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

Abstract

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.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12879-025-10963-x.

Background

Acute Encephalitis Syndrome (AES) comprises a group of clinically similar neurologic manifestations caused by different viruses, bacteria, fungi, parasites, spirochetes and chemical/toxins [1]. The definition of AES, which includes fever and altered sensorium (is characterized by a deviation from baseline mental status, which can be transient or permanent, and is often indicative of underlying neurological, metabolic, or systemic disorders) [2], is however broad enough to encompass a wide spectrum of acute central nervous system (CNS) infections, such as meningitis, meningo-encephalitis, and encephalitis [3–5].

AES is a major public health concern in India wherein annual outbreaks are reported from several regions. Yearly outbreaks of AES in India are marked by cases with extended hospitalization, high morbidity and mortality, predominantly affecting children across various regions [6–8].

The etiological spectrum of AES varies across states in India, influenced by differences in environmental, geographical, climatic, socio-economic factors, and the prevalence of specific pathogens [3, 6]. Until 1973, AES outbreaks were sporadically reported mainly from southern India [7]. However, AES outbreaks have since expanded to other regions and are now endemic in 355 districts across 24 states in the country [7–10].

The epidemiology of AES in India has been shaped by socio-economic and geographical factors, leading to regional variations in etiology, transmission, and fatality rates. The first major outbreak of Acute Encephalitis Syndrome (AES) caused by Japanese Encephalitis Virus (JEV) was reported in West Bengal in 1973, resulting in 700 cases and 300 deaths [11]. This was followed by a severe AES epidemic in Uttar Pradesh in 1978, which recorded over 3,500 cases and 1,100 deaths (CFR: 33%), marking the beginning of recurrent AES outbreaks in the region [12]. The Gorakhpur region of Uttar Pradesh has remained a hotspot for AES, with a devastating outbreak in 2005 resulting in 6,061 cases and 1,500 deaths, followed by recurrent outbreaks in 2006 and 2007 [13]. In 2014 and 2019, Bihar's Muzaffarpur district experienced AES outbreaks linked to hypoglycemic encephalopathy, with over 150 and 132 deaths, respectively [14, 15]. More recently, in 2016, an AES outbreak in Malkangiri, Odisha, primarily affecting a JE-unvaccinated tribal population, resulted in 325 cases and 91 deaths (CFR: 28%) [16].

Following a major outbreak of Japanese Encephalitis Virus (JEV) in eastern Uttar Pradesh in 2005, the Government of India introduced a single-dose JEV vaccine in 2006 across 11 endemic districts in four states namely Uttar Pradesh, Assam, West Bengal, and Karnataka [17]. Subsequently, as JEV cases were identified across various states through the surveillance established by the National Centre for Vector Borne Disease Control (NCVBDC), vaccination efforts were progressively expanded to 334 of 355 endemic districts, and adult vaccination was introduced in 42 districts across three states where adult cases were reported [10]. A two-dose schedule for JE vaccination was introduced in 2013 [17, 18]. Following the introduction of JEV vaccine, Japanese encephalitis (JE) cases declined across endemic states but the number of AES cases remained unaltered, with up to 70% of undiagnosed etiology [7, 19, 20]. This further complicated the issue and called for establishing expanded surveillance. Meanwhile, JE continued to spread and emerged as a major cause of AES in regions where the vaccine had not been introduced [21–23].

Effective, ongoing and standardized surveillance is critical for managing AES in India beyond just case detection. AES is an overarching syndrome, and its etiology includes several pathogens and is also shaped by socio-economic and geographical factors [19]. The AES outbreaks in Muzaffarpur, Bihar, in 2014 and 2019 were linked to malnutrition and hypoglycemic encephalopathy, underscoring the impact of poverty and dietary factors on AES susceptibility [15]. In Gorakhpur, Uttar Pradesh, poor sanitation and water stagnation have been linked to recurrent outbreaks, aggravated by vector-borne and bacterial pathogens [13]. The outbreak in Malkangiri, Odisha (2016) demonstrated the impact of limited healthcare access and low JE vaccination coverage among tribal populations, leading to a high case fatality rate (28%) [16]. Geographical influences, such as monsoon-driven JEV transmission in Assam and West Bengal, livestock exposure in Tamil Nadu and Karnataka and zoonotic spillover risks, as seen in Nipah virus outbreaks (2018, 2019, and 2023), in Kerala further illustrate the complexity of AES epidemiology.

