PERSiST: a flexible rainfall-runoff modelling toolkit for use with the INCA family of models

Runoff generation processes and pathways vary widely between catchments. Credible simulations of solute and pollutant transport in surface waters are dependent on models which facilitate appropriate, catchment-specific representations of perceptual models of the runoff generation process. Here, we present a flexible, semi-distributed landscape-scale rainfall-runoff modelling toolkit suitable for simulating a broad range of user-specified perceptual models of runoff generation and stream flow occurring in different climatic regions and landscape types. PERSiST (the Precipitation, Evapotranspiration and Runoff Simulator for Solute Transport) is designed for simulating present-day hydrology; projecting possible future effects of climate or land use change on runoff and catchment water storage; and generating hydrologic inputs for the Integrated Catchments (INCA) family of models. PERSiST has limited data requirements and is calibrated using observed time series of precipitation, air temperature and runoff at one or more points in a river network. Here, we apply PERSiST to the river Thames in the UK and describe a Monte Carlo tool for model calibration, sensitivity and uncertainty analysis

Modelling the bioaccumulation of persistent organic pollutants in agricultural food chains for regulatory exposure assessment

New models for estimating bioaccumulation of persistent organic pollutants in the agricultural food chain were developed using recent improvements to plant uptake and cattle transfer models. One model named AgriSim was based on K OW regressions of bioaccumulation in plants and cattle, while the other was a steady-state mechanistic model, AgriCom. The two developed models and European Union System for the Evaluation of Substances (EUSES), as a benchmark, were applied to four reported food chain (soil/air-grass-cow-milk) scenarios to evaluate the performance of each model simulation against the observed data. The four scenarios considered were as follows: (1) polluted soil and air, (2) polluted soil, (3) highly polluted soil surface and polluted subsurface and (4) polluted soil and air at different mountain elevations. AgriCom reproduced observed milk bioaccumulation well for all four scenarios, as did AgriSim for scenarios 1 and 2, but EUSES only did this for scenario 1. The main causes of the deviation for EUSES and AgriSim were the lack of the soil-air-plant pathway and the ambient air-plant pathway, respectively. Based on the results, it is recommended that soil-air-plant and ambient air-plant pathway should be calculated separately and the K OW regression of transfer factor to milk used in EUSES be avoided. AgriCom satisfied the recommendations that led to the low residual errors between the simulated and the observed bioaccumulation in agricultural food chain for the four scenarios considered. It is therefore recommended that this model should be incorporated into regulatory exposure assessment tools. The model uncertainty of the three models should be noted since the simulated concentration in milk from 5th to 95th percentile of the uncertainty analysis often varied over two orders of magnitude. Using a measured value of soil organic carbon content was effective to reduce this uncertainty by one order of magnitude.

Trial application of a model of resource utiliztion, costs, and outcomes for stroke (MORUCOS) to assist priority setting in stroke.

Background and Purpose— Cost-effectiveness data for stroke interventions are limited, and comparisons between studies are confounded by methodological inconsistencies. The aim of this study was to trial the use of the intervention module of the economic model, a Model of Resource Utilization, Costs, and Outcomes for Stroke (MORUCOS) to facilitate evaluation and ranking of the options.

Methods— The approach involves using an economic model together with added secondary considerations. A consistent approach was taken using standard economic evaluation methods. Data from the North East Melbourne Stroke Incidence Study (NEMESIS) were used to model "current practice" (base case), against which 2 interventions were compared. A 2-stage process was used to measure benefit: health gains (expressed in disability-adjusted life years [DALYs]) and filter analysis. Incremental cost-effectiveness ratios (ICERs) were calculated, and probabilistic uncertainty analysis was undertaken.

Results— Aspirin, a low-cost intervention applicable to a large number of stroke patients (9153 first-ever cases), resulted in modest health benefits (946 DALYs saved) and a mean ICER (based on incidence costs) of US $1421 per DALY saved. Although the health gains from recombinant tissue-type plasminogen activator (rtPA) were less (155 DALYs saved), these results were impressive given the small number of persons (256) eligible for treatment. rtPA dominates current practice because it is more effective and cost-saving.

