AI-Assisted COVID-19 Variant Detection in Wastewater
What it is for
Environmental Health
- Vsearch supports environmental surveillance of COVID-19 variants by processing wastewater nucleotide sequences, contributing to population-level public health monitoring.
- Run by
- Department of Health and Mental Hygiene (DOHMH)
- Where
- No fixed location
- Kept
- Not stated by the NYC Office of Technology and Innovation.
- Shared with
- Not stated by the NYC Office of Technology and Innovation.
- Your copy
- You cannot see the data it holds about you. What you can do
What it is for
This tool analyzes nucleotide sequences extracted from wastewater samples to identify and track COVID-19 variants circulating in New York City. It uses a sequence-alignment algorithm to merge, compare, and cluster genetic material, helping public health scientists detect emerging variants without collecting information about any individual. No personal or identifying information is used at any stage of the process.
What it collects and what happens to it
Data taken in
About a measurement
Anonymized data
- Nucleotide sequences extracted from laboratory wastewater samples, along with curated reference databases used for alignment. No personal or identifying information is collected.
Processing
Clustering & Segmentation
- Vsearch uses the Needleman-Wunsch global sequence-alignment algorithm to merge read pairs, dereplicate sequences, and detect chimeric genomic sequences. This pairwise alignment and clustering approach identifies related nucleotide sequences within environmental samples.
What it does
Deciding (Analytical AI)
Human decides
- Vsearch applies the Needleman-Wunsch algorithm to align and dereplicate nucleotide sequences and detect chimeric genomic sequences. Outputs are similarity or clustering results reviewed by public health laboratory scientists who make downstream variant identification decisions.
Outputs
About a measurement
Anonymized data
- Similarity or clustering results identifying related nucleotide sequences, used for organism identification or comparative genomic analysis of COVID-19 variants in wastewater. No individual-level data is produced.
Run by
Department of Health and Mental Hygiene (DOHMH)
- The Department of Health and Mental Hygiene, through its Disease Control – Public Health Laboratory division, deploys Vsearch as an intermediate step in the workflow to analyze COVID-19 variants in wastewater.
Built by
Not stated by the NYC Office of Technology and Innovation.
Kept for
Not stated by the NYC Office of Technology and Innovation.
Shared with
Not available to me
- No identifying information is collected or disclosed. Members of the public have no data about themselves in this system; access to outputs is limited to public health laboratory personnel.
Stored
Not stated by the NYC Office of Technology and Innovation.
How to read the colours
Can it identify you?
- Anonymized data
- Data about people with the link to who is broken. Stripped of identifiers, blurred, aggregated, or noised so this system can’t reasonably tie a record back to an individual.
- Pseudonymous data
- Each person’s data is tied to a token (hash, ID, template) that lets this system recognise the same person across events, but the token itself doesn’t reveal a name. Reidentification is possible with extra information.
- Identifiable data
- The data either contains a direct identifier (name, address, account name, recognisable face or voice, plate number) or carries a token this system uses to look up legal identity during processing.
Who completes the loop?
- Human decides
- This mode suggests; a person decides what to do next. The AI is always advisory — a human is in the loop on every decision. Example: a triage tool ranks cases for a clinician who chooses which to see first.
- Human executes
- This mode decides; a person carries out the result. Example: an optimizer plans the day’s trash-collection routes, and drivers run them.
- Autonomous
- This mode decides and acts on its own. No person reviews each decision or carries out the resulting action.
Definitions from the DTPR standard. Amber is about your data, violet about who decides. The fuller the shape and the deeper the colour, the more identifying the data or the less a person is involved.
- AI registerNYC Automated Decision Systems — Vsearch (2025)NYC Department of Health and Mental Hygiene, Disease Control – Public Health Laboratory. Reported 2025, first used June 2022.
- AI registerNYC Automated Decision Systems — Vsearch (2025)
- AI registerNYC Automated Decision Systems — Vsearch (2025)
- AI registerNYC Automated Decision Systems — Vsearch (2025)
- AI registerNYC Automated Decision Systems — Vsearch (2025)
- AI registerNYC Automated Decision Systems — Vsearch (2025)
- AI registerNYC Automated Decision Systems — Vsearch (2025)
- AI registerNYC Automated Decision Systems — Vsearch (2025)
- AI registerNYC Automated Decision Systems — Vsearch (2025)
- Register entryPublished by the NYC Office of Technology and Innovation. Reference ad69a5f6. This disclosure was drafted with AI assistance.Schema: ai@2026-05-06-beta
What you can do
Ask about this system
Questions go to the NYC Office of Technology and Innovation, not the vendor.
Your rights
- Right to Be Informed of AI UseThis system processes only environmental wastewater samples and contains no personal data. Members of the public are not subject to any individual decision from this tool. Information about the system is available through the NYC automated decision systems register.
Risks and safeguards
No risks or safeguards have been published for this system yet.