Inside Toronto’s Shelter System

Daily occupancy and monthly flow data from the City of Toronto — open, interactive, validated

Toronto shelter system data — daily occupancy and capacity, monthly system flow, validated against the City of Toronto’s open data. Interactive tables with date selectors.

daily_occ = FileAttachment("../data/daily_occupancy.json").json()
bt_data   = FileAttachment("../data/city_bridging_triage.json").json()

This page is a hub for Toronto shelter system datasets sourced from the City of Toronto’s open data portal. Each section covers one dataset — use the headings to jump to what you need.

NoteMonthly Shelter System Flow

The dashboards

Open each dashboard directly in your browser — they’re built for interactive use and work best full-screen on a phone.

• Monthly Snapshot →
• Year-to-Date Comparison →
• Historical Trends →

The three tabs below show different views of the data, with interactive filters on every chart.

Monthly Snapshot

A point-in-time view of the shelter system for any month from January 2018 forward. Use the date filter at the top to change months.

Open in a new tab →

Year-to-Date Comparison

Compares the current year’s cumulative figures against the same period the prior year. Useful for seeing whether the system is on track to exceed, match, or fall below last year.

Open in a new tab →

Historical Trends

Multi-year time series for the headline metrics, with filters for population group, year, and month. Useful for spotting long-term patterns or seasonal trends.

Open in a new tab →

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NoteDaily Occupancy & Capacity

function fmtDate(s) {
  const [y, m, d] = s.split("-").map(Number)
  return new Date(y, m - 1, d).toLocaleDateString("en-US", {
    year: "numeric", month: "long", day: "numeric"
  })
}

allDates = [...new Set(daily_occ.map(r => r.date))].sort().reverse()
latestDate = allDates[0]

BonQuery’s version of this table adds two features the City’s page doesn’t have. The date selector below lets you browse any date from January 2021 to the present; the City’s Daily Shelter & Overnight Service Usage page shows only its most recently published date. The Offline column (calculated as funded − actual) flags beds, rooms, or spaces temporarily out of service — see the data validation page for what these are and why they matter.

Daily Occupancy & Capacity for

latestRows = daily_occ.filter(r => r.date === latestDate)

function getVal(rows, key) {
  const row = rows.find(r => r.key === key)
  return row ? row.ind : null
}

validationChecks = {
  const rows = latestRows
  const checks = []

  // Check 1: all expected keys present
  const expectedKeys = [
    "all_shelter","room_based","singles_sector","singles_shelter","allied_summ",
    "temp_summ","iso_summ","fam_total","fam_emerg","fam_trans_r","fam_hotel",
    "sng_hotel","singles_total","emerg_total","mix_emerg","men_emerg","wom_emerg",
    "yth_emerg","trans_total","mix_trans","fam_trans_b","men_trans","wom_trans",
    "yth_trans","allied_total","respites","dropin","temp_resp","hotels","iso"
  ]
  const presentKeys = new Set(rows.map(r => r.key))
  const missingKeys = expectedKeys.filter(k => !presentKeys.has(k))
  checks.push({
    name: "All expected rows present",
    pass: missingKeys.length === 0,
    detail: missingKeys.length > 0 ? `Missing: ${missingKeys.join(", ")}` : null
  })

  // Check 2: All Shelter Programs total = sum of components
  const allShelter = getVal(rows, "all_shelter")
  const compSum = ["fam_total","sng_hotel","singles_total","allied_total","temp_resp","hotels","iso"]
    .reduce((s, k) => s + (getVal(rows, k) ?? 0), 0)
  checks.push({
    name: "All Shelter Programs rollup matches components",
    pass: allShelter === compSum,
    detail: allShelter !== compSum
      ? `all_shelter.ind=${allShelter}, component sum=${compSum}, diff=${allShelter - compSum}`
      : null
  })

  // Check 3: Singles sectors total = emergency + transitional
  const singlesTotal = getVal(rows, "singles_total")
  const emergTotal = getVal(rows, "emerg_total")
  const transTotal = getVal(rows, "trans_total")
  checks.push({
    name: "Singles sectors rollup: emergency + transitional = singles total",
    pass: singlesTotal === (emergTotal + transTotal),
    detail: singlesTotal !== (emergTotal + transTotal)
      ? `singles=${singlesTotal}, emerg+trans=${emergTotal + transTotal}`
      : null
  })

  // Check 4: For every row with non-null cap, occ + unocc = cap (within 1, for rounding)
  const capRows = rows.filter(r => r.cap !== null && r.cap > 0)
  const arithFails = capRows.filter(r => Math.abs(r.occ + r.unocc - r.cap) > 0.5)
  checks.push({
    name: "Internal arithmetic: occupied + unoccupied = actual capacity",
    pass: arithFails.length === 0,
    detail: arithFails.length > 0
      ? arithFails.map(r => `${r.key}: ${r.occ}+${r.unocc}≠${r.cap}`).join("; ")
      : null
  })

  return checks
}

allPass = validationChecks.every(c => c.pass)

