The Opioid Crisis

Opioid use disorder (OUD) continues to be one of the most urgent public health challenges of our time. Across the United States, opioid misuse including prescription pain relievers, heroin, and synthetic opioids like fentanyl has driven sharp increases in overdose deaths and non-fatal overdoses. These harms extend far beyond individuals, affecting families, and communities.

OUD is preventable and treatable. Evidence-based strategies including: harm reduction, Medication Assisted Recovery (MAR) and wraparound recovery supports reduce overdose risk and harms of opioid and substance use.

Impact on Suburban Cook County

Over the past decade, suburban Cook County has experienced increasing opioid-involved deaths and growing disparities across demographic groups. The crisis has been intensified by the emergence of fentanyl in the drug supply and by disruptions linked to the COVID-19 pandemic. The impact has been uneven: some municipalities and neighborhoods carry a disproportionate share of the burden, reflecting broader inequities driven by structural racism.

These harms affect many parts of everyday families and schools, workplaces, first responders, and healthcare systems. Communities experiencing systemic and structural disadvantages face higher risk yet fewer resources. Understanding where and for whom the burden is greatest helps direct prevention, treatment access, and outreach to the places that need them most.

CCDPH’s Response

This dashboard was developed by the Cook County Department of Public Health (CCDPH) to provide a clear, data driven picture of the opioid epidemic in suburban Cook County. It integrates multiple sources: death records, hospital discharge data, naloxone distribution, and census population estimates to highlight trends over time, differences across communities, and the reach of risk reduction strategies.

By making this information accessible, interactive, and downloadable, the dashboard aims to support community members, community organizations, healthcare providers, and policymakers in understanding the scope of the crisis and identifying opportunities for prevention, treatment, and recovery support. Together, these data are intended to guide action toward reducing overdose deaths and building healthier communities.

Explore CCDPH reports on opioid-involved overdose
In-depth analysis of opioid-involved overdose in suburban Cook.

Learn about naloxone
Find out where to get free kits and training in suburban Cook County.

Visit CCDPH Health Atlas
Interactive maps, charts, and tables on a wide range of health topics.
A dynamic companion to this dashboard for deeper, neighborhood-level insights.

Call the Illinois Helpline at 1-833-2FINDHELP for free spport, it’s accessible 24/7.

Summary
  • The age-adjusted opioid-involved death rate in suburban Cook County rose sharply from about 11 per 100,000 in 2013 to nearly 28 per 100,000 in 2022. This is about 2.5-fold increase over the decade.

  • Growth was gradual from 2013–2015, then accelerated in 2016 and again between 2019–2020.

  • The largest single-year increase occurred from 2019 to 2020, coinciding with the start of the COVID-19 pandemic.

  • Rates decreased slightly in 2021 but rebounded to a new high in 2022.

  • Overall, the trend shows sustained escalation over the decade, suggesting a persistent and intensifying public health crisis.

  • Provisional data for 2023 show a sharp decline in both age-adjusted rates (dropping below 20 per 100,000 by 2023) and death counts (falling to ~400 in 2023); however, these numbers are not yet confirmed and should be interpreted with caution.

(a) Opioid-involved Death Rates by Years (2013-2023)
(b) Opioid-involved Death Counts by Years (2013-2023)
Figure 1: Opioid-involved Deaths by Years in suburban Cook County (2013-2023)
Summary
  • Across 2013–2022, opioid-involved death rates were consistently highest among residents aged 35–44 and 45–54, both peaking near or above 50 per 100,000 in 2020. This represents an almost 3-fold increase from 2013.

  • The 25–34 age group saw sharp increases starting in 2015, reaching rates above 40 per 100,000 by 2020–2022. This indicates about a 1.5-fold increase from 2013.

  • Rates for 55–64 also rose steadily, approaching 40 per 100,000 by 2022, narrowing the gap with younger middle-aged groups. This indicates about 2-fold increase from 2015.

  • Adolescents and young adults (15–24) maintained the lowest rates but experienced a noticeable uptick after 2019.

