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Table 1 Summary of key model specifications of reviewed models

From: A systematic review of transmission dynamic studies of methicillin-resistant Staphylococcus aureus in non-hospital residential facilities

Settings

Nursing Homes

Articles

Chamchod et al. (2012) [22]

Batina et al. (2016a) [23]

Batina et al. (2016b) [24]

Aims

1. Study MRSA dissemination

2. Study persistence and prevalence of MRSA

3. Study intervention controls

1. Assess MRSA epidemic potential

2. Determine conditions at which USA300 and non-USA300 could be eliminated or reduced

3. Evaluate the impact of recent antibiotics exposure on MRSA prevalence and Ro

1. Predict long-term prevalence of USA300 and non-USA300

2. Assess the influence of potential risk factors on MRSA acquisition rates and average duration of colonization

Country (model inference)

Non-specific a

Wisconsin, United States

Wisconsin, United States

Model

 Typeb

Compartmental (deterministic);

Markov process (stochastic)

Compartmental (deterministic)

Markov process (stochastic)

Markov chain model

 Forecast period

1200/2000/4000 days

20 years to 30 years

120 months

Disease progression

 Host

Residents

Residents

Residents

 Vector

HCWs

Not applicable

Not applicable

 States involved among hosts

Susceptible, Colonized

Susceptible, Colonized

Susceptible, Colonized

 States involved among vectors

Decontaminated, contaminated

Not applicable

Not applicable

 MRSA Strains involved

MRSA as a whole

USA300, non-USA300

USA300, non-USA300

 Stratified by hosts’ recent antibiotics exposure

No

Yes

Yes

Transmission pathways

 Endogenous

  Residents to Residents

Yes

Yes

Not applicable d

  Residents to HCWs

Yes c

No

Not applicable d

  HCWs to Residents

Yes c

No

Not applicable d

  HCWs to HCWs

No c

No

Not applicable d

 Exogenous

  Importation of colonized cases

Yes

Yes

Not applicable d

Settings

Correctional facilities

Articles

Hartley et al. (2006) [27]

Kajita et al. (2007) [25]

Beauparlant et al. (2016) [26] g

Aims

1. Calculate the epidemiological weighte of an institution / subpopulation

1. Assess outbreak severity

2. Determine the conditions and consequences of outbreaks

3. Design interventions to control outbreaks

1. Determine effect of community dynamics on MRSA dynamics in prisons

2. Determine the effect of recidivisms on disease dynamics

Country (model inference)

Non-specific f

Los Angeles, United States

United States

Model

 Typeb

Mathematical formula

Compartmental (deterministic, stochastic)

Compartmental (deterministic)

 Forecast period

Not applicable

9 months

1000 days

Disease progression

 Host

Inmates

Inmates

Community, Inmates, Recidivists

 States involved among hosts

Colonized, Non-colonized

Susceptible, Colonized, Infected

Susceptible, Infected

 Strains involved

MRSA as a whole

CA-MRSA

MRSA as a whole

 Stratified by hosts’ recent antibiotics exposure

No

No

No

Transmission pathways

 Endogenous

  Inmates to Inmates

Not applicable

Yes h

Yes h,i

  Inmates to Staff

Not applicable

No

No

  Staff to Inmates

Not applicable

No

No

 Exogenous

  Importation of colonized cases

Not applicable

Yes

Yesj

Settings

Inter-facilities

Articles

Barnes et al. (2011) [28]

Lesosky et al. (2011) [31]

Lee et al. (2013a) [29]

Lee et al. (2013b) [30]

Aims

1. Predict long-term prevalence of facilities

2. Assess the effects of facility size, patient turnover and decolonization on MRSA prevalence

1. Determine how patient transfers affect MRSA transmission among patients in hospitals and NHs

[29]:

1. Quantify how MRSA prevalence in NHs affect those in hospitals

[30]: 1. Compare different contact intervention strategies (no intervention VS only clinically apparent MRSA infections VS all MRSA carriers)

Country (model inference)

Non-specific f

Non-specific k

California, United States

Model

 Typeb

Hybrid simulation model l

Stochastic, discrete time Monte Carlo simulation model

Agent-based model

 Forecast period

Not explicitly stated

365 days

[29]: 5 years after outbreak

[30]: 5 years after outbreak implementing contact precautions

 Facility involved

Hospitals, General LTCFs

Teaching hospitals (THs)m,

Non-teaching hospitals (NTHs)m, NHs

Hospitals, NHs

 Agent unit

Facility

Individual

Individual

Disease progression

 States involved

Susceptible, Persistently colonized, Colonized

Susceptible, Colonized/Infected

Susceptible, Colonized

 Strains involved

MRSA as a whole

MRSA as a whole

MRSA as a whole

Transmission pathways

Intra-facility

 Hospitals

  Patients to patients

Yes

Yes

Yes

  Patients to HCWs

No

No

No

  HCWs to HCWs

No

No

No

  HCWs to patients

No

No

No

 NHs/LTCFs

  Residents to residents

Yes

Yes

Yes

  Residents to HCWs

No

No

No

  HCWs to HCWs

No

No

No

  HCWs to residents

No

No

No

Inter- facility (patient sharing)

 Hospitals to Hospitals

No

Yes

Yes

 LTCFs/NHs to LTCFs/NHs

No

No

Yes

 Hospitals to LTCFs/NHs

Yes

Yes

Yes

 LTCFs/NHs to Hospitals

Yes

Yesn

Yesn

  1. Remarks
  2. a The study model was parameterized with data from the Norway, Ireland, France, Italy, and United States
  3. b The choice of continuous time versus discrete time model is not generally important for these systems, because the number of individuals is small and allows the efficient simulation of both model types. In general, equation-based compartment models (CMs) and agent-based models (ABMs) produce similar, but not exact, results [77, 78]. CMs are easier to implement than AMBs, but they rely on parsimony assumptions for objects in the same compartment; whereas ABMs can feature the heterogeneity characteristics down to an individual level
  4. c HCWs were either contaminated or decontaminated but not MRSA carriers
  5. d Pathway was not explicitly stated in this model, the probability of individual MRSA colonization state at time t had reflected the present amount of colonized in the facilities and individual current MRSA status. The current state at time t was assumed to be only dependent on their states at time t-1
  6. e Epidemiological weight indicates the level of release of newly colonized individuals into the community from the facility at an average daily rate
  7. f The study model was parameterized with data from the United States
  8. g This article was retrieved from Google search engine. The other 9 articles were retrieved from PUBMED
  9. h No classification over direct (social mixing) and indirect (sharing towels and personal items) transmission pathways
  10. i Include both inmates and recidivists
  11. j There were imported cases into the prisons from community. However, instead of presenting this importation as admission probability, the authors integrated the overall disease dynamics in the community and among recidivists, and allowed flows between individuals of the same disease states, regardless of subpopulation
  12. k The study model was parameterized with data from Canada
  13. l Each facility was treated an agent, while the disease progression within a facility was featured by a compartmental model
  14. m Lesosky divided hospitals into 2 types: teaching (bigger in size) and non-teaching (smaller in size)
  15. n It includes temporary hospital admission where beds in NH would be kept for the agent until his/her return [29, 30] or for 30 days [31]