// ── Validation banner ─────────────────────────────────────────────────────
validationBanner = {
  const CITY_CENSUS_URL = "https://www.toronto.ca/city-government/data-research-maps/research-reports/housing-and-homelessness-research-and-reports/shelter-census/"

  if (!allPass) {
    const failedChecks = validationChecks.filter(c => !c.pass)
    return html`<div style="
      background:var(--bq-warn-bg);border:1px solid var(--bq-warn-border);border-radius:4px;
      padding:8px 14px;font-size:0.88em;color:var(--bq-warn-fg);margin-bottom:12px">
      <strong>⚠ Validation issue detected for ${fmtDate(latestDate)}</strong>
      <details style="margin-top:6px">
        <summary style="cursor:pointer">Show details</summary>
        <ul style="margin:6px 0 0;padding-left:20px">
          ${failedChecks.map(c => html`<li>${c.name}${c.detail ? html` — <em>${c.detail}</em>` : ""}</li>`)}
        </ul>
      </details>
    </div>`
  }
  // ── City-vs-BonQuery banner hidden ────────────────────────────────────────
  // Bridging & Triage (29 ppl) and known capacity differences cause the
  // current validator to always fail. Re-enable after the capacity
  // reconciliation analysis so we can show a clean ✓ / * / status that
  // distinguishes documented structural differences from genuine discrepancies.
  return html``
}

viewof selectedDate = Inputs.select(allDates, {
  label: "Date",
  format: d => fmtDate(d)
})

html`<p class="bq-ckan-note">Latest available from City of Toronto Open Data: <strong>${fmtDate(latestDate)}</strong>.</p>`

dayRows = daily_occ.filter(r => r.date === selectedDate)

function n(v) { return v !== null && v !== undefined ? v.toLocaleString() : "—" }
function pct(v) { return v !== null && v !== undefined ? v.toFixed(1) + "%" : "—" }

function offlineCell(r) {
  if (r.cap === null || r.cap === undefined) return `<td></td>`
  if (r.cap_funding === null || r.cap_funding === undefined) return `<td></td>`
  const offline = r.cap_funding - r.cap
  if (offline <= 0) {
    return `<td class="bq-num">${offline.toLocaleString()}</td>`
  }
  return `<td class="bq-num bq-danger">${offline.toLocaleString()}</td>`
}

function tableRow(r, col1Label) {
  const pad = (r.indent ?? 0) * 16
  const cls = r.is_total ? "bq-row-total" : "bq-row"
  const bld = r.is_total ? " bq-bold" : ""
  if (r.col_type === "summary") {
    return `<tr class="${cls}">
      <td style="padding-left:${pad}px" class="${bld}">${r.label}</td>
      <td class="bq-num${bld}">${n(r.ind)}</td>
      <td></td><td></td><td></td><td></td><td></td>
    </tr>`
  }
  return `<tr class="${cls}">
    <td style="padding-left:${pad}px" class="${bld}">${r.label}</td>
    <td class="bq-num${bld}">${n(r.ind)}</td>
    <td class="bq-num">${n(r.occ)}</td>
    <td class="bq-num">${n(r.unocc)}</td>
    <td class="bq-num">${n(r.cap)}</td>
    ${offlineCell(r)}
    <td class="bq-num">${pct(r.rate)}</td>
  </tr>`
}

function sectionHeader(label, col1, col2, col3, col4) {
  return `<tr class="bq-th">
    <td>${label}</td>
    <td class="bq-num">Individuals</td>
    <td class="bq-num">${col1}</td>
    <td class="bq-num">${col2}</td>
    <td class="bq-num">${col3}</td>
    <td class="bq-num">${col4}</td>
    <td class="bq-num">Occupancy Rate</td>
  </tr>`
}

function summaryHeader() {
  return `<tr class="bq-th">
    <td>Occupancy Summary</td>
    <td class="bq-num">Individuals</td>
    <td colspan="5"></td>
  </tr>`
}

dailyTable = {
  const s = (key) => dayRows.find(r => r.key === key)

  const allShelterInd = s("all_shelter") ? s("all_shelter").ind : null
  const btEntry  = bt_data && bt_data.entries ? bt_data.entries[selectedDate] : null
  const btInd    = btEntry ? btEntry.bridging_triage : null
  const btStart  = bt_data && bt_data.first_captured
    ? bt_data.first_captured
    : "the date scraping began"
  const totalInd = (allShelterInd !== null && btInd !== null)
    ? allShelterInd + btInd
    : allShelterInd

  const totalAccomRow = `<tr class="bq-row-total bq-bold">
    <td>Total People Accommodated †</td>
    <td class="bq-num">${n(totalInd)}</td>
    <td></td><td></td><td></td><td></td><td></td>
  </tr>`
  const bridgingRow = btInd !== null
    ? `<tr class="bq-row-alt">
        <td style="padding-left:26px">Bridging &amp; Triage Programs</td>
        <td class="bq-num">${n(btInd)}</td>
        <td></td><td></td><td></td><td></td><td></td>
       </tr>`
    : `<tr class="bq-row-na">
        <td style="padding-left:26px">Bridging &amp; Triage Programs</td>
        <td class="bq-num" style="font-size:0.85em"
          >Not available for this date</td>
        <td></td><td></td><td></td><td></td><td></td>
       </tr>`

