Trust-building in temporary public health partnerships: a qualitative study of the partnership formation process of a Covid-19 test, trace and protect service.

BACKGROUND: Public health initiatives require coordinated efforts from healthcare, social services and other service providers. Organisational theory tells us that trust is essential for reaching collaborative effectiveness. This paper explores the drivers for initiating and sustaining trust in a temporary public health partnership, in response to a sudden health threat. METHODS: This qualitative study analysed the formation process of a multisector partnership for a Covid-19 contact tracing service. Data was collected through 12 interviews, two focus groups, one feedback workshop, and an online survey with workforce members from all seven partner organisations. Purposive maximum variation sampling was used to capture the reflections and experiences of workforce members from all seven partner organisations. A deductive code scheme was used to identify drivers for building and sustaining trust in inter-organisational collaboration. RESULTS: Relational mechanisms emanating from the commitment to the common aim, shared norms and values, and partnership structures affected trust-building. Shared values and the commitment to the common aim appeared to channel partners' behaviour when interacting, resulting in being perceived as a fair, reliable and supportive partner. Shared values were congruent with the design of the partnership in terms of governance structure and communication lines reflecting flat hierarchies and shared decision-making power. Tensions between partner organisations arose when shared values were infringed. CONCLUSIONS: When managing trust in a collaboration, partners should consider structural components like governance structure, organisational hierarchy, and communication channels to ensure equal power distribution. Job rotation, recruitment of candidates with the desired personality traits and attitudes, as well as training and development, encourage inter-organisational networking among employees, which is essential for building and strengthening relationships with partner organisations. Partners should also be aware of managing relational dynamics, channelling behaviours through shared values, objectives and priorities and fostering mutual support and equality among partner organisations.

Understanding the Impact of Social Networks on the Spread of Obesity.

Previous research has highlighted the significant role social networks play in the spread of non-communicable chronic diseases. In our research, we seek to explore the impact of these networks in more detail and gain insight into the mechanisms that drive this. We use obesity as a case study. To achieve this, we develop a generalisable hybrid simulation and optimisation approach aimed at gaining qualitative and quantitative insights into the effect of social networks on the spread of obesity. Our simulation model has two components. Firstly, an agent-based component mimics the dynamic structure of the social network within which individuals are situated. Secondly, a system dynamics component replicates the relevant behaviours of those individuals. The parameters from the combined model are refined and optimised using longitudinal data from the United Kingdom. The simulation produces projections of Body Mass Index broken down by different age groups and gender over a 10-year period. These projections are used to explore a range of scenarios in a computational study designed to address our research aims. The study reveals that, for the youngest population sub-groups, the network acts to magnify the impact of external and social factors on changes in obesity, whereas, for older sub-groups, the network mitigates the impact of these factors. The magnitude of that impact is inversely correlated with age. Our approach can be used by public health decision makers as well as managers in adult weight management services to enhance initiatives and strategies intended to reduce obesity. Our approach is generalisable to understand the impact of social networks on similar non-communicable diseases.

Why Resilience in Health Care Systems is More than Coping with Disasters: Implications for Health Care Policy.

Health care systems need to be resilient to deal with disasters like the global spread of the Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV-2) on top of serving the changing needs of a multi-morbid, ageing and often dispersed population. This paper identifies, discusses and augments critical dimensions of resilience retrieved from the academic literature. It pulls together an integrated concept of resilience characterised by organisational capabilities. Our concept does not focus on the micro-level like most resilience literature in health care but addresses the system level with many stakeholders involved. Distinguishing exogenous shocks to the health care system into adverse events and planned innovations provides the basis for our conclusions and insights. It becomes apparent only when dealing with planned interventions that transformative capabilities are indispensable to cope with sudden increases in health care pressures. Due to the current focus on absorptive and adaptive resilience, organisations over-rely on management capabilities that cannot generate a lasting increase in functionality. Therefore, reducing the resilience discussion to bouncing back from adverse events could deceive organisations into cultivating a suboptimal mix of organisational capabilities lacking transformative capabilities, which pave the way for a structural change that aims at a sustainably higher functionality.

Modeling disease progression and treatment pathways for depression jointly using agent based modeling and system dynamics.

