Environmental Surveillance & Disease Ecology

Environmental surveillance has emerged as a smart surveillance tool to detect, quantify and track pathogens of interest. It serves as an early warning system to take appropriate measures and build infrastructure to contain or circumvent public health crises. Monitoring public health by sample collection at individual patient level can be extremely costly. Environmental samples, such as wastewater samples, are composite samples that represent the contribution from many individuals in the community and are thus unbiased and cost efficient for routine surveillance of infectious diseases. Globally, wastewater-based epidemiology (WBE) has been used for over 40 years to track measles, cholera, polio and HIV outbreaks. More recently, with the ongoing pandemic, WBE has emerged as a cost -effective and efficient tool to predict rise in COVID-19 infections.

Environmental surveillance helps identify disease hotspots and needs to be combined with ecological drivers of diseases in both space and time. We strive to underpin this by studying the field of disease ecology which encompasses the ecological study of host-parasite interactions within the context of their environment and evolution. Many arboviruses, such as those that cause Chikungunya and Dengue, have zoonotic origins and their interactions with mosquito vectors have evolved in parallel with urbanisation of their key mosquito hosts (Aedes species), and this understanding is fundamental to the One Health approach. Vector-pathogen interactions are critical to the transmission and epidemiology of vector-borne diseases. Our work focusses on the mechanisms and scale of pathogen interactions at individual, population, and community levels. We take an interdisciplinary approach drawing on genetics, molecular ecology, epidemiology, and modelling to understand how biological, social, and physical aspects of our environment can influence disease transmission, intensity, and distribution.

Farah Ishtiaq, Mansi Malik

Sanjay Lamba, Shivranjani Moharir


In India, tracking of the COVID-19 pandemic relies heavily on testing symptomatic individuals for the presence of SARS-CoV-2 RNA and counting the positive tests over time. Many SARS-CoV-2 infected persons are asymptomatic or oligosymptomatic (few symptoms) and are generally not tested by RT-qPCR, leading to underestimation of COVID-19 cases. Furthermore, infected and even asymptomatic individuals start to shed the virus via faecal route 4-7 days in advance of symptoms and clinical testing, which means the increase in viral load in sewage water ahead of reported cases works as an early warning system. Wastewater-based epidemiology (WBE) thus complements the routine diagnostic surveillance by capturing near real-time virus circulation at a community level.

Investigator: Farah Ishtiaq

National Centre for Biological Sciences (NCBS), Bengaluru
Bangalore Water Supply and Sewerage Board (BWSSB), Bengaluru
Bruhat Bengaluru Mahanagara Palike (BBMP), Bengaluru
Biome Environmental Trust, Bengaluru

Routine monitoring of public health can help in the early detection of emerging or upcoming infectious disease waves in the community and can help in preventing future pandemics. Wastewater is the warehouse of thousands of parasitic, non-parasitic, infectious, non-infectious, and saprophytic microorganisms. These microorganisms find their way in the wastewater mainly through human or animal excreta or through soil. The qualitative and quantitative analysis of the microbiome of sewage water in a particular geographical location can be a read out of the general health of the people inhabiting that area.

We analyse environmental samples using molecular biology and genomics approaches for surveillance of pathogenic microbial diversity, including SARS-CoV-2, in wastewater. Since SARS-CoV-2 is shed by infected individuals in their faeces irrespective of their symptomatic status, wastewater-based epidemiology serves as a tool to monitor even dormant and unreported COVID-19 infections.

Investigator: Shivranjani C Moharir

CSIR – Centre for Cellular and Molecular Biology (CCMB), Hyderabad

The longitudinal data generated from wastewater-based surveillance of SARS-CoV-2 was modelling. Using statistical modelling and different machine learning approaches, we developed an early warning system and demonstrated how wastewater monitoring could be used for community-level detection and tracking of the SARS-CoV-2 virus, thereby informing public health policy decisions. In conclusion, monitoring temporal variation in viral loads in wastewater combined with other analyses can detect a virus outbreak at least one week in advance.

Investigator: Shivranjani C Moharir, Sanjay Lamba

CSIR – Centre for Cellular and Molecular Biology (CCMB), Hyderabad

Air surveillance of pathogens is a critical aspect of public health and epidemiological monitoring. It involves the systematic monitoring of the air to detect the presence of microorganisms, such as viruses, bacteria, and fungi. This surveillance is essential to understanding infectious disease transmission patterns and implementing timely preventive measures.

This project involves collecting and analyzing air samples from diverse environmental settings, including hospitals, zoos, densely populated areas, and sparsely populated regions.

Investigator: Shivranjani C Moharir

Communicable diseases need continuous surveillance activities to track, predict and control emerging, re-emerging, and novel infections that are potential threats to human health and wellbeing. Dengue and chikungunya are the two common vector borne diseases in India transmitted by the Aedes spp. mosquitoes Aedes aegypti and Aedes albopictus, respectively. The epidemiology of chikungunya and dengue infections is thus likely to be temporally and spatially linked. Similarly, bacterial infections such as scrub typhus (caused by Orientia tsutsugamushi) and Leptospirosis (caused by Leptospira) account for 35 – 50% and 52% cases, respectively, of acute undifferentiated febrile illness. Currently, there are no molecular markers that can be used in clinical settings for a speedy diagnosis.

The objectives of the project are

1. To estimate the seroprevalence of Malaria, Dengue, Chikungunya, Leptospirosis, Scrub typhus and Hepatitis using a combination of screening methods – ELISA in BBMP nodal laboratory and advanced molecular diagnostics at TIGS.

2. To perform sequencing of samples for serotyping and strain identification of Malaria, Dengue, Chikungunya, Leptospirosis, Scrub typhus and Hepatitis to help in determining the prevalent strains/sero types in Bengaluru city.

Investigator: Mansi Malik, Farah Ishtiaq

Bruhat Bengaluru Mahanagara Palike (BBMP), Bengaluru

We are working on the surveillance of vector-borne diseases from vectors and clinical samples collected across the Cauvery delta districts of Tamil Nadu. We are in the process of developing qRT-PCR based molecular assays for rapid and accurate detection of pathogens prevalent in the region.

Investigator: Mansi Malik

Central University of Tamil Nadu, Thiruvarur