Conclusions— If used to assess interventions across the stroke care continuum, MORUCOS offers enormous capacity to support decision-making in the prioritising of stroke services.

Assessing cost-effectiveness of drug interventions for schizophrenia

Objective: To assess from a health sector perspective the incremental cost-effectiveness of eight drug treatment scenarios for established schizophrenia.

Method: Using a standardized methodology, costs and outcomes are modelled over the lifetime of prevalent cases of schizophrenia in Australia in 2000. A two-stage approach to assessment of health benefit is used. The first stage involves a quantitative analysis based on disability-adjusted life years (DALYs) averted, using best available evidence. The robustness of results is tested using probabilistic uncertainty analysis. The second stage involves application of 'second filter' criteria (equity, strength of evidence, feasibility and acceptability) to allow broader concepts of benefit to be considered.

Results: Replacing oral typicals with risperidone or olanzapine has an incremental costeffectiveness ratio (ICER) of A$48 000 and A$92 000/DALY respectively. Switching from low-dose typicals to risperidone has an ICER of A$80 000. Giving risperidone to people experiencing side-effects on typicals is more cost-effective at A$20 000. Giving clozapine to people taking typicals, with the worst course of the disorder and either little or clear deterioration, is cost-effective at A$42 000 or A$23 000/DALY respectively. The least costeffective intervention is to replace risperidone with olanzapine at A$160 000/DALY.

Conclusions: Based on an A$50 000/DALY threshold, low-dose typical neuroleptics are indicated as the treatment of choice for established schizophrenia, with risperidone being reserved for those experiencing moderate to severe side-effects on typicals. The more expensive olanzapine should only be prescribed when risperidone is not clinically indicated. The high cost of risperidone and olanzapine relative to modest health gains underlie this conclusion. Earlier introduction of clozapine however, would be cost-effective. This work is limited by weaknesses in trials (lack of long-term efficacy data, quality of life and consumer satisfaction evidence) and the translation of effect size into a DALY change. Some stakeholders, including SANE Australia, argue the modest health gains reported in the literature do not adequately reflect perceptions by patients, clinicians and carers, of improved quality of life with these atypicals.

Economic evaluation alongside a phase II, multi-centre, randomised controlled trial of very early rehabilitation after stroke (AVERT)

BACKGROUND/PURPOSE: The effectiveness and costs of very early rehabilitation after stroke are unknown. This study assessed the cost effectiveness of very early mobilisation in addition to standard care (VEM) compared with standard care alone (SC). METHODS: Cost-effectiveness analysis alongside a phase II, multi-centre, randomised controlled trial (RCT) with blinded outcome assessments. Less than 24 h after stroke, patients were recruited from two stroke units and randomised to receive VEM or SC. The intervention continued until discharge or 14 days, whichever was sooner. The efficacy measure was a dichotomised modified Rankin Scale (mRS) at 3 months with mRS < or =2 representing good outcome. Costs were determined from medical records and patient interviews at 3, 6 and 12 months. National average (where available) or local costs were applied for the reference year 2004. Differences in mean total costs at 3 and 12 months were tested using t test assuming unequal variances. An incremental cost-effectiveness ratio was calculated and probabilistic uncertainty analysis was undertaken. RESULTS: The sample consisted of 38 VEM and 33 SC patients. A trend for good outcome with VEM compared to SC was found (adjusted OR 4.10, 95% CI 0.99-16.88, p = 0.051). Patients receiving VEM incurred significantly less costs at 3 months (AUD 13,559) compared with SC (AUD 21,860; p = 0.02). This difference in mean per patient total cost persisted at the 12-month assessment (VEM: AUD 17,564; SC: AUD 29,750; p = 0.03). VEM was found to be a 'dominant' (more effective, less cost) intervention when compared to SC at 3 months. CONCLUSION: These findings provide preliminary evidence that VEM is likely to be cost-effective. A large RCT is currently underway to confirm the cost effectiveness of VEM.

Assessing cost-effectiveness in obesity (ACE-Obesity) : an overview of the ACE approach, economic methods and cost results

Background : The aim of the ACE-Obesity study was to determine the economic credentials of interventions which aim to prevent unhealthy weight gain in children and adolescents. We have reported elsewhere on the modelled effectiveness of 13 obesity prevention interventions in children. In this paper, we report on the cost results and associated methods together with the innovative approach to priority setting that underpins the ACE-Obesity study.

