Monthly Traffic Safety Analysis

74 CRASHES IN
MALDEN, MA
FEBRUARY 2024

All metrics benchmarked againstFebruary 2023

Total crashes in MALDEN increased from 57 in February 2023 to 74 in February 2024, marking a 29.8% rise. The most notable shift was an 85.7% increase in hit-and-run crashes, rising from 14 incidents to 26 incidents year-over-year. Fatalities remained at zero in both periods.

74

29.8%was 57

Total Crash Events

0

Persons Killed

24

50.0%was 16

Persons Injured

26

85.7%was 14

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

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash incidents in MALDEN increased by 29.8% year-over-year, from 57 crashes in February 2023 to 74 crashes in February 2024. This indicates an upward trend in total crash occurrences. Total injuries also rose from 16 to 24, an increase of 50%.

26

Hit-and-Run Crashes — February 2024

85.7% vs prior (14)

Hit-and-run crashes significantly increased year-over-year, rising from 14 incidents in February 2023 to 26 incidents in February 2024. This represents an 85.7% increase in the number of hit-and-run crashes. The hit-and-run rate also trended upward, increasing from 24.6% of total crashes in February 2023 to 35.1% in February 2024.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

0

Other Killed

Prior: 00.0%

3

Pedestrians Injured

Prior: 250.0%

1

Cyclists Injured

Prior: 10.0%

19

Motorists Injured

Prior: 1346.2%

1

Other Injured

Prior: 0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · 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 Saturday in February 2023, with 12 crashes, to Friday in February 2024, with 13 crashes. The peak hour also changed, moving from 6 PM with 6 crashes in the prior period to 3 PM with 8 crashes in the current period. Overall, there was an increase in crash counts across most days of the week.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatalities remained at 0 in both February 2023 and February 2024, with no fatal crashes recorded in either period. Serious injuries (Severity A) decreased from 2 (3.5% of crashes) in February 2023 to 1 (1.4% of crashes) in February 2024. Minor injuries (Severity B) increased from 5 (8.8% of crashes) to 12 (16.2% of crashes), while possible injuries (Severity C) remained relatively stable, increasing from 5 (8.8% of crashes) to 6 (8.1% of crashes).

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes1.4%
-50.0%prior 2
Minor Injury12minor injury crashes16.2%
140.0%prior 5
Possible Injury6possible injury crashes8.1%
20.0%prior 5
No Injury38no injury crashes51.4%
35.7%prior 28

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Most severe injury per crash record

Top Contributing Factors

No improper driving remained the most frequently cited factor in both periods, increasing from 14 crashes in February 2023 to 19 crashes in February 2024. Factors like Failure to keep in proper lane or running off road and Failed to yield right of way, each associated with 2 crashes in February 2023, were not among the listed top factors in February 2024. Conversely, Inattention emerged as a significant factor in February 2024 with 9 crashes, having not been listed among the top factors in the prior period.

Officer-Reported Primary Contributing Cause

No improper driving19 (25.7%)35.7%prior 14
Inattention9 (12.2%)
Visibility obstructed2 (2.7%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (1.4%)
Driving too fast for conditions1 (1.4%)
Distracted1 (1.4%)
Other improper action1 (1.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in Clear weather conditions increased from 32 in February 2023 to 55 in February 2024. Crashes on Dry road surfaces also increased, from 39 to 58 year-over-year, while those on Wet surfaces decreased from 9 to 6. Crashes in Daylight conditions rose from 25 to 39, and those in Dark - lighted roadway conditions slightly increased from 22 to 23.

Weather

Clear55 (77.5%)
71.9%prior 32
Clear/Clear5 (7.0%)
Cloudy5 (7.0%)
-37.5%prior 8
Rain2 (2.8%)
Snow1 (1.4%)
Other1 (1.4%)
Unknown/Clear1 (1.4%)
Unknown/Unknown1 (1.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Weather condition at time of crash

Lighting

Daylight39 (56.5%)
56.0%prior 25
Dark - lighted roadway23 (33.3%)
4.5%prior 22
Dark - roadway not lighted2 (2.9%)
Dark - unknown roadway lighting2 (2.9%)
Dusk2 (2.9%)
-60.0%prior 5
Other1 (1.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Lighting condition field

Road Surface

Dry58 (90.6%)
48.7%prior 39
Wet6 (9.4%)
-33.3%prior 9

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Road surface condition field

Vehicles & Demographics

The total number of persons involved in crashes increased from 139 in February 2023 to 183 in February 2024. The 0-15 age group saw an increase from 5 persons to 11 persons, and the 35-44 age group increased from 16 persons to 22 persons. Honda and Toyota remained the top two vehicle makes involved in crashes, with Honda increasing from 21 to 29 and Toyota from 17 to 21.

Top Vehicle Makes (128 vehicles)

1
HONDA29 (22.7%)
38.1%prior 21
2
TOYOTA21 (16.4%)
23.5%prior 17
3
CHEVROLET9 (7%)
28.6%prior 7
4
FORD9 (7%)
12.5%prior 8
5
NISSAN6 (4.7%)
6
HYUNDAI6 (4.7%)
7
SUBARU5 (3.9%)
8
JEEP5 (3.9%)
9
ACURA3 (2.3%)
10
BMW3 (2.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Vehicle unit records

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

Sex Distribution (119 persons with recorded sex)

Male72 (60.5%)
38.5%prior 52
Female47 (39.5%)
6.8%prior 44

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Person-level records linked to crash events

Speed Limit Zones

Crashes occurring in 25 mph speed zones increased from 44 in February 2023 to 57 in February 2024. Crashes in 30 mph zones slightly decreased from 9 to 8. No fatal crashes were recorded in any speed zone during either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · 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: 2024-02-01 through 2024-02-29
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-02-01 through 2024-02-29 (29 days)
  • Geographic scope: MALDEN, MA
  • Total crash records analyzed: 74
  • Total persons involved: 183
  • Total vehicles involved: 128

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). "MALDEN, MA Crash Intelligence Report: February 2024." Published June 21, 2026. Reporting period: 2024-02-01 to 2024-02-29. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/malden/february-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

ThatCarHitMe.com · An Injuria.ai Company

Malden, MA Crash Report — February 2024 | ThatCarHitMe.com