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Detecting SARS-CoV2 using Houston鈥檚 wastewater

Dipali Pathak

713-984-710

Houston, TX -
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Researchers at 7m视频, in partnership with the and , have determined that testing the city鈥檚 wastewater for SARS-CoV2 provides a significant lead-indicator for the prediction of outbreaks at the regional level.

The researchers have been studying samples of wastewater collected by Houston Public Works. Using existing and newly established testing methods, they were able to identify the presence of the novel coronavirus in wastewater samples collected on a weekly basis from late May to the present from most of the 39 sites throughout the city.

Since there is evidence that coronavirus is shed in a person鈥檚 excrement, wastewater sampling is a cost effective, efficient, and highly comprehensive mechanism to capture total viral levels in the Houston population, with data down to the community and neighborhood level. In addition, such an approach is thought to capture those who shed the virus before symptoms are present or are asymptomatic carriers.

The effort at Baylor was spearheaded by microbiologist Dr. Anthony Maresso, director of BCM TAILOR Labs, the College鈥檚 initiative that specializes in quickly adjusting research efforts to meet infectious disease needs.

The data produced by the team enables city health officials to mobilize to the specific areas identified by the researchers as an at-risk area for a surge by increasing nasal testing, isolating congregant living facilities and implementing local education aimed at reducing community transmission. Many cities and governments have now implemented such programs across the global after several groups, including Houston鈥檚, showed its predicative attributes. This also includes effluents coming from plants, schools, campuses, hospitals or other institutions.

鈥淭his is not Houston鈥檚 first infectious disease crisis,鈥 said Maresso said. 鈥淲astewater sampling was pioneered by Joseph Melnick, the first chair of Baylor鈥檚 Department of Molecular Virology and Microbiology, to get ahead of polio outbreaks in Houston in the 1960s. This work essentially ushered in the field of environmental virology, and it began

here at Baylor. TAILOR Labs is just continuing that tradition by providing advanced science measures to support local public health intervention,鈥 Maresso said.

鈥淚t鈥檚 a cost effective way to gauge Houston鈥檚 total viral load. It tracks well ahead of positivity rate, 10 days in some cases,鈥 said Dr. Austen Terwilliger, director of operations at TAILOR. 鈥淎t the moment, we are at the lowest viral levels since we started sampling, which is excellent news.鈥

鈥淭he massive scope of data we鈥檝e collected and analyzed with the city of Houston and our Rice counterparts has allowed us to have what is perhaps a unique level of confidence in what we鈥檙e reporting,鈥 said Dr. Justin Clark, TAILOR鈥檚 data scientist.

The researchers hope to continue the program well into 2021 and even adapt the approach to other seasonal viruses or drug-resistant bacteria in hospitals.

Update as of July 2021:

The wastewater surveillance data has used by the Houston Health Department to respond to viral outbreaks in real-time for nearly 15 months, efforts that included sending strike teams to effected areas to strengthen public health strategies. Other cities around the world have now emulated the approach that began here in Houston.

Maresso and TAILOR Labs are now adapting the effort to survey for other viruses and bacteria of importance, including the tracking of HIV and possibly other respiratory viruses such as the flu. This work, pioneered to detect SARS-CoV-2, has the potential to contribute to the ending of other decades-long epidemics.

鈥淲e are at a unique crossroads with our war on viruses and bad bacteria,鈥 Maresso said. 鈥淲astewater monitoring will give us a novel and paradigm-changing advantage, particularly because this approach samples a population, not the individual, in an unbiased way. It is like being able to see the enemy all at once, monitor its movements and negate its sneaky ability to go undetected.鈥

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