How these numbers are made

Five categories can appear on a locality report. Air quality, schools and connectivity are wired to live sources. Safety and water carry local press coverage only. Power has no card of its own — no source publishes it at locality level — so reported outages appear as a flag on the report instead.

Nestra is in early access, across Delhi, Bengaluru, Gurugram, Hyderabad and Mumbai. A category with nothing sourced yet is left off a report rather than shown as a blank or filled with an estimate.

The headline figure is the CPCB National AQI, computed from 24-hour mean concentrations — which is how CPCB defines it. Not the latest single hour, which moves far more and reads higher.

Readings come from the nearest monitoring station, and the card always says how far away that station is. India's regulatory network has been silent since 27 August 2026, so most localities are currently served by community low-cost sensors measuring PM2.5 alone. Those cards say exactly that rather than presenting the number as a full AQI.

School locations come from OpenStreetMap, so the card answers one question: how many schools are near a locality, and how close. That is a real and useful thing to know, and it is honestly all open data supports here.

It is not a measure of school quality. No open Indian dataset publishes teaching quality, exam results or current staffing at locality level, so the card never shows one and never ranks schools. A locality with many schools nearby reads as good access — not good schools — and the card says exactly that.

Both come from local news coverage, read and classified per locality. They are the two categories where official Indian data is weakest: NCRB publishes crime at district level, a year or more late.

Neither is ever turned into a score. How often a place appears in the press tracks how much media attention it gets, not how often things happen there — a well-covered neighbourhood would look dangerous next to an identical one nobody writes about. So we describe the kind of incident reported, which survives that bias, and leave the ranking alone.

Every headline is judged individually for whether it describes an incident in that specific locality. The card shows how many were read and how many survived, so the count never reads as an exhaustive tally.

Some reports carry a short list of infrastructure the local press has written about — a metro extension, a flyover, a new hospital. These are press reports, not commitments. Indian infrastructure projects are announced years before they open, and many are delayed or dropped; some of the headlines are themselves about a delay.

Nothing in that list counts toward the Trust Score. How much a locality gets written about is not how much is being built there, so the section shows the dated headline and its source and leaves the reader to weigh it.

Where a locality falls in a modeled flood zone, the report says so and gives the depth a 1-in-100-year river flood would reach nearby. It comes from WRI Aqueduct Floods, a global model at about 1 km — so it is regional screening, not a street-level or observed figure, and the card says exactly that and links the source.

It is never turned into a score. A modeled hazard is a fact to weigh, not a number to average into the Trust Score, so a flood zone shows as a plain warning and a clear locality as a plain reassurance.

A weighted composite of the categories that can currently be scored, renormalised over what is actually present. Missing data never counts as a bad result — a locality with no air quality reading is not scored as though its air were poor.

The score names what it is based on, because it rarely rests on all five categories. Below that threshold no number is published at all, and the page shows the individual cards instead. A single measurement wearing the words “Trust Score” would be worse than no score.

Every figure carries one, and it is decided at the moment you read the page rather than when the data was stored — so a reading that was fresh when fetched degrades on its own as it ages, and is withheld entirely once too old to be meaningful.

Community-estimated means there is no reliable official source and the figure leans on press coverage or community sensors. It is never dressed up as official data.

• Publish a safety score from press coverage. The bias runs the wrong way and we have no way to correct for it yet.
• Dress a school count up as a quality ranking, or report a figure from too few samples.
• Fill an empty category with an estimate. Power and infrastructure have no data, and their cards say so.
• Average away a disagreement between sources. Where two sources conflict, the report shows both and says which is which.

Some of this will be wrong. A locality's name can appear in a national story that has nothing to do with living there; a monitoring station can be further away than it looks; a school OpenStreetMap maps nearby can have closed or moved since it was recorded.

Where we find such a case we fix it and say what it was, rather than quietly adjusting the number. If you spot one, tell us — you probably know your own neighbourhood better than any of these sources do.