A surveillance study carried out by Ravi et al. [19] utilizing a standardized laboratory diagnostic algorithm identified an infectious etiology (JE, scrub typhus, dengue, West Nile, S pneumoniae, herpes simplex virus, H influenzae, enterovirus, and N meningitidis) in up to 40.3% of AES cases reported between 2014 and 2017 across Uttar Pradesh, Assam, and West Bengal. In a four-year hospital-based study (2019–2022), Sonowal et al. [6] found that Orientia tsutsugamushi, causing Scrub Typhus (ST), was the most common pathogen in AES cases. Their study, which analyzed samples from 32 districts in Assam and several neighboring northeastern states, also identified other causative agents. In many parts of India, besides JE, ST has been documented as a major etiological agent responsible for AES [8, 24–26]. The etiological pattern of AES in the Western-ghats among states like Kerala, Karnataka, Tamil Nadu and Maharashtra is dominated by ST, Kyasanur Forest Disease (KFD) and dengue [24, 27, 28]. In Kerala, sporadic outbreaks of Nipah virus have also been reported [29]. In 2024, Chandipura virus (CHPV) was also identified as an etiological agent in cases reported from the states of Gujarat, Madhya Pradesh, Rajasthan, and Maharashtra [30]. Overall, though different regions of India have some common etiological agents causing AES, there are some unique region-specific pathogens. Currently, there exists a paucity of systematically collected data on the etiologies of AES across India, which hampers accurate diagnosis, effective treatment, and the formulation of targeted control strategies.

To address these gaps, the Indian Council of Medical Research (ICMR), the apex body for formulating, coordinating, and promoting biomedical research in India, constituted a Working Group of experts specializing in infectious diseases and working in AES-burdened hospitals across the country. The group was tasked with identifying priority AES-causing pathogens and formulating a standardized tiered laboratory diagnostic algorithm for initial pilot testing and subsequent nationwide implementation. In the current manuscript, the authors present a structured uniform protocol for nationwide surveillance of infectious causes of AES using a comprehensive tiered algorithm. This surveillance system aims to generate data that will reflect the epidemiological landscape of AES across India, ultimately supporting the development of targeted, region-specific public health interventions and effective resource allocation. Following successful implementation, the findings will be utilized to fine-tune the algorithm before scaling it up for nationwide use (manuscript under review). This protocol can also be adapted and implemented across different countries in the region where AES is a major public health problem.

Methods

Aim

The primary aim of the protocol is to establish a nationwide sentinel surveillance to determine the etiological profile (provides a systematic understanding of the pathophysiological origins of diseases, enabling targeted diagnosis, treatment, and preventive strategies) [31] of AES in children and adults admitted to selected hospitals in high AES-burden regions across India using a tiered multi-level diagnostic algorithm.

Design and methodology

The protocol is designed to establish systematic hospital-based sentinel surveillance for cases of AES. Prospectively collected surveillance data along with clinical details and laboratory testing at the participating hospitals, will be used to identify the causes of AES and the epidemiological and clinical characteristics of these infections.

Settings

Surveillance is planned at 12 sites across 11 states in the country namely Assam, Bihar, Delhi, Jammu & Kashmir, Kerala, Odisha, Puducherry, Rajasthan, Tamil Nadu, Uttar Pradesh and West Bengal, each representing distinct ecological, epidemiological, and healthcare contexts. One site has been selected in every state except for Kerala, wherein two sites from two districts have been included to capture cases of Nipah virus disease (Fig. 1).

Fig. 1.

Selected study sites for hospital-based surveillance of (AES)

Criteria for the site selection of sites

The proposed protocol will be implemented through selected hospitals attached to the Virus Research and Diagnostic Laboratories (VRDLs), a network of laboratories established by the Department of Health Research (DHR) under the Ministry of Health and Family Welfare (MoHFW) in India. These selected VRDLs are located within government medical colleges, which are tertiary care centres in the country’s health system and cater to a huge number of patients.

The criteria used in the protocol for selection of study sites is as follows:

1. AES patient footfall: The sites should have a high annual AES patient footfall (> 20 cases per month over the past year); site prioritisation was based on the number of AES cases that were enrolled in the previous year

2. Tertiary care hospitals: The site should be either a tertiary care hospital with access to advanced medical facilities for AES cases.

