Yearly Traffic Safety Analysis

135 CRASHES IN
IOWA, IA
2022

All metrics benchmarked against2021

In Decatur County, crash volume remained nearly unchanged year-over-year, with 135 total crashes in 2022 compared to 134 in 2021. Despite this stability in the number of incidents, the severity of outcomes worsened. The most notable shift was the recording of two fatalities in 2022, whereas there were none in the prior year.

135

▲ 0.7%was 134

Total Crash Events

Persons Killed

▲ 18.2%was 33

Persons Injured

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

Overall crash trends in Decatur County were stable, with total incidents increasing by just one crash from 2021 to 2022. However, this masks a negative trend in crash severity. Total injuries rose by 18.2% from 33 to 39, and the county experienced two traffic fatalities in 2022 after having zero in 2021.

Vulnerable Road User Casualties

Pedestrians Killed

Prior: 0→%

Motorists Killed

Prior: 0→%

Pedestrians Injured

Prior: 0→0.0%

Motorists Injured

Prior: 32↑21.9%

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 timing of crashes shifted between the two periods. The peak day for crashes moved from Friday in 2021 (27 crashes) to Saturday in 2022 (26 crashes). More significantly, the peak hour for incidents shifted from the late evening at 9 p.m. in 2021 (11 crashes) to the morning commute at 7 a.m. in 2022 (11 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

Crash severity increased significantly from 2021 to 2022. Two fatal crashes occurred in 2022, resulting in two deaths, compared to zero fatal incidents in the previous year. The number of serious injury crashes also doubled from 4 to 8. Consequently, the proportion of crashes resulting in no injuries decreased from 79.9% in 2021 to 76.3% in 2022.

Outcome by Severity (Crash Events)

Fatal2fatal crashes1.5%

Serious Injury8serious injury crashes5.9%

↑100.0%prior 4

Minor Injury10minor injury crashes7.4%

↓-9.1%prior 11

Possible Injury12possible injury crashes8.9%

→0.0%prior 12

No Injury103no injury crashes76.3%

↓-3.7%prior 107

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 with animals remained the leading contributing factor in both years, though the count of such incidents decreased from 57 in 2021 to 47 in 2022. Conversely, crashes attributed to 'Ran off road - straight' more than tripled, increasing from 4 to 15. Incidents involving 'Driving too fast for conditions' also saw a notable increase, rising from a count of 5 in 2021 to 12 in 2022.

Officer-Reported Primary Contributing Cause

Animal47 (34.8%)↓-17.5%prior 57

Ran off road - straight15 (11.1%)

Driving too fast for conditions12 (8.9%)↑140.0%prior 5

Lost Control12 (8.9%)↓-7.7%prior 13

FTYROW: Making left turn6 (4.4%)

Followed too close5 (3.7%)

Driver Distraction: Other interior distraction5 (3.7%)

Ran Stop Sign5 (3.7%)

Ran off road - right4 (3%)

FTYROW: From stop sign4 (3%)

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

Road & Environmental Conditions

While the number of crashes on dry roads was nearly identical year-over-year (70 in 2022 vs. 69 in 2021), incidents on adverse road surfaces showed a marked increase. Crashes occurring on roads with ice or frost rose from 2 in 2021 to 12 in 2022. Additionally, crashes during daylight hours increased from 46 to 56, while those in dark, unlighted conditions remained stable.

Weather

Clear60 (60.0%)

↓-4.8%prior 63

Cloudy21 (21.0%)

↑90.9%prior 11

Snow6 (6.0%)

↓-40.0%prior 10

Rain5 (5.0%)

Freezing rain/drizzle4 (4.0%)

Blowing Snow3 (3.0%)

Fog, smoke, smog1 (1.0%)

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

Lighting

Daylight56 (56.0%)

↑21.7%prior 46

Dark - roadway not lighted33 (33.0%)

↑3.1%prior 32

Dark - roadway lighted5 (5.0%)

↓-16.7%prior 6

Dusk5 (5.0%)

Dawn1 (1.0%)

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

Road Surface

Dry70 (69.3%)

↑1.4%prior 69

Ice/frost12 (11.9%)

Wet10 (9.9%)

↑42.9%prior 7

Snow6 (5.9%)

↓-40.0%prior 10

Gravel3 (3.0%)

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

Vehicles & Demographics

Ford and Chevrolet remained the most common vehicle makes involved in crashes during both periods. Analysis of persons involved shows a significant demographic shift, with the 35-44 age group seeing their involvement nearly double from 29 individuals in 2021 to 54 in 2022. The number of persons aged 21-25 involved in crashes also increased from 21 to 35.

Top Vehicle Makes (173 vehicles)

FORD32 (18.5%)

↓-5.9%prior 34

CHEV22 (12.7%)

↑10.0%prior 20

CHEVROLET15 (8.7%)

↑36.4%prior 11

GMC9 (5.2%)

↓-18.2%prior 11

JEEP8 (4.6%)

↑14.3%prior 7

DODGE8 (4.6%)

↓-11.1%prior 9

FREIGHTLINER7 (4%)

↑40.0%prior 5

TOYO5 (2.9%)

VOLVO4 (2.3%)

TOYT4 (2.3%)

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

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

Sex Distribution (167 persons with recorded sex)

Male124 (74.3%)

↑26.5%prior 98

Female43 (25.7%)

↑7.5%prior 40

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: 135
Total persons involved: 251
Total vehicles involved: 173

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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135 CRASHES INIOWA, IA2022