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Yearly Traffic Safety Analysis

2,120 CRASHES IN
CONNECTICUT, CT
2018

In 2018, Windham County recorded 2,120 traffic crashes, resulting in 13 fatalities and 733 injuries. These incidents involved 4,715 people and 3,533 vehicles. A notable temporal pattern emerged from the data, with crashes peaking on Fridays (365 incidents) and during the 3 p.m. hour (176 incidents), indicating a strong correlation with weekday afternoon commute times.

2,120

Total Crash Events

13

Persons Killed

733

Persons Injured

8.3%

Hit-and-Run Rate

Note: "Persons Killed" (13) counts individual fatalities across all crash events. "Fatal" in the severity table below (13) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-12-31 · Aggregate counts from crash, person, and vehicle records

176

Hit-and-Run Crashes — 2018

A total of 176 crashes, representing 8.3% of all incidents in Windham County, were classified as hit-and-run events. This classification is based on the initial determination made by the responding law enforcement officer at the scene of the crash. These incidents contributed to the overall crash statistics for the year.

Vulnerable Road User Casualties

Of the 13 total fatalities recorded, all were vehicle motorists. An additional 718 motorists sustained injuries. No pedestrians or cyclists were killed in 2018. However, 13 pedestrians and 2 cyclists were injured in traffic crashes during this period.

0

Pedestrians Killed

0

Cyclists Killed

13

Motorists Killed

13

Pedestrians Injured

2

Cyclists Injured

718

Motorists Injured

Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

Crash frequency in Windham County shows distinct daily and weekly patterns. The data indicates that Friday was the most common day for crashes, with 365 incidents, while the afternoon commute hour of 3 p.m. was the single busiest hour with 176 crashes. Overall, a majority of crashes, 1,418 or 67%, occurred during daylight hours.

Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-12-31 · Crash date field aggregated by weekday

Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The majority of crashes, 73.4% (1,557 incidents), resulted in no injuries. Injury-involved crashes, including serious, minor, and possible injuries, accounted for 26% of the total (550 incidents). There were 13 fatal crashes, representing 0.6% of all crashes, which resulted in a total of 13 fatalities.

Outcome by Severity (Crash Events)

Fatal13fatal crashes0.6%
Serious Injury21serious injury crashes1%
Minor Injury300minor injury crashes14.2%
Possible Injury229possible injury crashes10.8%
No Injury1,557no injury crashes73.4%

Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-12-31 · Most severe injury per crash record

Road & Environmental Conditions

A substantial majority of crashes in Windham County occurred under ideal driving conditions. Specifically, 70.5% of crashes (1,495) happened on dry road surfaces, 75.3% (1,596) in clear weather, and 66.9% (1,418) during daylight hours. Crashes in adverse conditions were less frequent, with 236 incidents occurring during rain and 367 on wet roads.

Weather

Clear1,596 (75.4%)
Rain236 (11.2%)
Cloudy99 (4.7%)
Snow87 (4.1%)
Freezing Rain or Freezing Drizzle46 (2.2%)
Blowing Snow25 (1.2%)
Fog, Smog, Smoke20 (0.9%)
Other4 (0.2%)
Sleet or Hail2 (0.1%)
Blowing Sand, Soil, Dirt1 (0.0%)

Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-12-31 · Weather condition at time of crash

Lighting

Daylight1,418 (67.0%)
Dark-Not Lighted357 (16.9%)
Dark-Lighted256 (12.1%)
Dawn42 (2.0%)
Dusk31 (1.5%)
Dark-Unknown Lighting10 (0.5%)
Other1 (0.0%)

Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-12-31 · Lighting condition field

Road Surface

Dry1,495 (70.7%)
Wet367 (17.4%)
Snow107 (5.1%)
Ice / Frost94 (4.4%)
Slush32 (1.5%)
Moving Water5 (0.2%)
Sand5 (0.2%)
Mud, Dirt, Gravel4 (0.2%)
Standing Water4 (0.2%)
Oil1 (0.0%)

Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-12-31 · Road surface condition field

Vehicles & Demographics

Among the 4,715 individuals involved in crashes, the 26-34 age group was the most represented with 775 people, followed by the 35-44 and 45-54 age groups. An analysis of the 3,533 vehicles involved shows that Ford was the most frequent make, appearing in 504 crash records. Other common makes included Toyota (244 vehicles) and Chevrolet (231 vehicles).

