{"id":1197,"date":"2021-03-19T10:55:44","date_gmt":"2021-03-19T17:55:44","guid":{"rendered":"https:\/\/knightlab.ucsd.edu\/wordpress\/?p=1197"},"modified":"2025-08-01T10:05:01","modified_gmt":"2025-08-01T17:05:01","slug":"sewage-handling-robots-help-ucsd-team-predict-coronavirus-outbreaks-in-san-diego","status":"publish","type":"post","link":"https:\/\/knightlab.ucsd.edu\/?p=1197","title":{"rendered":"Sewage-handling robots help UCSD team predict coronavirus outbreaks in San Diego"},"content":{"rendered":"

Automated process helps test city sewage for the SARS-CoV-2 coronavirus, enabling researchers to forecast the region’s caseload one to two weeks ahead of clinical diagnostic reports.<\/span><\/a><\/span><\/h3>\n

In earlier days of the COVID-19 pandemic, before diagnostic testing was widely available, it was difficult for public health officials to keep track of the infection\u2019s spread or predict where outbreaks were likely to occur. Attempts to get ahead of the coronavirus that causes the disease are still complicated by the fact that people can be infected and spread the virus even without experiencing symptoms themselves.<\/span><\/p>\n

When studies emerged showing that people testing positive for the virus \u2014 whether symptomatic or not \u2014 shed it in their stool, \u201cthe sewer seemed like the \u2018happening\u2019 place to look for it,\u201d said Smruthi Karthikeyan, an environmental engineer and postdoctoral researcher at the UC San Diego School of Medicine in La Jolla.<\/span><\/p>\n

From July to November, Karthikeyan and a team led by professor Rob Knight, director of the Center for Microbiome Innovation at UCSD, sampled sewage water to see if they could detect the coronavirus, SARS-CoV-2. They could. But concentrating the wastewater proved to be a slow and laborious multistep process.<\/span><\/p>\n

But in a paper published March 2 in mSystems<\/a><\/i>, the researchers describe how they have automated wastewater concentration with the help of liquid-handling robots. They demonstrated their system\u2019s robustness by comparing it with existing methods and showing that they can predict coronavirus cases in San Diego by a week with excellent accuracy and three weeks with fair accuracy, just using city sewage.<\/span><\/p>\n

2021-03-03-rtl-ww-dashboard.jpgSan Diego County has only one primary wastewater treatment plant, located on the coast in Point Loma. All excrement flushed away by San Diego\u2019s approximately 2.3 million residents, including those on the UC San Diego campus, ends up there.<\/span><\/p>\n

Seven days a week, Karthikeyan or a colleague have driven to the treatment plant to pick up wastewater samples collected and stored for them by onsite technicians.<\/span><\/p>\n

\u201cUnfortunately, we can\u2019t just directly test wastewater samples the way we would samples from patient nasal swabs,\u201d Karthikeyan said. \u201cThat\u2019s because the samples we get are highly diluted \u2014 just think of the number of people contributing to the waste stream, plus all the junk that gets flushed and makes it to the sewer system.\u201d<\/span><\/p>\n

Back in Knight\u2019s lab at UCSD, the researchers process the sewage using their robotic platform. The system extracts RNA \u2014 the genetic material that makes up the genomes of viruses like SARS-CoV-2 \u2014 from the samples and runs PCR (polymerase chain reaction) to search for the virus\u2019 signature genes.<\/span><\/p>\n

The automated, high-throughput system can process 24 samples every 40 minutes. Later the same day, Karthikeyan adds the data to a digital dashboard that tracks new positive cases.<\/span><\/p>\n

According to Knight, the technique is faster, cheaper and more sensitive than other approaches to wastewater surveillance. The team is able to identify a single coronavirus case in a building of about 500 people.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"

Automated process helps test city sewage for the SARS-CoV-2 coronavirus, enabling researchers to forecast the region’s caseload one to two weeks ahead of clinical diagnostic reports. In earlier days of<\/p>\n","protected":false},"author":1,"featured_media":1198,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[5],"tags":[],"class_list":["post-1197","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-news"],"_links":{"self":[{"href":"https:\/\/knightlab.ucsd.edu\/index.php?rest_route=\/wp\/v2\/posts\/1197","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/knightlab.ucsd.edu\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/knightlab.ucsd.edu\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/knightlab.ucsd.edu\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/knightlab.ucsd.edu\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=1197"}],"version-history":[{"count":2,"href":"https:\/\/knightlab.ucsd.edu\/index.php?rest_route=\/wp\/v2\/posts\/1197\/revisions"}],"predecessor-version":[{"id":1544,"href":"https:\/\/knightlab.ucsd.edu\/index.php?rest_route=\/wp\/v2\/posts\/1197\/revisions\/1544"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/knightlab.ucsd.edu\/index.php?rest_route=\/wp\/v2\/media\/1198"}],"wp:attachment":[{"href":"https:\/\/knightlab.ucsd.edu\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=1197"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/knightlab.ucsd.edu\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=1197"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/knightlab.ucsd.edu\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=1197"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}