Hospital-acquired infections (HAIs) have long remained a key healthcare concern, affecting countless individuals worldwide, and posing significant challenges for health systems. The limitations of traditional disease control strategies are seen in their inability to effectively evaluate real-time spatial and behavior data within healthcare facilities. This article puts forward a unique method designed to address this issue, by harnessing the ‘contagion potential (CP)’ – a quantifiable measure of infection risk based on individual characteristics and behavior. The application of CP offers a proactive framework to reduce the incidence of HAIs.
Uniquely, CP considers not just infection susceptibility and transmissibility, but also factors in individuals’ movement and interaction patterns within a healthcare facility. The proposed model focuses on minimizing mobility-driven and contact-mediated HAIs, and effectively integrates approximate location data, thus charting the infection risk landscape without the need for exact tracking. A considerable part of this dynamic framework rests on constant learning; with CP parameters being inferred and fine-tuned over time, accurate infection risk assessments at the individual and unit levels become possible.
What’s more, introducing CP-based optimization opens up opportunities for improved patient-to-unit placements, striking a balance between reducing contagion spread and addressing healthcare’s clinical and logistical needs. Validation of the framework’s effectiveness places reliance on experimental methods, applied to individual modules and integrated evaluations, where mobility trends simulate uniform and diversified mixing and social contact, while infection rates adhere to observed hospital trends.
The results indicate that the application of CP refines infection control efforts, streamlines healthcare resource distribution, and heightens patient safety standards. In summary, this data-driven, dynamic approach proposes an effective strategy to tackle the endemic issue of HAIs, leading to enahnced healthcare atmospheres and improved patient outcomes.
This open-access research article led by Satyaki Roy at the University of Alabama holds promise for infectious disease control strategies, designed under the terms of the Creative Commons Attribution License (CC BY).
Source: https://www.frontiersin.org/journals/public-health/articles/10.3389/fpubh.2025.1566854/full