  • Nearly all age groups experienced their largest year-to-year jumps between 2019 and 2020, suggesting a shared external driver during that period.

  • Provisional data for 2023 suggest declines across most age groups, with rates falling sharply from their 2020–2022 peaks; the 55–64 and 45–54 groups—previously among the highest drop below Illinois’ 2022 benchmark of 44.5 per 100,000, while proportional shares of deaths shift modestly toward midlife adults; however, these numbers are preliminary and not yet confirmed.

(a) Opioid-involved Death Rates by Age Groups (2013-2023)
(b) Opioid-involved Death Proportions (and Counts) by Age Groups (2013-2023)
Figure 2: Opioid-involved Deaths by Age Groups in suburban Cook County, IL (2013-2023)
Summary
  • From 2013–2022, females consistently had much higher opioid-involved death rates than males in suburban Cook County.

  • Female rates rose sharply after 2015, peaking at ~40 per 100,000 in 2020 and reaching a new high (~44) in 2022. Almost a 3 folds increase by 2022.

  • Male rates increased gradually over the decade, with a notable spike in 2020, but remained well below female rates.

  • Both sexes experienced their largest single-year rise between 2019 and 2020, suggesting a shared external driver.

  • The persistent gap points to potential sex-specific risk factors or differences in exposure, treatment access, or reporting. By 2023, this gap seems to be narrowing.

  • Provisional data for 2023 indicate notable declines in opioid-related death rates among both sexes, with male rates dropping sharply from a 2022 peak near 42 per 100,000 to well below the Illinois 2022 benchmark (37.3), and female rates falling to under 10 per 100,000; males continue to account for the large majority of deaths by proportion, but these numbers remain preliminary and unconfirmed.

(a) Opioid-involved Death Rates by Sex Categories (2013-2023)
(b) Opioid-involved Death Proportions (and counts) by Sex Categories (2013-2023)
Figure 3: Opioid-involved Deaths by Sex Categories in suburban Cook County, IL (2013-2023)
Summary
  • From 2013–2022, NH Black residents experienced the steepest and highest rise in opioid-involved death rates, peaking above 50 per 100,000 in 2022. This represents more than a 5-fold increase over the decade.

  • NH White residents saw persistently high rates, generally second to NH Black, with a peak around 30 per 100,000 in 2020.

  • Hispanic residents had lower rates than NH Black and NH White populations but showed steady growth, a 4-fold increase from 2013 to 2022.

  • NH Asian residents maintained consistently low rates, though slight increases appeared in some years.

  • The sharpest increases across most groups occurred between 2019 and 2020, highlighting a period of accelerated disparities.

  • Provisional data for 2023 show declines across all racial/ethnic groups, with NH Black residents, who have historically carried the highest burden, falling sharply from their 2020–2022 peaks, while NH White and Hispanic groups also drop from elevated levels; all values are preliminary and not yet confirmed.

(a) Opioid-involved Death Rates by Race / Ethnicity (2013-2023)
(b) Opioid-involved Death Proportions (and counts) by Race / Ethnicity (2013-2023)
Figure 4: Opioid-related Deaths Rates by Race / Ethnicity in suburban Cook County, IL (2013-2023)
Summary
  • High-burden clusters: Olympia Fields show the most extreme opioid-related death rates (over 1,000 per 100,000), far exceeding other municipalities, indicating localized crises that warrant targeted intervention.

  • Municipalities-level disparities: Small Municipalities like Phoenix and Dixmoor have disproportionately high rates despite lower absolute counts, suggesting that smaller populations may face heightened vulnerability when overdose events occur.

  • Urban vs. suburban spread: The map reveals concentrated darker clusters in south and west suburban Cook County, aligning with historically under-resourced areas and pointing to persistent health inequities.

  • Community-level burden: Municipalities such as Maywood and Melrose Park illustrate both high counts and elevated rates, underscoring how cumulative community burden may strain local healthcare, law enforcement, and social services.

