Yearly Traffic Safety Analysis

556 CRASHES IN
IOWA, IA
2024

All metrics benchmarked against2023

In Wapello County, total traffic crashes increased by 5.7% from 526 in 2023 to 556 in 2024. Despite the rise in total incidents, the number of people injured in these crashes decreased by 13.1% from 214 to 186. One of the most significant shifts was a 37.5% increase in non-collision, single-vehicle crashes, which rose from 152 to 209 incidents year-over-year.

556

▲ 5.7%was 526

Total Crash Events

4

Persons Killed

186

▼ -13.1%was 214

Persons Injured

4

▲ 33.3%was 3

Fatal Crash Events

Note: "Persons Killed" (4) counts individual fatalities across all crash events. "Fatal" in the severity table below (4) 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, Wapello County saw an upward trend in crash volume, with 30 more incidents in 2024 compared to 2023. However, this increase in crashes did not correspond to an increase in harm, as total fatalities remained stable at four and total injuries declined from 214 to 186. This suggests a potential shift toward less severe crash types, even as the total number of crashes rose.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

1

Cyclists Killed

Prior: 0→%

3

Motorists Killed

Prior: 4↓-25.0%

0

Other Killed

Prior: 0→0.0%

4

Pedestrians Injured

Prior: 6↓-33.3%

1

Cyclists Injured

Prior: 4↓-75.0%

179

Motorists Injured

Prior: 204↓-12.3%

2

Other Injured

Prior: 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 temporal patterns of crashes shifted year-over-year. The peak day for crashes moved from Tuesday (92 crashes) in 2023 to Friday (113 crashes) in 2024. Similarly, the peak hour for incidents shifted from the 7 a.m. morning commute hour in 2023 to the 5 p.m. evening commute hour in 2024.

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

While the number of fatal crashes increased from three to four, the overall proportion of crashes resulting in any injury decreased from 31.3% in 2023 to 27.5% in 2024. This was driven by a drop in the share of both serious injury crashes (from 3.0% to 2.0%) and minor injury crashes (from 13.5% to 8.8%). Consequently, the proportion of crashes with no injuries reported rose from 68.1% to 71.8% of all incidents.

Outcome by Severity (Crash Events)

Fatal4fatal crashes0.7%
↑33.3%prior 3
Serious Injury11serious injury crashes2%
↓-31.3%prior 16
Minor Injury49minor injury crashes8.8%
↓-31.0%prior 71
Possible Injury93possible injury crashes16.7%
↑19.2%prior 78
No Injury399no injury crashes71.8%
↑11.5%prior 358

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 in both years, with the count increasing from 97 in 2023 to 103 in 2024. The second-most cited factor, failure to yield right-of-way from a stop sign, saw its count decrease from 48 to 40. Incidents attributed to 'Lost Control' and 'Followed too close' both saw slight increases in count, from 34 to 36 and 33 to 36, respectively.

Officer-Reported Primary Contributing Cause

Animal103 (18.5%)↑6.2%prior 97
FTYROW: From stop sign40 (7.2%)↓-16.7%prior 48
Followed too close36 (6.5%)↑9.1%prior 33
Lost Control36 (6.5%)↑5.9%prior 34
Ran Stop Sign32 (5.8%)↑18.5%prior 27
FTYROW: Making left turn30 (5.4%)↑15.4%prior 26
Ran off road - left29 (5.2%)↑3.6%prior 28
Other (explain in narrative): Other27 (4.9%)↑80.0%prior 15
Driving too fast for conditions17 (3.1%)↑6.3%prior 16
Operating vehicle in an reckless, erratic, careless, negligent manner16 (2.9%)↓-11.1%prior 18

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

Road & Environmental Conditions

In both years, most crashes occurred in daylight, during clear weather, and on dry roads. However, there was a slight proportional increase in crashes under adverse conditions in 2024. The share of crashes on wet, icy, or snowy road surfaces grew from 12.0% in 2023 to 13.5% in 2024, and crashes during rain or snow increased from 5.9% to 6.5% of the total.

Weather

Clear374 (79.9%)
↑0.8%prior 371
Cloudy51 (10.9%)
↑21.4%prior 42
Rain17 (3.6%)
↑13.3%prior 15
Snow14 (3.0%)
↑75.0%prior 8
Fog, smoke, smog7 (1.5%)
↑40.0%prior 5
Freezing rain/drizzle3 (0.6%)
↓-50.0%prior 6
Other (explain in narrative)1 (0.2%)
Blowing Snow1 (0.2%)

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

Lighting

Daylight325 (69.0%)
↑6.9%prior 304
Dark - roadway lighted64 (13.6%)
↑8.5%prior 59
Dark - roadway not lighted55 (11.7%)
↑17.0%prior 47
Dawn15 (3.2%)
↓-6.3%prior 16
Dark - unknown roadway lighting7 (1.5%)
↓-41.7%prior 12
Dusk5 (1.1%)
↓-58.3%prior 12

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

Road Surface

Dry387 (82.5%)
↑0.8%prior 384
Wet34 (7.2%)
↑21.4%prior 28
Ice/frost22 (4.7%)
↑46.7%prior 15
Snow13 (2.8%)
↓-18.8%prior 16
Gravel6 (1.3%)
Slush5 (1.1%)
Sand1 (0.2%)
Mud, dirt1 (0.2%)

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

Vehicles & Demographics

The most common vehicle makes involved in crashes, Chevrolet and Ford, remained stable in rank and volume year-over-year. An analysis of persons involved shows a notable decrease in the 16-20 age group, which fell from 170 individuals in 2023 to 110 in 2024. The number of people involved from the 45-54 and 65+ age groups also saw significant decreases, dropping from 170 to 104 and 167 to 125, respectively.

Top Vehicle Makes (915 vehicles)

1
FORD148 (16.2%)
↓-5.1%prior 156
2
CHEV132 (14.4%)
↑3.9%prior 127
3
TOYT58 (6.3%)
↑28.9%prior 45
4
DODG54 (5.9%)
↑14.9%prior 47
5
CHEVROLET47 (5.1%)
↓-7.8%prior 51
6
JEEP47 (5.1%)
↓-6.0%prior 50
7
GMC39 (4.3%)
↑14.7%prior 34
8
DODGE31 (3.4%)
↑63.2%prior 19
9
HYUN23 (2.5%)
↑76.9%prior 13
10
BUIC23 (2.5%)
↑21.1%prior 19

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

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

Sex Distribution (587 persons with recorded sex)

Male350 (59.6%)
↓-29.1%prior 494
Female237 (40.4%)
↓-19.9%prior 296

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: 556
  • Total persons involved: 953
  • Total vehicles involved: 915

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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