk IDUs
Fig. 8
Fig. 8
MRSA model simulation with large metro demographics. Each simulation shows a restriction of individuals transition between sub-groups with the parameter values ωN=0,ωL=0,αL=0.0112,αH=0.0560 (a) Colonized individuals, (b) Infected individuals. Parameter values used are as given in Tables?6 and 7. Blue lines correspond to non-IDUs, green represent the low-risk IDUs and red represent the high-risk IDUs
Fig. 9
Fig. 9
MRSA model simulation with large metro demographics. Each simulation shows a restriction of individuals transition between sub-groups with the parameter values ωN=0.05825,ωL=0.116,αL=0.0112,αH=0.0560 (a) Colonized individuals, (b) Infected individuals. Parameter values used are as given in Tables?6 and 7. Blue lines correspond to non-IDUs, green represent the low-risk IDUs and red represent the high-risk IDUs
Fig. 10
Fig. 10
Simulation of the MRSA model (1) with IDUs showing the various effectiveness control strategies for total number of infected in each of the different subgroups: a Non-IDUs; b Low-risk IDUs; c High-risk IDUs. Parameter values used are as given in Tables?6 and 7. Blue lines correspond to low-effectiveness strategy, turquoise blue represent moderate-effectiveness strategy and magenta represent the high-effectiveness strategy
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