  • Geographic variation in exposure: Large portions of northern suburbs show lighter shading (lower rates), highlighting stark contrasts in opioid mortality risk across the county, reflecting differences in socioeconomic conditions, access to care, and structural determinants of health.

Table 1: Municipalities with the Highest Rates of Opioid-Related Deaths in suburban Cook County, Illinois (2018–2022)
Municipalities Count Rate
Olympia Fields 35 1149.3
Harvey 42 489.1
Phoenix 14 482.6
Maywood 49 365.7
Palos Heights 42 365.4
Dixmoor 28 275.3
Melrose Park 56 251.0
Robbins 21 236.0
Hazel Crest 42 230.3
East Hazel Crest 35 202.1
Figure 5: Opioid-Related Deaths Across Suburban Cook County Municipalities, Illinois (2018–2022): A Five-Year Overview
Summary
  • Sustained burden: Age-adjusted rates increase sharply (2013→2017), decrease in 2018, then rebound to a 2020 peak before easing,while annual visit counts follow the same pattern. By 2022 both remain far above early decade levels. Rates increased by 2.5-fold over the decade.

  • Magnitude matters: From 2013 to the 2020 apex, rates roughly tripled (3.2 folds), and visits rose from about hundreds to several thousand per year; even with the 2021–2022 pullback, visits stayed elevated relative to baseline.

  • Risk vs. Visits: Figure 6 (a) reflects changing risk (age-adjusted, not driven by population aging), whereas Figure 6 (b) translates that risk into operational demand for Emergency Departments (ED) staffing, naloxone supply, and care coordination.

  • Two inflection points: A step-up around 2016 aligns with the shift to a fentanyl-dominant supply; the 2020 spike coincides with COVID-19 service disruptions which is consistent with national nonfatal overdose patterns.

(a) Opioid-involved ED Visits Rates by Years (2013-2022)
(b) Opioid-inovlved ED Visits Counts by Year (2013-2022)
Figure 6: Opioid-related ED Visits by Years in suburban Cook County, IL (2013-2022)
Summary
  • Who is most affected: Rates are highest for 25–34 across the decade, peaking around 2017 and again near 2020 before easing.

  • Cohort aging into midlife: 35–44 and 45–54 climb steadily and remain high through 2020–2022; the proportion chart shows these midlife groups making up an increasing share of emergency department visits by the end of the series. This indicates an increase of 2-fold over the decade.

  • Youth decline, real but uneven: 15–24 peaks mid-decade then drops in both rate and share—progress that still warrants vigilance given polysubstance exposure and shifting supply.

  • Older adults rising: 55–64 year olds saw marked increases in rate and proportion; 65+ remains lowest but trends upward, flagging further exploration of risk and possible remedies for older adults.

  • Pandemic effect across ages: Most groups show a 2020 surge with only partial normalization by 2022, indicating a true escalation in harm during COVID-19 disruptions rather than improved detection alone.

(a) Opioid-related ED Visits Rates Trend by Age Groups (2013-2022)
(b) Opioid-related ED Visits Proportions (and counts) by Age Groups (2013-2022)
Figure 7: Opioid-related ED Visits by Age Groups in suburban Cook County, IL (2013-2022)
Summary
  • Diverging rate curves: Age-adjusted male rates rise sharply from 2013, peak in 2020, then ease; female rates are lower and flatter, with a smaller pandemic increase, both remain above early-decade levels by 2022. Male rates increased 3 folds over the decade.

  • Workload & risk: The proportion plot shows men account for ~70–75% of ED visits most years meaning ED workload is male-dominant.

  • Pandemic effect: A clear 2020 spike across sexes aligns with national nonfatal overdose trends during COVID-19 disruptions; 2021–2022 levels remain elevated, which might indicate a persistent burden rather than a transient adverse effect (no causal relationship was determined at this time).