Top Vehicle Makes (3,533 vehicles)

1
FORD504 (14.3%)
2
TOYOTA244 (6.9%)
3
CHEVROLET231 (6.5%)
4
HONDA197 (5.6%)
5
NISSAN183 (5.2%)
6
JEEP148 (4.2%)
7
CHEV144 (4.1%)
8
HYUNDAI124 (3.5%)
9
DODGE116 (3.3%)
10
GMC108 (3.1%)

Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-12-31 · Vehicle unit records

136 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (4,537 persons with recorded sex)

Male2,534 (55.9%)
Female2,003 (44.1%)

Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-12-31 · Person-level records linked to crash events

Speed Limit Zones

The 25 mph speed zone saw the highest number of crashes, with 560 incidents, accounting for 26.4% of the total. While lower speed zones had more crashes, the percentage of crashes that were fatal increased with speed. For instance, in the 45 mph zone, which had 259 crashes, 2.32% of those crashes were fatal, a significantly higher rate than the 0.18% fatal crash rate in the 25 mph zone.

Fatal crashes by zone: 25 mph: 1 of 560 (0.179%) · 30 mph: 1 of 238 (0.42%) · 35 mph: 1 of 343 (0.292%) · 40 mph: 1 of 204 (0.49%) · 45 mph: 6 of 259 (2.317%) · 50 mph: 1 of 62 (1.613%) · 65 mph: 2 of 234 (0.855%)

Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-12-31 · Posted speed limit at crash location

Top Towns

The 2,120 crashes in the county were geographically concentrated in a few key towns. The town of Windham experienced the highest number of incidents with 510 crashes, representing 24.1% of the county's total. Following Windham were Killingly with 430 crashes (20.3%) and Plainfield with 293 crashes (13.8%).

Top Towns

1
Windham510 (24.1%)
2
Killingly430 (20.3%)
3
Plainfield293 (13.8%)
4
Putnam215 (10.1%)
5
Brooklyn125 (5.9%)
6
Thompson116 (5.5%)
7
Woodstock95 (4.5%)
8
Canterbury68 (3.2%)
9
Pomfret52 (2.5%)

Showing top 9 of 15 reported. 6 additional (216 total) not shown: Ashford, Chaplin, Sterling, Hampton, Scotland, Eastford.

Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-12-31 · Crash-level records

Road Class

Collector roads were the site of the most crashes in Windham County, accounting for 511 incidents. Principal Arterials (437 crashes) and Minor Arterials (412 crashes) also saw significant crash volumes. Limited-access highways, including Interstates and Freeways/Expressways, collectively accounted for 309 crashes, or 14.6% of the total.

Road Class

Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-12-31 · Crash-level records

Route System

An analysis of roadway jurisdiction shows that state-maintained routes (including State, US, and Interstate routes) were the location for 1,391 crashes. This represents 67.2% of crashes on roads with a known system type. Locally maintained roads accounted for the remaining 679 crashes, or 32.8% of the total.

Route System

Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-12-31 · Crash-level records

Public vs Private Road

The vast majority of crashes occurred on public roadways, with 2,060 incidents recorded. A small fraction, 41 crashes or approximately 2%, took place on private roads, which can include locations like parking lots or private driveways.

Rural vs Urban

Crashes in Windham County were more common in areas designated as urban, which accounted for 1,385 incidents. Rural areas saw 658 crashes, representing 32.2% of the total where the designation was known. This highlights that nearly one-third of all crashes occurred in rural settings.

Rural vs Urban

Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-12-31 · Crash-level records

Junction Type

The majority of crashes, 1,460 incidents or 68.9%, occurred at locations not at an intersection. For crashes that did happen at junctions, T-intersections were the most common type with 321 crashes, followed by four-way intersections with 291 crashes. Combined, all types of intersections accounted for 31% of total crashes.

Junction Type

1
Not at Intersection1,460 (69%)
2
T-Intersection321 (15.2%)
3
Four-Way Intersection291 (13.7%)
4
Y-Intersection34 (1.6%)
5
Five-Point, or More5 (0.2%)
6
L-Intersection5 (0.2%)
7
Roundabout1

Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-12-31 · Crash-level records

Run-off-Road / Fixed-Object Strikes

Among single-vehicle crashes involving a fixed object, the most commonly struck object was a guardrail face, which was hit 150 times. This was followed by utility poles (109 times) and trees (103 times). Combined, collisions with trees and utility poles accounted for 212 incidents, representing 29.3% of all recorded fixed-object crashes.

