Abstract
INTRODUCTION Health data in low- and middle-income countries are often inconsistent and of poor quality, or simply non-existent. This impedes the ability of countries themselves and the international community to arrive at a precise understanding of national burden of disease patterns. The sophisticated statistical modeling and projection methods used internationally to compensate for missing country data cannot provide more than ‘best estimates,’ with no possibility of verifying their outputs. The result is continuing unnecessary morbidity and mortality, often in children under five years of age, as data deficiency translates into insufficient information to guide policy and technical interventions, and to enable prioritization in resource dissemination. This research therefore aims to assess the quality and quantity of data available at country level for the purpose of estimating the burden of disease. It highlights the frequently weak and fragmented nature of what data is present, together with capacity deficiencies at both institutional and individual level to gather, analyse and interpret health and related data. A particular focus is placed on assessing the burden of disease attributable to environmental risk factors, specifically for unsafe water, sanitation and hygiene, together with those elements of malnutrition deriving directly from these factors. Combining these two sets of risk factors to derive estimates of their burden of disease at country level is a new approach and not yet undertaken by countries. METHODS Case-study is the central method used. Two country cases (Uganda and Mozambique) were selected by convenience sampling as WHO missions on related topics were taking place at this time. Detailed information on institutional and individual data understanding and capacity was obtained through semi-structured interviews. Extensive evaluation or assessment of existing data and internationally applied methodologies has also been carried out to demonstrate the extent and impact of the present data weakness and paucity that form the rationale for carrying out this work. Other cases have been used to demonstrate the synthesis of water, sanitation and hygiene statistics and methods with those of malnutrition. RESULTS Enabling a move from globally generated estimates based on limited national data in which country users have little confidence, to better quality and reliable statistics based on stronger national data is the root of this study. Having clarified the health impacts of data deficiency, its principal contribution is the development and testing of a tool to overcome these deficiencies, offering country users a way to radically improve their national data systems. A prototype National Burden of Disease (NBD) Toolkit had earlier been developed by WHO but had operational weaknesses and hence poor uptake by countries. Moving from problem analysis to problem solving, this study has devised a method of linking the various spreadsheets comprising the NBD, creating a logical, simplified, and systematic interface between its elements and thereby making it easier and more appealing to the user. The tool, with its user-friendly interface, can thus now become a suitable support to national-level burden of disease estimation work, and contribute to creating further awareness of the value of timely data and their role in health development. DISCUSSION The present scope of work with the tool and interface fills a pressing gap, yet is limited. Further testing in a wider range of countries in different geographic regions is needed. Nonetheless, the initial results and growing uptake give confidence that this and similar future approaches will fall on fertile ground. As country-level institutions become more accustomed to using tools of this kind to fill long-standing data gaps and quality issues, it can be anticipated that they will feel greater confidence in their own data, reduced reliance on internationally-generated estimates and projections that are frequently not well understood, and an increased sense of ownership over the national process. CONCLUSION Greater capacity and confidence in the domain of data management will feed directly into health research and improvements in health planning and interventions. Key among these are improvements in access to safe water, sanitation and hygiene – an area in which data are notoriously elusive. As the world now moves towards a revised global framework for development goals and targets after 2015, a stronger and more effective evidence base is more critical than ever.