ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · MALDEN, MA · APRIL 2024
Purpose: Machine-readable JSON endpoint for AI agents, LLMs, researchers, and programmatic consumers. Returns all underlying crash data and AI-generated commentary without HTML.
Authentication: None required. Public endpoint.
GET: https://thatcarhitme.com/api/crash-data/reports/data/massachusetts/malden/april-2024-report
Monthly Traffic Safety Analysis
73 CRASHES IN
MALDEN, MA
APRIL 2024
Total crashes in MALDEN for April 2024 increased to 73, up 12.3% from 65 crashes in April 2023. A significant change was observed in total injuries, which rose by 80% from 15 in April 2023 to 27 in April 2024, including the emergence of 2 serious injuries in the current period compared to none in the prior period.
73
▲ 12.3%was 65
Total Crash Events
0
Persons Killed
27
▲ 80.0%was 15
Persons Injured
21
▼ -22.2%was 27
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. 13 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall crash data for MALDEN indicates an upward trend year-over-year. Total crashes increased by 12.3%, from 65 in April 2023 to 73 in April 2024. More notably, total injuries saw a substantial 80% increase, rising from 15 to 27 over the same period, while fatalities remained at zero in both months.
21
Hit-and-Run Crashes — April 2024
▼ -22.2% vs prior (27)
Hit-and-run crashes decreased from 27 incidents in April 2023 to 21 incidents in April 2024, representing a reduction of 6 crashes. Concurrently, the hit-and-run crash rate declined from 41.5% of total crashes in April 2023 to 28.8% in April 2024, indicating a positive trend in reducing such incidents.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
0
Motorists Killed
0
Other Killed
2
Pedestrians Injured
1
Cyclists Injured
23
Motorists Injured
1
Other Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal distribution of crashes showed some shifts year-over-year. In April 2024, crashes peaked on both Sundays and Saturdays with 13 incidents each, and the peak hour was 3 PM with 6 crashes. This contrasts with April 2023, where Sunday was the sole peak day with 17 crashes, and the peak hour was 6 PM with 7 crashes.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
There were no fatal crashes or fatalities reported in either April 2023 or April 2024. However, injury severity distributions changed, with April 2024 recording 2 serious injury crashes (2.7% of total crashes) compared to none in April 2023. Minor injury crashes increased from 6 (9.2% share) in April 2023 to 10 (13.7% share) in April 2024, and possible injury crashes also rose from 3 (4.6% share) to 11 (15.1% share) over the same period.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Most severe injury per crash record
Top Contributing Factors
The distribution of contributing factors showed some shifts year-over-year. Crashes attributed to "No improper driving" increased from 14 in April 2023 to 21 in April 2024, representing a 50% increase in count. "Failed to yield right of way" crashes rose from 1 to 5, a 400% increase in count, while "Inattention" crashes doubled from 2 to 4. Conversely, crashes due to "Operating vehicle in erratic, reckless, careless, negligent or aggressive manner" decreased from 3 to 1.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Weather conditions during crashes primarily involved clear skies in both periods, with 44 crashes in April 2024 and 37 in April 2023 occurring under clear conditions. The number of crashes occurring in the rain decreased from 9 in April 2023 to 6 in April 2024. Daylight conditions remained the predominant lighting factor, accounting for 42 crashes in April 2024 and 41 in April 2023. Crashes on dry road surfaces increased from 40 to 49, while those on wet surfaces decreased from 16 to 12.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Road surface condition field
Vehicles & Demographics
The age distribution of persons involved in crashes shifted year-over-year, with a notable increase in the 26-34 age group, rising from 14 persons in April 2023 to 30 in April 2024. Similarly, the 35-44 age group saw an increase from 18 to 28 persons, and the 45-54 age group from 12 to 25 persons. Regarding vehicle makes, Toyota became the top make involved in crashes in April 2024 with 25 vehicles, surpassing Honda which had 25 in April 2023 and 18 in April 2024.
Top Vehicle Makes (128 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Vehicle unit records
32 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (122 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Person-level records linked to crash events
Speed Limit Zones
The distribution of crashes by speed limit zone showed some changes year-over-year. The 25 mph zone maintained the highest number of crashes with 47 incidents in both April 2023 and April 2024. Crashes in the 30 mph zone increased from 12 in April 2023 to 18 in April 2024, while the 35 mph zone saw a slight increase from 3 to 4 crashes. No fatalities were reported in any speed limit zone during either period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · 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: 2024-04-01 through 2024-04-30
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2024-04-01 through 2024-04-30 (30 days)
- Geographic scope: MALDEN, MA
- Total crash records analyzed: 73
- Total persons involved: 161
- 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: April 2024." Published June 21, 2026. Reporting period: 2024-04-01 to 2024-04-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/malden/april-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
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly
Period: 2024-04-01 – 2024-04-30
Generated: June 21, 2026 · All rights reserved