Yearly Traffic Safety Analysis

174 CRASHES IN
IOWA, IA
2024

All metrics benchmarked against2023

In 2024, Chickasaw County recorded 174 total crashes, a 13.0% increase from the 154 crashes reported in 2023. Despite this rise in total incidents, the number of fatalities decreased from two to one, and total injuries fell from 54 to 49. The most significant contributing factor in both periods was collisions involving animals, which increased in count from 56 to 66 incidents year-over-year.

174

▲ 13.0%was 154

Total Crash Events

1

▼ -50.0%was 2

Persons Killed

49

▼ -9.3%was 54

Persons Injured

1

▼ -50.0%was 2

Fatal Crash Events

Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) 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

Traffic crashes in Chickasaw County increased by 13.0% from 2023 to 2024, rising from 154 to 174 incidents. While the overall volume of crashes grew, the number of resulting injuries decreased by 9.3% from 54 to 49, and the number of fatalities fell from two to one.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 1→0.0%

0

Cyclists Killed

Prior: 0→0.0%

0

Motorists Killed

Prior: 1↓-100.0%

1

Pedestrians Injured

Prior: 1→0.0%

1

Cyclists Injured

Prior: 1→0.0%

47

Motorists Injured

Prior: 51↓-7.8%

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 temporal patterns of crashes showed some shifts between 2023 and 2024. While Monday remained the peak day for crashes in both years (29 in 2023, 31 in 2024), the peak hour for incidents moved. In 2023, the highest volume occurred at 3 p.m. (13 crashes), whereas in 2024, the peaks shifted to the commute hours of 8 a.m. and 5 p.m., each with 14 crashes.

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

Crash severity generally decreased from 2023 to 2024. The number of fatal crashes fell from two to one, and the proportion of crashes resulting in a fatality dropped from 1.3% to 0.6%. Similarly, serious injury crashes decreased from nine incidents (5.8% of total) in 2023 to five (2.9% of total) in 2024. The share of crashes with no injuries increased from 75.3% in the prior year to 77.0% in the current year.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.6%
↓-50.0%prior 2
Serious Injury5serious injury crashes2.9%
↓-44.4%prior 9
Minor Injury16minor injury crashes9.2%
→0.0%prior 16
Possible Injury18possible injury crashes10.3%
↑63.6%prior 11
No Injury134no injury crashes77%
↑15.5%prior 116

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

Collisions with animals remained the leading contributing factor for crashes in both periods, with the count increasing by 17.9% from 56 incidents in 2023 to 66 in 2024. The second-ranked factor, "Failure to yield right-of-way from a stop sign," saw its count decrease by 42.9% from 14 to 8 crashes. Incidents where drivers "Followed too close" dropped from 9 to 3, while "Driver Distraction: Other interior distraction" increased from 4 to 7 incidents, becoming the third most common factor in 2024.

Officer-Reported Primary Contributing Cause

Animal66 (37.9%)↑17.9%prior 56
FTYROW: From stop sign8 (4.6%)↓-42.9%prior 14
Driver Distraction: Other interior distraction7 (4%)
Improper Backing6 (3.4%)
Lost Control6 (3.4%)↓-25.0%prior 8
Other (explain in narrative): Other5 (2.9%)↓-16.7%prior 6
FTYROW: Making left turn5 (2.9%)→0.0%prior 5
Driver Distraction: Inattentive/lost in thought5 (2.9%)
Operating vehicle in an reckless, erratic, careless, negligent manner5 (2.9%)→0.0%prior 5
Made improper turn5 (2.9%)

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 conditions under which crashes occurred showed some year-over-year changes. The proportion of crashes happening in daylight increased from 46.8% in 2023 to 52.9% in 2024, while crashes in unlit dark conditions fell from 18.8% to 9.2%. Crashes on dry road surfaces represented a smaller share of the total, decreasing from 59.1% to 50.0%. Notably, incidents on gravel roads more than doubled, increasing from 4 in 2023 to 10 in 2024.

Weather

Clear86 (75.4%)
↑10.3%prior 78
Cloudy9 (7.9%)
↓-25.0%prior 12
Snow5 (4.4%)
→0.0%prior 5
Fog, smoke, smog4 (3.5%)
Blowing Snow2 (1.8%)
Other (explain in narrative)2 (1.8%)
Rain2 (1.8%)
Freezing rain/drizzle2 (1.8%)
Severe Winds1 (0.9%)
Blowing sand, soil, dirt1 (0.9%)

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

Lighting

Daylight92 (73.0%)
↑27.8%prior 72
Dark - roadway not lighted16 (12.7%)
↓-44.8%prior 29
Dark - roadway lighted8 (6.3%)
↓-20.0%prior 10
Dark - unknown roadway lighting4 (3.2%)
Dawn3 (2.4%)
Dusk3 (2.4%)

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

Road Surface

Dry87 (71.9%)
↓-4.4%prior 91
Gravel10 (8.3%)
Wet9 (7.4%)
↑80.0%prior 5
Slush6 (5.0%)
Snow5 (4.1%)
↓-37.5%prior 8
Ice/frost4 (3.3%)

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

Vehicles & Demographics

The makes of vehicles involved in crashes saw a shift; while Ford was the most common make in 2023 with 47 vehicles, Chevrolet (CHEV) became the most frequent in 2024 with 49 vehicles. In terms of driver demographics, there was a notable decrease in the number of people aged 26-34 involved in crashes, falling from 60 in 2023 to 35 in 2024. The number of passengers involved in crashes also saw a significant decline, from 16 in the prior year to just 3 in the current year.

Top Vehicle Makes (252 vehicles)

1
CHEV49 (19.4%)
↑36.1%prior 36
2
FORD43 (17.1%)
↓-8.5%prior 47
3
GMC17 (6.7%)
↑112.5%prior 8
4
CHEVROLET13 (5.2%)
↓-27.8%prior 18
5
JEEP12 (4.8%)
↑50.0%prior 8
6
DODG11 (4.4%)
↑37.5%prior 8
7
BUIC8 (3.2%)
↑60.0%prior 5
8
CHRY7 (2.8%)
↑16.7%prior 6
9
KIA6 (2.4%)
10
TOYOTA6 (2.4%)

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

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

Sex Distribution (127 persons with recorded sex)

Male81 (63.8%)
↓-36.7%prior 128
Female46 (36.2%)
↓-37.8%prior 74

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: iowa, IA
  • Total crash records analyzed: 174
  • Total persons involved: 258
  • Total vehicles involved: 252

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). "iowa, 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/statewide/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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