[music]
Columbo: Excuse me ma’am. Trash. Where do you put the empty trash?
Speaker 2: No. [foreign language]
Columbo: No, no, no, no. Police, ma'am. Police, police. See? Trash. Trash, where--.
Speaker 2: [foreign language]
Columbo: See, where do you dump the trash?
Speaker 2: [foreign language]
Columbo: No, no, no, no. The trash. Where do you put the trash?
Speaker 2: [foreign language]
Columbo: I found it.
Melissa Harris-Perry: Those were the days when television detectives like Columbo were resourceful enough to sift through wastepaper baskets hunting for evidence that could tie a suspect to a dastardly crime. A matchbook with a scribbled address, a tissue blotter with lipstick, maybe even discarded food with traces of poison. Columbo knew that trash was investigative treasure.
Well, I'm not going to waste any more time getting to the point because it turns out, waste can in fact provide important evidence not just on television, but in real life, and not just the waste in our garbage cans, but also in our plumbing. Our digestive systems produce organic evidence, and I feel like it's my duty to tell you all about the science of sewage surveillance.
Joining us to talk about sewage surveillance is Newsha Ghaeli, president, and co-founder of Biobot Analytics. Welcome to The Takeaway, Newsha.
Newsha Ghaeli: Hi. Thank you. Thank you for having me.
Melissa Harris-Perry: What is sewage surveillance?
Newsha Ghaeli: Yes. Sewage surveillance or otherwise called wastewater monitoring or wastewater epidemiology is the science of looking at sewage as a source of information on human health and human behavior. If you think about it, our doctors look at our urine and stool all the time to understand our health, what's going on in our bodies, what foods we've eaten. Every day, you're flushing this information down the toilet, where it's aggregating in our city sewers, and mixing with sewage from 1,000s of other people, and flowing to the wastewater treatment plant. Wastewater monitoring collects samples from the wastewater treatment plant to be able to understand the health of the entire city in a single sample.
Melissa Harris-Perry: Okay. When you say it as wastewater epidemiology, it sounds much more public health-oriented and much less scary, I guess, in a certain way than sewage surveillance. By scary here, I guess I mean, we've talked a lot about digital metadata, but this is, I guess, in a certain way, organic metadata. I'm wondering if there are concerns about how this data might be used.
Newsha Ghaeli: Yes. The beauty of wastewater monitoring is that it is inclusive of everybody who lives in a city, and yet there is no way to understand whether a virus or something that you're detecting is coming from a specific person. In that way, it's an extremely privacy-protected way to look at health data, which otherwise has names and individual information associated to it.
Melissa Harris-Perry: What are some of the ways that this water epidemiology has been used successfully in the past?
Newsha Ghaeli: Yes, well, most recently, wastewater monitoring has been implemented across the United States and around the world to monitor and understand trends of the COVID-19 pandemic. It has demonstrated to be extremely valuable for public health agencies, and city leaders, government officials to look to wastewater, as the leading indicator of new disease incidence or prevalence.
Part of this is because we actually shed the virus days before we are symptomatic and actually become sick. We can detect it earlier via sewage, but also because inherent delays in our testing system, so think about it. If you go and want to get a COVID PCR test, sometimes it's not available, it might take multiple days, by the time you get your results back. Sewage has really demonstrated to be this leading indicator for new disease.
Melissa Harris-Perry: I'm going to go back to the point that it tells us about everyone but not about anyone in particular. How does knowing, for example, that a neighborhood or a community is shedding a higher rate of COVID at any given moment? How does that help in controlling or managing the outbreaks?
Newsha Ghaeli: One of the favorite examples that I like to use is actually not an action that was taken by a government agency or a public health department, but rather, in Boston, the Boston Children's Hospital was monitoring the local wastewater from the wastewater treatment plant that represents the greater Boston area. In December 2021, wastewater started showing a significant rise in SARS-CoV-2, the virus that causes COVID-19.
Within a week or so, that became known as the Omicron wave that we all just experienced, but the hospital actually postponed all non-emergency procedures for January and February of 2022 because they knew that wastewater would be leading new cases, which would then be leading hospitalizations. That right there is an example of this data being used to make a very operational very real-time decision in order to improve processes.
Melissa Harris-Perry: Now, what are some of the limitations? I love this example that you've used where it's not a government-based decision, it's a public health community-based decision and it makes perfect sense to me. I also wonder, is it possible to get it wrong? What if they had suspended those non-emergent surgeries and in fact, the Omicron hadn't come through the community in that way?
Newsha Ghaeli: Similar to let's say, weather data, we see wastewater data as a weather map of our health. Very situational awareness information that can help guide not only the response from public health agencies, but also local business leaders, but also all the way down to individuals. We can actually look at this information on a daily basis to help guide our behavior and our exposure within our community, whether we're going to ride public transportation or not, whether we're going to go to that party this weekend.
Similar to that, wastewater data is never going to give us diagnostic information on a community similar to clinical testing. If we see the wastewater virus concentration increasing, that's not going to fill the gap for having access to adequate clinical testing infrastructures. It can help us guide knowing when to increase clinical testing so that people can be diagnosed and therefore seek out treatment because it's never going to do that second more individual part of diagnosing someone to help them therefore go and get treatment.
Melissa Harris-Perry: You're actually in this game as a business, right? You actually are part of the business of this. In what ways is it a business? How can one be a wastewater surveillance entrepreneur?
Newsha Ghaeli: Biobot is based on research that my co-founder, Dr. Mariana Matus and I were doing while we were at MIT. We started this research in 2014, and after about a few years, we decided to start Biobot to really bring this technology to market. We felt that the technology and we would have a much bigger impact if this were a business where we could work directly with cities, counties, state government in order to actually leverage this technology for the things that they cared about.
Our customers, today, the majority of them are government, and they range anywhere from small local municipalities as small as just 20,000, 30,000 people all the way up to very large cities, like the Boston area I just used as an example. We work with counties, we work with state government agencies. We're very much focused on working with government.
Melissa Harris-Perry: Are there ways that either individuals or households, communities be thinking about this technology and its effect on our lives? Are there questions we should be asking to ensure that it is being used in ways that are ethical and privacy protecting?
Newsha Ghaeli: Yes, so as with any public health issue, whether it's COVID-19 or something else, any public health matter, we need to look at multiple datasets in order to actually understand what is going on in our community and design an appropriate response. When we are looking at multiple datasets, what ends up happening is that if one dataset is biased in a certain way, we then rely on the other datasets to help counter those biases. One thing that we always say at Biobot is we should never look at the wastewater data in isolation to make public health decisions. Rather it should be a complement to clinical testing, to hospitalizations, to other data that we're looking at as another source of truth.
One of the things that we wastewater, for example, complements clinical testing with is that it is not biased towards only the individuals who are accessing clinical care in a city. Wastewater is inclusive of everybody who uses the toilet, not just people who have health insurance, who might have a propensity to go to the doctors and so it counters that bias that clinical testing has.
Melissa Harris-Perry: I'm so glad. You see, I told you we were excited about this conversation. I was excited about this. Newsha Ghaeli is president and cofounder of Biobot analytics. Thanks for joining us today.
Newsha Ghaeli: Thank you for having me.
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