(a) Opioid-related ED Visits Rate Trends by Sex (2013-2022)
(b) Opioid-related ED Visits Proportions (and counts) by Sex (2013-2022)
Figure 8: Opioid-related ED Visits by Sex in suburban Cook County, IL (2013-2022)
Summary
  • Highest and growing burden among NH Black residents: Rates for NH Black residents surge after 2015 and remain the highest through 2020–2022 (≈200 per 100,000 at peak). This is an increase of 8.5 folds over the decade. The proportion of emergency department visits also shifts markedly toward NH Black patients, rising from roughly a quarter of visits early in the decade to about a third by 2021–2022.

  • NH White: elevated but declining late-decade: NH White rates climb through the mid 2010s, spike again in 2020, then fall by 2022. Their share of emergency department visits decreases from a clear majority in 2013 to near parity with NH Black by the end of the decade.

  • Hispanic: moderate rates, steady workload: Hispanic rates rise through the mid 2010s and ease slightly thereafter; their proportional contribution stays relatively stable, suggesting steady emergency department visits even as risk fluctuates.

  • NH Asian: consistently lowest, but interpret with caution: NH Asian rates remain lowest and counts are small (<~5% of visits most years).

(a) Opioid-related ED Visits Rates Trend by Race / Ethnicity (2013-2022)
(b) Opioid-related ED Visits Proportions (and counts) by Race / Ethnicity (2013-2022)
Figure 9: Opioid-related ED Visits By Race / Ethnicity in suburban Cook County, IL (2013-2022)
Summary
  • Extreme ED burden: Maywood reports the highest ED visit rate (3,436.6 per 100,000), far exceeding all other municipalities, reflecting heightened community-level strain on emergency health services.

  • Clustered high rates: Neighboring west suburban areas (Bellwood, Broadview, Berkeley) also show very high rates, suggesting a concentration of deaths in some west suburban communities.

  • Overlap with mortality patterns: Harvey and Phoenix again emerge with high emergency department visit rates, similar to their elevated opioid death burdens.

  • Unexpected hotspots: Smaller municipalities like Hometown and Dixmoor show disproportionately high rates relative to their size.

  • Geographic spread: The map shows dense clusters of dark-shaded (higher-rate) municipalities in central, western, and southern suburbs, while northern regions generally have lower rates—pointing to uneven risk environments across the county.

Table 2: Municipalities with the Highest Rates of Opioid-Related Emergency Department Visits in Suburban Cook County, Illinois (2018–2022)
Municipalities Count Rate
Maywood 49 3436.6
Bellwood 49 1750.2
Broadview 42 1643.3
Harvey 42 1426.1
Phoenix 14 1405.3
Hometown 28 1361.0
Dixmoor 28 1344.5
Elmhurst 14 1328.8
Blue Island 35 1326.8
Berkeley 35 1324.7
Figure 10: Opioid-Related ED Visits Across Suburban Cook County Municipalities, Illinois (2018–2022): A Five-Year Overview
Summary
  • Peak then steady decline: Hospital admission rates rise sharply to a 2016–2017 peak (about 90 → about 85 per 100,000) and then fall about 65–70% to about 30 by 2022; counts mirror this pattern (about 2,100 → about 750), indicating a real contraction in inpatient burden, not just demographic change (rates are age-adjusted).

  • Divergence from ED trends: Unlike ED visits (which peak in 2020), admissions keep dropping through the pandemic, which might be related to higher admission thresholds.

  • Pandemic acceleration: The continued decline in 2020–2022 aligns with broad U.S. reductions in hospital admissions and emergency department volumes during COVID-19, even as overdose harms remained high.

  • Nuances: Decreasing admissions (rates and counts) do not imply reduced opioid harm; they more likely reflect care setting shifts and capacity strategies.

(a) Opioid-related Hospital Admissions Rates Trend by Years (2013-2022)
(b) Opioid-related Hospital Admissions Counts by Years (2013-2022)
Figure 11: Opioid-related Hospital Admissions by Years in suburban Cook County, IL (2013-2022)
Summary
  • Peak-and-decline across ages: Admission rates spike in 2016–2017 for every age group (highest in 25–34), then decline steadily through 2022; counts mirror this fall.