3. Availability of serology and molecular testing facilities: The sites should have both serological and molecular diagnostic capabilities to support a comprehensive approach to AES testing and diagnosis.

4. High concordance in External Quality Assurance Programs (EQAP): Laboratories should have over 90% concordance in EQAP for various pathogens to ensure high diagnostic accuracy and reliability.

5. Commitment to active participation: The site should be able to actively engage with various clinical departments in their respective hospitals for recruitment of cases.

6. Geographical diversity: The selected sites should provide broad geographical representation from various regions of the country to be able to collect comprehensive, region-specific data.

7. Consistent data reporting: The sites should have a proven track record of consistent entry of diagnostic reports, reflecting their adherence to data reporting standards.

8. Special etiological representation such as Nipah-reporting sites.

Study sites

A designated regional level laboratory, Regional-VRDL (RVRDL), Jawaharlal Institute of Postgraduate Medical Education and Research (JIPMER), Puducherry, has been designated for overall coordination of the study and will be linked with the participating laboratories in a hub and spoke model. The RVRDL JIPMER, Puducherry is a regional lab with a BSL- 3 facility and extensive expertise in diagnosis of viral etiologies. This laboratory has an ambit to test 40–45 viral pathogens of public health importance with experience in virus isolation. For quality control and assurance, King George's Medical University (KGMU), Lucknow has been included in the protocol. The institute’s established role in national health initiatives and its involvement in previous infectious disease research including AES make it highly capable of supporting standardized, high-quality data collection and laboratory practices essential for this multi-center study. All participating laboratories included in the protocol will be linked to the National Institute of Virology (NIV), the apex virology institute at Pune, India for conducting Next-Generation Sequencing (NGS) on a designated subset of surveillance samples. This institute was selected due its robust facilities for high-throughput sequencing and pathogen discovery, making it uniquely equipped to perform in-depth genomic analysis on AES cases, particularly for detecting novel or unknown pathogens.

Prioritization of AES-associated pathogens and development of testing algorithm

The ICMR constituted a Working Group of expert microbiologists and clinicians working in this field to identify the priority pathogens for AES in the Indian context and to develop a comprehensive algorithm for the surveillance of AES. The study group conducted an in-depth literature review with covering the past 20 years with key search terms included"Acute Encephalitis Syndrome,""AES etiology,""AES surveillance,""viral encephalitis,""bacterial meningitis,""Indian encephalitis outbreaks,""emerging encephalitis pathogens,""neuroinfections in India,"and"AES epidemiology in South-East Asia."To further refine the search results, Boolean operators such as AND, OR, and NOT were utilized. The literature review incorporated a wide range of peer-reviewed scientific journals, government reports, and surveillance program data to ensure a comprehensive understanding of AES and its associated pathogens. Key medical and public health databases used for this review included PubMed, Scopus, Web of Science and Google Scholar. Surveillance data and epidemiological insights were obtained from the WHO Global Health Observatory and the National Center for Disease Control (NCDC), India. To ensure the relevance and quality of the literature review, inclusion criteria focused on studies published in peer-reviewed journals or government reports, research conducted in India or South-East Asia, and publications from the last 20 years (2003–2023). Studies on AES etiology, epidemiology, surveillance, outbreak investigations, and systematic reviews were prioritized, along with research providing insights into clinical manifestations, diagnostic methods, and treatment outcomes. Exclusion criteria eliminated studies unrelated to AES, small case reports, non-English publications without translations, and research lacking clear diagnostic criteria for AES pathogens. Additionally, the working Group integrated insights from expert microbiologists and clinicians, findings from national surveillance programs like the National Vector Borne Disease Control Programme (NVBDCP), and observations from outbreak investigations. This facilitated the development of a comprehensive list of AES-associated pathogens.

These prioritized pathogens were segregated into two main categories: Priority- 1 includes the most common pathogens detected in clinical settings, while Priority 2 comprises less common pathogens that are important to be included in diagnosis/surveillance from a One Health/zoonotic outbreak perspective. The prioritization exercise was grounded in several critical factors to ensure a comprehensive and holistic approach to AES surveillance. High-priority pathogens endemic to specific regions, such as West Nile Virus, Chandipura Virus, and Nipah Virus, were identified due to their established presence, necessitating focused diagnostic and surveillance efforts in these areas. Additionally, pathogens with a history of causing outbreaks, including Dengue, Chikungunya, West Nile Virus, Chandipura Virus, Kyasanur Forest Disease (KFD), Crimean-Congo Hemorrhagic Fever (CCHF), and Nipah Virus, were emphasized to anticipate and manage outbreak risks effectively. Furthermore, zoonotic pathogens like Brucella associated with a history of animal contact, received special attention, aligning with the One Health approach that integrates human, animal, and environmental health considerations (manuscript under review).