Run-off-Road / Fixed-Object Strikes

1
Guardrail Face150 (20.7%)
2
Utility Pole/Light Support109 (15.1%)
3
Tree (standing)103 (14.2%)
4
Other Fixed Object (wall, building, tunnel, etc.)95 (13.1%)
5
Other Post, Pole or Support49 (6.8%)
6
Embankment40 (5.5%)
7
Cable Barrier34 (4.7%)
8
Ditch26 (3.6%)
9
Mailbox24 (3.3%)

Showing top 9 of 21 reported. 12 additional (94 total) not shown: Guardrail End, Curb, Traffic Sign Support, Fence, Other Traffic Barrier, Concrete Traffic Barrier, Culvert, Bridge Pier or Support, Impact Attenuator/Crash Cushion, Struck by Falling, Shifting Cargo or Anything Set in Motion by Motor Vehicle, Bridge Rail, Traffic Signal Support.

Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-12-31 · Crash-level records

Vehicle Type

Passenger cars were the most prevalent vehicle type involved in crashes, with 2,086 units recorded. Utility vehicles (612) and pickup trucks (433) were the next most common. Notably, crashes also involved 71 medium or heavy trucks, 43 motorcycles, and 12 school buses.

Vehicle Type

1
Passenger Car2,086 (59.6%)
2
(Sport) Utility Vehicle612 (17.5%)
3
Pick Up433 (12.4%)
4
Passenger Van98 (2.8%)
5
Medium / Heavy Trucks (more than 10,000 lbs (4,536 kg))71 (2%)
6
Other Light Trucks (10,000 lbs (4,536 kg) or less)55 (1.6%)
7
Motorcycle43 (1.2%)
8
Cargo Van (10,000 lbs/4,536 kg or less)37 (1.1%)
9
Other34 (1%)

Showing top 9 of 16 reported. 7 additional (30 total) not shown: School Bus, Moped, Motor Home, Other Bus, Low Speed Vehicle, All Terrain Vehicle (ATV), Transit Bus.

Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-12-31 · Vehicle unit records

Traffic Control Device

Analysis of traffic controls at crash locations, based on 3,528 vehicle records, shows the majority occurred where no control device was present (2,523 vehicles). A significant number also occurred at locations with traffic control signals (624 vehicles) or stop signs (316 vehicles). This indicates that most incidents happened on uncontrolled road segments rather than at controlled intersections.

Traffic Control Device

"Other" combines 4 smaller categories (8 records): Other (4), Marked Uncontrolled Crosswalk (2), Yield Sign (1), Bicycle Detection (1).

Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-12-31 · Vehicle unit records

Vulnerable Road Users & Motorcycles

In 2018, there were 60 crashes involving vulnerable road users or motorcyclists. Motorcyclists were the largest group with 41 incidents. The remaining crashes involved pedestrians (16) and bicyclists (3), with these two groups of vulnerable road users accounting for 19 incidents, or 31.7% of the total in this category.

Driver Contributing Action

Among drivers for whom a contributing action was cited, the most common error was failing to keep in the proper lane, attributed to 470 drivers. The second most frequent action was following too closely, noted for 441 drivers. Failing to yield the right-of-way was the third most common contributing action, recorded for 262 drivers.

Driver Contributing Action

1
No Contributing Action1,306 (39.1%)
2
Failed to Keep in Proper Lane470 (14.1%)
3
Followed Too Closely441 (13.2%)
4
Failed to Yield Right-of-Way262 (7.8%)
5
Ran Off Roadway178 (5.3%)
6
Operated Motor Vehicle in Inattentive, Careless, Negligent, or Erratic Manner138 (4.1%)
7
Improper Turn104 (3.1%)
8
Other Contributing Action90 (2.7%)
9
Improper Backing85 (2.5%)

Showing top 9 of 18 reported. 9 additional (264 total) not shown: Ran Stop Sign, Swerved or Avoided Due to Wind, Slippery Surface, Motor Vehicle, Object, Non-Motorist in Roadway, etc., Improper Passing, Over-Correcting/Over-Steering, Ran Red Light, Operated Motor Vehicle in Reckless or Aggressive Manner, Disregarded Other Traffic Sign, Wrong Side or Wrong Way, Disregarded Other Road Markings.

Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-12-31 · Person-level records linked to crash events

Driver Condition

While most drivers were recorded as 'Apparently Normal', 246 drivers were noted as having a condition that may have contributed to the crash. The most common of these was being under the influence of medications, drugs, or alcohol, which was recorded for 112 drivers. An additional 66 drivers were identified as being asleep or fatigued at the time of their crash.