  • Opioid-invovled hospital admissions concentrates in midlife: After 2016, 35–44 and 45–54 maintain the largest proportions of hospitalizations, even as their rates fall.

  • Youth and older adults diverge: 15–24 drops sharply in both rate and share after 2016, while 55–64 (and to a lesser extent 65+) retain a meaningful and slightly rising proportion.

  • No pandemic rebound in admissions: Unlike emergency department visits, hospitalizations continue to fall through 2020–2022, consistent with heightened admission thresholds.

(a) Opioid-related Hospital Admissions Rates by Age Groups (2013-2022)
(b) Opioid-related Hospital Admissions Proportions (and counts) by Age Groups (2013-2022)
Figure 12: Opioid-related Admissions by Age Groups in suburban Cook County,IL (2013-2022)
Summary
  • Different curves, same peak window: Age-adjusted male admission rates jump earliest and highest (peak around 2016–2017) and then decline steadily; female rates peak later/lower and also fall by 2022 both sexes are well below mid-decade highs, with males still above females.

  • No pandemic rebound: Unlike ED visits, hospital admissions keep dropping through 2020–2022, consistent with higher admission thresholds (this observation requires further investigation).

(a) Opioid-related Hospital Admissions Rates by Sex (2013-2022)
(b) Opioid-related Hospital Admissions Proportions (and count) by Sex (2013-2022)
Figure 13: Opioid-related Hospital Admissions by Sex in suburban Cook County, IL (2013-2022)
Summary
  • Peak then broad decline across groups: Hospital admission rates surge in 2016–2017 for all races / ethnicities, then decrease steadily through 2022. The drop is most pronounced for NH Black residents (highest mid-decade peak, still above others by 2022), and substantial for NH White and Hispanic groups; NH Asian remains lowest throughout.

  • No pandemic rebound in admissions: Unlike ED trends, admissions continue to decline through 2020–2022, consistent with higher admission thresholds.

  • Equity signal remains clear: Even as rates fall, NH Black residents carry the highest per-resident admission risk across most years, indicating persistent exposure and access barriers.

(a) Opioid-related Hospital Admissions Rates by Race / Ethnicity (2013-2022)
(b) Opioid-related Hospital Admissions Proportions (and count) by Race / Ethnicity (2013-2022)
Figure 14: Opioid-related Admissions By Race / Ethnicity in suburban Cook County, IL (2013-2022)
Summary
  • Concentrated hospital burden: Maywood again stands out with the highest admission rate (1,100.1 per 100,000), showing a persistent pattern of opioid-related harm across multiple indicators (deaths, ED, and hospitalizations).

  • Regional clustering: Blue Island, and several south suburban Municipalities (Dixmoor, Harvey, Phoenix, Riverdale, Calumet Park) report high admission rates, suggesting geographic inequities already visible in mortality and ED data.

  • Small communities, big impact: Municipalities like Dixmoor and Phoenix have smaller populations but disproportionately high hospitalization rates.

  • Overlap with opioid-related deaths / ED hotspots: Areas such as Harvey and Maywood consistently appear across all three outcomes, highlighting structural vulnerabilities.

  • Geographic disparities: The map shows central, south, and western suburbs shaded darkest, while northern regions remain lighter.

Table 3: Municipalities Burden of Opioid-Related Hospital Admissions in suburban Cook County, Illinois (2018–2022)
Municipalities Count Rate
Maywood 49 1100.1
Blue Island 35 786.6
Dixmoor 28 705.2
Hometown 28 691.3
Harvey 42 635.2
Phoenix 14 625.9
Riverdale 28 622.4
Calumet Park 14 616.9
Bellwood 49 582.1
Broadview 42 553.2
Figure 15: Opioid-Related Hospital Admissions Across Suburban Cook County Municipalities, Illinois (2018–2022): A Five-Year Overview
Summary
  • Steady growth: Naloxone distribution by CCDPH rose sharply from just a few hundred kits in 2020 to over 4,000 kits by 2024, showing a consistent expansion.

