Estimating the duration and cost of weed eradication programmes

Two prerequisites for realistically embarking upon an eradication programme are that cost-benefit analysis favours this strategy over other management options and that sufficient resources are available to carry the programme through to completion. These are not independent criteria, but it is our view that too little attention has been paid to estimating the investment required to complete weed eradication programmes. We deal with this problem by using a two-pronged approach: 1) developing a stochastic dynamic model that provides an estimation of programme duration; and 2) estimating the inputs required to delimit a weed incursion and to prevent weed reproduction over a sufficiently long period to allow extirpation of all infestations. The model is built upon relationships that capture the time-related detection of new infested areas, rates of progression of infestations from the active to the monitoring stage, rates of reversion of infestations from the monitoring to active stage, and the frequency distribution of time since last detection for all infestations. This approach is applied to the branched broomrape (Orobanche ramosa) eradication programme currently underway in South Australia. This programme commenced in 1999 and currently 7450 ha are known to be infested with the weed. To date none of the infestations have been eradicated. Given recent (2008) levels of investment and current eradication methods, model predictions are that it would take, on average, an additional 73 years to eradicate this weed at an average additional cost (NPV) of $AU67.9m. When the model was run for circumstances in 2003 and 2006, the average programme duration and total cost (NPV) were predicted to be 159 and 94 years, and $AU91.3m and $AU72.3m, respectively. The reduction in estimated programme length and cost may represent progress towards the eradication objective, although eradication of this species still remains a long term prospect.

Reducing the global burden of depression : population level analysis of intervention cost-effectiveness in 14 world regions

International evidence on the cost and effects of interventions for reducing the global burden of depression remain scarce. Aims: To estimate the population-level cost-effectiveness of evidence-based depression interventions and their contribution towards reducing current burden. Method: Primary-care-based depression interventions were modelled at the level of whole populations in 14 epidemiological subregions of the world. Total population-level costs (in international dollars or I$) and effectiveness (disability adjusted life years (DALYs) averted) were combined to form average and incremental cost-effectiveness ratios. Results: Evaluated interventions have the potential to reduce the current burden of depression by 10–30%. Pharmacotherapy with older antidepressant drugs, with or without proactive collaborative care, are currently more cost-effective strategies than those using newer antidepressants, particularly in lower-income subregions. Conclusions: Even in resource-poor regions, each DALYaverted by efficient depression treatments in primary care costs less than 1 year of average per capita income, making such interventions a cost-effective use of health resources. However, current levels of burden can only be reduced significantlyif there is a substantialincrease substantial increase intreatment coverage.

Correcting for bias when estimating the cost of hospital-acquired infection : an analysis of lower respiratory tract infections in non-surgical patients

Hospital acquired infections (HAI) are costly but many are avoidable. Evaluating prevention programmes requires data on their costs and benefits. Estimating the actual costs of HAI (a measure of the cost savings due to prevention) is difficult as HAI changes cost by extending patient length of stay, yet, length of stay is a major risk factor for HAI. This endogeneity bias can confound attempts to measure accurately the cost of HAI. We propose a two-stage instrumental variables estimation strategy that explicitly controls for the endogeneity between risk of HAI and length of stay. We find that a 10% reduction in ex ante risk of HAI results in an expected savings of £693 ($US 984).