Methods : The Assessing Cost-Effectiveness (ACE) approach combines technical rigour with 'due process' to facilitate evidence-based policy analysis. Technical rigour was achieved through use of standardised evaluation methods, a research team that assembles best available evidence and extensive uncertainty analysis. Cost estimates were based on pathway analysis, with resource usage estimated for the interventions and their 'current practice' comparator, as well as associated cost offsets. Due process was achieved through involvement of stakeholders, consensus decisions informed by briefing papers and 2nd stage filter analysis that captures broader factors that influence policy judgements in addition to cost-effectiveness results. The 2nd stage filters agreed by stakeholders were 'equity', 'strength of the evidence', 'feasibility of implementation', 'acceptability to stakeholders', 'sustainability' and 'potential for side-effects'.

Results : The intervention costs varied considerably, both in absolute terms (from cost saving [6 interventions] to in excess of AUD50m per annum) and when expressed as a 'cost per child' estimate (from <AUD1.0 [reduction of TV advertising of high fat foods/high sugar drinks] to >AUD31,000 [laparoscopic adjustable gastric banding for morbidly obese adolescents]). High costs per child reflected cost structure, target population and/or under-utilisation.

Conclusions : The use of consistent methods enables valid comparison of potential intervention costs and cost-offsets for each of the interventions. ACE-Obesity informs policy-makers about cost-effectiveness, health impact, affordability and 2nd stage filters for important options for preventing unhealthy weight gain in children. In related articles cost-effectiveness results and second stage filter considerations for each intervention assessed will be presented and analysed.

Estimating the contribution of carnivorous waterbirds to nutrient loading in freshwater habitats

1. We estimated nitrogen (N) and phosphorus (P) loading into wetlands by carnivorous waterbirds with alternative physiological models using a food-intake and an excreta-production approach. The models were applied for non-breeding and breeding Dutch inland carnivorous waterbird populations to quantify their contribution to nutrient loading on a landscape scale.

2. Model predictions based on food intake exceeded those based on excretion by 59–62% for N and by 2–36% for P, depending on dietary assumptions. Uncertainty analysis indicated that the intake model was most affected by errors in energy requirement, while the excretion model was dependent on faecal nutrient composition.

3. Per capita loading rate of non-breeders increased with body mass from 0.3–0.8 g N day⁻¹ and 0.15 g P day⁻¹ in little gulls Larus minutus to 4.5–11.5 g N day⁻¹ and 2.1–3.2 g P day⁻¹ in great cormorants Phalacrocorax carbo. For breeding birds, the estimated nutrient loading by a family unit over the entire breeding period ranged between 17.6–443.0 g N and 8.6 g P for little tern Sterna albifrons to 619.6–1755.6 g N and 316.2–498.1 g P for great cormorants.

4. We distinguished between external (i.e. importing) and internal (i.e. recycling) nutrient loading by carnivorous waterbirds. For the Netherlands, average external-loading estimates ranged between 38.1–91.5 tonnes N and 16.7–18.2 tonnes P per year, whilst internal-loading estimates ranged between 53.1–140.5 tonnes N and 25.2–39.2 tonnes P and per year. The average contribution of breeding birds was estimated to be 17% and 32% for external and internal loading respectively. Most important species were black-headed gull Larus ridibundus and mew gull Larus canus for external loading, and great cormorant and grey heron Ardea cinerea for internal loading.

5. On a landscape scale, loading by carnivorous waterbirds was of minor importance for freshwater habitats in the Netherlands with 0.26–0.65 kg N ha⁻¹ a⁻¹ and 0.12–0.16 kg P ha⁻¹ a⁻¹. However, on a local scale, breeding colonies may be responsible for significant P loading.

Modelling of potential food policy interventions in Fiji and Tonga and their impacts on noncommunicable disease mortality

Background: To compare the likely costs and benefits of a range of potential policy interventions in Fiji and Tonga targeted at diet-related noncommunicable diseases (NCDs), in order to support more evidence-based decision-making.

