Mapping the distance between fire hazard and disaster for communities in Canadian forests.

Communities interspersed throughout the Canadian wildland are threatened by fires that have become bigger and more frequent in some parts of the country in recent decades. Identifying the fireshed (source area) and pathways from which wildland fire may ignite and spread from the landscape to a community is crucial for risk-reduction strategy and planning. We used outputs from a fire simulation model, including fire polygons and rate of spread, to map firesheds, fire pathways and corridors and spread distances for 1980 communities in the forested areas of Canada. We found fireshed sizes are larger in the north, where the mean distances between ecumene and fireshed perimeters were greater than 10 km. The Rayleigh Z test indicated that simulated fires around a large proportion of communities show significant directional trends, and these trends are stronger in the Boreal Plains and Shields than in the Rocky Mountain area. The average distance from which fire, when spreading at the maximum simulated rate, could reach the community perimeter was approximately 5, 12 and 18 km in 1, 2 and 3 days, respectively. The average daily spread distances increased latitudinally, from south to north. Spread distances were the shortest in the Pacific Maritime, Atlantic Maritime and Boreal Plains Ecozones, implying lower rates of spread compared to the rest of the country. The fire corridors generated from random ignitions and from ignitions predicted from local fire history differ, indicating that factors other than fuel (e.g. fire weather, ignition pattern) play a significant role in determining the direction that fires burn into a community.

Beyond resilience: Responses to changing climate and disturbance regimes in temperate forest landscapes across the Northern Hemisphere.

Climate change has profound impacts on forest ecosystem dynamics and could lead to the emergence of novel ecosystems via changes in species composition, forest structure, and potentially a complete loss of tree cover. Disturbances fundamentally shape those dynamics: the prevailing disturbance regime of a region determines the inherent variability of a system, and its climate-mediated change could accelerate forest transformation. We used the individual-based forest landscape and disturbance model iLand to investigate the resilience of three protected temperate forest landscapes on three continents-selected to represent a gradient from low to high disturbance activity-to changing climate and disturbance regimes. In scenarios of sustained strong global warming, natural disturbances increased across all landscapes regardless of projected changes in precipitation (up to a sevenfold increase in disturbance rate over the 180-year simulation period). Forests in landscapes with historically high disturbance activity had a higher chance of remaining resilient in the future, retaining their structure and composition within the range of variability inherent to the system. However, the risk of regime shift and forest loss was also highest in these systems, suggesting forests may be vulnerable to abrupt change beyond a threshold of increasing disturbance activity. Resilience generally decreased with increasing severity of climate change. Novelty in tree species composition was more common than novelty in forest structure, especially under dry climate scenarios. Forests close to the upper tree line experienced high novelty in structure across all three study systems. Our results highlight common patterns and processes of forest change, while also underlining the diverse and context-specific responses of temperate forest landscapes to climate change. Understanding past and future disturbance regimes can anticipate the magnitude and direction of forest change. Yet, even across a broad gradient of disturbance activity, we conclude that climate change mitigation is the most effective means of maintaining forest resilience.

Ants find shortest paths using simple, local rules.

Garg et al. (2023, Proceedings of the National Academy of Sciences, 120[6], e2207959120) build simulation models to understand how turtle ants collectively find efficient paths through branched networks, highlighting the importance of bidirectional traffic, leakage of ants at junctions, and the ability to increase flow as key components for efficiency. Their findings provide new, biologically realistic mechanisms that could improve applications in our own engineered networks.

Estimating the contribution of overweight and obesity to ethnic inequalities in cardio-metabolic diseases in the Netherlands: a simulation study.

