Monthly Traffic Safety Analysis

41 CRASHES IN
NORTH ANDOVER, MA
APRIL 2022

All metrics benchmarked againstApril 2021

In April 2022, NORTH ANDOVER recorded 41 crashes, marking a 57.7% increase from the 26 crashes reported in April 2021. This period also saw a significant rise in total injuries, climbing from 3 to 8, representing a 166.7% increase year-over-year.

41

57.7%was 26

Total Crash Events

0

Persons Killed

8

166.7%was 3

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

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall crash data for April in NORTH ANDOVER indicates a substantial upward trend year-over-year. Total crashes increased by 57.7%, rising from 26 in April 2021 to 41 in April 2022. Concurrently, total injuries surged by 166.7%, from 3 to 8, while fatalities remained at zero in both periods.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

8

Motorists Injured

Prior: 3166.7%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · 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 Saturday in both April 2021 (6 crashes) and April 2022 (12 crashes). However, the peak crash hour shifted from 5 PM with 3 crashes in April 2021 to 12 PM with 6 crashes in April 2022, indicating a change in the busiest time for incidents.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatalities remained at zero in both April 2021 and April 2022. The proportion of crashes resulting in injuries increased year-over-year, with 17.1% of crashes involving possible injuries in April 2022 compared to 11.5% (3 injury crashes out of 26 total) in April 2021. Consequently, the share of 'No Injury' crashes decreased from 88.5% to 80.5%.

Outcome by Severity (Crash Events)

Possible Injury7possible injury crashes17.1%
250.0%prior 2
No Injury33no injury crashes80.5%
43.5%prior 23

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Most severe injury per crash record

Top Contributing Factors

Among contributing factors, 'Inattention' increased from 7 crashes in April 2021 to 10 crashes in April 2022, while 'No improper driving' also rose from 7 to 10 crashes. 'Followed too closely' emerged as a significant factor in April 2022 with 8 crashes, which was not a top factor in the prior period. Conversely, 'Failed to yield right of way' decreased from 3 crashes to 1 crash year-over-year.

Officer-Reported Primary Contributing Cause

Inattention10 (24.4%)42.9%prior 7
No improper driving10 (24.4%)42.9%prior 7
Followed too closely8 (19.5%)
Other improper action3 (7.3%)
Disregarded traffic signs, signals, road markings2 (4.9%)
Failed to yield right of way1 (2.4%)
Over-correcting/over-steering1 (2.4%)
Visibility obstructed1 (2.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Clear' weather conditions increased from 21 in April 2021 to 32 in April 2022. Similarly, crashes under 'Daylight' conditions rose from 20 to 34 year-over-year. Crashes on 'Wet' road surfaces also saw an increase, from 3 in April 2021 to 5 in April 2022.

Weather

Clear32 (80.0%)
60.0%prior 20
Rain5 (12.5%)
Cloudy3 (7.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Weather condition at time of crash

Lighting

Daylight34 (85.0%)
70.0%prior 20
Dark - lighted roadway6 (15.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Lighting condition field

Road Surface

Dry35 (87.5%)
59.1%prior 22
Wet5 (12.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (75 vehicles)

1
HONDA15 (20%)
114.3%prior 7
2
FORD9 (12%)
3
TOYOTA7 (9.3%)
-30.0%prior 10
4
NISSAN6 (8%)
5
CHEVROLET5 (6.7%)
6
SUBARU4 (5.3%)
7
MAZDA3 (4%)
8
MERCEDES-BENZ3 (4%)
9
JEEP3 (4%)
-40.0%prior 5
10
HYUNDAI2 (2.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Vehicle unit records

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

Sex Distribution (84 persons with recorded sex)

Female43 (51.2%)
43.3%prior 30
Male41 (48.8%)
57.7%prior 26

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes in higher speed limit zones saw increases, with incidents in 40 mph zones rising from 4 in April 2021 to 9 in April 2022, and those in 35 mph zones increasing from 7 to 11. Conversely, crashes in 30 mph zones decreased from 7 to 5, and in 45 mph zones from 3 to 1. Notably, crashes occurred in 10 mph (2 crashes), 15 mph (4 crashes), and 65 mph (1 crash) zones in April 2022, which were not reported in April 2021.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · 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: 2022-04-01 through 2022-04-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2022-04-01 through 2022-04-30 (30 days)
  • Geographic scope: NORTH ANDOVER, MA
  • Total crash records analyzed: 41
  • Total persons involved: 90
  • Total vehicles involved: 75

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: April 2022." Published June 21, 2026. Reporting period: 2022-04-01 to 2022-04-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/north-andover/april-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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North Andover, MA Crash Report — April 2022 | ThatCarHitMe.com