Yearly Traffic Safety Analysis

198 CRASHES IN
IOWA, IA
2023

All metrics benchmarked against2022

In 2023, Madison County recorded 198 total crashes, a 5.7% decrease from the 210 crashes reported in 2022. Despite the overall reduction in collisions, the number of fatalities doubled, increasing from 2 in 2022 to 4 in 2023. The most significant contributing factor change was an 80% decrease in crashes involving a driver under the influence, from 10 incidents in 2022 to 2 in 2023.

198

▼ -5.7%was 210

Total Crash Events

4

▲ 100.0%was 2

Persons Killed

66

▼ -8.3%was 72

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 crash volume in Madison County showed a downward trend, with total crashes decreasing by 5.7% from 210 in 2022 to 198 in 2023. The number of people injured also declined by 8.3% from 72 to 66. In contrast, the number of fatalities doubled from 2 to 4 over the same period.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 0→0.0%

4

Motorists Killed

Prior: 2↑100.0%

1

Cyclists Injured

Prior: 0→%

65

Motorists Injured

Prior: 70↓-7.1%

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 year-over-year. In 2023, the highest number of crashes occurred on Fridays (35), a change from 2022 when Monday was the peak day with 37 crashes. The peak hour for collisions also moved from the 7 a.m. morning commute hour in 2022 (21 crashes) to the 5 p.m. evening commute hour in 2023 (21 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

Crash severity increased in 2023 compared to the previous year. The rate of fatal crashes more than doubled, rising from 0.95% of all crashes in 2022 to 2.02% in 2023. While the share of crashes resulting in serious injuries (4.0% vs. 5.7%) and minor injuries (9.6% vs. 12.4%) decreased, the proportion of crashes involving possible injuries increased from 6.7% to 10.6%.

Outcome by Severity (Crash Events)

Fatal4fatal crashes2%
↑100.0%prior 2
Serious Injury8serious injury crashes4%
↓-33.3%prior 12
Minor Injury19minor injury crashes9.6%
↓-26.9%prior 26
Possible Injury21possible injury crashes10.6%
↑50.0%prior 14
No Injury146no injury crashes73.7%
↓-6.4%prior 156

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 leading contributing factor in both periods, with a slight decrease in count from 72 crashes in 2022 to 68 in 2023. The count of crashes attributed to "Lost Control" decreased by 29%, from 24 in 2022 to 17 in 2023. Conversely, crashes involving a vehicle running off the road to the left increased in count by 71%, from 7 incidents in 2022 to 12 in 2023, making it the third most common factor in the current period.

Officer-Reported Primary Contributing Cause

Animal68 (34.3%)↓-5.6%prior 72
Lost Control17 (8.6%)↓-29.2%prior 24
Ran off road - left12 (6.1%)↑71.4%prior 7
Other (explain in narrative): Other10 (5.1%)↓-28.6%prior 14
Ran off road - straight10 (5.1%)↓-16.7%prior 12
Followed too close9 (4.5%)↑12.5%prior 8
FTYROW: From yield sign8 (4%)↑33.3%prior 6
FTYROW: From stop sign6 (3%)
Driving too fast for conditions5 (2.5%)
Driver Distraction: Other interior distraction5 (2.5%)

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

Road & Environmental Conditions

The proportion of crashes occurring in clear weather and daylight conditions remained relatively stable year-over-year. In 2023, 52.0% of crashes happened in clear weather, compared to 52.9% in 2022, while 47.0% occurred in daylight, versus 46.7% previously. There was a notable decrease in the share of crashes on gravel roads, which fell from 11.0% of all incidents in 2022 to 6.1% in 2023. Conversely, the share of crashes on dry road surfaces increased from 49.0% to 55.1%.

Weather

Clear103 (72.5%)
↓-7.2%prior 111
Cloudy20 (14.1%)
↑66.7%prior 12
Snow10 (7.0%)
↑42.9%prior 7
Rain6 (4.2%)
↑20.0%prior 5
Fog, smoke, smog2 (1.4%)
↓-60.0%prior 5
Other (explain in narrative)1 (0.7%)

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

Lighting

Daylight93 (62.8%)
↓-5.1%prior 98
Dark - roadway not lighted34 (23.0%)
↓-15.0%prior 40
Dark - roadway lighted10 (6.8%)
↑25.0%prior 8
Dawn7 (4.7%)
Dusk2 (1.4%)
Dark - unknown roadway lighting2 (1.4%)

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

Road Surface

Dry109 (75.7%)
↑5.8%prior 103
Gravel12 (8.3%)
↓-47.8%prior 23
Snow10 (6.9%)
→0.0%prior 10
Wet6 (4.2%)
→0.0%prior 6
Ice/frost3 (2.1%)
↓-62.5%prior 8
Mud, dirt3 (2.1%)
Slush1 (0.7%)

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

Vehicles & Demographics

The most common vehicle makes involved in crashes remained consistent between 2022 and 2023, with Chevrolet and Ford vehicles accounting for the highest counts in both periods. An analysis of persons involved in crashes shows a notable decrease in the 16-20 age group, which dropped from 63 individuals in 2022 to 47 in 2023. In contrast, the number of individuals aged 65 and older involved in crashes increased from 53 to 59.

Top Vehicle Makes (277 vehicles)

1
CHEV51 (18.4%)
↑2.0%prior 50
2
FORD48 (17.3%)
↓-4.0%prior 50
3
CHEVROLET13 (4.7%)
↓-23.5%prior 17
4
TOYT11 (4%)
↑37.5%prior 8
5
DODG11 (4%)
↓-35.3%prior 17
6
GMC11 (4%)
7
RAM9 (3.2%)
→0.0%prior 9
8
JEEP9 (3.2%)
↓-30.8%prior 13
9
NISS9 (3.2%)
↑50.0%prior 6
10
KIA8 (2.9%)
↑33.3%prior 6

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

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

Sex Distribution (255 persons with recorded sex)

Male137 (53.7%)
↓-19.9%prior 171
Female118 (46.3%)
↑12.4%prior 105

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: 198
  • Total persons involved: 418
  • Total vehicles involved: 277

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

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