Only 5.4% of the world's population was covered by comprehensive smoke-free laws in 2008, up from 3.1% in 2007, according to the World Health Organization’s (WHO) second report on the global tobacco epidemic. The report also describes countries' efforts to implement the tobacco control package called MPOWER, which WHO introduced in 2008 to help countries implement some of the demand reduction measures in the WHO Framework Convention and its guidelines. These measures are: monitor tobacco use and the policies to prevent it; protect people from tobacco smoke; offer people help to quit tobacco use; warn about the dangers of tobacco; enforce bans on tobacco advertising, promotion and sponsorship; and raise taxes on tobacco. Less than 10% of the world's population is covered by any one measure, the report states. The report tracks the global tobacco epidemic, giving governments and other stakeholders a tool to see where evidence-based demand reduction interventions have been implemented and where more progress is needed. It gives country-by-country tobacco use prevalence figures as well as data about cigarette taxation, bans on tobacco advertising, promotion and sponsorship, support for treatment of tobacco dependence, enforcement of tobacco-free laws and monitoring of the epidemic.
Monitoring equity and research policy
This report presents a historical reflection on research evaluation studies, their recurrent themes and challenges, and their implications. It critically examines studies of how scientific research drives innovation and socioeconomic benefits. First, it provides a predominantly descriptive historical overview of some landmark studies in the research evaluation field, from the late 1950s until the present day, and highlights some of their key contributions. Then, it reflects on the historical overview analytically, in order to discuss some of the methodological developments and recurrent themes in research evaluation studies. The report concludes by discussing the enduring challenges in research evaluation studies and their implications. The authors emphasise that this report does not address all of the key studies in the research evaluation field. The evaluation literature today is so extensive that a selective approach is necessary to focus on those studies that they feel provide the most valuable insights in the context of biomedical and health research evaluation.
Researchers should protect the welfare of research participants by providing methods to reduce their risk of acquiring HIV. This is especially important given that late-phase HIV vaccine trials enrol HIV-uninfected trial volunteers from high-risk populations. This study recommends that current normative guidance be systematically reviewed and actual practice at vaccine sites be documented. Adding new tools to the current package of prevention services will involve complex decision making with few set standards, and regulatory and scientific challenges. The paper recommends that stakeholders (including regulators) should convene to consider standards of evidence for new tools, and that decision-making processes be explicitly documented and researched. A further critical ethical task is exploring the threshold at which adding new tools will compromise the validity of trial results.
This paper sought to investigate the feasibility, the ease of implementation, and the extent to which community health workers with little experience of data collection could be trained and successfully supervised to collect data using mobile phones in a large baseline survey. A web-based system was developed to allow electronic surveys or questionnaires to be designed (on a word processor), sent to, and conducted on standard entry level mobile phones. The web-based interface permitted comprehensive daily real-time supervision of CHW performance, with no data loss. The system permitted the early detection of data errors in combination with real-time quality control and data collector supervision. In conclusion, the benefits of mobile technology, combined with the improvement that mobile phones offer over personal digital assistants (PDAs) – or palmtop computers – in terms of data loss and uploading difficulties, make mobile phones a feasible method of data collection that needs to be further explored.
This paper studied policymaking processes in Mozambique, South Africa and Zimbabwe to understand the factors affecting the use of research evidence in national policy development, with a particular focus on the findings from randomised control trials. It used a qualitative case-study methodology to explore the policy-making process. It carried out key informants interviews with a range of research and policy stakeholders in each country, reviewed documents and developed timelines of key events. Prior experience of particular interventions, local champions, stakeholders and international networks, and the involvement of researchers in policy development were important in knowledge translation for both case studies. In contrast to treatment policies for eclampsia, a diverse group of stakeholders with varied interests, differing in their use and interpretation of evidence, was involved in malaria policy decisions in the three countries. The paper concluded that translating research knowledge into policy is a complex and context sensitive process. Researchers aiming to enhance knowledge translation need to be aware of factors influencing the demand for different types of research; interact and work closely with key policy stakeholders, networks and local champions; and acknowledge the roles of important interest groups.
This paper aims to assess current priority setting methods and the extent to which they adequately include health policy and systems research (HPSR) and to draw out lessons regarding how HPSR priority setting can be enhanced to promote relevant HPSR and to strengthen developing country leadership of research agendas. Priority setting processes can be distinguished by the level at which they occur, their degree of comprehensiveness in terms of the topic addressed, the balance between technical versus interpretive approaches and the stakeholders involved. When HPSR is considered through technical, disease-driven priority setting processes it is systematically under-valued. More successful approaches for considering HPSR are typically nationally driven, interpretive and engage a range of stakeholders. There is still a need however for better defined approaches to enable research funders to determine the relative weight to assign to disease specific research versus HPSR and other forms of cross-cutting health research. While country-level research priority setting is key, there is likely to be a continued need for the identification of global research priorities for HPSR. The paper argues that such global priorities can and should be driven by country level priorities.
Performance targets for global TB control were first formulated in 1991 at the 44th World Health Assembly. National TB control programmes were encouraged to achieve CDRs of at least 70% and cure rates in excess of 85%. However, even in situations where both targets were reached and achievements sustained, incidence rates failed to decline as predicted. The vast differences that exist between endemic and non-endemic areas (in other words, case density) and the impact this has on transmission dynamics within communities are rarely appreciated. Most source cases have fairly fixed circles of social interaction. This implies that once the majority of close contacts have been infected, the risk of infecting new people may decline even though the source case remains highly infectious. This phenomenon is referred to as transmission saturation. There is a need to reconsider the accuracy and applicability of current mathematical models and to identify pragmatic ways of quantifying additional factors that may be at play in endemic areas. The incorporation of case density and transmission saturation in future mathematical models may assist.
This article addresses considerations of equity. Policies or programmes that are effective can improve the overall health of a population. However, the impact of such policies and programmes on inequities may vary: they may have no impact on inequities, they may reduce inequities, or they may exacerbate them, regardless of their overall effects on population health. Four questions are proposed as useful to guide equity analysis: Which groups or settings are likely to be disadvantaged in relation to the option being considered? Are there plausible reasons for anticipating differences in the relative effectiveness of the option for disadvantaged groups or settings? Are there likely to be different baseline conditions across groups or settings such that that the absolute effectiveness of the option would be different, and the problem more or less important, for disadvantaged groups or settings? Are there important considerations that should be made when implementing the option in order to ensure that inequities are reduced, if possible, and that they are not increased?
This article addresses the use of evidence to inform judgements about the balance between the pros and cons of policy and programme options. It suggests five questions that can be considered when making these judgements: What are the options that are being compared? What are the most important potential outcomes of the options being compared? What is the best estimate of the impact of the options being compared for each important outcome? How confident can policymakers and others be in the estimated impacts? Is a formal economic model likely to facilitate decision making?
This article addresses the issue of decision making in situations in which there is insufficient evidence at hand. Policymakers often have insufficient evidence to know with certainty what the impacts of a health policy or programme option will be, but they must still make decisions. The article suggests four questions that can be considered when there may be insufficient evidence to be confident about the impacts of implementing an option: Is there a systematic review of the impacts of the option? Has inconclusive evidence been misinterpreted as evidence of no effect? Is it possible to be confident about a decision despite a lack of evidence? Is the option potentially harmful, ineffective or not worth the cost?