Using contact network dynamics to implement efficient interventions against pathogen spread in hospital settings

Long-term care facilities (LTCF) are hotspots for pathogen transmission. Infection control interventions are essential, but the high density and heterogeneity of inter-individual contacts within LTCF may hinder their efficacy. Here, we explore how the patient-staff contact structure may inform effective intervention implementation. Using an individual-based model, we reproduced methicillin-resistant Staphylococcus aureus colonisation dynamics over a detailed contact network recorded within an LTCF, and examined the potential impact of three types of interventions against transmission (reallocation reducing the number of unique contacts per staff, reinforced contact precautions, and vaccination protecting against acquisition), targeted towards specific populations. All three interventions were effective when applied to all nurses or healthcare assistants (median reduction in MRSA colonisation incidence up to 21%), but the benefit did not exceed 8% when targeting any other single staff category. We identified “supercontactor” individuals with most contacts (“frequency-based”, overrepresented amongst nurses, porters and rehabilitation staff) or with the longest cumulative time spent in contact (“duration-based”, overrepresented amongst healthcare assistants and geriatric and persistent-vegetative-state patients). Targeting supercontactors enhanced interventions against pathogen spread in the LTCF. With contact precautions, targeting frequency-based staff supercontactors led to the highest incidence reduction (13%). Vaccinating duration-based patient supercontactors led to a higher reduction (22%) than all other approaches. Targeting supercontactors remained the most effective strategy when varying epidemiological parameters, indicating this approach can be broadly applied to prevent transmission of other nosocomial pathogens. Importantly, both staff and patients may be supercontactors, highlighting the importance of including patients in measures to prevent pathogen transmission in LTCF. Classification: Biological Sciences, Biophysics and Computational Biology Significance statement Pathogen transmission is a challenge in long-term care facilities (LTCF) due to frequent and heterogeneous contacts of staff and patients. By characterising this contact structure and understanding the categories of staff and patients more likely to be “supercontactors”, with either more or longer contacts than others, we can implement more efficient interventions against pathogen spread. We illustrate this using a mathematical model to reproduce transmission of methicillin-resistant Staphylococcus aureus across a detailed contact network recorded in a LTCF. We show how the most efficient implementation strategy depends on the intervention (reallocation, contact precautions, vaccination) and target population (staff, patients, supercontactors). By varying epidemiological parameters, we demonstrate that these results are broadly applicable to prevent transmission of other nosocomial pathogens. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This project has received funding from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No 101034420 (PrIMAVeRa). This Joint Undertaking receives support from the European Union's Horizon 2020 research and innovation programme and EFPIA. This communication reflects the authors' view and that neither IMI nor the European Union, EFPIA, or any Associated Partners are responsible for any use that may be made of the information contained therein. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes Model results and analysis scripts are available online at