OBJECTIVES: Overweight and obesity (OWOB) starts in childhood, influences adult cardiovascular risk, and is not equally distributed across ethnic groups. It is unclear which effects can be expected from reductions in OWOB across the life course on inequalities in cardio-metabolic diseases in a multi-ethnic population. This study aims to estimate the effects of three scenarios of changes in OWOB (the Normal-Weight-for-All scenario, the No-Ethnic-Difference-over-the-Life-Course scenario, the and No-Ethnic-Differences-in-Childhood scenario). STUDY DESIGN: A simulation study. METHODS: We combine data from multiple data sources and use the Dynamic Modeling for Health Impact Assessment (DYNAMO-HIA) model to estimate the effects of three scenarios on the cumulative incidence of diabetes mellitus, ischaemic heart disease (IHD) and stroke between 18 and 70 years in the five largest ethnic groups in the Netherlands. RESULTS: In the scenario where all individuals have normal weight, the cumulative incidence decreased in all ethnic minority groups for all diseases, with largest decreases among South-Asian Surinamese, where the reduction of diabetes incidence exceeded 50%. In the scenario where the prevalence of OWOB in each ethnic-minority group was reduced to the current level among the Dutch-origin population, ethnic inequalities in cardio-metabolic diseases were substantially reduced, particularly when lowered prevalence of OWOB persisted across the lifespan. Reductions were the largest for diabetes and for the Asian Surinamese population. CONCLUSIONS: A substantial part of the well-known ethnic inequalities in incidence of diabetes, IHD, and stroke can be attributed to OWOB. Interventions aimed at reducing OWOB have clear potential to reduce the health inequalities in these outcomes, especially for diabetes, in particular when they have an impact across the lifespan.

Health and economic impact of improved glucose, blood pressure and lipid control among German adults with type 2 diabetes: a modelling study.

AIMS/HYPOTHESIS: The aim of this study was to estimate the long-term health and economic consequences of improved risk factor control in German adults with type 2 diabetes. METHODS: We used the UK Prospective Diabetes Study Outcomes Model 2 to project the patient-level health outcomes and healthcare costs of people with type 2 diabetes in Germany over 5, 10 and 30 years. We parameterised the model using the best available data on population characteristics, healthcare costs and health-related quality of life from German studies. The modelled scenarios were: (1) a permanent reduction of HbA1c by 5.5 mmol/mol (0.5%), of systolic BP (SBP) by 10 mmHg, or of LDL-cholesterol by 0.26 mmol/l in all patients, and (2) achievement of guideline care recommendations for HbA1c (≤53 mmol/mol [7%]), SBP (≤140 mmHg) or LDL-cholesterol (≤2.6 mmol/l) in patients who do not meet the recommendations. We calculated nationwide estimates using age- and sex-specific quality-adjusted life year (QALY) and cost estimates, type 2 diabetes prevalence and population size. RESULTS: Over 10 years, a permanent reduction of HbA1c by 5.5 mmol/mol (0.5%), SBP by 10 mmHg or LDL-cholesterol by 0.26 mmol/l led to per-person savings in healthcare expenditures of €121, €238 and €34, and 0.01, 0.02 and 0.015 QALYs gained, respectively. Achieving guideline care recommendations for HbA1c, SBP or LDL-cholesterol could reduce healthcare expenditure by €451, €507 and €327 and gained 0.03, 0.05 and 0.06 additional QALYs in individuals who did not meet the recommendations. Nationally, achieving guideline care recommendations for HbA1c, SBP and LDL-cholesterol could reduce healthcare costs by over €1.9 billion. CONCLUSIONS/INTERPRETATION: Sustained improvements in HbA1c, SBP and LDL-cholesterol control among diabetes patients in Germany can lead to substantial health benefits and reduce healthcare expenditures.

Pollinator foraging tactics have divergent consequences for the mating system of a tropical plant.