The prioritized list was reviewed through several iterations by a second group of experts before finalization.

A tiered multilevel syndromic surveillance (with a near real-time collection, analysis, interpretation, and dissemination of health-related data to help decision-makers with the early identification of the impact (or absence of impact) of potential health threats) [32] testing algorithm was then developed based on the list of priority pathogens. The developed algorithm (Fig. 2) is divided into 5 Levels based on decreasing prevalence of pathogens and consequently optimizing the chances of identification of etiologic agents of AES. The algorithm is designed to prioritize testing for the common treatable agents, thus combining public health relevance with clinical action. This algorithmic approach will not only help in optimizing the cost of testing but also will help in managing the laboratory workflow.

Fig. 2.

Proposed testing algorithm for AES surveillance. ##Prioritize when subject has typical vesicular rash of chickenpox; #Prioritize when subject has typical maculopapular rash of measles. BUSE: Blood Urea and Serum Electrolytes; WBC: white blood cell; LFT: Liver Function Test; KFT: Kidney Function Test; CSF: Cerebrospinal fluid; TAT: Turnaround Time; NGS: Next-generation sequencing; PCR: polymerase chain reaction; JE: Japanese encephalitis; ELISA: enzyme-linked immunosorbent assay

Study participants

At each site, it is proposed to enrol consenting inpatients (children and adults) between the ages of 1 and 65 who meet the AES case definition, as determined by treating clinicians, at selected hospitals.

Sample size determination

As per the protocol, it is proposed to enroll a total of 540 cases per site per year (Approximately 45 per site per month or 12 cases per week), assuming that each site has the caseload to recruit the proposed number of eligible participants based on reviewing the previous year’s medical records.

It is thus proposed to enroll 7,128 AES patients (540 per site across 12 sites, plus an additional 10% to account for non-response or missing information over a period of 12 months). This sample size would be sufficient to estimate the aetiologies which account for at least 5% of AES cases, with a relative precision of 15% and 95% confidence level and design effect of two. As a precaution, to account for a low-incidence AES season, if the average monthly AES case load for a site is less than 50, then sub-sites linked to the main sites, with data on estimated AES caseloads, will be identified during the preparatory phase. Including cases from sub-sites will ensure that the cumulative case load (site + sub-site/s) meets the monthly target. If the number of cases admitted in a month is fewer than 45, additional cases will be recruited in the subsequent month to meet the target. In each site, child (< 15 years) to adult enrollment ratio of 3:1 will be maintained (Table 1).

Table 1.

Mapping of pathogen and diagnostics

Pathogen	Serum	Buffy coat/EDTA	CSF	Throat swab/Nasopharyngeal swab	Urine	Preferred Tests
Sample Volume	Age ≤ 12 years [Upto 5 ml—3 ml in plain vial and 2 ml in EDTA vial] Age > 13 years [Upto 8 ml- 5 ml in plain vial and 3 ml in EDTA vial		Age ≤ 12 years—3 ml Age > 13 years- 5 ml	To be collected in 3 ml VTM	All ages—3–5 ml
Malaria	×	Yes	×	×	×	Rapid Diagnostic Test – any World Health Organization preapproved
JE	Yes	×	Yes	×	×	IgM Capture (MAC) ELISA – In house [40]
Dengue	Yes	×	Yes	×	×	IgM Capture (MAC) ELISA – In house [40], Pan Bio Dengue NS1 antigen capture ELISA, RealStar® Dengue RT-PCR Kit
Chikungunya	Yes	×	Yes	×	×	IgM Capture (MAC) ELISA – In house [26], RealStar® Chikungunya RT-PCR Kit
Scrub typhus	Yes	Yes	Yes	×	×	Scrub Typhus Detect™ IgM ELISA RT-PCR – in house [39]
Measles (If rash present)	Yes	×	Yes	Yes	×	Euroimmun Measles IgM ELISA PCR – Conventional PCR@
Viral agents Herpes Simplex Virus 1/2, Varicella Zoster Virus, Human parechovirus, Human herpesvirus virus 6, Enterovirus, Cytomegalovirus	×	×	Yes	×	×	BIOFIRE® FILMARRAY® Meningitis/Encephalitis (ME) Panel
Bacterial agents Escherichia coli K1, Haemophilus influenza, Listeria monocytogenes, Neisseria meningitides, Streptococcus agalactiae, Streptococcus pneumoniae	×	×	Yes	×	×	BIOFIRE® FILMARRAY® Meningitis/Encephalitis (ME) Panel
Yeast Cryptococcus (C. neoformans/C. gattii)	×	×	Yes	×	×	BIOFIRE® FILMARRAY® Meningitis/Encephalitis (ME) Panel
Leptospira	Yes	×	Yes	×	×	Panbio™ Leptospira IgM ELISA RT-PCR* – in house
Mycobacteria	No	No	Yes	×	×	Xpert® MTB/RIF
Enterovirus	×	×	×	Yes	×	RealStar® Enterovirus RT-PCR Kit
Nipah Virus	Yes	×	Yes	Yes	Yes	Truenat® Nipah
West Nile Virus	Yes	×	Yes	×	×	West Nile Detect™ IgM Capture ELISA PCR* – in house

