Background: Care homes are vulnerable to widespread transmission of COVID-19 with poor outcomes for staff and residents. Infection control interventions in care homes need to not only be effective in containing the spread of COVID-19 but also feasible to implement in this special setting which is both a healthcare institution and a home. Methods: We developed an agent-based model that simulates the transmission dynamics of COVID-19 via contacts between individuals, including residents, staff members, and visitors in a care home setting. We explored a representative care home in Scotland in our base case and explore other care home setups in an uncertainty analysis. We evaluated the effectiveness of a range of intervention strategies in controlling the spread of COVID-19. Results: In the presence of the reference interventions that have been implemented in many care homes, including testing of new admissions, isolation of symptomatic residents, and restricted public visiting, routine testing of staff appears to be the most effective and practical approach. Routine testing of residents is no more effective as a reference strategy while routine testing of both staff and residents only shows a negligible additive effect. Modelling results are very sensitive to transmission probability per contact, but the qualitative finding is robust to varying parameter values in our uncertainty analysis. Conclusions: Our model predictions suggest that routine testing should target staff in care homes in conjunction with adherence to strict hand hygiene and using personal protective equipment to reduce risk of transmission per contact.

Background: This study examines the impact of visitation and cohorting policies as well as the care home population size upon the spread of COVID-19 and the risk of outbreak occurrence in this setting. Methods: Agent-based modelling Results: The likelihood of the presence of an outbreak in a care home is associated with the care home population size. Cohorting of residents and staff into smaller, self-contained units reduces the spread of COVID-19. Restricting the number of visitors to the care home to shield its residents does not significantly impact the cumulative number of infected residents and risk of outbreak occurrence in most scenarios. Only when the community prevalence where staff live is considerably lower than the prevalence where visitors live (the former prevalence is less than or equal to 30% of the latter), relaxing visitation increases predicted infections much more significantly than it does in other scenarios. Maintaining a low infection probability per resident-visitor contact helps reduce the effect of allowing more visitors into care homes. Conclusions: Our model predictions suggest that cohorting is effective in controlling the spread of COVID-19 in care homes. However, according to predictions shielding residents in care homes is not as effective as predicted in a number of studies that have modelled shielding of vulnerable population in the wider communities.

Background: Health care−associated infections (HAIs) are a global health burden because of their significant impact on patient health and health care systems. Mechanistic simulation modeling that captures the dynamics between patients, pathogens, and the environment is increasingly being used to improve understanding of epidemiological patterns of HAIs and to facilitate decisions on infection prevention and control (IPC). The purpose of this review is to present a systematic review to establish (1) how simulation models have been used to investigate HAIs and their mitigation and (2) how these models have evolved over time, as well as identify (3) gaps in their adoption and (4) useful directions for their future development. Methods: The review involved a systematic search and identification of studies using system dynamics, discrete event simulation, and agent-based model to study HAIs. Results: The complexity of simulation models developed for HAIs significantly increased but heavily concentrated on transmission dynamics of methicillin-resistant Staphylococcus aureus in the hospitals of highincome countries. Neither HAIs in other health care settings, the influence of contact networks within a health care facility, nor patient sharing and referring networks across health care settings were sufficiently understood.Conclusions: This systematic review provides a broader overview of existing simulation models in HAIs to identify the gaps and to direct and facilitate further development of appropriate models in this emerging field.

Although system dynamics [SD] and agent-based modelling [ABM] have individually served as effective tools to understand the Covid-19 dynamics, combining these methods in a hybrid simulation model can help address Covid-19 questions and study systems and settings that are difficult to study with a single approach. To examine the spread and outbreak of Covid-19 across multiple care homes via bank/agency staff and evaluate the effectiveness of interventions targeting this group, we develop an integrated hybrid simulation model combining the advantages of SD and ABM. We also demonstrate how we use several approaches adapted from both SD and ABM practices to build confidence in this model in response to the lack of systematic approaches to validate hybrid models. Our modelling results show that the risk of infection for residents in care homes using bank/agency staff was significantly higher than those not using bank/agency staff (Relative risk [RR] 2.65, 95% CI 2.57–2.72). Bank/agency staff working across several care homes had a higher risk of infection compared with permanent staff working in a single care home (RR 1.55, 95%CI 1.52–1.58). The RR of infection for residents is negatively correlated to bank/agency staff’s adherence to weekly PCR testing. Within a network of heterogeneous care homes, using bank/agency staff had the most impact on care homes with lower intra-facility transmission risks, higher staff-to-resident ratio, and smaller size. Forming bubbles of care homes had no or limited impact on the spread of Covid-19. This modelling study has implications for policy makers considering developing effective interventions targeting staff working across care homes during the ongoing and future pandemics.

Healthcare-Associated Infections (HAIs) are a major public health problem as they pose a serious risk for patients and providers, increasing morbidity, mortality, and length of stay as well as costs to patients and the health system. Prevention and control of HAIs has, therefore, become a priority for most healthcare systems. Systems simulation models have provided insights into the dynamics of HAIs and help to evaluate the effect of infection control interventions. However, as each systems simulation modeling method has strengths and limitations, combining these methods in hybrid models can offer a better tool to gain complementary views on, and deeper insights into, HAIs. Hybrid models can, therefore, assist decision-making at different levels of management, and provide a balance between simulation performance and result accuracy. This paper discusses these benefits in more depth but also highlights some challenges associated with the use of hybrid simulation models for modeling HAIs.