Yearly Traffic Safety Analysis

815 CRASHES IN
IOWA, IA
2022

All metrics benchmarked against2021

In 2022, Webster County recorded 815 total crashes, an 8.6% decrease from the 892 crashes reported in 2021. While overall collisions and fatalities declined, the number of people injured in crashes increased from 184 to 215. A notable year-over-year shift was the decrease in fatalities from 5 in 2021 to 2 in 2022.

815

▼ -8.6%was 892

Total Crash Events

2

▼ -60.0%was 5

Persons Killed

215

▲ 16.8%was 184

Persons Injured

2

▼ -60.0%was 5

Fatal Crash Events

Note: "Persons Killed" (2) counts individual fatalities across all crash events. "Fatal" in the severity table below (2) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Crash trends in Webster County show a general decrease from 2021 to 2022. Total crashes fell by 8.6%, from 892 to 815 incidents. While the number of fatalities decreased from 5 to 2, the total number of injuries rose from 184 to 215.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

0

Cyclists Killed

Prior: 1↓-100.0%

2

Motorists Killed

Prior: 4↓-50.0%

0

Other Killed

Prior: 0→0.0%

2

Pedestrians Injured

Prior: 1↑100.0%

5

Cyclists Injured

Prior: 4↑25.0%

207

Motorists Injured

Prior: 178↑16.3%

1

Other Injured

Prior: 1→0.0%

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · 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 between the two periods. The peak day for crashes moved from Tuesday (157 crashes) in 2021 to Monday (129 crashes) in 2022. The peak hour for collisions also shifted earlier, from 5 p.m. in the prior year (85 crashes) to 3 p.m. in the current year (62 crashes).

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The severity of crashes saw a mixed change year-over-year. The number of fatal crashes decreased from 5 in 2021 to 2 in 2022, and the fatal crash rate fell from 0.56% to 0.25%. However, the proportion of crashes resulting in injuries increased, with minor injury crashes rising from 5.7% of all collisions in 2021 to 7.7% in 2022.

Outcome by Severity (Crash Events)

Fatal2fatal crashes0.2%
↓-60.0%prior 5
Serious Injury14serious injury crashes1.7%
↑7.7%prior 13
Minor Injury63minor injury crashes7.7%
↑23.5%prior 51
Possible Injury111possible injury crashes13.6%
↓-0.9%prior 112
No Injury625no injury crashes76.7%
↓-12.1%prior 711

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · Most severe injury per crash record

Top Contributing Factors

Collisions involving an animal remained the top contributing factor in both periods, though the count decreased from 147 in 2021 to 110 in 2022. 'Driving too fast for conditions' saw a slight increase in count from 58 to 61 incidents, moving from the fourth to the third most common factor. The count for crashes involving 'Lost Control' increased from 37 to 46, while crashes attributed to 'Followed too close' decreased from 60 to 43.

Officer-Reported Primary Contributing Cause

Animal110 (13.5%)↓-25.2%prior 147
Other (explain in narrative): Other98 (12%)↑14.0%prior 86
Driving too fast for conditions61 (7.5%)↑5.2%prior 58
FTYROW: From stop sign56 (6.9%)↑3.7%prior 54
Lost Control46 (5.6%)↑24.3%prior 37
Followed too close43 (5.3%)↓-28.3%prior 60
FTYROW: Making left turn32 (3.9%)↑23.1%prior 26
Driver Distraction: Other interior distraction30 (3.7%)↓-28.6%prior 42
Ran off road - left30 (3.7%)↓-9.1%prior 33
Ran Stop Sign20 (2.5%)→0.0%prior 20

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes in both years predominantly occurred in clear weather, during daylight hours, and on dry roads, with the share of crashes under these conditions remaining stable. However, there was an increase in crashes occurring in adverse conditions. Collisions in snowy weather rose from 18 to 32, and crashes on snow-covered road surfaces increased from 50 in 2021 to 65 in 2022.

Weather

Clear509 (70.4%)
↓-8.9%prior 559
Cloudy132 (18.3%)
↓-0.8%prior 133
Snow32 (4.4%)
↑77.8%prior 18
Blowing Snow20 (2.8%)
↑185.7%prior 7
Rain18 (2.5%)
↓-37.9%prior 29
Freezing rain/drizzle10 (1.4%)
↓-16.7%prior 12
Other (explain in narrative)1 (0.1%)
Fog, smoke, smog1 (0.1%)

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · Weather condition at time of crash

Lighting

Daylight484 (67.1%)
↓-6.2%prior 516
Dark - roadway lighted110 (15.3%)
↓-8.3%prior 120
Dark - roadway not lighted92 (12.8%)
↓-9.8%prior 102
Dusk17 (2.4%)
↑30.8%prior 13
Dawn12 (1.7%)
→0.0%prior 12
Dark - unknown roadway lighting6 (0.8%)

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · Lighting condition field

Road Surface

Dry532 (73.4%)
↓-7.3%prior 574
Snow65 (9.0%)
↑30.0%prior 50
Ice/frost59 (8.1%)
↓-9.2%prior 65
Wet48 (6.6%)
↓-17.2%prior 58
Gravel12 (1.7%)
↓-14.3%prior 14
Slush6 (0.8%)
↓-14.3%prior 7
Mud, dirt2 (0.3%)
Water (standing or moving)1 (0.1%)

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · Road surface condition field

Vehicles & Demographics

The top vehicle makes involved in crashes remained consistent, with Chevrolet and Ford vehicles being the most common in both 2021 and 2022. An analysis of persons involved in crashes shows a demographic shift, with fewer individuals in the 16-20 and 21-25 age groups involved in crashes. Conversely, involvement increased for several older age brackets, most notably the 45-54 group, which grew from 152 individuals in 2021 to 199 in 2022.

Top Vehicle Makes (1,400 vehicles)

1
CHEV254 (18.1%)
↑21.5%prior 209
2
FORD197 (14.1%)
↓-15.1%prior 232
3
DODG83 (5.9%)
↓-2.4%prior 85
4
NR73 (5.2%)
↑12.3%prior 65
5
GMC71 (5.1%)
↑16.4%prior 61
6
JEEP66 (4.7%)
↑24.5%prior 53
7
CHEVROLET64 (4.6%)
↓-43.4%prior 113
8
TOYO59 (4.2%)
↓-15.7%prior 70
9
CHRY49 (3.5%)
→0.0%prior 49
10
BUIC48 (3.4%)
↑45.5%prior 33

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · Vehicle unit records

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

Sex Distribution (1,178 persons with recorded sex)

Male624 (53.0%)
↓-1.6%prior 634
Female554 (47.0%)
↑5.7%prior 524

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · 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: 2022-01-01 through 2022-12-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2022-01-01 through 2022-12-31 (365 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 815
  • Total persons involved: 1,879
  • Total vehicles involved: 1,400

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: 2022." Published September 9, 2026. Reporting period: 2022-01-01 to 2022-12-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/2022-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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