Sample-to-Answer Rapid, Multiplexed and PCR-Free Detection of Arboviral Fever Diseases in Resource Limited Settings
Arthropod-borne viruses (arboviruses) comprise many of the most important ‘emerging pathogens’ due to their geographic spread and their increasing impact on vulnerable human populations. Arboviral diseases are poised to become more common with globalization. We have demonstrated high seroprevalence for flaviviruses in multiple regions with marked regional variability and have documented the occurrence of many unrecognized human arboviral infections.
Diagnostics are lacking at health care centers making accurate diagnosis of these infections impossible. The similarity of symptoms to other illnesses means that effective diagnosis will work best if diagnostic systems are able to simultaneously check for the presence of multiple possible infectious agents in a rapid fashion at point of care settings. Despite significant effort in developing new diagnostic technologies, there is strong evidence showing that current front-line diagnostic approaches do not always correctly identify arboviral diseases. Without accurate diagnostics, arbovirus outbreaks are detected late, and sporadic cases go undetected, leading to delayed response to outbreaks, ineffective effort to prevent further disease spread, and substantial introduction risk to naïve countries. There is urgent need for easy-to-operate and rapidly deployable clinical diagnostics tools that can provide sample-to-answer manner.
This research program will lead to field deployable rapid assays for detection of three high-impact biodefense pathogens: dengue virus strains 1 through 4 (DENV1-4); zika virus (ZIVK); and chikungunya virus (CHIKV). The integrated diagnostic platform will utilize a novel surrogate approach, and open source robotics technology. The system will be designed to initiate diagnosis from serum/plasma/blood and provide a sample-to answer diagnostic within less than 35 minutes. This collaborative interdisciplinary program will build upon ongoing field surveillance of arboviral infections in Grenada, extending application of our novel approach to development of a clinical platform for low-risk successful technology to the diagnosis of biodefense arboviral pathogens in humans from ongoing Grenadian surveillance programs in the validation phase of this application. Collaborative work for this NIH/NIAID R01 project involves integration of biosensor engineering (Yanik Group), molecular virology (Pinsky Group), and infectious diseases epidemiology (LaBeaud Group) to build and field-test our novel point-of-care viral diagnostic platform with Windward Islands Research and Education Foundation (WINDREF) and St. George’s University teams. Our proposed work is innovative, as it is using a novel approach to solve a long-standing problem, rapid and accurate arboviral diagnosis in health care settings. Once this project is successfully completed, our collaborations will ensure that project findings are realized in policy and prevention efforts at all levels and will translate into effective intervention platforms.
PI: Ali Ahmet Yanik, Desiree LaBeaud, Ben Pinsky