Monthly Traffic Safety Analysis

32 CRASHES IN
SALEM, MA
JULY 2023

All metrics benchmarked againstJuly 2022

Total crashes in Salem, MA, decreased significantly by 43.86% from 57 in July 2022 to 32 in July 2023. While both periods reported zero fatalities, the most notable shift was the overall reduction in crash incidents. Despite fewer hit-and-run crashes, the hit-and-run rate increased from 7.0% to 9.4% year-over-year.

32

-43.9%was 57

Total Crash Events

0

Persons Killed

11

-42.1%was 19

Persons Injured

3

-25.0%was 4

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.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Total crashes decreased from 57 in July 2022 to 32 in July 2023, representing a 43.86% reduction year-over-year. This indicates a notable downward trend in overall crash incidents for the month.

3

Hit-and-Run Crashes — July 2023

-25.0% vs prior (4)

The number of hit-and-run crashes decreased from 4 in July 2022 to 3 in July 2023. Despite this reduction in count, the hit-and-run rate increased from 7.0% in the prior period to 9.4% in the current period.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

1

Pedestrians Injured

Prior: 0%

10

Motorists Injured

Prior: 19-47.4%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The peak day for crashes shifted from Thursday with 11 crashes in July 2022 to Friday with 8 crashes in July 2023. The peak crash hour also changed significantly, moving from 11 AM with 9 crashes in the prior period to 10 PM with 2 crashes in the current period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Total injuries decreased from 19 in July 2022 to 11 in July 2023. While both periods reported zero fatalities, July 2023 recorded 1 serious injury crash, a severity level not present in the prior period. Minor injury crashes increased from 3 to 5, while possible injury crashes decreased from 9 to 4.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes3.1%
Minor Injury5minor injury crashes15.6%
66.7%prior 3
Possible Injury4possible injury crashes12.5%
-55.6%prior 9
No Injury22no injury crashes68.8%
-47.6%prior 42

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Most severe injury per crash record

Top Contributing Factors

The count of crashes where 'Failed to yield right of way' was a factor decreased from 11 in July 2022 to 4 in July 2023. Crashes attributed to 'Failure to keep in proper lane or running off road' also saw a reduction, from 7 in the prior period to 3 in the current period. Conversely, 'Followed too closely' remained constant at 6 crashes in both periods.

Officer-Reported Primary Contributing Cause

Followed too closely6 (18.8%)0.0%prior 6
No improper driving5 (15.6%)-16.7%prior 6
Failed to yield right of way4 (12.5%)-63.6%prior 11
Disregarded traffic signs, signals, road markings3 (9.4%)
Failure to keep in proper lane or running off road3 (9.4%)-57.1%prior 7
Other improper action2 (6.3%)
Inattention1 (3.1%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway1 (3.1%)
Driving too fast for conditions1 (3.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in clear weather conditions decreased from 54 in July 2022 to 24 in July 2023. There was a notable increase in crashes on wet road surfaces, rising from 2 in the prior period to 7 in the current period. Crashes during daylight hours decreased from 44 to 21, while those in dark-lighted roadway conditions remained stable at 10.

Weather

Clear/Clear23 (71.9%)
-47.7%prior 44
Rain/Rain3 (9.4%)
Cloudy/Cloudy1 (3.1%)
Clear1 (3.1%)
-90.0%prior 10
Cloudy/Rain1 (3.1%)
Fog, smog, smoke/Fog, smog, smoke1 (3.1%)
Cloudy/Fog, smog, smoke1 (3.1%)
Clear/Rain1 (3.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Weather condition at time of crash

Lighting

Daylight21 (65.6%)
-52.3%prior 44
Dark - lighted roadway10 (31.3%)
0.0%prior 10
Dusk1 (3.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Lighting condition field

Road Surface

Dry25 (78.1%)
-54.5%prior 55
Wet7 (21.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes decreased from 111 in July 2022 to 58 in July 2023. Honda vehicles involved in crashes decreased from 19 to 7, while Toyota vehicles decreased from 17 to 15. The age group 65+ saw a significant decrease in persons involved, from 25 to 5.

Top Vehicle Makes (58 vehicles)

1
TOYOTA15 (25.9%)
-11.8%prior 17
2
FORD8 (13.8%)
-20.0%prior 10
3
HONDA7 (12.1%)
-63.2%prior 19
4
JEEP5 (8.6%)
5
VOLVO3 (5.2%)
6
DODGE2 (3.4%)
7
LEXUS2 (3.4%)
8
MERCEDES-BENZ2 (3.4%)
9
NISSAN2 (3.4%)
-81.8%prior 11
10
CHEVROLET2 (3.4%)
-60.0%prior 5

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Vehicle unit records

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

Sex Distribution (69 persons with recorded sex)

Male37 (53.6%)
-51.9%prior 77
Female32 (46.4%)
-27.3%prior 44

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 30 mph zones decreased from 10 in July 2022 to 4 in July 2023, while crashes in 20 mph zones decreased from 3 to 1. Crashes in 25 mph zones remained consistent at 17 for both periods. The prior period also reported 5 crashes in 1 mph zones and 1 crash in a 10 mph zone, categories not present in the current period's data.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · 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: 2023-07-01 through 2023-07-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-07-01 through 2023-07-31 (31 days)
  • Geographic scope: SALEM, MA
  • Total crash records analyzed: 32
  • Total persons involved: 74
  • Total vehicles involved: 58

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). "SALEM, MA Crash Intelligence Report: July 2023." Published June 21, 2026. Reporting period: 2023-07-01 to 2023-07-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/salem/july-2023-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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Salem, MA Crash Report — July 2023 | ThatCarHitMe.com