^*Nucleic acid analysis of Leptospira, Measles and West Nile will be undertaken at JIPMER, Puducherry for confirmation

@KIPMR, Chennai (WHO reference lab) will perform conventional PCR on all IgM measles positive samples

Inclusion criteria

Any patient ≥ 1 year to ≤ 65 years of age, providing informed consent from parent/family member, and admitted to one of the participating hospitals with the following criteria will be enrolled [1].

Measured fever (≥ 38 °C) at presentation or a history of fever (reported) within the preceding 7 days, along with at least one of the following:

• i.Change in mental status, defined as confusion, disorientation, coma, or inability to talk
• ii.Increase in irritability, somnolence, or aberrant behavior that is more severe than that associated with a typical febrile illness
• iii.New onset of seizures (excluding simple febrile seizure, which is defined as seizure that occurs in a child aged 1 year to ≤ 6 years, whose only finding is fever and a single generalized convulsion lasting less than 15 min, and who recovers consciousness within 60 min of the seizure).

Exclusion criteria

Patients will not be enrolled if diagnosed with any of the following conditions:

• i.Patients with a known non-infectious etiological for AES eg: known cases of epilepsy including trauma, toxic exposure, cerebrovascular accident, metabolic disorders and known malignancy
• ii.Patients admitted to the hospital within the preceding 15 days of onset of symptoms

Clinical specimen collection, processing, and handling

Specimens will be collected using aseptic techniques and labeled with assigned study numbers, then transported to the laboratory for processing and clinical testing. Each sample will be labeled using a unique ID and aliquoted accordingly as per the Standard operating procedures (SOP). The details for specimen collection are outlined below:

Specimen collection at enrolment

At enrollment, a trained physician or technician will collect cerebrospinal fluid (CSF), blood, urine, and throat swab specimens for testing under this protocol. Venous blood will be collected using aseptic techniques from the hand or ante-cubital fossa. CSF collection will involve a sterile lumbar puncture performed by the treating clinician as part of routine care unless contraindicated. CSF samples will be collected aseptically in sterile tubes using a hollow-bore spinal needle, ideally before the administration of antibiotics. Throat or nasal swabs will be collected in a viral transport medium (VTM). For Nipah virus diagnosis in Acute Encephalitis Syndrome (AES) cases in West Bengal and Kerala, an additional urine sample will be collected from the catheter.

Biological specimens collected at the treating hospitals will undergo routine clinical pathology, biochemistry, and limited infectious pathogen evaluations. CSF specimens will be analyzed for protein and glucose levels, cell counts (total and differential), wet mount, Gram stain, India ink preparation, and culture. Blood specimens will undergo testing for hemoglobin, white blood cell (WBC) counts with differential, platelet counts (if available), blood culture, blood gases, blood sugar (glucometer/automated or semi-automated analyzer), and biochemistry, including liver and kidney function tests (LFT, KFT) and electrolytes. These tests will follow standardized hospital laboratory procedures.

Testing algorithm for AES causing pathogens

The CSF, serum, whole blood and/or urine aliquots collected in the study will be used to ascertain the association of potential pathogen to acute encephalitis in the syndrome as per the developed testing algorithm (Fig. 2).