  • Acceleration after 2022: The biggest increase occurred between 2022 and 2024, where distributions increased more than 3 folds.

  • Combined impact: By August 2025, CCDPH distributed 15,409 kits, while community partners funded by CCDPH provided 25,418 kits by 2024, bringing the CCDPH total to 40,827 kits.

  • Ongoing naloxone kits distribution through 2025: Numbers from the ongoing NLX kits distribution are still being collected, but through August of 2025, kits distributed exceeded 5,000 (25% more than 2024).

CCDPH

15,409

Naloxone Kits distributed by CCDPH from 2020 to 2025

Community Partners

25,418

Naloxone Kits distributed by community partners across suburban Cook County by 2024

Overall

40,827

Naloxone Kits distributed by CCDPH and community partners in the county
Figure 16: Naloxone Kits Distribution by CCDPH Trend in Suburban Cook County, IL (2020 - August 2025)
Summary
  • Naloxone expansion: Distribution of Naloxone (NLX) kits increased steadily, surpassing 4,000 annually by 2024, reflecting sustained scale-up of harm reduction infrastructure.

  • Fentanyl test strips plateau: Test strip distribution rose sharply by 2021, then plateaued around 200–220 per year through 2024.

  • Training surge: Training of individuals grew modestly through 2023, then peaked dramatically in 2024 (>900 trained), which might indicate a surge in community engagement.

  • Overdose response trend: Naloxone doses used in overdoses peaked in 2022–2023 (about 50 per year), then declined through 2024.

Figure 17: Naloxone Distribution, Training, and Overdose Response Activities in Suburban Cook County, IL (2020–2025)
Figure 18: Naloxone Distributed by CCDPH Across Suburban Cook County, IL (2024)

How to use Guide:

This dashboard is designed as a public health decision-support tool for exploring opioid-related outcomes in suburban Cook County. It provides interactive charts, tables, and static maps that allow users to examine trends and disparities across time, population groups, and geography.

  1. Navigation
    • Use the tabs across the top of each section (e.g., Overall Trends, Age Groups, Sex, Race/Ethnicity, Municipalities, Townships) to switch between different perspectives on the data.

    • Each section begins with a summary callout highlighting the most important findings.

  2. Charts and Graphs

    • Most line and bar charts are interactive:

    • Hover over data points to view exact values, case counts, or rates.

    • Legends can be toggled on/off to isolate specific groups.

    • Charts include both rates (standardized for population size and age distribution) and counts (absolute numbers), providing complementary views of the data.

  3. Maps
    • Geographic maps are static illustrations but shaded by burden level (darker = higher rates).

    • These maps provide spatial context, highlighting clusters of opioid mortality, ED visits, and hospital admissions across suburban Cook County.

  4. Tables
    • Summary tables (e.g., municipalities, townships) list counts, and age-adjusted rates.

    • Tables allow easy comparison across jurisdictions and provide precise values behind the maps.

  5. Download Options

    • All charts include download buttons, enabling export of figures for presentations, reports, or further analysis.

    • Downloads are available in common formats (i.e., PNG).

  6. Interpretation Notes

    • Counts show the raw number of cases but do not account for differences in population size.

    • Rates (especially age-adjusted rates) provide a fair comparison between groups and over time.

    • Multi-year aggregations (2018–2022) are used for small-area geographies to reduce volatility from small numbers.

Data Source:

  1. Vital Statistics (Death Records)

    • Source: Illinois Department of Public Health (IDPH) death certificate files.

    • Coverage: 2013–2022.

    • Content: Records of all resident deaths occurring in suburban Cook County.

    • Use: Identification of opioid-related deaths (via ICD-9 & ICD-10 underlying or multiple cause codes) and calculation of age-adjusted mortality rates and annual counts.

  2. Hospital Discharge Data

    • Source: Illinois Department of Public Health (IDPH) hospital discharge database.

