Use of diagnostic algorithms and new technologies to study the incidence and prevalence of viral upper respiratory tract infections and their complications in high risk populations

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Abstract
Most studies on the natural history of viral upper respiratory tract infections and their complications rely for ascertainment on self-assessed cold/flu illness or the identification of presumed complications. The criteria for cold/flu definition, however, are variable within and between individuals and illness is not prerequisite for a viral upper respiratory tract infection. These factors bias estimates of the incidence and prevalence of viral upper respiratory tract infections and their complications. Here we review new methodologies that can be adapted for use in future studies to refine those estimates. We present a theoretical basis for standardized assignment of cold/flu episodes using a minimal algorithm template that operates on a structured set of symptoms/signs. We emphasize the greater accuracy of information derived from longitudinal studies that incorporate identification algorithms and assay of nasal secretions for causal virus by polymerase chain reaction and for proinflammatory chemicals to confirm nasal inflammation. The methodologies and sampling strategies that we describe hold promise for better characterizing the incidence of complications for symptomatic and asymptomatic expressions of a viral upper respiratory tract infection caused by specific viruses. These data can then be used to estimate the efficacy and efficiency in a specified target population of prophylactic or intercurrent treatments to prevent the complications.