Monthly Traffic Safety Analysis

37 CRASHES IN
SWANSEA, MA
JULY 2024

All metrics benchmarked againstJuly 2023

In July 2024, Swansea experienced a 7.5% decrease in total crashes compared to July 2023, with 37 crashes recorded this year versus 40 last year. Despite this reduction in overall incidents, the number of injuries increased by 25%, rising from 12 to 15. This indicates a shift towards more severe outcomes per crash.

37

-7.5%was 40

Total Crash Events

0

Persons Killed

15

25.0%was 12

Persons Injured

2

-33.3%was 3

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. 1 crash with unreported severity is not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, Swansea saw a decrease in total crash incidents in July 2024, with 37 crashes representing a 7.5% reduction from the 40 crashes reported in July 2023. Conversely, the number of individuals injured in crashes rose by 25%, from 12 in the prior year to 15 in the current period, suggesting an increase in injury severity per crash.

2

Hit-and-Run Crashes — July 2024

-33.3% vs prior (3)

Hit-and-run crashes decreased from 3 incidents in July 2023 to 2 incidents in July 2024. Correspondingly, the hit-and-run rate fell from 7.5% of all crashes in the prior period to 5.4% in the current period, indicating a downward trend.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

15

Motorists Injured

Prior: 1225.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · 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 significantly year-over-year. In July 2024, Monday became the peak day for crashes with 9 incidents, up from 6 on Mondays in July 2023, while Sunday crashes sharply declined from 8 to 1. The peak hour also moved from 12 PM in July 2023 (6 crashes) to 4 PM in July 2024 (5 crashes), with crashes at 4 PM increasing from 1 to 5.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

There were no fatalities reported in either July 2024 or July 2023. While the number of serious injury crashes remained constant at 2, minor injury crashes increased from 6 to 8. The proportion of crashes resulting in any injury (serious, minor, or possible) rose from 22.5% of total crashes in July 2023 to 29.7% in July 2024.

Outcome by Severity (Crash Events)

Serious Injury2serious injury crashes5.4%
0.0%prior 2
Minor Injury8minor injury crashes21.6%
33.3%prior 6
Possible Injury1possible injury crashes2.7%
0.0%prior 1
No Injury25no injury crashes67.6%
-7.4%prior 27

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factor in July 2024 was 'Followed too closely,' which saw a 200% increase from 4 crashes in July 2023 to 12 crashes. 'Inattention' also doubled, rising from 3 crashes to 6 crashes year-over-year. Conversely, 'Failure to keep in proper lane or running off road' decreased by 42.8%, from 7 crashes to 4, and 'No improper driving' decreased by 57.1%, from 7 crashes to 3.

Officer-Reported Primary Contributing Cause

Followed too closely12 (32.4%)
Inattention6 (16.2%)
Failure to keep in proper lane or running off road4 (10.8%)-42.9%prior 7
No improper driving3 (8.1%)-57.1%prior 7
Failed to yield right of way3 (8.1%)-40.0%prior 5
Exceeded authorized speed limit1 (2.7%)
Emotional1 (2.7%)
Distracted1 (2.7%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (2.7%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway1 (2.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The majority of crashes in both periods occurred under clear weather and dry road conditions. Crashes in clear weather decreased slightly from 34 to 32, and crashes during rain decreased from 5 to 2. Daylight crashes increased from 29 to 31, while crashes in dark-lighted conditions decreased from 5 to 3, and dark-not lighted conditions decreased from 5 to 2.

Weather

Clear32 (86.5%)
-5.9%prior 34
Rain2 (5.4%)
-60.0%prior 5
Clear/Cloudy1 (2.7%)
Cloudy1 (2.7%)
Cloudy/Rain1 (2.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · Weather condition at time of crash

Lighting

Daylight31 (83.8%)
6.9%prior 29
Dark - lighted roadway3 (8.1%)
-40.0%prior 5
Dark - roadway not lighted2 (5.4%)
-60.0%prior 5
Dusk1 (2.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · Lighting condition field

Road Surface

Dry32 (86.5%)
-5.9%prior 34
Wet5 (13.5%)
0.0%prior 5

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes decreased from 78 in July 2023 to 70 in July 2024. Regarding age distribution, crashes involving individuals aged 26-34 saw a decrease from 13 to 9, while those aged 0-15 decreased from 5 to 3. Honda and Ford vehicles saw increased involvement, with Honda rising from 8 to 13 and Ford from 5 to 11, while Toyota involvement decreased from 10 to 7.

Top Vehicle Makes (70 vehicles)

1
HONDA13 (18.6%)
62.5%prior 8
2
FORD11 (15.7%)
120.0%prior 5
3
HYUNDAI7 (10%)
16.7%prior 6
4
TOYOTA7 (10%)
-30.0%prior 10
5
CHEVROLET5 (7.1%)
6
NISSAN5 (7.1%)
-16.7%prior 6
7
GMC3 (4.3%)
8
JEEP3 (4.3%)
9
SUBARU2 (2.9%)
-66.7%prior 6
10
VOLKSWAGEN2 (2.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · Vehicle unit records

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

Sex Distribution (72 persons with recorded sex)

Male47 (65.3%)
27.0%prior 37
Female25 (34.7%)
-41.9%prior 43

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 40 mph speed zones significantly increased from 4 in July 2023 to 13 in July 2024. Conversely, crashes in 45 mph zones saw a notable decrease from 9 to 2, and incidents in 65 mph zones dropped from 5 to 1. There were no fatal crashes reported across any speed limit in either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · 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: 2024-07-01 through 2024-07-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-07-01 through 2024-07-31 (31 days)
  • Geographic scope: SWANSEA, MA
  • Total crash records analyzed: 37
  • Total persons involved: 80
  • Total vehicles involved: 70

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). "SWANSEA, MA Crash Intelligence Report: July 2024." Published June 21, 2026. Reporting period: 2024-07-01 to 2024-07-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/swansea/july-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

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Swansea, MA Crash Report — July 2024 | ThatCarHitMe.com