Assessing data availability for the development of REDD-plus national reference levels

<p>Abstract</p> <p>Background</p> <p>Data availability in developing countries is known to be extremely varied and is one of the constraints for setting the national reference levels (RLs) for the REDD-plus (i.e. 'Policy approaches and positive incentives on issues relating to reducing emissions from deforestation and forest degradation in developing countries; and the role of conservation, sustainable management of forests and enhancement of forest carbon stocks in developing countries') under the UNFCCC. Taking Thailand as a case study country, this paper compares three types of RLs, which require different levels of datasets, including a simple historic RL, a projected forest-trend RL, and a business-as-usual (BAU) RL.</p> <p>Results</p> <p>Other than the finding that different RLs yielded different estimations on future deforestation areas, the analysis also identified the characteristics of each RL. The historical RL demanded simple data, but can be varied in accordance with a reference year or period. The forest-trend RL can be more reliable than the historical RL, if the country's deforestation trend curve is formed smoothly. The complicated BAU RL is useful as it can demonstrate the additionality of REDD-plus activities and distinguish the country's unintentional efforts.</p> <p>Conclusions</p> <p>With the REDD-plus that involves widespread participation, there should be steps from which countries choose the appropriate RL; ranging from simpler to more complex measures, in accordance with data availability in each country. Once registered with REDD-plus, the countries with weak capacity and capability should be supported to enhance the data collection system in that country.</p

Estimating health workforce needs for antiretroviral therapy in resource-limited settings

BACKGROUND: Efforts to increase access to life-saving treatment, including antiretroviral therapy (ART), for people living with HIV/AIDS in resource-limited settings has been the growing focus of international efforts. One of the greatest challenges to scaling up will be the limited supply of adequately trained human resources for health, including doctors, nurses, pharmacists and other skilled providers. As national treatment programmes are planned, better estimates of human resource needs and improved approaches to assessing the impact of different staffing models are critically needed. However there have been few systematic assessments of staffing patterns in existing programmes or of the estimates being used in planning larger programmes. METHODS: We reviewed the published literature and selected plans and scaling-up proposals, interviewed experts and collected data on staffing patterns at existing treatment sites through a structured survey and site visits. RESULTS: We found a wide range of staffing patterns and patient-provider ratios in existing and planned treatment programmes. Many factors influenced health workforce needs, including task assignments, delivery models, other staff responsibilities and programme size. Overall, the number of health care workers required to provide ART to 1000 patients included 1–2 physicians, 2–7 nurses, <1 to 3 pharmacy staff, and a much wider range of counsellors and treatment supporters. We estimate from these data that the equivalent of 20 000 to 100 000 physicians, nurses, pharmacists and other core clinical staff will be needed to meet the WHO target of treating 3 million people by the end of 2005. The total number of staff, including counsellors, administrators and other cadres, could be substantially higher. DISCUSSION: These data are consistent with other estimates of human resource requirements for antiretroviral therapy, but highlight the considerable variability of current staffing models and the importance of a broad range of factors in determining personnel needs. Few outcome or cost data are currently available to assess the effectiveness and efficiency of different staffing models, and it will be important to develop improved methods for gathering this information as treatment programmes are scaled up