Hospital-level work organization drives the spread of SARS-CoV-2 within hospitals: insights from a multi-ward model
This article has been Reviewed by the following groups
Listed in
- Evaluated articles (ScreenIT)
Abstract
extensive protective measures, SARS-CoV-2 widely circulates within healthcare facilities, posing a significant risk to both patients and healthcare workers. Several control strategies have been proposed; however, the global efficacy of local measures implemented at the ward level may depend on hospital-level organizational factors. We aimed at better understanding the role of between-ward interactions on nosocomial outbreaks and their control in a multiward psychiatric hospital in Western France. We built a stochastic compartmental transmission model of SARS-CoV-2 in the 24-wards hospital, accounting for the various infection states among patients and staff, and between-ward connections resulting from staff sharing. We first evaluated the potential of hospital-wide diffusion of local outbreaks, depending on the ward they started in. We then assessed control strategies, including a screening area upon patient admission, an isolation ward for COVID-19 positive patients and changes in staff schedules to limit between-ward mixing. Much larger and more frequent outbreaks occurred when the index case originated in one of the most connected wards with up to four times more transmissions when compared to the more isolated ones. The number of wards where infection spreads was brought down by up to 53 % after reducing staff sharing. Finally, we found that setting up an isolation ward reduced the number of transmissions by up to 70 %, while adding a screening area before admission seemed ineffective.
Hospital acquired COVID-19 poses a major problem to many countries. Despite extensive protective measures, transmission within hospitals still occurs regularly and threatens those essential to the fight against the pandemic while putting patients at risk. Using a stochastic compartmental model, we simulate the spread of SARS-CoV-2 in a multi-ward hospital, assessing the effect of different scenarios and infection control strategies. The novelty of our method resides in the consideration of staff sharing data to better reflect the field reality. Our results highlight the poor efficiency of implementing a screening area before hospital admission, while the setting up of an isolation ward dedicated to COVID-19 patients and the restriction of healthcare workers movements between wards significantly reduce epidemic spread.
Article activity feed
-
SciScore for 10.1101/2021.09.09.21262609: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:In order to keep the model as generic and as simple as possible in a context of limited data, we made several assumptions and limitations that should be highlighted. First, we assumed homogeneous mixing within the HCW and patient populations. Regarding HCWs, the risks of exposure are most probably profession-dependent. Similarly, small …
SciScore for 10.1101/2021.09.09.21262609: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:In order to keep the model as generic and as simple as possible in a context of limited data, we made several assumptions and limitations that should be highlighted. First, we assumed homogeneous mixing within the HCW and patient populations. Regarding HCWs, the risks of exposure are most probably profession-dependent. Similarly, small clusters of contacts may exist within the patient population. The homogeneous mixing assumption may have led us to overestimate the risk of epidemic spread. Second, we estimated transmission rates using data from an outbreak observed in a specific ward and those estimates were then used to characterize all other wards. In doing so, we assumed the same contact patterns n all wards. Third, given that visits were strictly prohibited during the first pandemic wave, we did not account for contamination of patients and HCWs by visitors. In further analyses, this assumption should be relaxed to avoid underestimating the epidemic risk. Also, it would be of interest to account for vaccination in both patient and HCW populations in the model. Vaccine roll-out in LTCFs and hospitals surely plays an important role in further mitigating the spread of infection. Moreover, testing strategies based on network structure could be designed so as to make better use of testing resources in the hospital setting. Following the end of the first lockdown on 11 May 2020, the hospital has been implementing contact tracing to break chains of transmission. Resulting contac...
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We found bar graphs of continuous data. We recommend replacing bar graphs with more informative graphics, as many different datasets can lead to the same bar graph. The actual data may suggest different conclusions from the summary statistics. For more information, please see Weissgerber et al (2015).
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
Results from scite Reference Check: We found no unreliable references.
-
