AI-Assisted Genomic Alignment for Wastewater COVID-19 Surveillance
What it is for
- Bowtie2 is an intermediate step in the wastewater surveillance workflow used to analyze COVID-19 variants circulating in the community by processing environmental biological samples.
- 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.
What it is for
Bowtie2 is a bioinformatics tool used by the NYC Department of Health and Mental Hygiene to align genetic sequencing data from wastewater samples against a reference genome. It is an intermediate computational step in a workflow that identifies COVID-19 variants circulating in the community. No personal or identifying information about individuals is collected or processed — the input is environmental biological material, not data about named people.
What it collects and what happens to it
Data taken in
- Laboratory-generated sequencing reads from wastewater biological samples, plus an indexed organism reference genome. These are environmental measurements with no link to identifiable individuals.
Processing
- Bowtie2 applies Burrows-Wheeler alignment — a string-matching and index-based technique — to classify sequencing reads against reference genome positions, identifying sequence variants present in wastewater samples.
What it does
- Bowtie2 reads raw laboratory-generated sequencing reads and aligns them to an indexed reference genome using Burrows-Wheeler transformations, producing structured genomic alignment output for downstream variant analysis.
Outputs
- Genomic alignments indicating sequence variation relative to the reference genome, supporting COVID-19 variant analysis and wastewater surveillance comparisons. Outputs are aggregate environmental data with no individual-level identification.
Run by
- The NYC Department of Health and Mental Hygiene's Public Health Laboratory deploys Bowtie2 as part of its wastewater surveillance workflow to detect and monitor COVID-19 variants in New York City.
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 stated by the NYC Office of Technology and Innovation.
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 — Bowtie2 (2025 Register Entry)NYC Department of Health and Mental Hygiene, Disease Control – Public Health Laboratory. Reported 2025, first used June 2022.
- AI registerNYC AI Use Cases 2025 — Bowtie2
- AI registerNYC AI Use Cases 2025 — Bowtie2
- AI registerNYC AI Use Cases 2025 — Bowtie2
- AI registerNYC AI Use Cases 2025 — Bowtie2
- AI registerNYC AI Use Cases 2025 — Bowtie2
- AI registerNYC AI Use Cases 2025 — Bowtie2
- AI registerNYC AI Use Cases 2025 — Bowtie2
- Register entryPublished by the NYC Office of Technology and Innovation. Reference 79787360. 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 Algorithmic TransparencyBowtie2 is open-source software publicly available at https://github.com/BenLangmead/bowtie2. Its algorithmic logic, based on Burrows-Wheeler transformations, is fully documented and auditable by the public.
Risks and safeguards
No risks or safeguards have been published for this system yet.