Assessment of the acute encephalitis surveillance system in Bongaigaon district of Assam, India, 2020

Introduction: Japanese encephalitis (JE) is a significant cause of acute encephalitis syndrome (AES) in Asia, with Northeast India, particularly Assam, being a hotspot. Effective surveillance is crucial for disease control. This study aims to describe the AES surveillance system in Bongaigaon distri...

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Main Authors: Hiren Gogoi, Mohammad Ahmad, Kapil Goel, Arunima Sen, Kalyani Dabbagatla
Format: Article
Language:English
Published: Wolters Kluwer Medknow Publications 2025-05-01
Series:Journal of Family Medicine and Primary Care
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Online Access:https://journals.lww.com/10.4103/jfmpc.jfmpc_1445_24
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Summary:Introduction: Japanese encephalitis (JE) is a significant cause of acute encephalitis syndrome (AES) in Asia, with Northeast India, particularly Assam, being a hotspot. Effective surveillance is crucial for disease control. This study aims to describe the AES surveillance system in Bongaigaon district, Assam, assess its attributes, and provide recommendations for improvement. Methods: The weekly compilation reports (Forms P, S, L) submitted by 34 sentinel surveillance sites were reviewed from January 2018 to December 2020. Nodal officers and health providers were interviewed from 38 government and one private health care facilities using a semistructured questionnaire. Result: A total of 51 AES cases and 32 JE cases were identified. The overall positivity rate was 38.6% and the case fatality rate was 18% for AES and 25% for JE. Maximum JE cases (66%) were in the age group >31 years. No JE-positive case was found below 5 years. The case incidence was 6.90 for AES and 4.33 for JE per 100,000 population. Only 1% was vaccinated. The quality of surveillance was good for most indicators, except timeliness of case detection, and representativeness of private hospitals which were found to be moderate. Conclusion: The AES surveillance system in Bongaigaon district is well established. Overall, the system is simple and acceptable and has good data quality but requires improvement for timeliness of suspected case reporting and representativeness. Inclusion of potential private hospitals in the reporting system and regular orientation of nodal officers and health care providers would improve case detection and reporting.
ISSN:2249-4863
2278-7135