Introduction: Depression is a common mental health condition that affects millions of people worldwide. Care pathways for depression are complex and the demand across different parts of the healthcare system is often uncertain and not entirely understood. Clinical progression with depression can be equally complex and relates to whether or not a patient is seeking care, the care pathway they are on, and the ability for timely access to healthcare services. Considering both pathways and progression for depression are however rarely studied together in the literature. Methods: This paper presents a hybrid simulation modeling framework that is uniquely able to capture both disease progression, using Agent Based Modeling, and related care pathways, using a System Dynamics. The two simulation paradigms within the framework are connected to run synchronously to investigate the impact of depression progression on healthcare services and, conversely, how any limitations in access to services may impact clinical progression. The use of the developed framework is illustrated by parametrising it with published clinical data and local service level data from Wales, UK. Results and discussion: The framework is able to quantify demand, service capacities and costs across all care pathways for a range of different scenarios. These include those for varying service coverage and provision, such as the cost-effectiveness of treating patients more quickly in community settings to reduce patient progression to more severe states of depression, and thus reducing the costs and utilization of more expensive specialist settings.

Why local air pollution is more than daily peaks: modelling policies in a city in order to avoid premature deaths.

We use a predator-prey representation of an urban system to analyse how policy interventions can prevent the adverse effects of air pollution on people's health. The number of residents is treated as prey variable, and particulate matter that consists of particles with a diameter of up to 10 micrometres (PM10) as predator variable. This representation allows integration of population trends and the effects of environmental interventions on the average level of PM10 concentration (which establishes a baseline for the potential health burden for residents). For the case of Graz, Austria, we illustrate the insights generated regarding the interdependency of market-based and technological pollution controls, and propose an indicator that assesses the cost of delayed interventions by counting additional premature deaths caused by polluted environments.

Modelling for the proposed roll-out of the '111' service in Wales: a case study.

NHS Direct Wales provides a single point of access where members of the public can telephone and seek medical support and/or advice. The service is provided for all the Health Boards in Wales by a single virtual call centre run from a main location in Swansea with 2 satellite locations. Patients in Wales can also access a local General Practitioner service during the evenings and at weekends, by phoning their Out of Hours service. The introduction of a '111' service is intended to combine these two operations on a pan-Wales basis using the existing NHS Direct Wales call centre and staff, with the existing Health Board Out of Hours 'hubs'. The merger of the two services is intended to improve the overall performance of both services. This paper focuses on the planned introduction of '111' in Cwm Taf and Hywel Dda University Health Boards. The purpose of the case study was to support the merger of the two telephony systems from both an organisational and service delivery perspective, by developing a Discrete Event Simulation to model the impact on service levels and staffing. In particular, to examine the percentage increase / decrease in the staffing requirements needed under partial or full integration of the two services. The results from the scenario analysis highlight that extra staffing resources would be required in certain groups (nurses and call handlers) whilst savings could be achieved in others, provided that there wasn't an increase in call volume after implementation of the new service.

A model of chaotic drug markets and their control.

This paper explores the idea that drug markets may be chaotic in a mathematical sense by considering a discrete-time model of populations of drug users and drug sellers for which initiation into either population is a function of relative numbers of both populations. The structure of the system follows that considered in an arms control context by Behrens, Feichtinger and Prskawetz (Behrens D.A., Feichtinger G., & Prskawetz A. (1997). Complex Dynamics and Control of Arms Race. European Journal of Operations Research, 100, 192-215). The model presented in this paper summarizes prerequisites for possible chaotic behavior of the number of addicts and drug dealers frequenting a local drug market. Interestingly, even if the uncontrolled market dynamics do not exhibit chaotic patterns, a static intervention like removing a constant fraction of addicts each time period can easily create chaos--but even if static control would create chaos, dynamic controls can be crafted that avoid it. Especially OGY controls seem to work well for this example.

Markov chain modeling of initiation and demand: the case of the U.S. cocaine epidemic.

Everingham and Rydell's Markov chain model of cocaine demand is modified and updated in light of recent data. Key insights continue to hold, e.g., that the proportion of cocaine demand stemming from heavy vs. light users changed dramatically over the 1980s. New insights emerge, e.g., pertaining to the average duration of a career of heavy use (about 12 years) and the negative relationship between levels of heavy use and epidemic "infectivity" or the number of new initiates per current user per year. This illustrates how simple modeling can yield insights directly relevant to managing complex drug control policy questions.