Discussion

Our ABM confirmed the importance of HH compliance for all patients regardless of their infectious status (ie, standard precautions). This result is consistent with the literature.^{Reference Barnes, Morgan, Harris, Carling and Thom13,Reference Triola and Holzman15,Reference Austin, Bonten, Weinstein, Slaughter and Anderson24,Reference D’Agata, Horn and Webb25,Reference Cooper, Medley and Scott27,Reference D’Agata, Webb and Horn28} In our 50-repetition model, an 80% HH compliance rate prevented secondary cases in half of our simulations (44% of cases in the 1,000-simulation model). This scenario was the most effective of all our simulated experiments. However, our experience in the field tells us that this compliance is not currently achieved in most departments. A more realistic, albeit still elevated rate, namely that at 60%, showed interesting results, with a median cumulative number of cases at 1 year of 17 VRE patients for all 3 units (43 beds). This result is consistent with that of the ABM reported by Triola and Holzman,^{Reference Triola and Holzman15} who showed that this rate was sufficient to avoid an epidemic in an ICU. However, the compliance rates most often reported in the literature rarely exceed 50%.^{Reference Temime, Opatowski, Pannet, Brun-Buisson, Boëlle and Guillemot12,Reference Austin, Bonten, Weinstein, Slaughter and Anderson24,Reference D’Agata, Horn and Webb25,Reference D’Agata, Webb and Horn28-Reference Eveillard, Hitoto and Raymond34} In this setting, VRE dissemination does not appear to be under control according to our simulations, which are in agreement with the results of the deterministic model of Austin et al.^{Reference Austin, Bonten, Weinstein, Slaughter and Anderson24} A significant decrease in the number of VRE cases was highlighted between 40% HH compliance and 60% HH compliance, in keeping with the results reported in the literature.^{Reference Triola and Holzman15,Reference D’Agata, Horn and Webb25,Reference D’Agata, Webb and Horn28}

In our calculations of HH compliance, we considered the performance of HH before and after a care intervention, while also taking into account its effectiveness. These 2 concepts were not differentiated given that the ultimate measure was contamination or not of the hands in a cross-transmission context.

The second simulated IPC bundle was contact precautions for the management of VRE carriers. With HH compliance rates of 40% or 50% for noncarriers, and higher rates of 70% and 80% for VRE patients, the number of cases decreased significantly in our simulations. Despite this decrease, an HH compliance rate of 70% for carriers and 50% for noncarriers remained less effective than the overall 60% compliance rate for all. Comparison with the reported literature data is nonetheless complex because contact precautions are often not differentiated from standard precautions or other IPC measures.^{Reference Austin, Bonten, Weinstein, Slaughter and Anderson24,Reference Yahdi, Abdelmageed, Lowden and Tannenbaum35}

In the present study, we simulated contact precautions by simply increasing the rate of HH compliance for VRE carriers. This choice was made given that caregiver hands were the only vector of VRE transmission. However, this increasing rate of HH compliance (so a decrease risk of transmission) could simulated other precautions belong to contact precautions, such as clothing protection.

Another means to limit the spread of VRE is the cohorting of VRE patients within the same unit without a dedicated team and hospitalized with non-VRE patients. Notably, this measure can be applied when the establishment of a dedicated team or isolation unit is not possible, due to a lack of human and/or logistical resources. This measure allows providers to limit the number of VRE-exposed patients and caregivers. In 2005, Hotchkiss et al^{Reference Hotchkiss, Strike, Simonson, Broccard and Crooke11} tested this scenario in ICUs and showed its effectiveness, although the approach had limits at high transmission rates and when all caregiver categories were not dedicated to the cohorted patients.^{Reference Hotchkiss, Strike, Simonson, Broccard and Crooke11} Our simulations also showed a moderate effect in this setting. The higher the HH compliance, the less the effect of cohorting. In addition, our results showed that the threshold above which the cohorting is implemented and lifted influenced its effectiveness. Waiting for the presence of 10 VRE carriers in a 43-bed department before implementing cohorting represented a threshold too high unless the cohorting remained in place in the long term.