Method: A relatively simple and quick macro-simulation methodology was developed. Logic models were developed by local stakeholders and used to identify costs and dietary impacts of policy changes. Costs were confined to government costs, and excluded cost offsets. The best available evidence was combined with local data to model impacts on deaths from noncommunicable diseases over the lifetime of the target population. Given that the modelling necessarily entailed assumptions to compensate for gaps in data and evidence, use was made of probabilistic uncertainty analysis.

Results: Costs of implementing policy changes were generally low, with the exception of some requiring additional long-term staffing or construction activities. The most effective policy options in Fiji and Tonga targeted access to local produce and high-fat meats respectively, and were estimated to avert approximately 3% of diet-related NCD deaths in each population. Many policies had substantially lower benefits. Cost-effectiveness was higher for the low-cost policies. Similar policies produced markedly different results in the two countries.

Conclusion: Despite the crudeness of the method, the consistent modelling approach used across all the options, allowed reasonable comparisons to be made between the potential policy costs and impacts. This type of modelling can be used to support more evidence-based and informed decision-making about policy interventions and facilitate greater use of policy to achieve a reduction in NCDs.

Organized blood pressure control programs to prevent stroke in Australia : would they be cost-effective?

Background and Purpose—: High blood pressure (BP) is the most important modifiable stroke risk factor. Worldwide high BP in many people is uncontrolled or people are unaware of their BP status. We aimed to assess whether a program of organized multidisciplinary care and medication would be cost-effective for improving BP control for the prevention of stroke.

Methods—: A novel aspect was to simulate the intervention to match recent primary care initiatives (eg, new Medicare reimbursement items) to ensure policy relevance. Current practice and additional costs of each intervention were included using the best available evidence. The differences in the cost per quality-adjusted life year (QALY) gained for the interventions were compared against current practice. Cost-effectiveness was defined as cost per QALY gained was less than Australian dollars (AUD) 50 000 (societal perspective; reference year 2004). The robustness of estimates was assessed with probabilistic multivariable uncertainty analysis.

Results—: For primary prevention, the median cost per QALY gained was AUD11 068 (95% uncertainty interval AUD5201 to AUD18 696) in those aged 75 years or older and was AUD17 359 (95% uncertainty interval AUD10 516 to AUD26 036) in those aged 55 to 84 years with >=15% absolute risk of stroke. Primary prevention interventions were not cost-effective if aged younger than 50 years. The median cost per QALY gained for secondary prevention was AUD1811 and AUD4704, depending on which medications were modeled.

Conclusions—: Organized care for BP control targeted at specific populations offers excellent value over current practice. Organized care for secondary prevention provided the greatest benefits and strongest cost-effectiveness. Translation into clinical practice requires improved use of relevant Medicare policy in Australia.

A discrete simulation approach to spatial allocation of commodity production for revenue optimisation over a local region

A simulation approach is described for the spatial allocation of crops across a region in order to maximise total revenue. The model uses inputs from GIS-based land suitability analysis to provide data on yields for a range of commodities, where the land suitability for the crops can be determined by either biophysical models or multi-criteria analysis. The objective of the study was to gain some indication of the magnitude of improvement possible in revenue, based on the convergence results for the optimisation (subject to estimated production quantities and market prices). The basic structure of the model allows for scaling up to larger problems with additional inputs and finer cell resolution. The software produces a visualisation of crop spatial allocation across the region and is compatible with statistical uncertainty analysis. The results of model simulations revealed a significant increase in revenue is possible using this approach and, when projected over the full region, suggests the possibility of significant economic benefits.

Adaptation to climate change in regional Australia : a decision-making framework for modelling policy for rural production

A decision-making framework was developed and applied in regional Australia to identify adaptation issues arising in agricultural systems and rural production as a consequence of climate change. Australian agriculture is very susceptible to the adverse impacts of climate change, with major shifts in temperature and rainfall projected. An advantage of the framework is that it provides a suite of tools to aid in the formulation of strategies for sustainable regional development and adaptation. The decision-making framework uses a participatory approach that integrates land suitability analysis with uncertainty analysis and spatial optimisation to determine optimal agricultural land use (at a regional scale) for current and possible future climatic conditions. It thus provides a robust analytic approach to (i) recognise regions under threat of productivity declines, (ii) identify alternative cropping systems better adapted to likely future climatic conditions and (iii) investigate policy actions to improve the sub-optimal situations created by climate change. The decision-making framework and its methods were applied in a case study of the South West Region of Victoria.