Resolving the consequences of pollinator foraging behaviour for plant mating systems is a fundamental challenge in evolutionary ecology. Pollinators may adopt particular foraging tactics: complete trapline foraging (repeated movements along a fixed route), sample-and-shift trapline foraging (a variable route that incorporates information from previous experiences) and territorial foraging (stochastic movements within a restricted area). Studies that integrate these pollinator foraging tactics with plant mating systems are generally lacking. We investigate the consequences of particular pollinator foraging tactics for Heliconia tortuosa. We combine parentage and sibship inference analysis with simulation modelling to: estimate mating system parameters; infer the foraging tactic adopted by the pollinators; and quantify the impact of pollinator foraging tactics on mating system parameters. We found high outcrossing rates, ubiquitous multiple paternity and a pronounced departure from near-neighbour mating. We also found that plants repeatedly receive pollen from a series of particular donors. We infer that the pollinators primarily adopt complete trapline foraging and occasionally engage in sample-and-shift trapline foraging. This enhances multiple paternity without a substantial increase in near-neighbour mating. The particular pollinator foraging tactics have divergent consequences for multiple paternity and near-neighbour mating. Thus, pollinator foraging behaviour is an important driver of the ecology and evolution of plant mating systems.

The application of simulation methods during the COVID-19 pandemic: A scoping review.

With the outbreak of COVID-19 pandemic, simulation modelling approaches have become effective tools to simulate the potential effects of different intervention measures and predict the dynamic COVID-19 trends. In this scoping review, Studies published between February 2020 and May 2022 that investigated the spread of COVID-19 using four common simulation modeling methods were systematically reported and summarized. Publication trend, characteristics, software, and code availability of included articles were analyzed. Among the included 340 studies, most articles used agent-based model (ABM; n = 258; 75.9 %), followed by the models of system dynamics (n = 42; 12.4 %), discrete event simulation (n = 25; 7.4 %), and hybrid simulation (n = 15; 4.4 %). Furthermore, our review emphasized the purposes and sample time period of included articles. We classified the purpose of the 340 included studies into five categories, most studies mainly analyzed the spread of COVID-19 under policy interventions. For the sample time period analysis, most included studies analyzed the COVID-19 spread in the second wave. Our findings play a crucial role for policymakers to make evidence-based decisions in preventing the spread of COVID-19 pandemic and help in providing scientific decision-makings resilient to similar events and infectious diseases in the future.

System dynamics models of depression at the population level: a scoping review.

AIMS: Depression is a disease driven by dynamic processes both at the individual- and system-level. System dynamics (SD) models are a useful tool to capture this complexity, project the future prevalence of depression and understand the potential impact of interventions and policies. SD models have been used to model infectious and chronic disease, but rarely applied to mental health. This scoping review aimed to identify population-based SD models of depression and report on their modelling strategies and applications to policy and decision-making to inform research in this emergent field. METHODS: We searched articles in MEDLINE, Embase, PsychInfo, Scopus, MedXriv, and abstracts from the System Dynamics Society from inception to October 20, 2021 for studies of population-level SD models of depression. We extracted data on model purpose, elements of SD models, results, and interventions, and assessed the quality of reporting. RESULTS: We identified 1899 records and found four studies that met the inclusion criteria. Studies used SD models to assess various system-level processes and interventions, including the impact of antidepressant use on population-level depression in Canada; the impact of recall error on lifetime estimates of depression in the USA; smoking-related outcomes among adults with and without depression in the USA; and the impact of increasing depression incidence and counselling rates on depression in Zimbabwe. Studies included diverse stocks and flows for depression severity, recurrence, and remittance, but all models included flows for incidence and recurrence of depression. Feedback loops were also present in all models. Three studies provided sufficient information for replicability. CONCLUSIONS: The review highlights the usefulness of SD models to model the dynamics of population-level depression and inform policy and decision-making. These results can help guide future applications of SD models to depression at the population-level.

Prioritizing Healthcare Interventions: A Comparison of Multicriteria Decision Analysis and Cost-Effectiveness Analysis.

