Monthly Traffic Safety Analysis

51 CRASHES IN
TEWKSBURY, MA
APRIL 2024

All metrics benchmarked againstApril 2023

Current period (April 2024) saw 51 total crashes in TEWKSBURY, MA, a substantial increase of 466.67% compared to the 9 crashes reported in the prior period (April 2023). This surge in crash incidents is the most notable year-over-year shift, with total injuries also rising from 0 to 10.

51

466.7%was 9

Total Crash Events

0

Persons Killed

10

Persons Injured

6

500.0%was 1

Hit-and-Run Crashes

Note: "Persons Killed" (0) counts individual fatalities across all crash events. "Fatal" in the severity table below (0) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 2 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash incidents in TEWKSBURY, MA, have seen a significant increase year-over-year, rising from 9 crashes in April 2023 to 51 crashes in April 2024. This represents a substantial 466.67% increase in total crashes. Injuries also escalated from 0 in the prior period to 10 in the current period, indicating a worsening safety trend.

6

Hit-and-Run Crashes — April 2024

500.0% vs prior (1)

Hit-and-run crashes increased significantly year-over-year, rising from 1 incident in April 2023 to 6 incidents in April 2024. The hit-and-run crash rate also saw a slight increase, moving from 11.1% in the prior period to 11.8% in the current period, indicating an upward trend.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

1

Cyclists Injured

Prior: 0%

9

Motorists Injured

Prior: 0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal distribution of crashes shifted notably year-over-year. In April 2023, the peak crash day was Saturday with 3 crashes, and the peak hour was 4 PM with 2 crashes. For April 2024, crashes were highest on Thursday and Friday, each with 10 incidents, and the peak hour moved to 10 AM, recording 7 crashes.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Outcome by Severity (Crash Events)

Minor Injury6minor injury crashes11.8%
Possible Injury2possible injury crashes3.9%
No Injury41no injury crashes80.4%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Most severe injury per crash record

Top Contributing Factors

Several contributing factors saw significant increases in crash counts year-over-year. Crashes attributed to "No improper driving" increased from 0 in April 2023 to 17 in April 2024. Incidents involving "Inattention" rose from 1 to 7, and "Operating vehicle in erratic, reckless, careless, negligent or aggressive manner" increased from 1 to 6. "Failed to yield right of way" crashes also increased from 1 to 5, while "Followed too closely" crashes went from 2 to 3.

Officer-Reported Primary Contributing Cause

No improper driving17 (33.3%)
Inattention7 (13.7%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner6 (11.8%)
Failed to yield right of way5 (9.8%)
Followed too closely3 (5.9%)
Disregarded traffic signs, signals, road markings2 (3.9%)
Other improper action2 (3.9%)
Over-correcting/over-steering2 (3.9%)
Distracted1 (2%)
Visibility obstructed1 (2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The distribution of crash conditions shifted year-over-year. Crashes in daylight conditions increased substantially, accounting for 82.4% (42 crashes) in April 2024, up from 55.6% (5 crashes) in April 2023. Conversely, crashes in 'Dark - roadway not lighted' conditions decreased from 22.2% (2 crashes) to 2.0% (1 crash). On road surfaces, dry conditions increased in share from 66.7% (6 crashes) to 72.5% (37 crashes), while wet conditions, despite an increase in count from 3 to 10, saw their share decrease from 33.3% to 19.6%.

Weather

Clear35 (68.6%)
483.3%prior 6
Cloudy/Rain3 (5.9%)
Cloudy3 (5.9%)
Rain2 (3.9%)
Rain/Cloudy2 (3.9%)
Rain/Snow2 (3.9%)
Snow1 (2.0%)
Snow/Sleet, hail (freezing rain or drizzle)1 (2.0%)
Cloudy/Sleet, hail (freezing rain or drizzle)1 (2.0%)
Clear/Cloudy1 (2.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Weather condition at time of crash

Lighting

Daylight42 (82.4%)
740.0%prior 5
Dark - lighted roadway5 (9.8%)
Dark - roadway not lighted1 (2.0%)
Dawn1 (2.0%)
Dusk1 (2.0%)
Other1 (2.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Lighting condition field

Road Surface

Dry37 (72.5%)
516.7%prior 6
Wet10 (19.6%)
Snow3 (5.9%)
Slush1 (2.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (93 vehicles)

1
FORD14 (15.1%)
2
CHEVROLET12 (12.9%)
3
HONDA11 (11.8%)
4
TOYOTA10 (10.8%)
5
NISSAN7 (7.5%)
6
JEEP4 (4.3%)
7
VOLKSWAGEN4 (4.3%)
8
HYUNDAI3 (3.2%)
9
MERCEDES-BENZ3 (3.2%)
10
GMC3 (3.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Vehicle unit records

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

Sex Distribution (101 persons with recorded sex)

Male61 (60.4%)
306.7%prior 15
Female40 (39.6%)
3900.0%prior 1

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 35 mph speed zones saw a substantial increase, rising from 1 crash in April 2023 to 20 crashes in April 2024. Incidents in 65 mph speed zones also increased from 7 to 8 crashes year-over-year. No fatalities were recorded in any speed zone during either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Posted speed limit at crash location

Data Sources & Methodology

Primary Data Source

All crash data in this report is sourced from Massachusetts Crash Data (MassDOT CDV), accessed programmatically via the Arcgis_yearly 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: Arcgis_yearly 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: 2024-04-01 through 2024-04-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-04-01 through 2024-04-30 (30 days)
  • Geographic scope: TEWKSBURY, MA
  • Total crash records analyzed: 51
  • Total persons involved: 113
  • Total vehicles involved: 93

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). "TEWKSBURY, MA Crash Intelligence Report: April 2024." Published June 21, 2026. Reporting period: 2024-04-01 to 2024-04-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/tewksbury/april-2024-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

Tewksbury, MA Crash Report — April 2024 | ThatCarHitMe.com