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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.

Background Financial risk protection and equity are two fundamental components of the global commitment to achieve Universal Health Coverage (UHC), which mandates health system reform based on population needs, disease incidence, and economic burden to ensure that everyone has access to health services without any financial hardship. We estimated disease-specific incidences of catastrophic out-of-pocket health expenditure and distress financing to investigate progress toward UHC financial risk indicators and investigated inequalities in financial risk protection indicators by wealth quintiles. In addition, we explored the determinants of financial hardship indicators as a result of hospitalization costs. Methods In order to conduct this research, data were extracted from the latest Bangladesh Household Income and Expenditure Survey (HIES), conducted by the Bangladesh Bureau of Statistics in 2016–2017. Financial hardship indicators in UHC were measured by catastrophic health expenditure and distress financing (sale/mortgage, borrowing, and family support). Concentration curves (CC) and indices (CI) were estimated to measure the pattern and severity of inequalities across socio-economic classes. Binary logistic regression models were used to assess the determinants of catastrophic health expenditure and distress financing. Results We found that about 26% of households incurred catastrophic health expenditure (CHE) and 58% faced distress financing on hospitalization in Bangladesh. The highest incidence of CHE was for cancer (50%), followed by liver diseases (49.2%), and paralysis (43.6%). The financial hardship indicators in terms of CHE (CI = -0.109) and distress financing (CI = -0.087) were more concentrated among low-income households. Hospital admission to private health facilities, non-communicable diseases, and the presence of chronic patients in households significantly increases the likelihood of higher UHC financial hardship indicators. Conclusions The study findings strongly suggest the need for national-level social health security schemes with a particular focus on low-income households, since we identified greater inequalities between low- and high-income households in UHC financial hardship indicators. Regulating the private sector and implementing subsidized healthcare programmes for diseases with high treatment costs, such as cancer, heart disease, liver disease, and kidney disease are also expected to be effective to protect households from financial hardship. Finally, in order to reduce reliance on OOPE, the government should consider increasing its allocations to the health sector.

Background Community-based health insurance (CBHI) is a part of the health system in Bangladesh, and overcoming the obstacles of CBHI is a significant policy concern that has received little attention. The purpose of this study is to analyze the implementation barriers of voluntary CBHI schemes in Bangladesh and the strategies to overcome these barriers from the perspective of national stakeholders. Methods This study is exploratory qualitative research, specifically case study design, using key informant interviews to investigate the barriers of CBHI that are faced during the implementation. Using a topic guide, we conducted thirteen semi-structured in-depth interviews with key stakeholders directly involved in the CBHI implementation process. The data were analyzed using the Framework analysis method. Results The implementation of CBHI schemes in Bangladesh is being constrained by several issues, including inadequate population coverage, adverse selection and moral hazard, lack of knowledge about health insurance principles, a lack of external assistance, and insufficient medical supplies. Door-to-door visits by local community-health workers, as well as regular promotional and educational campaigns involving community influencers, were suggested by stakeholders as ways to educate and encourage people to join the schemes. Stakeholders emphasized the necessity of external assistance and the design of a comprehensive benefits package to attract more people. They also recommended adopting a public–private partnership with a belief that collaboration among the government, microfinance institutions, and cooperative societies will enhance trust and population coverage in Bangladesh. Conclusions Our research concludes that systematically addressing implementation barriers by including key stakeholders would be a significant reform to the CBHI model, and could serve as a foundation for the planned national health protection scheme for Bangladesh leading to universal health coverage.