OBJECTIVES: To investigate the extent to which stated preferences for treatment criteria elicited using multicriteria decision analysis (MCDA) methods are consistent with the trade-offs (implicitly) applied in cost-effectiveness analysis (CEA), and the impact of any differences on the prioritization of treatments. METHODS: We used existing MCDA and CEA models developed to evaluate interventions for knee osteoarthritis in the New Zealand population. We established equivalent input parameters for each model, for the criteria "treatment effectiveness," "cost," "risk of serious harms," and "risk of mild-to-moderate harms" across a comprehensive range of (hypothetical) interventions to produce a complete ranking of interventions from each model. We evaluated the consistency of these rankings between the 2 models and investigated any systematic differences between the (implied) weight placed on each criterion in determining rankings. RESULTS: There was an overall moderate-to-strong correlation in intervention rankings between the MCDA and CEA models (Spearman correlation coefficient = 0.51). Nevertheless, there were systematic differences in the evaluation of trade-offs between intervention attributes and the resulting weights placed on each criterion. The CEA model placed lower weights on risks of harm and much greater weight on cost (at all accepted levels of willingness-to-pay per quality-adjusted life-year than did respondents to the MCDA survey. CONCLUSIONS: MCDA and CEA approaches to inform intervention prioritization may give systematically different results, even when considering the same criteria and input data. These differences should be considered when designing and interpreting such studies to inform treatment prioritization decisions.

The dynamics of frailty development and progression in older adults in primary care in England (2006-2017): a retrospective cohort profile.

BACKGROUND: Frailty is a common condition in older adults and has a major impact on patient outcomes and service use. Information on the prevalence in middle-aged adults and the patterns of progression of frailty at an individual and population level is scarce. To address this, a cohort was defined from a large primary care database in England to describe the epidemiology of frailty and understand the dynamics of frailty within individuals and across the population. This article describes the structure of the dataset, cohort characteristics and planned analyses. METHODS: Retrospective cohort study using electronic health records. Participants were aged ≥50 years registered in practices contributing to the Oxford Royal College of General Practitioners Research and Surveillance Centre between 2006 to 2017. Data include GP practice details, patient sociodemographic and clinical characteristics, twice-yearly electronic Frailty Index (eFI), deaths, medication use and primary and secondary care health service use. Participants in each cohort year by age group, GP and patient characteristics at cohort entry are described. RESULTS: The cohort includes 2,177,656 patients, contributing 15,552,946 person-years, registered at 419 primary care practices in England. The mean age was 61 years, 52.1% of the cohort was female, and 77.6% lived in urban environments. Frailty increased with age, affecting 10% of adults aged 50-64 and 43.7% of adults aged ≥65. The prevalence of long-term conditions and specific frailty deficits increased with age, as did the eFI and the severity of frailty categories. CONCLUSION: A comprehensive understanding of frailty dynamics will inform predictions of current and future care needs to facilitate timely planning of appropriate interventions, service configurations and workforce requirements. Analysis of this large, nationally representative cohort including participants aged ≥50 will capture earlier transitions to frailty and enable a detailed understanding of progression and impact. These results will inform novel simulation models which predict future health and service needs of older people living with frailty. STUDY REGISTRATION: Registered on www.clinicaltrials.gov October 25th 2019, NCT04139278 .

Cross-Jurisdiction Comparative Research in Work Disability Prevention: Introduction to the Special Series.

The systems that societies construct to support work disability prevention can have powerful effects on both the experiences of people with work disability as well as their health and employment outcomes. Comparative studies between jurisdictions provide an opportunity to gain insights into these system level impacts, by comparing system features, processes and experiences; and by determining if jurisdictional variation affects outcomes. In turn, this can prompt policy and practice reform. Reflecting the diversity of work disability systems globally, there is growing interest in cross-jurisdiction comparative research in the field. This special series presents seven articles addressing important methodological and conceptual aspects of comparative research in work disability prevention, and presents practical examples of how jurisdictions vary and the impact this can have on workers.

Widespread regeneration failure in forests of Greater Yellowstone under scenarios of future climate and fire.