Specimen transport and storage

Approximately 5% of positive samples and 20% of cases that test negative for all pathogens, as per the testing algorithm from all sites, will be transported to NIV Pune at − 20 °C in triple-layer packaging with dry ice for Next Generation Sequencing (NGS).

In exceptional and unforeseen circumstances causing delay in transportation, samples will be stored at − 80^o C at each site until transported. Serum/CSF samples will be stored in a minimum of three aliquots (around 500µL each) along with all possible attempts to minimize the freeze–thaw cycles.

Next generation sequencing (NGS)

Next generation sequencing will be carried out for genomic characterization on serum, CSF, and throat swab specimens. In addition to NGS, novel pathogen discovery tools such as: metagenomics, bioinformatics pipelines, and pathogen-specific enrichment techniques will be employed to identify previously undetected or novel pathogens. The data generated through NGS will help in understanding the circulating genotypes/lineages of different pathogens and identify unknown/novel pathogens which are missed by routine tests conducted [33].

Data collection at enrolment

The information will be collected using a standardized case report form (CRF) (Supplementary material- Additional file 1) from hospital records/interviews, including basic demographic, clinical (e.g., symptoms, signs, treatment prior to enrollment), and epidemiologic risk details. The information will be filled in the CRF and informed consent will be obtained for each enrolled patient. The patient surveillance ID number, name, age, sex, date of illness onset, date and time of specimen collection, and type and aliquot of specimen will be recorded on each CRF form. The CRF will also capture details such as results of tests performed for routine clinical care as well as for any additional specimens obtained for pathogen-based testing. Additionally, the CRF will also document the results of radiographic imaging. The short-term outcomes, including current cognitive status and residual neurological/joint problems at discharge will be recorded in the patient discharge form.

Ethics approval and consent to participate

Approvals from the respective Institutional Ethics Committees (IECs) will be obtained for all the sites and sub-sites. All patient data shall be collected after obtaining written informed consent and written/verbal assent as per the national ethical guidelines [34]. For all identified AES cases, trained study coordinators will discuss the study in brief with the patients or parents (in children aged 7–17 years) in local vernacular language. For all patients, written informed consent or assent (in children aged 7–17 years) will be obtained and documented and patient information sheet will be provided. They will be assured that their clinical treatment will be continued as standard care, irrespective of their participation in the study, and that they can drop out of the study at any point of time. It will be emphasized that anonymity and confidentiality will be maintained at all levels and only the summary analyzed data will be presented and shared with research and programmatic stakeholders.

Study timeline

The surveillance program will be initially implemented in research mode for a period of one year. After optimization and standardization of various study components, the AES surveillance program will be integrated into the public health surveillance program of India.

Data analysis

The clinical, epidemiological, and laboratory data will be linked by individual site and patient ID numbers. An online web portal will be used to collect patient details and document the testing results, and to conduct periodic data cleaning and analysis. Analysis will be conducted using Epi Info and/or, STATA, and/or additional statistical programs.

Data analysis will include the following components:

1. The proportion of AES cases with identified etiological.

2. The proportion of AES cases caused by specific pathogens.

3. Clinical characteristics, risk factors and clinical outcomes associated with specific etiologies as compared to cases with no identified pathogen. Unusual and unreported presentations would be specifically looked into for various etiologies.

4. Usefulness of the testing algorithm will be presented by calculating the yield of positive etiologies at each level of the algorithm

5. Seasonal and geographical distribution of AES by etiology.

Data management and quality control

A web-based data system and database will be housed at ICMR–National Institute of Epidemiology, Chennai. Data server is protected with multiple layers of firewall to ensure safety and daily data backups with a mirror server at a different location to prevent any data loss. To ensure patient confidentiality, clinical and laboratory data will be entered with no personal identifiers and source documents will only identify participants by patient ID number. The data entry portal will be designed with logical checks to prevent inconsistent entries and entry will be restricted to drop-down items to the extent possible with only a few free-text entries. This is to ensure highly consistent and complete dataset for analysis ensuring adequate data quality. Only authorized field personnel and the data manager will have access to the data. JIPMER, Puducherry will serve as the nodal laboratory for coordinating the surveillance data. Adherence to protocol and Standard Operating Procedures (SOPs) will be monitored and ensured with the site study coordinators, and study monitoring by weekly data review and meeting with site PIs over conference calls. Site visits and data audits at each study site will also be conducted at regular intervals. These audits will include a review of documents such as informed consent forms, primary outcome data documentation, and also report protocol deviations (if any),

Dissemination plan

A dissemination board/committee will be created to share the outcomes from this surveillance project. The dissemination board consists of subject experts, project PIs and key co-investigators. Findings will be presented to the National Programmes (National Center for Vector Borne Diseases Control and Integrated Disease Surveillance Program under the Ministry of Health & Family Welfare, Government of India) as well as via published manuscripts with open access to the scientists and the public.

