In a study, researchers have identified 11 such “bellwether” sites across Bengaluru that offer early warning signs, allowing public health authorities to act faster and smarter in managing future outbreaks.
Published Jun 27, 2025 | 7:00 AM ⚊ Updated Jun 27, 2025 | 7:00 AM
Researcher drawing water from STPs for wastewater surveillance (#COVIDActionCollab)
Synopsis: Scientists have found that wastewater flowing through specific sewage treatment plants (STPs) can predict disease outbreaks, not just Covid-19, but potentially other respiratory illnesses as well, several days before cases are clinically reported.
In the lanes around Ashwath Nagar and the tree-lined neighbourhoods near Lalbagh in Bengaluru, a quiet but powerful health surveillance system is at work, not in clinics, but beneath our feet.
Scientists have found that wastewater flowing through specific sewage treatment plants (STPs) can predict disease outbreaks, not just Covid-19, but potentially other respiratory illnesses as well, several days before cases are clinically reported.
In a study published in The Lancet Regional Health – Southeast Asia, researchers have identified 11 such “bellwether” sites across the city that offer early warning signs, allowing public health authorities to act faster and smarter in managing future outbreaks.
The study, conducted by a team from the Tata Institute for Genetics and Society (TIGS), Biome Environmental Trust, and the National Centre for Biological Sciences, monitored SARS-CoV-2 (the virus causing Covid-19) levels in Bengaluru’s wastewater over a two-year period from December 2021 to January 2024.
Rather than relying solely on case numbers, which often reflect only those with access to testing or healthcare, wastewater surveillance detects fragments of the virus in human faeces flushed down toilets. This method captures both symptomatic and asymptomatic infections, offering a population-wide lens on disease spread.
“This is essentially a wastewater surveillance system for tracking disease and pathogen trends. We call them ‘indicator sites’ because, based on the city’s geography and the structure of its sewer network, we identify specific points that reflect the overall health situation of the city,” TIGS Director and co-author Dr Rakesh Mishra told South First.
He added that’s what they had been doing through this longitudinal study. These 11 sites have consistently provided a reliable indication of trends across Bengaluru. By monitoring these key locations, they can say whether a disease is increasing or decreasing in the community.
Bengaluru, a city of over 11 million residents, has a centralised sewage system that covers nearly 80 percent of its population. The researchers collected and analysed over 2,800 samples from 26 sewage treatment plants (STPs), ranging from large facilities serving millions to smaller plants connected to just a few thousand homes.
Using sensitive genetic tests (RT-qPCR), the team detected viral fragments of SARS-CoV-2 in the water. They then mapped how levels of the virus changed over time and compared these trends with clinical COVID-19 case reports.
Interestingly, the wastewater data often provided an 8–14 day lead time over clinical reporting, meaning the sewage knew before the symptoms showed up.
The researchers identified four major Covid-19 surges in Bengaluru during this period — BA.2.10, BA.2.X, XBB, and JN.1 variants. While clinical testing caught the first three waves, the fourth surge (driven by JN.1) went almost entirely undetected by hospitals and laboratories.
The JN.1 surge had the lowest false positive rate and a higher true positive rate. Each surge was analysed not just for its intensity but also for how early it was detected at different sites. The team used statistical models and algorithms to distinguish between ‘signal’ — a true surge — and ‘noise’, or random fluctuations in data.
From the 26 sites, the study singled out 11 locations as “bellwether” STPs — facilities that consistently provided early and reliable signals across all four surges.
These included:
The study used a toolkit called the COVID-SURGE algorithm, which applies a set of logical rules to detect meaningful changes in virus levels in wastewater. For example, if the viral load in a sample suddenly doubles compared to the previous one, or if detectable virus returns after weeks of undetectable levels, it may indicate the start of a surge.
The researchers adapted this algorithm into a simple Excel-based calculator so that public health officials can use it without needing complex software or coding skills.
It worked surprisingly well. The tool accurately flagged the start of surges in over 80 percent of the sites during BA.2.10 and XBB outbreaks. It was less effective during the JN.1 surge, largely due to a ‘variant soup’—multiple co-circulating versions of the virus that made signals murkier.
Still, even in low-transmission phases or when clinical testing was absent, the wastewater provided critical insights.
“We can confidently predict disease trends about a week in advance. Based on the data, we can say with reasonable certainty that if there’s a rising trend, it’s likely to peak in about a week. The accuracy of this prediction, of course, depends on how frequently we collect the data,” said Dr Mishra.
He pointed out that if sampling is done weekly, we’re limited to about a one-week lead time. However, if we sample more frequently — say, every few days — our predictions become more reliable, and we might be able to forecast trends 10 to 12 days ahead, provided the surveillance system is well established and functioning properly.
“More importantly, this approach doesn’t just tell us when an outbreak might happen, but also where it’s happening in the city. So, instead of taking action across the entire city, which may be inefficient or unnecessary, we can target interventions to specific areas. That’s particularly important in a city with 10 to 1.5 crore people — blanket approaches aren’t always feasible,” he poi outnted.
From this study, Dr Mishra said that they learned that when a specific sewage treatment plant (STP) showed an uptick in viral load, it reflects the situation in the neighbourhood feeding into that plant. It’s not the STP itself — it’s about the ward or locality from which the wastewater is coming.
“So yes, the catchment area of each STP plays a crucial role. It allows us to understand the hyper-local spread of a pathogen, and enables authorities to deploy resources in a focused, efficient manner to contain the situation,” said Mishra.
This study is largely focused on SARS-CoV-2. In fact, it has evolved into a robust system that allows the researchers to track increases and decreases in infection levels over time.
“We’re able to monitor trends—for example, we recently picked up signals of rising activity through wastewater. But having said that, this system is not limited to SARS-CoV-2. We can clearly use it to monitor other viruses — particularly respiratory viruses — and even certain types of bacteria and fungi. One important area is antimicrobial resistance, where we can track specific resistant bacterial strains,” said Dr Mishra.
He added that three key factors needed to be considered: Which pathogens to monitor, how frequently to sample, and where to sample.
All of these are dynamic and must be adapted to the local context. For example, if it’s flu season in Bengaluru, it makes sense to increase surveillance for influenza. However, if the same is not true in a place like Assam or Delhi, then there’s no need to monitor flu there at that time.
“This is not a one-size-fits-all system. It needs to be localised and optimised based on region-specific disease patterns. There are multiple possibilities. Some pathogens, like dengue, are difficult to monitor through wastewater. But many others can be effectively tracked,” said Dr. Mishra.
Dr Mishra said that if there’s a rise in disease prevalence, we can increase the frequency of sampling. If the situation is stable or declining, we can reduce the frequency. In other words, it allows us to conserve resources and avoid generating unnecessary volumes of data.
“This study sets an example for other urban areas. Localised research can help identify key sampling sites, and depending on the trends seen in either clinical reports or wastewater data, authorities can decide whether surveillance should be weekly, monthly, or even less frequent. In this way, we are better positioned to make strategic public health decisions and use limited resources efficiently. That’s the key takeaway from this study,” said Dr Mishra.
(Edited by Muhammed Fazil.)