Changing climate and disturbance regimes are increasingly challenging the resilience of forest ecosystems around the globe. A powerful indicator for the loss of resilience is regeneration failure, that is, the inability of the prevailing tree species to regenerate after disturbance. Regeneration failure can result from the interplay among disturbance changes (e.g., larger and more frequent fires), altered climate conditions (e.g., increased drought), and functional traits (e.g., method of seed dispersal). This complexity makes projections of regeneration failure challenging. Here we applied a novel simulation approach assimilating data-driven fire projections with vegetation responses from process modeling by means of deep neural networks. We (i) quantified the future probability of regeneration failure; (ii) identified spatial hotspots of regeneration failure; and (iii) assessed how current forest types differ in their ability to regenerate under future climate and fire. We focused on the Greater Yellowstone Ecosystem (2.9 × 106  ha of forest) in the Rocky Mountains of the USA, which has experienced large wildfires in the past and is expected to undergo drastic changes in climate and fire in the future. We simulated four climate scenarios until 2100 at a fine spatial grain (100 m). Both wildfire activity and unstocked forest area increased substantially throughout the 21st century in all simulated scenarios. By 2100, between 28% and 59% of the forested area failed to regenerate, indicating considerable loss of resilience. Areas disproportionally at risk occurred where fires are not constrained by topography and in valleys aligned with predominant winds. High-elevation forest types not adapted to fire (i.e., Picea engelmannii-Abies lasiocarpa as well as non-serotinous Pinus contorta var. latifolia forests) were especially vulnerable to regeneration failure. We conclude that changing climate and fire could exceed the resilience of forests in a substantial portion of Greater Yellowstone, with profound implications for carbon, biodiversity, and recreation.

The opioid crisis: need for systems science research.

The opioid epidemic in the United States has had a devastating impact on millions of people as well as on their families and communities. The increased prevalence of opioid misuse, use disorder and overdose in recent years has highlighted the need for improved public health approaches for reducing the tremendous harms of this illness. In this paper, we explain and call for the need for more systems science approaches, which can uncover the complexities of the opioid crisis, and help evaluate, analyse and forecast the effectiveness of ongoing and new policy interventions. Similar to how a stream of systems science research helped policy development in infectious diseases and obesity, more systems science research is needed in opioids.

Development of a mechanistic dengue simulation model for Guangzhou.

Dengue infection in China has increased dramatically in recent years. Guangdong province (main city Guangzhou) accounted for more than 94% of all dengue cases in the 2014 outbreak. Currently, there is no existing effective vaccine and most efforts of control are focused on the vector itself. This study aimed to evaluate different dengue management strategies in a region where this disease is emerging. This work was done by establishing a dengue simulation model for Guangzhou to enable the testing of control strategies aimed at vector control and vaccination. For that purpose, the computer-based dengue simulation model (DENSiM) together with the Container-Inhabiting Mosquito Simulation Model (CIMSiM) has been used to create a working dengue simulation model for the city of Guangzhou. In order to achieve the best model fit against historical surveillance data, virus introduction scenarios were run and then matched against the actual dengue surveillance data. The simulation model was able to predict retrospective outbreaks with a sensitivity of 0.18 and a specificity of 0.98. This new parameterisation can now be used to evaluate the potential impact of different control strategies on dengue transmission in Guangzhou. The knowledge generated from this research would provide useful information for authorities regarding the historic patterns of dengue outbreaks, as well as the effectiveness of different disease management strategies.

Evaluating a risk assessment tool to improve triaging of patients to colonoscopies.

