Detection and discovery of viral pathogens associated with dengue-like symptoms

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Large-scale viral surveillance studies are critical to monitoring the global emergence of infectious disease and yield important information about the prevalence and seasonality of circulating virus species and the possible existence of novel species. Many large epidemiologic studies that have been conducted in temperate countries have not been repeated in tropical settings, however, and are likely to reveal viral burden and incidence variations due to inherent environmental and social differences. Dengue virus (DV) is an archetypal emerging infectious disease that infects an estimated 50-100 million people annually in a rapidly expanding geographic range and is the most common vector-borne viral disease of humans. Currently available lab diagnostic methods, however, fail to detect DV infection in 30-70% of patients presenting with hallmark dengue symptoms. The purpose of this study is twofold: to use the best available diagnostic technologies to delineate the spectrum of viral pathogens in a developing tropical environment with respect to dengue-like illnesses and to utilize the data provided by the extensive screening as a platform for the discovery of novel or divergent human viral pathogens. In collaboration with Eva Harris, this study will use the Virochip (UCSF) to characterize human sera and PBMC samples from Nicaraguan patients from the proposed hospital-based study presenting with dengue-like symptoms over multiple seasons. This will allow us to capture both the prevalence, seasonality and dual infection rates for all known viruses in suspected dengue cases over time. We also propose to utilize ultra-deep sequencing for a select number of samples based on several criteria including severity of symptoms for discovery of previously uncharacterized agents. We will pursue full genome cloning and molecular characterization for promising leads, including development of PCR-based rapid diagnostics and serological reagents for subsequent association studies.