Multidisciplinary studies of disease burden in the Diseases of the Most Impoverished Programme.

Jacqueline LDeen; Lorenzvon Seidlein; John DClemens; (2004) Multidisciplinary studies of disease burden in the Diseases of the Most Impoverished Programme. Journal of health, population, and nutrition, 22 (3). pp. 232-239. ISSN 1606-0997 https://material-uat.leaf.cosector.com/id/eprint/10256
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With limited healthcare resources, rational prioritization of healthcare interventions requires knowledge and analysis of disease burden. In the absence of actual disease-burden data from less-developed countries, various types of morbidity and mortality estimates have been made. Besides having questionable reliability, these estimates do not capture the full burden of a disease since they provide only the number of cases and deaths. The modelling methods that include disability are more comprehensive but are difficult to understand, and their reliability is affected by baseline approximations. To provide policy-makers with information needed for rational decision-making, the Diseases of the Most Impoverished (DOMI) Programme of the International Vaccine Institute has used a multidisciplinary approach to describe the burden of disease due to typhoid fever, shigellosis, and cholera. Recognizing the relative advantages and disadvantages of various methodologies, the programme employs passive clinic-based surveillance in defined communities to provide prospective data. The prospective data are complemented with retrospectively-collected information from existing sources, frequently less accurate and complete but readily available for the whole population over extended periods. To create a more complete picture, economic and qualitative studies specific to each disease are incorporated in these prospective studies. The goal is to achieve a more complete and realistic picture by combining the results of these various methodologies, acknowledging the strengths and limitations of each. These projects also build in-country capacity in terms of treatment, diagnosis, epidemiology, and data management.


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