Discussion

For the past two decades, AES surveillance in India has primarily focused on JEV however, in recent years the etiological spectrum of AES has shifted towards scrub typhus and other causative agents and emerging pathogens. The diagnosis of these pathogens is impeded by restricted laboratory capacities and lack of systematic testing. Emerging pathogens such as Nipah virus, Chandipura virus (CHPV), KFD and West Nile are not even included in the routine testing of AES. More than 70% of AES cases have no known cause, posing additional challenges for the detection and understanding of other potential causes of AES, leading to insufficient epidemiological data and an incomplete understanding of the disease burden across the country [20]. Currently available information on AES in India is based on small, discrete datasets from individual centers with limited number of patients and varied testing methodologies, thereby making it potentially unrepresentative of the breadth of AES etiology and its burden across India. This paucity of data hinders accurate diagnosis, effective treatment, and the formulation of effective responses and targeted control strategies. In this context, it is crucial to expand the focus on identifying the predominant regional pathogens causing AES, taking into account various factors such as local geography, endemic disease burden, demographics and seasonality. The variation in the etiological spectrum underscores the diverse and multifactorial nature of AES across the country, necessitating specific surveillance, diagnostic, and management approaches.

The current protocol presents a model for a tiered laboratory algorithm for AES surveillance, establishing standardized approaches for pathogen detection and monitoring. It provides a structured framework that can serve as a template and guide for similar initiatives in other countries, enabling the implementation of robust surveillance systems tailored to diverse healthcare settings. The proposed protocol is expected to provide valuable insights into diagnostics, prevalence, risk factors, clinical characteristics, and the relative frequency of AES-causing agents thereby, providing critical information for enhancing diagnosis, clinical management, and AES control strategies nationwide.

The changing landscape of AES in India highlights the need for a systematic, standardized surveillance and diagnostic approaches from representative sites across India [19]. Arriving at a diagnosis is critically important for patients who may die without early diagnosis and clinical management as in case of treatable causes of AES like Scrub Typhus, Dengue and Leptospirosis.

Quality surveillance data is essential for also understanding AES epidemiology, planning interventions, and developing policies [35]. For effective public health interventions, arriving at an etiological cause is important in India due to is geographical variation. In Assam, intervention is primarily the JE vaccine as JE is the prevalent etiology. In Muzzafarpur, Bihar, nutritional interventions and prompt correction of hypoglycemia have been proved to avoid deaths and decrease incident cases [7]. In Uttar Pradesh, interventions such as empirical treatment with doxycycline and azithromycin have helped avoid deaths as Scrub Typhus fever turning into AES, and AES deaths were prevented [36]. Once the etiology is identified using systematic algorithm with effective surveillance, interventions can be suitable tailored for pathogen or cause. In Bihar a situational analysis of PHCs was done by ICMR with WHO to make sure all facilities were equipped with glucometer and rapid dextrose infusions to correct hypoglycemia. Also in Gorakhpur, Uttar Pradesh, the health system advised empirical doxycycline and azithromycin for fever cases among children and also made sure these drugs were made available at primary health care levels. Comprehensive public health measures, including improved surveillance, vaccination campaigns, and infrastructure development, have contributed to a steady decline in AES incidence and case fatality rates in Uttar Pradesh [37], demonstrating the importance of surveillance-informed interventions.

Risk factors will be assessed through this surveillance using a cross-sectional study design, with positive cases for each etiology and appropriate controls selected from within the surveillance population. Furthermore, the inclusion of NGS into the protocol offers a critical advantage by enabling genomic characterization of pathogens in cases where conventional diagnostic methods fail to identify difficult-to-detect/novel and emerging etiological agents thus providing critical insights into pathogen diversity, evolution, and transmission patterns. Following successful pilot testing, this approach can lay the groundwork for a robust surveillance system, scalable for nationwide implementation offering a proactive and responsive framework to address AES.

