Yearly Traffic Safety Analysis

9 CRASHES IN
AKRON, IA
2024

All metrics benchmarked against2023

Total crashes in AKRON increased by 12.5% year-over-year, rising from 8 crashes in the prior year to 9 crashes in the current year. Despite this increase in crash frequency, total injuries saw a substantial decrease of 75%, falling from 4 injuries in the prior year to 1 injury in the current year, representing the most notable shift.

9

▲ 12.5%was 8

Total Crash Events

0

Persons Killed

1

▼ -75.0%was 4

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.

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall crash frequency in AKRON shows a slight upward trend, with total crashes increasing from 8 in the prior year to 9 in the current year. This represents a 12.5% rise in the number of reported crashes year-over-year.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 0→0.0%

1

Motorists Injured

Prior: 4↓-75.0%

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · 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 Friday in the prior year (3 crashes) to Wednesday in the current year (3 crashes). Additionally, the peak hour for crashes moved from 7 p.m. (1 crash) in the prior year to 3 p.m. (2 crashes) in the current year, indicating a change in the busiest times for incidents.

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

There were no fatal crashes reported in either the current or prior year. Total injuries decreased significantly by 75%, from 4 injuries in the prior year to 1 injury in the current year. The proportion of crashes resulting in any injury also decreased, from 50% (4 out of 8 crashes) in the prior year to 11.1% (1 out of 9 crashes) in the current year.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes11.1%
No Injury8no injury crashes88.9%
↑100.0%prior 4

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Most severe injury per crash record

Top Contributing Factors

Crashes attributed to 'Improper Backing' increased by 1, from 1 in the prior year to 2 in the current year. Similarly, 'Animal' related crashes also increased by 1, rising from 1 in the prior year to 2 in the current year. Several new contributing factors, such as 'Equipment failure' (1 crash) and 'Driver Distraction: Manual operation of an electronic communication device' (1 crash), appeared in the current year's data that were not present in the prior year's top factors.

Officer-Reported Primary Contributing Cause

Improper Backing2 (22.2%)
Animal2 (22.2%)
Equipment failure1 (11.1%)
Other (explain in narrative): Other1 (11.1%)
Made improper turn1 (11.1%)
Operating vehicle in an reckless, erratic, careless, negligent manner1 (11.1%)
Driver Distraction: Manual operation of an electronic communication device1 (11.1%)

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The proportion of crashes occurring in clear weather decreased from 75% (6 out of 8 crashes) in the prior year to 55.6% (5 out of 9 crashes) in the current year. The number of crashes in cloudy conditions remained consistent at 2 in both periods. The road surface conditions section is empty for the current period, thus no comparative analysis can be made.

Weather

Clear5 (71.4%)
↓-16.7%prior 6
Cloudy2 (28.6%)

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Weather condition at time of crash

Lighting

Daylight6 (85.7%)
→0.0%prior 6
Dark - roadway lighted1 (14.3%)

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Lighting condition field

Vehicles & Demographics

Top Vehicle Makes (16 vehicles)

1
FORD5 (31.3%)
2
CHEV3 (18.8%)
3
CHEVROLET2 (12.5%)
4
HYUNDAI1 (6.3%)
5
MONS1 (6.3%)
6
CADI1 (6.3%)
7
TOYT1 (6.3%)
8
DODG1 (6.3%)
9
GMC1 (6.3%)

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Vehicle unit records

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

Sex Distribution (8 persons with recorded sex)

Female5 (62.5%)
↓-37.5%prior 8
Male3 (37.5%)
↓-50.0%prior 6

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Person-level records linked to crash events

Data Sources & Methodology

Primary Data Source

All crash data in this report is sourced from Iowa Crash Data, accessed programmatically via the ArcGIS 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 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 2024-12-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2024-01-01 through 2024-12-31 (366 days)
  • Geographic scope: AKRON, IA
  • Total crash records analyzed: 9
  • Total persons involved: 16
  • Total vehicles involved: 16

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). "AKRON, IA Crash Intelligence Report: 2024." Published September 9, 2026. Reporting period: 2024-01-01 to 2024-12-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/akron/2024-annual-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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