Diagnostic and surveillance algorithm for acute encephalitis syndrome: A systematic approach to etiological identification

Background

Acute Encephalitis Syndrome (AES) is a major public health concern, causing sporadic cases and outbreaks with high morbidity and mortality. Its diverse aetiology includes many zoonotic pathogens, and its diagnosis and management in India are complicated by geographical, seasonal, and cultural diversity, along with limited diagnostic resources. As part of the ICMRs “One Health" initiative, this paper addresses the need for a structured diagnostic and surveillance algorithm to enhance etiological identification and improve AES management and public health response.

Objective

To develop a systematic diagnostic and surveillance algorithm for AES diagnosis, prioritizing investigations based on clinical, epidemiological, and laboratory findings to optimize patient outcomes and strengthen public health interventions.

Result

The proposed approach prioritizes AES etiological diagnosis based on geographical and seasonal pathogen prevalence, alignment with national programs, treatment availability, diagnostic feasibility, clinical and radiological suspicion, and public health surveillance needs. AES cases should be managed at secondary or tertiary care facilities, where appropriate tests can be conducted based on resource feasibility. A subset of positive and negative samples should undergo genomic characterization to identify novel pathogens.

Conclusion

This framework will enhance pathogen identification, improve patient management, and support public health efforts, reinforcing ICMR's commitment to combating AES through the “One Health" approach.