Driver Condition

1
Apparently Normal2,977 (92.4%)
2
Under the Influence of Medications/Drugs/Alcohol112 (3.5%)
3
Asleep or Fatigued66 (2%)
4
Emotional (depressed, angry, disturbed, etc.)26 (0.8%)
5
Ill (sick), Fainted17 (0.5%)
6
Physically Impaired15 (0.5%)
7
Other10 (0.3%)

Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-12-31 · Person-level records linked to crash events

Pre-Crash Driver Action

The most common pre-crash action for vehicles was driving straight ahead, which was the case for 1,654 vehicles involved in collisions. Negotiating a curve and turning left were the next most frequent actions, each recorded for 309 vehicles. These actions represent the moments immediately preceding the crash event.

Pre-Crash Driver Action

1
Straight Ahead1,654 (47.4%)
2
Negotiating a Curve309 (8.8%)
3
Turning Left309 (8.8%)
4
Stopped in Traffic298 (8.5%)
5
Slowing185 (5.3%)
6
Turning Right154 (4.4%)
7
Parked148 (4.2%)
8
Entering Traffic Lane108 (3.1%)
9
Backing98 (2.8%)

Showing top 9 of 17 reported. 8 additional (230 total) not shown: Overtaking/Passing, Changing Lanes, Other, Making U-Turn, Leaving Traffic Lane, Wrong way (or Wrong Side), Traveling in Bike Lane, Overtaking/Passing Cyclist.

Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-12-31 · Vehicle unit records

Point of Impact

The front of the vehicle was the most common point of impact, identified as 'Sector 12 (North)' in 988 instances, or 28.2% of impacts where the location was specified. The rear of the vehicle, 'Sector 6 (South)', was the second most frequent impact point, recorded 504 times (14.4%). This suggests a high prevalence of frontal and rear-end collisions.

Point of Impact

"Other" combines 9 smaller categories (518 records): Sector 9 (West) in the 12-point Clock Diagram (111), Sector 5 (South by SouthEast) in the 12-point Clock Diagram (97), Sector 8 (SouthWest) in the 12-point Clock Diagram (96), Sector 3 (East) in the 12-point Clock Diagram (93), Sector 4 (SouthEast) in the 12-point Clock Diagram (65), Non-Collision (27), Undercarriage (14), Top (13), Cargo loss (2).

Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-12-31 · Vehicle unit records

Pedestrian/Cyclist Action

Of the 16 pedestrians involved in crashes, 6 were determined to have taken no improper action. For those with contributing actions, behaviors included wrong-way walking (2 pedestrians), being in the roadway improperly (2), and not being visible in dark clothing (2).

Pedestrian/Cyclist Action

1
No Improper Action6 (37.5%)
2
Wrong-Way Riding or Walking2 (12.5%)
3
In Roadway Improperly (Standing, Lying, Working, Playing)2 (12.5%)
4
Not Visible (Dark Clothing, No Lighting, etc.)2 (12.5%)
5
Improper Passing1 (6.3%)
6
Failure to Obey Traffic Signs, Signals, or Officer1 (6.3%)
7
Inattentive (Talking, Eating, etc.)1 (6.3%)
8
Failure to Yield Right-Of-Way1 (6.3%)

Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-12-31 · Non-motorist records linked to crash events

Manner of Collision

The most frequent type of collision was front-to-rear, which accounted for 536 crashes or 25.3% of the total. Angle collisions were the second most common pattern, with 406 incidents representing 19.2% of all crashes. These two types alone constitute nearly half of all multi-vehicle crashes.

Manner of Collision

"Other" combines 1 smaller categories (6 records): Rear to rear (6).

Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-12-31 · Crash-level records

Person Type

Of the 4,715 people involved in crashes, the vast majority were drivers, accounting for 3,393 individuals or 71.9% of the total. Passengers made up the next largest group with 1,080 people (22.9%). A small number of pedestrians (16) and bicyclists (3) were also involved.

Person Type

Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-12-31 · Crash-level records

Person Injury Severity

Among all 4,715 individuals involved in crashes, 79.5% (3,747 people) were not injured. A total of 733 people, or 15.5%, sustained some level of injury, ranging from possible to serious. Fatal injuries were recorded for 13 individuals, representing 0.28% of all persons involved.

Person Injury Severity

Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-12-31 · Crash-level records

Occupant Safety Equipment

Based on records for 4,085 vehicle occupants where restraint use was noted, the vast majority utilized safety equipment. However, 71 individuals, or 1.7% of this group, were recorded as not using any restraint system. The most common restraint type used was a shoulder and lap belt, reported for 3,637 occupants.

Occupant Safety Equipment

"Other" combines 3 smaller categories (29 records): Booster Seat (15), Other (8), Child Restraint, Type Unknown (6).

Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-12-31 · Person-level records linked to crash events

Vehicles Per Crash

Two-vehicle collisions were the most common crash configuration, accounting for 1,205 incidents or 56.8% of the total. Single-vehicle crashes were also frequent, with 818 incidents making up 38.6% of all crashes. Multi-vehicle pile-ups involving three or more vehicles were less common, with 97 such incidents recorded.

Vehicles Per Crash

Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-12-31 · Crash-level records

Data Sources & Methodology

Primary Data Source

All crash data in this report is sourced from Connecticut Crash Data, accessed programmatically via the Csv Open Data API (SODA). This dataset contains official police-reported motor vehicle traffic crash records maintained by the reporting jurisdiction's law enforcement agency. Records are published to the open data portal by the municipality and are subject to the portal's terms of use.

Data Retrieval

  • Access method: Csv Open Data API (SoQL queries)
  • Data format: Structured JSON via REST API
  • Record types queried: Crash events, person records, and vehicle unit records
  • Date filter applied: 2018-01-01 through 2018-12-31
  • Report generated: August 20, 2026

Data Coverage

  • Reporting period: 2018-01-01 through 2018-12-31 (365 days)
  • Geographic scope: connecticut, CT
  • Total crash records analyzed: 2,120
  • Total persons involved: 4,715
  • Total vehicles involved: 3,533

Analytical Methodology

  • Severity classification: Uses the KABCO injury scale (K=Fatal, A=Incapacitating injury, B=Non-incapacitating injury, C=Possible injury, O=No injury/property damage only), the standard classification in U.S. Model Minimum Uniform Crash Criteria (MMUCC). Severity is assigned per crash event based on the most severe injury in that crash. A single fatal crash (K) may involve multiple fatalities; therefore the "Persons Killed" count in the headline KPIs may differ from the "Fatal" crash count in the severity breakdown.
  • Contributing factors: Reflect the officer-determined primary contributory cause recorded at the time of the crash report. These are preliminary determinations and may not reflect final investigation findings.
  • Hit-and-run classification: Based on the hit-and-run indicator field in the official crash report, as determined by the responding officer at the scene.
  • Temporal analysis: Day-of-week and hour-of-day distributions are computed from the crash date/time timestamp in each record.
  • Demographics: Age and sex distributions are drawn from person-level records linked to each crash event. A single crash may involve multiple persons.
  • Vehicle data: Make information is drawn from vehicle unit records linked to each crash event.
  • AI commentary: Narrative sections are generated by Google Gemini (large language model) based on the structured data. Commentary is descriptive, not predictive, and should not be interpreted as expert opinion.

Limitations & Disclaimers

  • Only crashes reported to and documented by law enforcement are included. Minor incidents, unreported crashes, and near-misses are not captured in this dataset.
  • Data reflects conditions at the time of the initial police report and may be subject to subsequent corrections, reclassifications, or supplements by the reporting agency.
  • Open data portal records may experience a publication lag - recently occurring crashes may not yet appear in the dataset at the time of report generation.
  • AI-generated commentary is produced by a large language model and is intended to highlight patterns in the data. It does not constitute legal, medical, or professional analysis.
  • Percentages are calculated from reported data and are subject to rounding.

Non-Affiliation Disclosure

This report is produced independently by ThatCarHitMe.com (Injuria.ai). It is not affiliated with, endorsed by, or produced in partnership with any law enforcement agency, municipal government, state department of transportation, or the National Highway Traffic Safety Administration (NHTSA). Data is sourced from publicly available government open data portals.

Data License

The underlying crash data is provided under the municipality's Open Data Terms of Use and is made available to the public for unrestricted use. This analysis and report is © 2026 Injuria.ai and may be cited with attribution using the suggested citation below.

Corrections & Feedback

If you believe any data in this report is inaccurate or have questions about our methodology, please contact: data@injuria.ai. We are committed to accuracy and will issue corrections promptly.

Suggested Citation

ThatCarHitMe.com (Injuria.ai). "connecticut, CT Crash Intelligence Report: 2018." Published August 20, 2026. Reporting period: 2018-01-01 to 2018-12-31. Data source: Connecticut Crash Data, Csv Open Data. Available at: https://thatcarhitme.com/crash-data/connecticut/statewide/2018-annual-report

About the Publisher

ThatCarHitMe.com is a crash data intelligence platform developed by Injuria.ai, a legal technology company specializing in traffic safety analytics. We aggregate and analyze publicly available government crash data to produce structured intelligence reports for communities, researchers, journalists, and legal professionals. Our reports combine programmatic data retrieval from official open data portals with AI-assisted narrative analysis.

Questions about this report's data or methodology: data@injuria.ai

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