Effectiveness of Timely Isolation of Patients with Respiratory Infection in a Children's Hospital: a Simulation Study

Relevance. Hospital-acquired acute respiratory viral infections (ARVI) are a significant cause of high morbidity in pediatric hospitals, especially in departments for small children. To control HCAI, there is still a need for evidence-based anti-epidemic and preventive measures. Mathematical modeling is known to be an attractive approach for objectively assessing infection control measures. In this study, we demonstrate effectiveness of timely isolation of the source of respiratory infection (i.e. an infected individuals) which might be revealed in a large pediatric hospital.
Materials & Methods. We developed an agent-based model of the spread of nosocomial respiratory infection to assess the effectiveness of timely isolation of patients with ARVI. Primary data on the incidence of ARVI, the number of beds, and the frequency of infection in a multidisciplinary non-infectious children's hospital at the regional level were used. The model also implements the ability of the agent to change the department. To simulate the anti-epidemic measure, we included in the developed simulation model the execution of a local algorithm of actions by a doctor in the event of detection of a patient with ARVI (50% probability of non-compliance with isolation; almost all sources of infection are isolated; 100% decision-making, the ideal option).
Results. The maximum absolute daily increase in ARVI cases were observed in scenarios where the rules for isolating the source of infection were violated; here the median equaled 32.9 (IQR 32.4-33.4) cases, ranging from 4.0 to 34.8 cases. With an increase in the probability of isolating a patient with ARVI, the indicator decreased: with a 50% probability of isolating the source, the median was 5.7 (5-6.5); 90% probability – 3.1 (2.8-3.6); 100% probability – 2.9 (2.6-3.4) cases. According to model estimates, when comparing the departments over time, we noted their unequal involvement in the epidemic process and wave-like spread of infection. Statistically significant differences in the predicted number of ARVI cases with different probabilities of isolation were revealed.
Conclusion. We used a simulation agent-based approach to modeling nosocomial ARVI. This allowed us to correctly describe the spread of infection among patients in a children's hospital, as well as to assess the effectiveness of timely isolation of the source of infection. In our model, we took into account various options for the interaction of agents with each other. In addition, we fit importations of the infection and studied how they could facilitate the spread of the infection. The solid evidence was obtained of the effectiveness of timely isolation of the source of infection identified in healthcare settings, which can be used to justify control measures.

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