Yearly Traffic Safety Analysis

112 CRASHES IN
IOWA, IA
2023

All metrics benchmarked against2022

In 2023, Decatur County recorded 112 total crashes, a 17.0% decrease from the 135 crashes reported in 2022. Despite the overall reduction in collisions, the number of fatalities doubled, increasing from 2 in the prior year to 4 in the current year. This increase in fatalities occurred alongside a slight rise in total injuries from 39 to 41.

112

▼ -17.0%was 135

Total Crash Events

4

▲ 100.0%was 2

Persons Killed

41

▲ 5.1%was 39

Persons Injured

4

▲ 100.0%was 2

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 · 2023-01-01 to 2023-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall traffic crashes in Decatur County showed a downward trend, decreasing by 17.0% from 135 incidents in 2022 to 112 in 2023. However, the severity of these crashes worsened, with total fatalities doubling from 2 to 4 and total injuries increasing slightly from 39 to 41 year-over-year.

Vulnerable Road User Casualties

4

Motorists Killed

Prior: 1↑300.0%

0

Other Killed

Prior: 0→0.0%

38

Motorists Injured

Prior: 39↓-2.6%

3

Other Injured

Prior: 0→%

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · 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 2022 and 2023. The peak day for crashes moved from Saturday (26 crashes) in the prior year to Sunday (21 crashes) in the current year. The peak hour for collisions also changed, moving from 7 a.m. in 2022 (11 crashes) to 7 p.m. in 2023 (12 crashes).

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

While total crashes declined, the severity of collisions increased from 2022 to 2023. The number of fatal crashes doubled from 2 to 4, and the fatal crash rate rose from 1.48% to 3.57%. The proportion of crashes resulting in any level of injury or a fatality increased from 23.7% in 2022 to 33.9% in 2023, while no-injury crashes decreased from 76.3% to 66.1% of all incidents.

Outcome by Severity (Crash Events)

Fatal4fatal crashes3.6%
↑100.0%prior 2
Serious Injury6serious injury crashes5.4%
↓-25.0%prior 8
Minor Injury10minor injury crashes8.9%
→0.0%prior 10
Possible Injury18possible injury crashes16.1%
↑50.0%prior 12
No Injury74no injury crashes66.1%
↓-28.2%prior 103

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Most severe injury per crash record

Top Contributing Factors

Collisions involving an 'Animal' remained the top contributing factor in both periods but decreased in count from 47 in 2022 to 33 in 2023. 'Lost Control' became the second-most cited factor in 2023 with 14 crashes, up from 12 in the prior year. Conversely, crashes attributed to 'Driving too fast for conditions' saw a significant drop, falling from 12 incidents in 2022 to just 4 in 2023.

Officer-Reported Primary Contributing Cause

Animal33 (29.5%)↓-29.8%prior 47
Lost Control14 (12.5%)↑16.7%prior 12
Ran off road - straight10 (8.9%)↓-33.3%prior 15
Followed too close7 (6.3%)↑40.0%prior 5
Swerving/Evasive Action6 (5.4%)
Operating vehicle in an reckless, erratic, careless, negligent manner5 (4.5%)
FTYROW: Making left turn4 (3.6%)↓-33.3%prior 6
Driving too fast for conditions4 (3.6%)↓-66.7%prior 12
Other (explain in narrative): Other4 (3.6%)
Ran off road - left4 (3.6%)

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in clear weather and daylight conditions remained relatively stable year-over-year. However, there was a notable decrease in crashes under adverse conditions. Collisions on wet, snowy, or icy road surfaces fell from 28 in 2022 to 17 in 2023, and crashes in dark, unlighted conditions decreased from 33 to 23.

Weather

Clear61 (70.9%)
↑1.7%prior 60
Cloudy14 (16.3%)
↓-33.3%prior 21
Freezing rain/drizzle4 (4.7%)
Rain3 (3.5%)
↓-40.0%prior 5
Snow2 (2.3%)
↓-66.7%prior 6
Fog, smoke, smog1 (1.2%)
Blowing Snow1 (1.2%)

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Weather condition at time of crash

Lighting

Daylight54 (62.1%)
↓-3.6%prior 56
Dark - roadway not lighted23 (26.4%)
↓-30.3%prior 33
Dusk5 (5.7%)
→0.0%prior 5
Dawn2 (2.3%)
Dark - roadway lighted2 (2.3%)
↓-60.0%prior 5
Dark - unknown roadway lighting1 (1.1%)

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Lighting condition field

Road Surface

Dry67 (77.0%)
↓-4.3%prior 70
Wet7 (8.0%)
↓-30.0%prior 10
Gravel6 (6.9%)
Slush3 (3.4%)
Snow3 (3.4%)
↓-50.0%prior 6
Ice/frost1 (1.1%)
↓-91.7%prior 12

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Road surface condition field

Vehicles & Demographics

Ford and Chevrolet remained the top two vehicle makes involved in crashes in both 2022 and 2023, though the number of vehicles from both makes decreased in the current period. The number of Fords involved in crashes fell from 32 to 24, and Chevrolets dropped from a combined 37 to 29. Analysis of persons involved shows a notable increase in the 16-20 age group, which grew from 28 individuals in 2022 to 36 in 2023, while involvement for the 35-44 age group decreased from 54 to 41.

Top Vehicle Makes (160 vehicles)

1
FORD24 (15%)
↓-25.0%prior 32
2
CHEV17 (10.6%)
↓-22.7%prior 22
3
CHEVROLET12 (7.5%)
↓-20.0%prior 15
4
DODG10 (6.3%)
5
FREIGHTLINER9 (5.6%)
↑28.6%prior 7
6
GMC8 (5%)
↓-11.1%prior 9
7
TOYT8 (5%)
8
KIA6 (3.8%)
9
JEEP6 (3.8%)
↓-25.0%prior 8
10
HONDA5 (3.1%)

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records

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

Sex Distribution (146 persons with recorded sex)

Male91 (62.3%)
↓-26.6%prior 124
Female55 (37.7%)
↑27.9%prior 43

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · 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: 2023-01-01 through 2023-12-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2023-01-01 through 2023-12-31 (365 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 112
  • Total persons involved: 237
  • Total vehicles involved: 160

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: 2023." Published September 9, 2026. Reporting period: 2023-01-01 to 2023-12-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/2023-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

ThatCarHitMe.com · An Injuria.ai Company