Monthly Traffic Safety Analysis

14 CRASHES IN
SWAMPSCOTT, MA
MARCH 2022

All metrics benchmarked againstMarch 2021

In March 2022, Swampscott experienced 14 crashes, a 40% increase compared to 10 crashes in March 2021. The most significant year-over-year change was a 700% increase in total injuries, rising from 1 to 8.

14

40.0%was 10

Total Crash Events

0

Persons Killed

8

700.0%was 1

Persons Injured

0

Fatal Crash Events

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.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash data for Swampscott in March 2022 indicates a rising trend compared to March 2021, with total crashes increasing by 40% from 10 to 14. This period also saw a substantial 700% increase in total injuries, from 1 to 8.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

0

Other Killed

Prior: 00.0%

7

Motorists Injured

Prior: 1600.0%

1

Other Injured

Prior: 0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · 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 year-over-year. In March 2021, the peak day for crashes was Tuesday with 4 incidents, while in March 2022, Friday became the peak day, also with 4 incidents. The peak crash hour moved from 1p with 3 crashes in the prior period to 7p with 2 crashes in the current period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatal crashes remained at zero in both March 2021 and March 2022. However, total injuries increased significantly from 1 in the prior period to 8 in the current period. Minor injuries rose from 1 crash (10% of total) to 5 crashes (35.7% of total), and possible injuries, which were not present in the prior period, accounted for 2 crashes (14.3% of total) in the current period.

Outcome by Severity (Crash Events)

Minor Injury5minor injury crashes35.7%
400.0%prior 1
Possible Injury2possible injury crashes14.3%
No Injury7no injury crashes50%
-12.5%prior 8

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Most severe injury per crash record

Top Contributing Factors

The count of crashes attributed to 'No improper driving' increased from 3 in March 2021 to 6 in March 2022, representing a 100% increase. 'Failed to yield right of way', which accounted for 1 crash in the prior period, was not a top factor in the current period. New contributing factors in the current period include 'Failure to keep in proper lane or running off road' and 'Inattention', each with 1 crash.

Officer-Reported Primary Contributing Cause

No improper driving6 (42.9%)
Failure to keep in proper lane or running off road1 (7.1%)
Inattention1 (7.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Clear' weather remained at 9 incidents in both periods. However, the current period saw a wider range of adverse weather conditions, including 1 crash each in Cloudy, Rain, Rain/Cloudy, Snow, and Snow/Sleet, hail conditions, which were not present in the prior period. Regarding lighting, crashes in 'Dark - lighted roadway' conditions increased from 1 in March 2021 to 7 in March 2022, while 'Daylight' crashes decreased from 9 to 6.

Weather

Clear9 (64.3%)
0.0%prior 9
Cloudy1 (7.1%)
Rain1 (7.1%)
Rain/Cloudy1 (7.1%)
Snow1 (7.1%)
Snow/Sleet, hail (freezing rain or drizzle)1 (7.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Weather condition at time of crash

Lighting

Dark - lighted roadway7 (50.0%)
Daylight6 (42.9%)
-33.3%prior 9
Dusk1 (7.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Lighting condition field

Road Surface

Dry9 (64.3%)
Ice2 (14.3%)
Wet2 (14.3%)
Slush1 (7.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (25 vehicles)

1
HONDA5 (20%)
-16.7%prior 6
2
TOYOTA5 (20%)
3
SUBARU3 (12%)
4
JEEP2 (8%)
5
NISSAN2 (8%)
6
ACURA2 (8%)
7
VOLKSWAGEN1 (4%)
8
BMW1 (4%)
9
DODGE1 (4%)
10
INFI1 (4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Vehicle unit records

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

Sex Distribution (32 persons with recorded sex)

Female17 (53.1%)
70.0%prior 10
Male15 (46.9%)
87.5%prior 8

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in the 30 mph speed limit zone increased from 6 in March 2021 to 11 in March 2022, an 83.3% rise. Crashes in the 20 mph zone decreased from 2 to 1. A crash in the 15 mph zone in the prior period was not observed in the current period, while a crash in the 10 mph zone appeared in the current period. No fatal crashes were recorded in any speed zone during either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · 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: 2022-03-01 through 2022-03-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2022-03-01 through 2022-03-31 (31 days)
  • Geographic scope: SWAMPSCOTT, MA
  • Total crash records analyzed: 14
  • Total persons involved: 33
  • Total vehicles involved: 25

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). "SWAMPSCOTT, MA Crash Intelligence Report: March 2022." Published June 21, 2026. Reporting period: 2022-03-01 to 2022-03-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/swampscott/march-2022-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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Swampscott, MA Crash Report — March 2022 | ThatCarHitMe.com