Protocol for nationwide surveillance of Acute Encephalitis Syndrome (AES) in a network of tertiary care hospitals in India.

Background: Advances in laboratory diagnostics have greatly enhanced the understanding of the infectious aetiologies of Acute Encephalitis Syndrome (AES) globally. However, these diagnostic tests are not widely utilized in many public-sector clinical settings in India. Significant gaps thus remain in the knowledge and understanding of the burden, etiological spectrum, and risk factors associated with AES occurring in India.

Methods: The current manuscript outlines a protocol designed to characterize the infectious causes of AES in affected regions of India through a network of 12 selected tertiary care hospitals and their associated Virus Research and Diagnostic Laboratories (VRDLs). A standardized tiered testing algorithm accounting for a wide range of possible etiological agents of infectious AES has been developed for use in the protocol, which aims to employ serological and molecular techniques to diagnose AES-causing priority pathogens. Pathogens of interest have been grouped in the testing algorithm into five levels (Levels 1-5) in decreasing order of priority based on their reported incidence. Clinical samples from each patient will be collected at presentation at respective sites, and relevant demographic and clinical data will be obtained from hospital records. Approximately 20% of samples which test negative for Level 1-4 pathogens will be subjected to Next-Generation Sequencing (NGS) to identify less well known/rare infectious causes of AES (Level 5 pathogens). De-identified clinical and laboratory data will be recorded into a web-based portal and managed by a designated nodal laboratory responsible for coordinating and overseeing the surveillance. The protocol ensures quality laboratory testing through an External Quality and Assessment Programme (EQAP).

Discussion: Results from this nationwide surveillance will yield crucial data to identify the causes of Acute Encephalitis Syndrome (AES) across India, supporting targeted public health interventions that could help reduce the disease burden. Additionally, this protocol serves as a model for a tiered laboratory algorithm for AES surveillance, providing a framework to guide similar initiatives in other regions.