Monthly Traffic Safety Analysis

60 CRASHES IN
NORTH ANDOVER, MA
JANUARY 2024

All metrics benchmarked againstJanuary 2023

In January 2024, NORTH ANDOVER experienced 60 total crashes, a 5.3% increase compared to the 57 crashes reported in January 2023. Total injuries also increased from 11 to 14. The most notable year-over-year shift was a 100% increase in speeding-related crashes, rising from 3 to 6.

60

5.3%was 57

Total Crash Events

0

Persons Killed

14

27.3%was 11

Persons Injured

3

-40.0%was 5

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. 5 crashes with unreported severity are not shown in the severity breakdown.

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

Trend Summary

Overall, crashes in NORTH ANDOVER showed a slight upward trend, increasing by 5.3% from 57 crashes in January 2023 to 60 crashes in January 2024. Total injuries also increased by 27.3%, from 11 to 14. Fatalities remained at zero in both periods.

3

Hit-and-Run Crashes — January 2024

-40.0% vs prior (5)

Hit-and-run crashes decreased by 40%, from 5 in January 2023 to 3 in January 2024. The hit-and-run rate also decreased, moving from 8.8% of total crashes in the prior period to 5% in the current period.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

14

Motorists Injured

Prior: 1127.3%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-01-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The peak day for crashes remained Tuesday in both periods, increasing from 12 crashes in January 2023 to 16 crashes in January 2024. The peak hour shifted from 2 PM in January 2023 to 4 PM in January 2024, with both hours recording 7 crashes. Sunday saw a significant increase in crashes, rising from 5 to 10.

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

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

Crash Severity Breakdown

There were no fatal crashes in either period. Total injuries increased by 27.3%, from 11 in January 2023 to 14 in January 2024. Minor injuries increased by 50%, from 4 to 6, while possible injuries decreased by 33.3%, from 3 to 2. The proportion of crashes involving injury increased from 19.3% in January 2023 to 23.3% in January 2024.

Outcome by Severity (Crash Events)

Minor Injury6minor injury crashes10%
50.0%prior 4
Possible Injury2possible injury crashes3.3%
-33.3%prior 3
No Injury47no injury crashes78.3%
-2.1%prior 48

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

Severity Distribution (Crash Events)

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

Top Contributing Factors

Crashes attributed to 'No improper driving' increased by 23.8%, from 21 to 26. 'Inattention' crashes decreased by 40%, from 15 to 9, while 'Driving too fast for conditions' crashes increased by 66.7%, from 3 to 5. 'Followed too closely' crashes decreased significantly from 5 to 1, an 80% reduction in count.

Officer-Reported Primary Contributing Cause

No improper driving26 (43.3%)23.8%prior 21
Inattention9 (15%)-40.0%prior 15
Driving too fast for conditions5 (8.3%)
Failed to yield right of way5 (8.3%)
Visibility obstructed2 (3.3%)
Over-correcting/over-steering2 (3.3%)
Disregarded traffic signs, signals, road markings2 (3.3%)
Operating defective equipment1 (1.7%)
Glare1 (1.7%)
Wrong side or wrong way1 (1.7%)

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

Road & Environmental Conditions

Crashes occurring in 'Snow' weather conditions increased by 125%, from 4 in January 2023 to 9 in January 2024. Crashes in 'Dark - lighted roadway' conditions increased by 118.2%, from 11 to 24. Conversely, crashes on 'Wet' road surfaces decreased by 35.7%, from 14 to 9.

Weather

Clear31 (51.7%)
0.0%prior 31
Snow9 (15.0%)
Cloudy8 (13.3%)
0.0%prior 8
Rain3 (5.0%)
-40.0%prior 5
Snow/Blowing sand, snow2 (3.3%)
Clear/Other2 (3.3%)
Snow/Sleet, hail (freezing rain or drizzle)1 (1.7%)
Cloudy/Snow1 (1.7%)
Rain/Snow1 (1.7%)
Snow/Cloudy1 (1.7%)

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

Lighting

Daylight30 (50.8%)
-16.7%prior 36
Dark - lighted roadway24 (40.7%)
118.2%prior 11
Dusk3 (5.1%)
Dark - roadway not lighted2 (3.4%)
-60.0%prior 5

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

Road Surface

Dry34 (56.7%)
0.0%prior 34
Snow12 (20.0%)
50.0%prior 8
Wet9 (15.0%)
-35.7%prior 14
Slush3 (5.0%)
Ice2 (3.3%)

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

Vehicles & Demographics

The total number of vehicles involved in crashes increased by 8.5%, from 106 in January 2023 to 115 in January 2024. The 65+ age group saw a 26.1% decrease in persons involved, from 23 to 17. In contrast, the 21-25 age group experienced a 50% increase, from 10 to 15 persons involved.

Top Vehicle Makes (115 vehicles)

1
HONDA17 (14.8%)
0.0%prior 17
2
TOYOTA16 (13.9%)
14.3%prior 14
3
FORD9 (7.8%)
0.0%prior 9
4
JEEP9 (7.8%)
28.6%prior 7
5
CHEVROLET7 (6.1%)
-12.5%prior 8
6
DODGE5 (4.3%)
7
BMW4 (3.5%)
8
HYUNDAI4 (3.5%)
-42.9%prior 7
9
SUBARU4 (3.5%)
10
RAM4 (3.5%)

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

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

Sex Distribution (119 persons with recorded sex)

Female62 (52.1%)
24.0%prior 50
Male57 (47.9%)
-9.5%prior 63

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

Speed Limit Zones

Crashes in 25 mph zones saw a substantial increase of 175%, rising from 4 to 11. Crashes in 40 mph zones also increased by 75%, from 12 to 21. Conversely, crashes in 30 mph zones decreased by 35.7%, from 14 to 9. No fatalities were recorded in any speed zone during either period.

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

Data Coverage

  • Reporting period: 2024-01-01 through 2024-01-31 (31 days)
  • Geographic scope: NORTH ANDOVER, MA
  • Total crash records analyzed: 60
  • Total persons involved: 134
  • Total vehicles involved: 115

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). "NORTH ANDOVER, MA Crash Intelligence Report: January 2024." Published June 21, 2026. Reporting period: 2024-01-01 to 2024-01-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/north-andover/january-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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North Andover, MA Crash Report — January 2024 | ThatCarHitMe.com