Objectives: The prevalence of Clostridioides difficile infection (CDI) has been shown to vary markedly between European countries, both in hospitals and in the community. Determining the true prevalence has proven challenging. Without systematic testing in hospitals, the unchecked transmission of CDI can lead to large outbreaks in more susceptible cohorts. We investigate the success of CDI surveillance and control measures across Europe, by examining the dynamics of disease spread from the community into a hospital setting. We focus on national differences, such as variability in testing and sampling, disease prevalence in communities and hospitals, and antimicrobial usage.
Methods: We developed a stochastic, compartmental, dynamic mathematical model parameterized using sampling and testing rate data from COMBACTE-CDI, a multicountry study in which all diarrhoeal stool samples (N = 3163) from European laboratories were tested for CDI, and data for antimicrobial usage and incidence of hospital cases sourced from the European Centre for Disease Prevention and Control.
Results: The framework estimates the prevalence of CDI among hospital patients across European countries and explores how national differences impact the dynamics, transmission, and relative incidence of CDI within the hospital setting. The model illustrates the mechanisms influencing these national differences, namely, antimicrobial usage rates, national sampling and testing rates, and community prevalence of CDI.
Discussion: Differential costs for testing and practicalities of scaling up testing mean every country needs to consider balancing CDI testing costs against the costs of treatment and care of patients with CDI.
Keywords: Clostridioides difficileinfection; Europe; Hospital infection; Mathematical model.
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