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ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · CONNECTICUT, CT · APRIL 2020
Purpose: Machine-readable JSON endpoint for AI agents, LLMs, researchers, and programmatic consumers. Returns all underlying crash data and AI-generated commentary without HTML.
Authentication: None required. Public endpoint.
GET: https://thatcarhitme.com/api/crash-data/reports/data/connecticut/statewide/april-2020-report
Monthly Traffic Safety Analysis
3,582 CRASHES IN
CONNECTICUT, CT
APRIL 2020
In April 2020, Connecticut recorded 3,582 total crashes, a 57.7% decrease from the 8,463 crashes in April 2019. Despite the significant drop in overall collisions, the number of fatalities doubled from 12 to 24 year-over-year, and the fatal crash rate more than quadrupled.
3,582
▼ -57.7%was 8,463
Total Crash Events
24
▲ 100.0%was 12
Persons Killed
1,224
▼ -56.3%was 2,802
Persons Injured
598
▼ -37.5%was 957
Hit-and-Run Crashes
Note: "Persons Killed" (24) counts individual fatalities across all crash events. "Fatal" in the severity table below (22) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.
Source: Connecticut Crash Data · Csv Open Data · 2020-04-01 to 2020-04-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Year-over-year data for April shows a sharp decline in traffic incidents, with total crashes falling by 57.7% and injuries decreasing by 56.3%. However, this overall reduction in crashes was accompanied by a concerning counter-trend in severity, as total fatalities doubled from 12 in April 2019 to 24 in April 2020.
598
Hit-and-Run Crashes — April 2020
▼ -37.5% vs prior (957)
Although the total number of hit-and-run crashes decreased from 957 in April 2019 to 598 in April 2020, the hit-and-run rate as a percentage of all crashes increased significantly. In April 2020, hit-and-runs accounted for 16.7% of all collisions, a notable rise from the 11.3% rate recorded in the prior year.
Vulnerable Road User Casualties
4
Pedestrians Killed
0
Cyclists Killed
20
Motorists Killed
32
Pedestrians Injured
13
Cyclists Injured
1,179
Motorists Injured
Source: Connecticut Crash Data · Csv Open Data · 2020-04-01 to 2020-04-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes shifted significantly year-over-year, likely reflecting changes in travel behavior during the early 2020 pandemic. In April 2020, the peak day for crashes was Thursday with 603 incidents, a change from April 2019's peak on Monday with 1,451 incidents. The peak hour also shifted slightly earlier from 3 PM (725 crashes) in the prior year to 2 PM (303 crashes) in the current year.
Source: Connecticut Crash Data · Csv Open Data · 2020-04-01 to 2020-04-30 · Crash date field aggregated by weekday
Source: Connecticut Crash Data · Csv Open Data · 2020-04-01 to 2020-04-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
While overall crashes decreased, the severity of those crashes increased in April 2020 compared to the previous year. The fatal crash rate rose from 0.13% to 0.61%. The proportion of crashes involving a serious injury also increased from 1.1% to 1.4%, while the share of crashes with no injuries decreased from 75.5% to 73.5% of the total.
Severity is per crash event (most severe injury). 22 fatal crash events resulted in 24 persons killed.
Outcome by Severity (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2020-04-01 to 2020-04-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2020-04-01 to 2020-04-30 · Most severe injury per crash record
Road & Environmental Conditions
The distribution of crashes across environmental conditions remained relatively stable year-over-year, with only minor shifts. In April 2020, 73.6% of crashes occurred in daylight, compared to 78.3% in the prior year. Crashes in clear weather accounted for 71.9% of the total, a slight decrease from 73.5% in April 2019, while crashes on dry roads made up 74.5% of incidents, compared to 76.0% previously.
Weather
Source: Connecticut Crash Data · Csv Open Data · 2020-04-01 to 2020-04-30 · Weather condition at time of crash
Lighting
Source: Connecticut Crash Data · Csv Open Data · 2020-04-01 to 2020-04-30 · Lighting condition field
Road Surface
Source: Connecticut Crash Data · Csv Open Data · 2020-04-01 to 2020-04-30 · Road surface condition field
Vehicles & Demographics
The top three vehicle makes involved in crashes remained Honda, Toyota, and Ford in both April 2020 and April 2019, with their order unchanged despite lower volumes. The demographic profile of individuals involved in crashes showed minor year-over-year shifts. The proportion of persons from the 26-34 age group increased from 17.0% to 18.7%, while the share for the 16-20 age group decreased from 9.0% to 8.3%.
Top Vehicle Makes (6,354 vehicles)
Source: Connecticut Crash Data · Csv Open Data · 2020-04-01 to 2020-04-30 · Vehicle unit records
668 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (7,117 persons with recorded sex)
Source: Connecticut Crash Data · Csv Open Data · 2020-04-01 to 2020-04-30 · Person-level records linked to crash events
Speed Limit Zones
In April 2020, a larger proportion of crashes occurred in lower speed zones compared to the previous year, with 72.4% of incidents happening in zones of 35 mph or less, up from 65.9% in April 2019. Despite this, the fatal crash rate increased dramatically in higher speed zones. For instance, in 55 mph zones, the fatal crash rate rose from 0% in 2019 to 1.7% in 2020, and in 65 mph zones, the rate increased from 0.25% to 1.5%.
Fatal crashes by zone: 1 mph: 1 of 462 (0.216%) · 15 mph: 1 of 30 (3.333%) · 25 mph: 7 of 1,311 (0.534%) · 30 mph: 2 of 286 (0.699%) · 35 mph: 3 of 396 (0.758%) · 40 mph: 1 of 193 (0.518%) · 45 mph: 2 of 126 (1.587%) · 55 mph: 3 of 177 (1.695%) · 65 mph: 2 of 130 (1.538%)
Source: Connecticut Crash Data · Csv Open Data · 2020-04-01 to 2020-04-30 · Posted speed limit at crash location
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: 2020-04-01 through 2020-04-30
- Report generated: August 20, 2026
Data Coverage
- Reporting period: 2020-04-01 through 2020-04-30 (30 days)
- Geographic scope: connecticut, CT
- Total crash records analyzed: 3,582
- Total persons involved: 7,735
- Total vehicles involved: 6,354
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: April 2020." Published August 20, 2026. Reporting period: 2020-04-01 to 2020-04-30. Data source: Connecticut Crash Data, Csv Open Data. Available at: https://thatcarhitme.com/crash-data/connecticut/statewide/april-2020-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
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Connecticut Crash Data · Csv
Period: 2020-04-01 – 2020-04-30
Generated: August 20, 2026 · All rights reserved
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