    • Coverage: 2013–2022.

    • Content: Emergency Department (ED) visits and inpatient admissions attributed to non-fatal opioid overdoses. Geographic locations are based on the residence of the patients.

    • Use: Estimation of non-fatal overdose burden across time, stratified by demographic and geographic groups.

  3. CCDPH Behavioral Health Unit

    • Source: Cook County Department of Public Health (Behavioral Health Unit records).

    • Coverage: 2020–August 2025.

    • Content: Data on naloxone kit distribution, training activities, and overdose reversal reports.

    • Use: Monitoring harm-reduction reach, volume, and geographic distribution across suburban Cook County.

  4. Cook County Medical Examiner’s Data

    • Source: Cook County Medical Examiner Office (MEO) open data portal.

    • Coverage: 2023-2024.

    • Content: Provisional drug-involved overdose deaths in suburban Cook County, IL.

    • Use: Identification of opioid-involved overdose deaths in suburban Cook County, IL for the years 2023 and 2024.

  5. U.S. Census Data (Suburban Cook County)

    • Source: American Community Survey (ACS) and intercensal population estimates.

    • Coverage: Annual estimates, 2013–2024.

    • Content: Demographic denominators (age, sex, race/ethnicity, geographic units).

    • Use: Construction of age-specific and age-adjusted rates, ensuring comparability over time and between groups.

  6. U.S. Standard Population (Year 2000)

    • Source: National Center for Health Statistics (NCHS).

    • Coverage: Standard reference population for rate adjustment.

    • Use: Age-adjustment of death, ED visit, and hospitalization rates to the 2000 U.S. standard population, allowing fair comparisons across groups and over time.

Calculation:

  1. Case Identification

    • Opioid-related deaths: These are deaths where opioids (such as prescription pain medicines, heroin, or fentanyl) were found to have played a role. The cause of death is identified using medical records and death certificates. The Medical Examiner’s Office confirms these cases when opioids are listed as a factor.

    • Non-fatal overdoses (ED visits and admissions): These are situations where a person overdosed on opioids but survived and needed emergency medical care. They may have been treated in an emergency department or admitted to the hospital.

    • Naloxone distribution: Counts of naloxone kits, trainings, and overdose reversals documented by CCDPH and community partners.

  2. Crude Rates

    • This is the number of cases in a community compared to the size of the population, without adjusting for age or other factors. It’s a simple way to compare the overall burden across places or groups, but it does not account for differences in age distribution.

    • Calculated as:

\[ \text{Crude Rate} = \frac{C}{P} \times 100{,}000 \] where:

C = number of cases in the group

P = population of the group

Expressed per 100,000 residents

Provides the observed rate in a given subgroup (e.g., age, sex, race/ethnicity, municipality).

  1. Age-Specific Rates

    • Computed within 10-year age groups using corresponding population denominators from the U.S. Census / ACS.

    • Serves as the building block for age-adjusted rates.

  2. Age-Adjusted Rates

    • Calculated via the direct method using the 2000 U.S. Standard Population:
\[ R \;=\; \frac{\sum_{i} w_{i} r_{i}}{\sum_{i} w_{i}} \] where:
  • (r_i) = age-specific rate in stratum i

  • (w_i) = standard population weight for stratum i

    • Expressed per 100,000 residents.

    • Allows comparison of rates over time and across groups without confounding by age distribution differences.

  1. Geographic Assignment

    • Deaths, visits, and admissions were assigned to suburban Cook County municipalities, townships, or ZIP Code Tabulation Areas (ZCTAs) based on the residential address of the individual (not event location).
  2. Data Aggregation & Limitations

    • Annual counts and rates were generated for 2013–2023.

    • Data from 2023, is yet to be confirmed, therefore, caution ought to be used when interpreting the results.

    • Stratifications include age group, sex, race/ethnicity, and geography.

    • Multi-year summaries (2018–2022) were used for municipalities and townships to stabilize small numbers and reduce rate volatility.