  const summaryKeys = ["all_shelter","room_based","singles_sector","singles_shelter","allied_summ","temp_summ","iso_summ"]
  const roomKeys    = ["fam_total","fam_emerg","fam_trans_r","fam_hotel","sng_hotel"]
  const bedKeys     = ["singles_total","emerg_total","mix_emerg","men_emerg","wom_emerg","yth_emerg",
                       "trans_total","mix_trans","fam_trans_b","men_trans","wom_trans","yth_trans"]
  const alliedKeys  = ["allied_total","respites","dropin"]

  return html`
    <div style="overflow-x:auto;margin:0 0 1rem">
    <table class="bq-table">
      ${summaryHeader()}
      ${totalAccomRow}
      ${bridgingRow}
      ${summaryKeys.map(k => s(k) ? tableRow(s(k)) : "").join("")}

      ${sectionHeader("Shelter Programs, Room-Based", "Occupied Rooms", "Unoccupied Rooms", "Actual Room Capacity", "Offline Rooms")}
      ${roomKeys.map(k => s(k) ? tableRow(s(k)) : "").join("")}

      ${sectionHeader("Shelter Programs, Bed-Based", "Occupied Beds", "Unoccupied Beds", "Actual Bed Capacity", "Offline Beds")}
      ${bedKeys.map(k => s(k) ? tableRow(s(k)) : "").join("")}

      ${sectionHeader("Allied Services", "Occupied Spaces", "Unoccupied Spaces", "Actual Space Capacity", "Offline Spaces")}
      ${alliedKeys.map(k => s(k) ? tableRow(s(k)) : "").join("")}

      <tr class="bq-th">
        <td>Temporary Programs, Bed/Space-Based</td>
        <td class="bq-num">Individuals</td>
        <td class="bq-num">Occupied Beds/Spaces</td>
        <td class="bq-num">Unoccupied</td>
        <td class="bq-num">Actual Capacity</td>
        <td class="bq-num">Offline Beds/Spaces</td>
        <td class="bq-num">Occupancy Rate</td>
      </tr>
      ${s("temp_resp") ? tableRow(s("temp_resp")) : ""}

      ${sectionHeader("Temporary Programs, Room/Unit-Based", "Occupied Rooms", "Unoccupied Rooms", "Actual Room Capacity", "Offline Rooms")}
      ${s("hotels") ? tableRow(s("hotels")) : ""}

      ${sectionHeader("Temporary Isolation/Recovery Programs", "Occupied Rooms", "Unoccupied Rooms", "Actual Room Capacity", "Offline Rooms")}
      ${s("iso") ? tableRow(s("iso")) : ""}
    </table>
    <p class="bq-footnote">
      † Total People Accommodated = All Shelter Programs + Bridging &amp; Triage Programs.
      Bridging &amp; Triage figures are not published to the City of Toronto open data (CKAN)
      export. BonQuery scrapes them daily from the City's shelter census page when the City
      posts the table; data is available from ${btStart} onward.
      On days when the City has not yet published (weekends, holidays, or publication delays),
      the Bridging &amp; Triage row will show "Not available for this date" and the Total
      will reflect All Shelter Programs only.
    </p>
    </div>`
}

This table reproduces the City of Toronto’s Daily Shelter & Overnight Service Usage report using the City’s open data. The All Shelter Programs subtotal and all breakdown rows are derived from the CKAN open data export. Bridging & Triage Programs are tracked in the City’s operational system but not published to open data; BonQuery scrapes this figure daily from the City’s shelter census page and displays it where available. The Total People Accommodated figure equals All Shelter Programs + Bridging & Triage when both are available. Some capacity and unoccupied-bed figures may differ slightly from the City’s live dashboard due to offline-bed reporting differences between the CKAN export and the City’s operational system. A full side-by-side comparison is available on the data validation page.

Contains information licensed under the Open Government Licence – Toronto. Source: City of Toronto Open Data — Daily Shelter & Overnight Service Occupancy & Capacity. Aggregated by BonQuery.

BonQuery’s aggregated data is available for download from 2021 to present: JSON · CSV

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NoteShelter System Requests for Referrals

Monthly average daily calls to Toronto’s 24/7 shelter referral line — calls referred to a shelter space, unmatched individual callers, and total calls handled — with interactive date controls. Replicates and extends the City’s Shelter System Requests for Referrals page. Data sourced from two separate CKAN resources (call wrap-up codes and service queue); see the page for important caveats on combining the two series.

• Shelter System Requests for Referrals →

Open in a new tab →

Contains information licensed under the Open Government Licence – Toronto. Source: City of Toronto Open Data — Central Intake Calls. Analysis and charts by BonQuery.