BACKGROUND: Colonoscopy is the gold standard in the diagnosis of significant bowel disease (SBD), including colorectal cancer, high-risk adenoma and inflammatory bowel disease. As the demand for colonoscopy services is placing significant pressure on hospital resources, new solutions are needed to manage patients more efficiently and effectively. AIM: We investigated the impact of using a risk assessment tool (RAT) to improve selection of patients for colonoscopy procedures to detect SBD. METHODS: A hybrid simulation model was constructed to replicate the current patient triage bookings and waiting times in a large metropolitan hospital. The model used data on 327 patients who were retrospectively assessed for risk of SBD. Risk assessment incorporated blood and faecal immunochemical test results, gender and age in addition to patient symptoms. The model was calibrated over 12 months to current outcomes and was compared with the RAT and a third scenario where low-risk patients did not proceed to a colonoscopy. One-way sensitivity analyses were undertaken. RESULTS: Using the RAT was expected to shorten waiting times by 153 days for moderately-urgent patients and 138 days for non-urgent patients. If low-risk patients did not proceed to colonoscopy, waiting times were expected to reduce for patients with SBD by 17 days producing cost-savings of AU$373 824 through avoided colonoscopies. CONCLUSIONS: A hybrid model that combines patient-level characteristics with hospital-level resource constraints can demonstrate improved efficiency in a hospital clinic. Further research on risk assessment is required to improve quality patient care and reduce low-value service delivery.

Integrating HIV, syphilis, malaria and anaemia point-of-care testing (POCT) for antenatal care at dispensaries in western Kenya: discrete-event simulation modelling of operational impact.

BACKGROUND: Despite WHO advocating for an integrated approach to antenatal care (ANC), testing coverage for conditions other than HIV remains low and women are referred to distant laboratories for testing. Using point-of-care tests (POCTs) at peripheral dispensaries could improve access to testing and timely treatment. However, the effect of providing additional services on nurse workload and client wait times are unknown. We use discrete-event simulation (DES) modelling to understand the effect of providing four point-of-care tests for ANC on nurse utilization and wait times for women seeking maternal and child health (MCH) services. METHODS: We collected detailed time-motion data over 20 days from one high volume dispensary in western Kenya during the 8-month implementation period (2014-2015) of the intervention. We constructed a simulation model using empirical arrival distributions, activity durations and client pathways of women seeking MCH services. We removed the intervention from the model to obtain wait times, length-of-stay and nurse utilization rates for the baseline scenario where only HIV testing was offered for ANC. Additionally, we modelled a scenario where nurse consultations were set to have minimum durations for sufficient delivery of all WHO-recommended services. RESULTS: A total of 183 women visited the dispensary for MCH services and 14 of these women received point-of-care testing (POCT). The mean difference in total waiting time was 2 min (95%CI: < 1-4 min, p = 0.026) for MCH women when integrated POCT was given, and 9 min (95%CI: 4-14 min, p < 0.001) when integrated POCT with adequate ANC consult times was given compared to the baseline scenario. Mean length-of-stay increased by 2 min (95%CI: < 1-4 min, p = 0.015) with integrated POCT and by 16 min (95%CI: 10-21 min, p < 0.001) with integrated POCT and adequate consult times compared to the baseline scenario. The two nurses' overall daily utilization in the scenario with sufficient minimum consult durations were 72 and 75%. CONCLUSION: The intervention had a modest overall impact on wait times and length-of-stay for women seeking MCH services while ensuring pregnant women received essential diagnostic testing. Nurse utilization rates fluctuated among days: nurses experienced spikes in workload on some days but were under-utilized on the majority of days. Overall, our model suggests there was sufficient time to deliver all WHO's required ANC activities and offer integrated testing for ANC first and re-visits with the current number of healthcare staff. Further investigations on improving healthcare worker, availability, performance and quality of care are needed. Delivering four point-of-care tests together for ANC at dispensary level would be a low burden strategy to improve ANC.

Early-stage Hodgkin lymphoma in the modern era: simulation modelling to delineate long-term patient outcomes.