A modelling framework for optimisation of commodity production by minimising the impact of climate change

The agricultural sector is vulnerable to the impact of climate change due to decreasing rainfall, increasing temperature, and the frequency of extreme weather events. A modelling framework was developed and applied to identify issues, problems and opportunities arising in regional agricultural systems as a consequence of climate change. This integrated framework blends together land suitability analysis, uncertainty analysis and an optimisation approach to establish optimal agricultural land-use patterns on a regional scale for current and possible future climate scenarios. The framework can also be used to identify (i) regions under threat of productivity decline, and (ii) alternative crops and their locations that can cope better with changing climate. The methods and contents of the framework are presented by means of a case study developed in the South West Region of Victoria, Australia. The results can be used to assess land suitability in support of optimised crop allocations across a local region, and to underpin the development of a regional adaptation policy framework designed to reduce the vulnerability of the agriculture sector to the impacts of climate change.

Application of GIS-based computer modelling to planning for adaption to climate change in rural areas

A GIS-based computer modelling methodology was developed and applied to identify climate change adaptation issues arising in regional agricultural production systems (including forestry). Agricultural production in Australia is very susceptible to the adverse impacts of climate change due to projected shifts in rainfall and temperature. The methodology integrates land suitability analysis with uncertainty analysis and spatial (regional) optimisation to determine optimal agricultural land use at a regional scale for current and possible future climatic conditions. The approach can be used to recognise regions under threat of productivity decline, identify alternative cropping systems that may be better adapted to likely future conditions, and investigate implementation actions to improve the sub-optimal situations created by climate change. An example of how the methodology may be used is outlined through a case study involving the South West Region of Victoria, Australia. The case study provides information on the tools available to support the formulation of a regional adaptation strategy.

Stochastic Assessment Of Environmental Flows In Semiarid Environments

The regimen of environmental flows (EF) must be included as terms of environmental demand in the management of water resources. Even though there are numerous methods for the computation of EF, the criteria applied at different steps in the calculation process are quite subjective whereas the results are fixed values that must be meet by water planners. This study presents a friendly-user tool for the assessment of the probability of compliance of a certain EF scenario with the natural regimen in a semiarid area in southern Spain. 250 replications of a 25-yr period of different hydrological variables (rainfall, minimum and maximum flows, ...) were obtained at the study site from the combination of Monte Carlo technique and local hydrological relationships. Several assumptions are made such as the independence of annual rainfall from year to year and the variability of occurrence of the meteorological agents, mainly precipitation as the main source of uncertainty. Inputs to the tool are easily selected from a first menu and comprise measured rainfall data, EF values and the hydrological relationships for at least a 20-yr period. The outputs are the probabilities of compliance of the different components of the EF for the study period. From this, local optimization can be applied to establish EF components with a certain level of compliance in the study period. Different options for graphic output and analysis of results are included in terms of graphs and tables in several formats. This methodology turned out to be a useful tool for the implementation of an uncertainty analysis within the scope of environmental flows in water management and allowed the simulation of the impacts of several water resource development scenarios in the study site.

Does The Risk Of Groundwater Depletion Drive Tube-Well Technology Adoption: A Case Of Pakistan

We employ a moment-based approach to empirically analyse farmer’s decisions about adoption of tube-well technology under depleting groundwater resources using a farm level data from 200 farming households in the Punjab province, Pakistan. The results indicate that the higher the expected profit the greater the probability of adoption. Similarly, with increasing variance the probability of adopting tube-well increases significantly indicating that farmers choose to adopt tube-well technology in order to hedge against production risks. Statistical non-significant the third moment i.e., skewness indicates that farmer generally do not consider downside yield risk when decide to adopt tube-well technology whereas highly significant fourth moment (kurtosis) employ that probability of adoption decreases as a result of extreme events in profit distribution. In addition, we show that land tenureship and three other exogenous variables, i.e., extension services, access to different sources of information and off-farm income play a significant role in the adoption process.