# An agent-based model to simulate the transmission dynamics of bloodborne pathogens within hospitals

## TL;DR

The paper introduces a new model to simulate how bloodborne viruses like hepatitis spread in hospitals, showing how resource levels and screening can affect infection risks.

## Contribution

The novel contribution is an agent-based SEI model for simulating bloodborne pathogen transmission in hospitals, validated with real-world data from Egypt and Ethiopia.

## Key findings

- The model shows low HCV transmission risk in high-resource hospitals but increased risk in low-resource settings due to device shortages.
- Systematic screening in high-risk wards can significantly reduce infection risks.
- The model was successfully applied to HBV transmission in an Ethiopian hospital, demonstrating its adaptability.

## Abstract

Mathematical models are powerful tools to analyze pathogen spread and assess control strategies in healthcare settings. Nevertheless, available models focus on nosocomial transmission through direct contact or aerosols rather than through blood, even though bloodborne pathogens remain a significant source of iatrogenic infectious risk. Herein, we propose an agent-based SEI (Susceptible-Exposed-Infected) model to reproduce the transmission of bloodborne pathogens dynamically within hospitals. This model simulates the dynamics of patients between hospital wards, from admission to discharge, as well as the dynamics of the devices used during at-risk invasive procedures, considering that patient contamination occurs after exposure to a contaminated device. We first illustrate the use of this model through a case study on hepatitis C virus (HCV) in Egypt. Model parameters, such as HCV upon-admission prevalence and transition probabilities between wards or ward-specific probabilities of undergoing different invasive procedures, are informed with data collected in Ain Shams University Hospital in Cairo. Our results suggest a low risk of HCV acquisition for patients hospitalized in this university hospital. However, we show that in a low-resource hospital, frequent device shortages could lead to increased risk. We also find that systematically screening patients in a few selected high-risk wards could significantly reduce this risk. We then further explore potential model applications through a second illustrative case study based on HBV nosocomial transmission in Ethiopia. In the future, this model could be used to predict the potential burden of emerging bloodborne pathogens and help implement effective control strategies in various hospital contexts.

Bloodborne pathogens (BBPs) such as HCV, HBV or HIV, are a major public health concern as they can lead to a variety of medical conditions, including cirrhosis and cancers with significant mortality and morbidity. If infection control measures are inadequate, transmission of such pathogens to patients can occur via contaminated devices during invasive procedures within healthcare settings. The aim of our work was to build a tool to help assess the potential for BBP transmission to patients using mathematical modelling. Using data collected in an Egyptian hospital we evaluated the risk of HCV infection for hospitalized patients in two different scenarios: the case of a high-resource setting and the one of a low-resource setting. We found that although the risk of infection in high-resource settings is low, frequent device shortages could lead to increased risk in low-resource settings. We also found that screening patients upon admission in the setting or in specific wards could lead to a significant risk reduction. Our model was further tested on nosocomial HBV transmission in an Ethiopian hospital. In the future, this model could be used to predict the potential burden of emerging BBPs.