We developed a novel simulation model integrating multiple data sets to project long-term outcomes with contemporary therapy for early-stage Hodgkin lymphoma (ESHL), namely combined modality therapy (CMT) versus chemotherapy alone (CA) via 18 F-fluorodeoxyglucose positron emission tomography response-adaption. The model incorporated 3-year progression-free survival (PFS), probability of cure with/without relapse, frequency of severe late effects (LEs), and 35-year probability of LEs. Furthermore, we generated estimates for quality-adjusted life years (QALYs) and unadjusted survival (life years, LY) and used model projections to compare outcomes for CMTversusCA for two index patients. Patient 1: a 25-year-old male with favourable ESHL (stage IA); Patient 2: a 25-year-old female with unfavourable ESHL (stage IIB). Sensitivity analyses assessed the impact of alternative assumptions for LE probabilities. For Patient 1, CMT was superior to CA (CMT incremental gain = 0·11 QALYs, 0·21 LYs). For Patient 2, CA was superior to CMT (CA incremental gain = 0·37 QALYs, 0·92 LYs). For Patient 1, the advantage of CMT changed minimally when the proportion of severe LEs was reduced from 20% to 5% (0·15 QALYs, 0·43 LYs), whereas increasing the severity proportion for Patient 2's LEs from 20% to 80% enhanced the advantage of CA (1·1 QALYs, 6·5 LYs). Collectively, this detailed simulation model quantified the long-term impact that varied host factors and alternative contemporary treatments have in ESHL.

Development and validation of a new population-based simulation model of osteoarthritis in New Zealand.

OBJECTIVE: To describe the construction and preliminary validation of a new population-based microsimulation model developed to analyse the health and economic burden and cost-effectiveness of treatments for knee osteoarthritis (OA) in New Zealand (NZ). METHOD: We developed the New Zealand Management of Osteoarthritis (NZ-MOA) model, a discrete-time state-transition microsimulation model of the natural history of radiographic knee OA. In this article, we report on the model structure, derivation of input data, validation of baseline model parameters against external data sources, and validation of model outputs by comparison of the predicted population health loss with previous estimates. RESULTS: The NZ-MOA model simulates both the structural progression of radiographic knee OA and the stochastic development of multiple disease symptoms. Input parameters were sourced from NZ population-based data where possible, and from international sources where NZ-specific data were not available. The predicted distributions of structural OA severity and health utility detriments associated with OA were externally validated against other sources of evidence, and uncertainty resulting from key input parameters was quantified. The resulting lifetime and current population health-loss burden was consistent with estimates of previous studies. CONCLUSION: The new NZ-MOA model provides reliable estimates of the health loss associated with knee OA in the NZ population. The model structure is suitable for analysis of the effects of a range of potential treatments, and will be used in future work to evaluate the cost-effectiveness of recommended interventions within the NZ healthcare system.

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.

Decision makers' experience of participatory dynamic simulation modelling: methods for public health policy.

BACKGROUND: Systems science methods such as dynamic simulation modelling are well suited to address questions about public health policy as they consider the complexity, context and dynamic nature of system-wide behaviours. Advances in technology have led to increased accessibility and interest in systems methods to address complex health policy issues. However, the involvement of policy decision makers in health-related simulation model development has been lacking. Where end-users have been included, there has been limited examination of their experience of the participatory modelling process and their views about the utility of the findings. This paper reports the experience of end-user decision makers, including senior public health policy makers and health service providers, who participated in three participatory simulation modelling for health policy case studies (alcohol related harm, childhood obesity prevention, diabetes in pregnancy), and their perceptions of the value and efficacy of this method in an applied health sector context. METHODS: Semi-structured interviews were conducted with end-user participants from three participatory simulation modelling case studies in Australian real-world policy settings. Interviewees were employees of government agencies with jurisdiction over policy and program decisions and were purposively selected to include perspectives at different stages of model development. RESULTS: The 'co-production' aspect of the participatory approach was highly valued. It was reported as an essential component of building understanding of the modelling process, and thus trust in the model and its outputs as a decision-support tool. The unique benefits of simulation modelling included its capacity to explore interactions of risk factors and combined interventions, and the impact of scaling up interventions. Participants also valued simulating new interventions prior to implementation in the real world, and the comprehensive mapping of evidence and its gaps to prioritise future research. The participatory aspect of simulation modelling was time and resource intensive and therefore most suited to high priority complex topics with contested options for intervening. CONCLUSION: These findings highlight the value of a participatory approach to dynamic simulation modelling to support its utility in applied health policy settings.