The idea and practice of the entrepreneurial university has emerged in response to growing expectations of universities contributing to economic development and has, in turn, been subject to a growing body of research. However, much of the work is focused on individual activities or institutions, typically overemphasising commercialisation activities and certain types of universities. Furthermore, much of this research is de-contextualised and does not consider the systems in which universities operate. As a result, we have a variety of unit theories of constituent parts of the entrepreneurial university without considering the wider (feedback) effects and implications — in other words: we are, in effect, not seeing the forest for the trees. Drawing on in-depth quantitative and qualitative field work and the literature, we develop a programmatic theory of the entrepreneurial university and the institutionalised entrepreneurial activities. Using causal loop diagrams, we capture the systemness and the interdependencies between universities’ entrepreneurial activities and their dynamic capabilities. The model highlights how universities are part of a larger system and how this influences their external engagement activities. The result is a more holistic understanding of entrepreneurial universities that reconciles existing work and guides future research. We discuss practical implications and policy levers derived from this systemic perspective.Plain English SummaryWe provide a systemic model for understanding and diagnosing the capabilities of entrepreneurial universities based on in-depth qualitative and quantitative work. Universities are expected to contribute to society and the economy through activities that go beyond the traditional missions of research and teaching. Academic research on entrepreneurial universities tends to focus on discrete activities in universities or case studies at the cost of a wider understanding of the concept. The result is a limited understanding of how these activities and the university’s capabilities influence each other and co-evolve. We thus propose a new way of understanding how entrepreneurial universities behave, engage, and develop in a systematic fashion. For future research, new methodological approaches are required to operationalise this systemic view including the need to harmonise datasets covering entrepreneurial universities. For policy and practice, understanding the interconnectedness of activities and missions highlights the trade-offs and helps mitigate unintended consequences from different policy actions. The model developed in this paper serves as a tool for thinking and diagnosis for university managers and policy makers that can be applied to different contexts.

This paper reports on a project in which a group support system (GSS) equipped with a causal mapping facility was used to acquire knowledge from experts in seven European cities in order to understand the systemicity of risks which cities may face. The practical constraints demanded that participants’ experience and wisdom about the city risk environment was collected in a short period of time: three 1-day workshops. The acquisition of knowledge posed a number of important epistemological challenges which are explored in our discussion. The GSS was faced with the need to (1) facilitate sharing of knowledge with others, (2) manage the complexity of expert knowledge, (3) acknowledge the time demands on experts, (4) manage and merge multiple perspectives, and (5) acknowledge the subjectivity of knowledge in this domain. By discussing how the GSS process attended directly to these epistemological issues and to methodological considerations that linked to these issues, the paper contributes to a better understanding of the application of GSS for knowledge acquisition, particularly in comparison with other possible methods.

Care homes are vulnerable to widespread transmission of severe acute respiratory coronavirus virus 2 (SARS-CoV-2) with poor outcomes for staff and residents. Infection control interventions in care homes need to not only be effective in containing the spread of coronavirus disease 2019 (COVID-19) but also feasible to implement in this special setting which is both a healthcare institution and a home. 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. 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. Modeling results are very sensitive to transmission probability per contact, but the qualitative finding is robust to varying parameter values in our uncertainty analysis. 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.

Residents living in long-term care facilities (LTCFs) are at high risk of contracting healthcare-associated infections (HAIs). The unique operational and cultural characteristics of LTCFs and the currently evolving models of healthcare delivery in Scotland create great challenges for infection prevention and control (IPC). Existing literature that discusses the challenges of infection control in LTCFs focuses on operational factors within a facility and does not explore the challenges associated with higher levels of management and the lack of evidence to support IPC practices in this setting. 1-7 Here, we provide a broader view of challenges faced by LTCFs in the context of the current health and social care models in Scotland. Many of these challenges are also faced in the rest of the United Kingdom and internationally.

Mixing Operational Research (OR) methods is becoming more commonplace. Discrete-Event Simulation (DES) and System Dynamics (SD) are popular modelling methods previously applied to a range of situations for various purposes, which are starting to be mixed in healthcare. However, the practicalities of mixing DES and SD in practice remain unclear. Radiotherapy treatment is a complex multi-stage process where technology and best practice continue to evolve. This paper describes a project undertaken to explore the treatment planning process using mixed OR methods. It presents insights obtained through mixing OR methods within a real-world project. The model development process, the role of each modelling method and the benefits of undertaking a mixed OR methods project design are described. Lessons for mixing DES and SD, and more generally mixing OR methods, are discussed.