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A Murine Model of Dengue Virus-induced Acute Viral Encephalitis-like Disease
Published on: April 28, 2019
Etiological Profile and Clinico Epidemiological Patterns of Acute Encephalitis Syndrome in Tamil Nadu, India
Vijayan Senthil Kumar1, Srinivasan Sivasubramanian1, Padmapriya Padmanabhan1
1Department of Virology, State Viral Research and Diagnostic Laboratory, King Institute of Preventive Medicine and Research, Chennai, Tamil Nadu, India.
Introduction:
Establishing the etiological cause of acute encephalitis syndrome (AES) is challenging due to the distinct distribution of various etiological agents. This study aims to determine the etiological profiles of both viruses and bacteria and their associated clinico-epidemiological features among the AES suspected cases in Tamil Nadu, India.
Methods:
Samples of 5136 suspected AES cases from January 2016 to December 2020 (5 years) were subjected to the detection of etiological agents for AES through serological and molecular diagnosis methods. Further, the clinical profile, age- and gender-wise susceptibility of cases, co-infection with other AES etiological agents, and seasonality pattern with respect to various etiological agents were examined.
Results:
AES positivity was established in 1480 cases (28.82%) among the 5136 suspected cases and the positivity for male and female groups were 57.77% and 42.23%, respectively. The pediatric group was found to be more susceptible than others. Among the etiological agents tested, the Japanese encephalitis virus (JEV) was the predominant followed by Cytomegalovirus, Herpes Simplex virus, Epstein-Barr virus, Varicella Zoster virus, and others. Co-infection with other AES etiological agents was observed in 3.5% of AES-positive cases. Seasonality was observed only for vector-borne diseases such as JEV, dengue virus, and West Nile virus infections in this study.
Conclusion:
AES was found to be a significant burden for Tamil Nadu with a diverse etiological spectrum including both sporadic and outbreak forms. Overlapping clinical manifestations of AES agents necessitate the development of region-specific diagnostic algorithm with distinct etiological profiles for early detection and effective case management.
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