Yearly Traffic Safety Analysis

700 CRASHES IN
IOWA, IA
2024

All metrics benchmarked against2023

In 2024, Webster County recorded 700 total crashes, an 8.9% decrease from the 768 crashes in 2023. This overall reduction was accompanied by a significant year-over-year improvement in crash outcomes. The most notable shift was a 50% decrease in total fatalities, which fell from 8 in the prior period to 4 in the current period.

700

▼ -8.9%was 768

Total Crash Events

4

▼ -50.0%was 8

Persons Killed

149

▼ -23.6%was 195

Persons Injured

3

▼ -62.5%was 8

Fatal Crash Events

Note: "Persons Killed" (4) counts individual fatalities across all crash events. "Fatal" in the severity table below (3) 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 crash trends in Webster County showed a notable improvement year-over-year. Total crashes fell by 8.9%, from 768 in 2023 to 700 in 2024. More significantly, the human cost of these incidents decreased, with total injuries dropping by 23.6% (from 195 to 149) and fatalities being cut in half from 8 to 4.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 0→%

0

Cyclists Killed

Prior: 0→0.0%

3

Motorists Killed

Prior: 8↓-62.5%

0

Other Killed

Prior: 0→0.0%

9

Pedestrians Injured

Prior: 2↑350.0%

2

Cyclists Injured

Prior: 3↓-33.3%

136

Motorists Injured

Prior: 189↓-28.0%

2

Other Injured

Prior: 1↑100.0%

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 timing of crashes shifted between the two periods. The day with the most crashes changed from Thursday (142 incidents) in 2023 to Monday (117 incidents) in 2024. However, the afternoon rush hour remained the most common time for collisions, with the 3 p.m. hour being the peak in both years, recording 68 crashes in 2023 and 61 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

Crash severity decreased significantly year-over-year. The number of fatal crashes dropped from 8 in 2023 to 3 in 2024, and their share of all crashes fell from 1.0% to 0.4%. Similarly, serious injury crashes declined from 21 (2.7% of total) to 13 (1.9% of total). Consequently, the proportion of crashes involving no injuries increased from 74.7% in the prior period to 77.1% in the current period.

Severity is per crash event (most severe injury). 3 fatal crash events resulted in 4 persons killed.

Outcome by Severity (Crash Events)

Fatal3fatal crashes0.4%
↓-62.5%prior 8
Serious Injury13serious injury crashes1.9%
↓-38.1%prior 21
Minor Injury54minor injury crashes7.7%
↓-18.2%prior 66
Possible Injury90possible injury crashes12.9%
↓-9.1%prior 99
No Injury540no injury crashes77.1%
↓-5.9%prior 574

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

The leading contributing factors remained broadly consistent, though their counts changed. Collisions involving an animal continued to be the top factor in both periods, with a slight decrease in count from 99 to 96. "Failure to yield from a stop sign" became more prominent, increasing from 51 to 55 incidents and moving from the fourth to the third-ranked factor. Conversely, crashes attributed to "lost control" saw a notable decrease in count, falling from 37 incidents in 2023 to 24 in 2024.

Officer-Reported Primary Contributing Cause

Animal96 (13.7%)↓-3.0%prior 99
Other (explain in narrative): Other61 (8.7%)↓-19.7%prior 76
FTYROW: From stop sign55 (7.9%)↑7.8%prior 51
Followed too close51 (7.3%)↓-10.5%prior 57
Driving too fast for conditions37 (5.3%)↑37.0%prior 27
Ran off road - left34 (4.9%)↑9.7%prior 31
Driver Distraction: Other interior distraction29 (4.1%)↓-21.6%prior 37
FTYROW: Making left turn24 (3.4%)↑14.3%prior 21
Lost Control24 (3.4%)↓-35.1%prior 37
Ran Stop Sign18 (2.6%)↓-5.3%prior 19

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 were largely stable year-over-year, with no major shifts in patterns. In both 2024 and 2023, the vast majority of incidents happened in clear weather, during daylight hours, and on dry road surfaces. For instance, crashes on dry roads accounted for 68.7% of the total in 2024, nearly identical to the 69.0% share in 2023. Crashes in snowy conditions saw a minor increase from 17 to 23 incidents, but this did not represent a significant change in the overall distribution.

Weather

Clear428 (69.6%)
↓-14.1%prior 498
Cloudy127 (20.7%)
→0.0%prior 127
Snow23 (3.7%)
↑35.3%prior 17
Rain19 (3.1%)
↓-26.9%prior 26
Blowing Snow6 (1.0%)
↑20.0%prior 5
Fog, smoke, smog4 (0.7%)
↓-33.3%prior 6
Freezing rain/drizzle4 (0.7%)
↓-20.0%prior 5
Blowing sand, soil, dirt1 (0.2%)
Severe Winds1 (0.2%)
Other (explain in narrative)1 (0.2%)

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

Lighting

Daylight423 (68.0%)
↓-7.0%prior 455
Dark - roadway lighted95 (15.3%)
↓-3.1%prior 98
Dark - roadway not lighted64 (10.3%)
↓-25.6%prior 86
Dusk16 (2.6%)
↓-30.4%prior 23
Dawn13 (2.1%)
↓-23.5%prior 17
Dark - unknown roadway lighting11 (1.8%)
↑22.2%prior 9

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

Road Surface

Dry481 (78.2%)
↓-9.2%prior 530
Wet51 (8.3%)
↓-26.1%prior 69
Ice/frost37 (6.0%)
↓-17.8%prior 45
Snow30 (4.9%)
↓-6.3%prior 32
Gravel10 (1.6%)
→0.0%prior 10
Slush4 (0.7%)
Mud, dirt2 (0.3%)

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

Vehicles & Demographics

Chevrolet and Ford vehicles were the top two makes involved in crashes in both periods. The number of Chevrolets involved decreased slightly from 230 to 217, while Fords increased from 187 to 196. A significant change was observed in the age of persons involved in crashes; the 16-20 age group saw its involvement drop from 259 persons in 2023 to 182 in 2024, and the 26-34 age group's involvement fell from 238 to 141 persons.

Top Vehicle Makes (1,189 vehicles)

1
CHEV217 (18.3%)
↓-5.7%prior 230
2
FORD196 (16.5%)
↑4.8%prior 187
3
TOYO61 (5.1%)
↑10.9%prior 55
4
DODG58 (4.9%)
↓-26.6%prior 79
5
JEEP49 (4.1%)
↓-22.2%prior 63
6
BUIC48 (4%)
↓-12.7%prior 55
7
GMC45 (3.8%)
↓-32.8%prior 67
8
CHEVROLET42 (3.5%)
↑10.5%prior 38
9
NR42 (3.5%)
↓-28.8%prior 59
10
TOYT39 (3.3%)
↓-15.2%prior 46

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

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

Sex Distribution (771 persons with recorded sex)

Male401 (52.0%)
↓-34.5%prior 612
Female370 (48.0%)
↓-26.1%prior 501

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: 700
  • Total persons involved: 1,211
  • Total vehicles involved: 1,189

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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