Finally, we simulated the creation of an isolation unit dedicated to VRE carriers, supported by dedicated staff. This measure is rarely assessed in the modeling of VRE transmission, whereas this measure is recommended when an outbreak is not under control, particularly in France.⁴ In our model, this technique showed its effectiveness although did not systematically prevent the spread ofVRE, most likely due to the presence of contagious patients outside of the isolation unit that had not yet been detected or treated in the ICU. Again, the threshold above which the isolation unit is implemented and stopped is a key element. With 50% HH compliance for all patients, the implementation of an isolation unit as soon as 1 case is present enables controlling the VRE spread. With a threshold of 10 cases, this approach is less effective.

These results should be interpreted while keeping in mind the hypotheses of the model. To prevent further complication of our model and to facilitate its interpretation, we considered that rooms were single rooms and caregivers’ hands was the only vector of VRE transmission. However, the environment (surfaces or medical devices) is also a known transmission vector.^{Reference Wolfensberger, Clack and Kuster2-Reference Rutala and Weber37} Some researchers have attempted to take the latter into account in various ways, although showing incongruent results.^{Reference Barnes, Morgan, Harris, Carling and Thom13,Reference Wolkewitz, Dettenkofer, Bertz, Schumacher and Huebner26,Reference McBryde and McElwain38} Additional models are thus needed to better understand the importance of this vector.

Furthermore, we considered that the HH compliance rates were identical for all caregivers as well as before and after patient contact. Studies show that compliance is higher after an intervention with the patient than before the intervention, and that it can vary depending on the type of caregiver, the type of care, or the time of day.^{Reference Pittet, Mourouga and Perneger30,Reference Erasmus, Daha and Brug32,Reference Eveillard, Hitoto and Raymond34} Taking these parameters into account in future models would certainly be valuable.

The probabilities of VRE transmission during treatment care are difficult to estimate. Data reported in the literature are highly variable^{Reference Wolfensberger, Clack and Kuster2,Reference Barnes, Morgan, Harris, Carling and Thom13,Reference Milazzo, Bown, Eberst, Phillips and Crawford16,Reference Austin, Bonten, Weinstein, Slaughter and Anderson24,Reference Pittet, Mourouga and Perneger30,Reference Perencevich, Fisman, Lipsitch, Harris, Morris and Smith39} ; hence, the reason we defined these probabilities as random variables following β distributions with large variances reflecting parameter uncertainty. These parameters are essential because they influence the number of cases generated, as shown by our sensitivity analyses. These analyses reflect the robustness of our model because the effectiveness of the IPC measures relative to each other was not influenced by the variation of these parameters.

In the present model, 50 simulations were performed for each scenario; however, we were unable to find a published reference indicating the number of required simulations. Our sensitivity analysis showed that increasing the number of simulations to 1,000, applied to certain scenarios, did not alter the results.

A strength of our model is our consideration of the delay between contamination and the detection of VRE carriage by screening (weekly screening in our simulations). During this delay, the patient is contagious but is not yet detected as a carrier; the patient is not eligible for contact precautions, cohorting, or an isolation unit, so VRE diffusion can easily occur if standard precautions are not properly applied. This further contributes to the importance of universal adherence to standard precautions. Hotchkiss et al^{Reference Hotchkiss, Strike, Simonson, Broccard and Crooke11} showed the importance of this delay by studying the time between a patient becoming contaminated and the removal of that patient from the ICU by transfer to an isolation unit, discharge, or death. This delay plays a key role in the risk of transmission although, in reality, such risk is not readily reducible.

A key feature of ABMs is that they are spatially explicit. A meta-analysis conducted in 2019 highlighted the lack of publications regarding transmission models of multidrug-resistant infectious agents that include spatial diffusion.^{Reference Niewiadomska, Jayabalasingham and Seidman40} To reproduce real-life situations as closely as possible, we differentiated the categories of caregivers as well as caregiver–patient ratios according to time of day. We also simulated patient flows between units with different lengths of stay, all with the aim of assessing the effect of the measures with minimal bias.

Finally, VRE transmission simulations were not different between several different wards, whereas interward diffusion can be a cause of an outbreak that is difficult to manage. Studies often involve 1 ward type, mostly ICUs. However, ICUs are different from conventional units, particularly in terms of the number of beds and the caregiver–patient ratio.

In conclusion, our ABM simulating the VRE transmission in several care units showed that although contact precautions, cohorting, and an isolation unit likely represent good complements to standard precautions, these may not be necessary in theory if proper hand hygiene is adhered to with a high level of compliance (≥70%).