| dc.description.abstract | Introduction: Attributing a causative agent to any Acute Febrile Illness (AFI) in a timely manner remains challenging, yet an important task towards clinical care and public health response. Therefore, there is need for a diagnostic assay with capacity to detect a wide array of pathogen targets. This study aims at examining the utility of the AFI TaqMan Array Card (AFI-TAC) for differential diagnosis of AFI causing etiologies, verification of s its performance and characterization of pathogens detected. This study will help enhance timely diagnosis of AFIs, precise patient care and management. Methods: This was a cross-sectional retrospectivestudy.VHF negative blood and plasma samples archived at the Uganda Virus Research Institute-Viral Hemorrhagic Fevers (UVRI-VHF) Laboratory (August 2018 to March 2019) were tested on AFI-TAC while previously positive samples were used for assay verification. The nucleic acids were extracted by Magmax bead-based method and analyzed using AFI-TAC comprising of 35 pathogen targets (17 viral targets, 13 bacterial targets, and 5 protozoa targets) and 6 intrinsic controls by RT-PCR followed by sequencing of the V4 region of the16S rRNA gene of bacterial agents identified. Results: A total of 182 were included of which 152 (81.7%) were from Uganda, 22 (11.8%) from Democratic Republic of Congo, 7 (3.76%) from South Sudan, and1 (0.54%) from Kenya. the median age was of 27 years, the majority being 145 adults, (80%) and37 (20%) children. TAC detected seven pathogen targets including 50 Plasmodium species (26.9%) of which 34 were Plasmodium falciparum, 2 Yellow fever virus (1.07%), 3 non-typhus salmonella (1.6%), Salmonella typhi (1.07%), 1Leptospira (0.54%), Streptococcus pneumonia (0.54%), and Rickettsia (0.54%).Next Generation Sequencing (NGS)of the V4 region of the 16S rRNA gene revealed Proteobacteria as the dominant phylum in each sample. Conclusion: The use of TAC is feasible, readily adoptable in the Ugandan setting and may be incorporated in the national testing algorithm for routine differential diagnostics of AFIs. | en_US |
