Yearly Traffic Safety Analysis

202 CRASHES IN
IOWA, IA
2023

All metrics benchmarked against2022

In 2023, Jefferson County recorded 202 total crashes, a 2.4% decrease from the 207 crashes reported in 2022. Despite the overall drop in collisions, the number of people injured rose from 67 to 79, an increase of 17.9% year-over-year. Fatalities decreased from 2 in the prior period to 1 in the current period.

202

▼ -2.4%was 207

Total Crash Events

1

▼ -50.0%was 2

Persons Killed

79

▲ 17.9%was 67

Persons Injured

1

▼ -50.0%was 2

Fatal Crash Events

Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) 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 Jefferson County saw a minor decrease of 2.4%, from 207 incidents in 2022 to 202 in 2023. While total crashes and fatalities (down from 2 to 1) declined, the number of reported injuries increased by 17.9% year-over-year, from 67 to 79.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

0

Cyclists Killed

Prior: 0→0.0%

1

Motorists Killed

Prior: 2↓-50.0%

1

Pedestrians Injured

Prior: 1→0.0%

2

Cyclists Injured

Prior: 1↑100.0%

76

Motorists Injured

Prior: 65↑16.9%

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 peak day for crashes shifted slightly; while Friday was the top day in 2022 with 44 crashes, in 2023 both Thursday and Friday were the peak days with 37 crashes each. A more significant change occurred in the peak hour, which moved from the 5 p.m. evening commute in 2022 (27 crashes) to the 11 a.m. hour in 2023 (15 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

The number of fatal crashes in Jefferson County decreased from 2 in 2022 to 1 in 2023, with total fatalities also dropping from 2 to 1. However, the proportion of crashes resulting in an injury increased from 28.5% to 35.1% year-over-year. This was driven by a rise in minor injury crashes, which increased from 14 to 27, while serious injury crashes fell from 10 to 7.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.5%
↓-50.0%prior 2
Serious Injury7serious injury crashes3.5%
↓-30.0%prior 10
Minor Injury27minor injury crashes13.4%
↑92.9%prior 14
Possible Injury37possible injury crashes18.3%
↑5.7%prior 35
No Injury130no injury crashes64.4%
↓-11.0%prior 146

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, though the count decreased from 73 in 2022 to 62 in 2023. 'Lost Control' also saw a notable drop in count, falling from 22 crashes to 15. The top three primary factors were consistent across both years, with 'Animal', 'Lost Control', and 'Followed too close' leading the list in both periods, although all saw their counts decline.

Officer-Reported Primary Contributing Cause

Animal62 (30.7%)↓-15.1%prior 73
Lost Control15 (7.4%)↓-31.8%prior 22
Followed too close12 (5.9%)↓-14.3%prior 14
FTYROW: From stop sign10 (5%)↑11.1%prior 9
Ran off road - straight10 (5%)↑11.1%prior 9
Other (explain in narrative): Other9 (4.5%)↑12.5%prior 8
Ran Stop Sign9 (4.5%)↑12.5%prior 8
FTYROW: Making left turn8 (4%)↑60.0%prior 5
Operating vehicle in an reckless, erratic, careless, negligent manner6 (3%)
Ran off road - left6 (3%)

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

Road & Environmental Conditions

Crash conditions remained broadly similar year-over-year, with most incidents in both periods occurring in clear weather on dry roads. In 2023, 112 crashes happened in clear weather, compared to 107 in 2022. There was a notable increase in crashes occurring in dark, unlit roadway conditions, which rose from 25 incidents in 2022 to 35 in 2023.

Weather

Clear112 (74.7%)
↑4.7%prior 107
Cloudy21 (14.0%)
↑40.0%prior 15
Snow6 (4.0%)
↓-14.3%prior 7
Rain4 (2.7%)
Fog, smoke, smog2 (1.3%)
Freezing rain/drizzle2 (1.3%)
Other (explain in narrative)1 (0.7%)
Severe Winds1 (0.7%)
Blowing Snow1 (0.7%)

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

Lighting

Daylight101 (65.2%)
↑8.6%prior 93
Dark - roadway not lighted35 (22.6%)
↑40.0%prior 25
Dark - roadway lighted8 (5.2%)
↓-46.7%prior 15
Dusk5 (3.2%)
→0.0%prior 5
Dawn3 (1.9%)
Dark - unknown roadway lighting3 (1.9%)

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

Road Surface

Dry119 (77.3%)
↑5.3%prior 113
Wet12 (7.8%)
↑71.4%prior 7
Gravel9 (5.8%)
Ice/frost8 (5.2%)
↑14.3%prior 7
Slush2 (1.3%)
Snow2 (1.3%)
↓-80.0%prior 10
Mud, dirt1 (0.6%)
Other (explain in narrative)1 (0.6%)

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

Vehicles & Demographics

The top vehicle makes involved in crashes shifted, with Chevrolet taking the top spot from Ford. The number of crashes involving Chevrolets increased from 35 to 48, while those involving Fords decreased from 51 to 40. The age demographics of persons involved in collisions also changed; the 26-34 age group was the largest in 2023 with 80 individuals, up from 71 in 2022. Conversely, the 35-44 age group saw its involvement decrease from 80 individuals in 2022 to 43 in 2023.

Top Vehicle Makes (286 vehicles)

1
CHEV48 (16.8%)
↑37.1%prior 35
2
FORD40 (14%)
↓-21.6%prior 51
3
TOYT17 (5.9%)
↓-19.0%prior 21
4
TOYO13 (4.5%)
↑8.3%prior 12
5
GMC11 (3.8%)
↓-15.4%prior 13
6
HOND11 (3.8%)
↓-15.4%prior 13
7
DODG11 (3.8%)
↓-35.3%prior 17
8
CHEVROLET10 (3.5%)
↓-9.1%prior 11
9
JEEP9 (3.1%)
↑80.0%prior 5
10
KIA8 (2.8%)
↓-11.1%prior 9

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

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

Sex Distribution (274 persons with recorded sex)

Male159 (58.0%)
↓-0.6%prior 160
Female115 (42.0%)
↓-8.7%prior 126

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: 202
  • Total persons involved: 427
  • Total vehicles involved: 286

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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