Analysis of social interactions and risk factors relevant to the spread of infectious diseases at hospitals and nursing homes

Abstract

Ensuring the safety of healthcare workers is vital to overcome the ongoing COVID-19 pandemic. We here present an analysis of the social interactions between the healthcare workers at hospitals and nursing homes. Using data from an automated hand hygiene system, we inferred social interactions between healthcare workers to identify transmission paths of infection in hospitals and nursing homes. A majority of social interactions occurred in medication rooms and kitchens emphasising that health-care workers should be especially aware of following the infection prevention guidelines in these places. Using epidemiology simulations of disease at the locations, we found no need to quarantine all healthcare workers at work with a contagious colleague. Only 14.1% and 24.2% of the health-care workers in the hospitals and nursing homes are potentially infected when we disregard hand sanitization and assume the disease is very infectious. Based on our simulations, we observe a 41% and 26% reduction in the number of infected healthcare workers at the hospital and nursing home, when we assume that hand sanitization reduces the spread by 20% from people to people and 99% from people to objects. The analysis and results presented here forms a basis for future research to explore the potential of a fully automated contact tracing systems.

Hospital vulnerability to spread of respiratory infections: close contact data collection and mathematical modelling

“…A limited number of studies have used wearable sensor technology to study CPIs in hospitals. Some have relied on sensors worn only by HCWs, interacting with each other (9) or with fixed-point sensors which interact with the sensors worn by HCWs (10,11). Before the COVID-19 pandemic, studies using sensors worn by patients and HCWs have been conducted in paediatrics (12), geriatry (13), acute care (14) and long-term care (15).…”

“…The average number of hours per 24 hour period during which individuals of type x were present in the ward, x H , was estimated by taking the average total time individuals of type x were present (\emph{i.e.} carrying the captor) and normalising to T , the total duration of the investigation in the ward (Equation [11]).…”

How have mathematical models contributed to understanding the transmission and control of SARS-CoV-2 in healthcare settings? A systematic search and review

“…Several models have quantified the relative burden of SARS-CoV-2 infection and transmission among patients and HCWs over the course of the pandemic. HCWs were identified as being at high risk of occupational exposure to infection, either from colleagues or patients [14][15][16]. During the first wave in early 2020, they have been estimated to be the most important source of onward nosocomial transmission, both to patients and other HCWs [17,18].…”

“…Several studies have found that, when available, PPE use is highly effective for reducing infection risk among both HCWs and patients. Although predicted reductions in infection risk naturally depend on assumptions underlying PPE's impact on viral transmissibility, which vary considerably across studies and for which data are sorely lacking, several studies suggest that widespread PPE use remains a key SARS-CoV-2 prevention strategy, even when conferring comparatively low levels of protection [15,29,37,[48][49][50]. By preventing infection, PPE use has also been shown to reduce HCW workplace absence [37] and workday loss [22].…”

“…Regarding different types of PPE that may be used, Hüttel et al [15] found hand sanitizer to be an effective means of reducing risk as a supplement to other strategies. Regarding timing, earlier introduction of PPE was found to allow a much more efficient response [22] and to enable prevention of large outbreaks [25].…”