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Analyzing the Epidemic Risk of SARS-CoV-2 Infection within Hospital Wards: A Sensor-Based Approach

Healthcare facilities, such as hospitals, are particularly susceptible to disease outbreaks. This vulnerability is heightened in the case of airborne diseases, such as COVID-19, where the rate of close contact between individuals substantially influences the infection risk. Consequently, understanding the patterns of close contacts in hospitals and applying that knowledge to anticipate epidemic risks and prioritize preventive steps can be crucial.

In a pioneering study published in Scientific Reports, epidemiologists used wearable sensors to collect data on close proximity interactions (CPIs) within hospital wards and thus, understand the epidemic risk of SARS-CoV-2 more accurately. The study, conducted over a 36-hour period across 15 wards in three hospitals during the first wave of the pandemic, engaged 2114 participants comprising healthcare workers, patients, and visitors.

Highly heterogenous contact behavior was observed across the wards, characterized by different patterns of interactions among individuals. Contact intensity among healthcare workers was consistently high across all wards, whereas patients showed variable contact patterns across different wards. The frequency and duration of contacts recorded through the wearable sensors enabled the researchers to construct a dynamic network of interaction patterns which helped in predicting the heightened risk of airborne pathogen spread within certain wards.

The risk attributed to a single index case varied significantly across the wards, ranging from 0.12 to 0.49 secondary infections per day. Emergency wards experienced relatively lower epidemic risk due to limited time spent by patients and visitors in these areas, whereas high rates of patient-to-patient transmission significantly increased the risk in geriatric wards. Interestingly, visitors, primarily in pediatric wards, also presented a heightened transmission risk.

Simulations were employed to assess the potential impact of targeting high-contact individuals for prevention. The most significant impact, a 20% reduction in epidemic risk, was observed when individuals with the highest cumulative contact hours were targeted, with the resources better pointed towards patients than healthcare workers.

This pioneering research not only elucidates the patterns of interactions within hospital wards during an epidemic but also highlights the importance of monitoring these patterns in formulating effective preventive measures. This study opens new doors for research into airborne nosocomial risk prevention and management, emphasizing the need to take into account the varying patterns across different hospital wards for devising effective infection prevention strategies.


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