Limitations

Countries can leverage this model to gradually build up the diagnostic infrastructure for AES surveillance although a key challenge to be overcome would be the limited availability of diagnostic kits for certain pathogens included in the algorithm. There may also be logistical challenges in data collection across distant sites, this project uses an online portal, with offline data entry facility for entering data in a realtime manner. Technology can be used appropriately as per resource availability in various settings. There can also be variability in hospital capacity for conducting robust diagnostic testing, hence hospitals/health facilities may need upgradation and training before such an algorithm can be implemented across diverse regions. Additionally, the reliance on existing patient caseloads may introduce biases related to underreporting or misclassifying AES cases, hence sensitization of clinicians in reporting cases and careful monitoring of surveillance system is crucial to avoid bias.

Conclusion

The changing landscape of AES in India highlights the need for a systematic, standardized surveillance and diagnostic approaches from representative sites across India [38]. Once this standardized algorithm is implemented across the country, we will know heterogeneity of AES as a syndrome, the etiological profile of pathogens, seasonal patterns, age group affected and risk factors. Earlier, implementation of a standardized diagnostic algorithm in an enhanced surveillance platform resulted in a 3.1-fold increase in identifying AES etiologies beyond JEV alone [19]. Also, clinicians would be appropriately sensitized regionally through dissemination workshops, and they would be encouraged to provide evidence-based treatment to patients, according to specific etiology.

A study in Uttar Pradesh revealed inadequacies in AES surveillance data quality, hindering the development of effective prevention and control measures [35]. Quality data generated via this systematic surveillance can help identify risk factors and formulate control and prevention strategy. We will also disseminate our study findings to the National center for vector borne disease control and the National Center for disease control and high AES burden states, through dissemination workshops. We would then help formulate policy and will integrate our data-based recommendations with the current national guidelines on AES.

Abbreviations

JEV

Japanese encephalitis virus

HSV

Herpes simplex virus

ZIKV

Enterovirus, Zika virus

DENV

Dengue virus

CHPV

Chandipura virus

KFD

Kyasanur Forest Disease

CHIKV

Chikungunya virus

WNV

West Nile virus

AES

Acute Encephalitis Syndrome

NGS

Next-generation sequencing

ICMR

Indian Council of Medical Research

DHR

Department of Health Research

MoHFW

Ministry of Health and Family Welfare

EQAP

External Quality Assessment Project

KGMU

King George's Medical University

JIPMER

Jawaharlal Institute of Postgraduate Medical Education and Research

NIV

National Institute of Virology

IEC

Information, Education and Communication

CRF

Case report form

CSF

Cerebrospinal fluid

SOP

Standard operating procedure

NCVBDC

National Center for Vector Borne Diseases Control

NCDC

National Centre for Disease Control

WBC

White blood cell

LFT

Liver function test

KFT

Kidney function test

VRDLs

Virus Research and Diagnostic Laboratories

EQAP

Educational Quality and Assessment Programme

VTM

Viral transport medium

IDSP

Integrated Disease Surveillance Programme

Authors’ contributions

N.G, A.V, H.K, L.M and R.D conceptualized and designed the study. N.G, A.V, H.K, L.M, R.D, M.C, R.L, V.P.V, L.D, M.M, R.V, R.S.A, S.R, P.Y, A.J, A.S, K.K, S.B, A.P.M, M.S, BM, BM, M.C, A.S, B.F, M.M were involved in the protocol development. S.J, A.V, H.K, N.G, R.D and LM. contributed significantly to writing the manuscript. N.G: Supervised and reviewed the final draft. All authors read and approved the final manuscript

Funding

This proposed surveillance is funded by the Indian Council of Medical Research (ICMR). (Grant No: VU/45/2023/ECD).

Data availability

Not applicable.

Declarations

Ethics approval and consent to participate

All procedures in studies involving human participants were performed in accordance with the National Ethical Guidelines for Biomedical and Health Research involving human participants and approved by the Ethics Committees of each institutes involved in the study. This project has been prospectively registered with the IEC in JIPMER, IEC letter no JIP/IEC-OS/2023/470 dated 01.02.2024 and also in the lead organization and all hospitals admitting patients. Written informed consent will be obtained from parents of all enrolled patients.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.