Although numerous difficulties are associated with prevalence estimation, estimates are necessary to make practical decisions for resource allocation and program planning. Development in at least three areas is needed to improve drug prevalence estimation: (1) improving the understanding of drug use phenomena; (2) consistent, comprehensive, and accurate data collection systems; and (3) continued development and improved use of appropriate estimation techniques. An estimate derived by any particular method is the result of interplay between theory, methodology, and empirical data. Choice of the estimation model depends on the phenomenon under study and on available data. By applying multiple approaches, each capitalizing on some salient aspect of the prevalence problem, confidence in the results is increased or at least inconsistencies are identified. In addition, alternative models using different approaches and data sources are necessary to validate each other when estimates overlap. The resulting multiple-mode approach is considered to be appropriate in prevalence estimation for making policy decisions on enforcement, treatment, and prevention. The authors discuss sampling, self-report validity, event-based and person-based data systems, static estimation models, synthetic estimation techniques, closed and open population models, dynamic models, and system dynamics modeling. 71 references and 2 tables
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