Yearly Traffic Safety Analysis

258 CRASHES IN
IOWA, IA
2023

All metrics benchmarked against2022

In Jackson County, total vehicle crashes increased from 214 in 2022 to 258 in 2023, representing a 20.6% year-over-year rise. While the number of fatalities decreased from 3 to 1, the number of persons injured saw a significant increase of 50.9%, climbing from 57 to 86. The most notable shift in crash causation was a 42.4% increase in the count of collisions involving animals, which rose from 59 to 84 incidents.

258

▲ 20.6%was 214

Total Crash Events

1

▼ -66.7%was 3

Persons Killed

86

▲ 50.9%was 57

Persons Injured

1

▼ -66.7%was 3

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

Crash data for Jackson County indicates a rising trend in traffic incidents year-over-year. Total crashes increased by 20.6%, from 214 in 2022 to 258 in 2023. This was accompanied by a 50.9% increase in persons injured, though total fatalities declined from 3 to 1.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

0

Cyclists Killed

Prior: 0→0.0%

1

Motorists Killed

Prior: 3↓-66.7%

1

Pedestrians Injured

Prior: 0→%

1

Cyclists Injured

Prior: 0→%

84

Motorists Injured

Prior: 57↑47.4%

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

Temporal crash patterns showed some shifts between the two periods. The peak day for crashes moved from Friday (43 crashes) in 2022 to Thursday (44 crashes) in 2023. The peak hour for collisions shifted earlier, from 7 p.m. in 2022 (16 crashes) to a more pronounced spike at 5 p.m. in 2023 (29 crashes), which more than doubled the 14 crashes recorded during that same hour in the prior year.

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 the number of fatal crashes decreased from 3 in 2022 to 1 in 2023, the severity of non-fatal crashes shifted. The count of serious injury crashes remained stable with 9 incidents in 2023 compared to 8 in 2022. However, minor injury crashes more than doubled, increasing from 13 in 2022 to 32 in 2023, and their share of all crashes grew from 6.1% to 12.4%.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.4%
↓-66.7%prior 3
Serious Injury9serious injury crashes3.5%
↑12.5%prior 8
Minor Injury32minor injury crashes12.4%
↑146.2%prior 13
Possible Injury27possible injury crashes10.5%
↑8.0%prior 25
No Injury189no injury crashes73.3%
↑14.5%prior 165

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 with animals remained the top contributing factor in both periods, with the count of these incidents increasing by 42.4% from 59 in 2022 to 84 in 2023. 'Lost Control' also saw a significant 43.5% increase in count, rising from 23 to 33 crashes. Conversely, crashes attributed to 'FTYROW: From stop sign' decreased in count by 43.8%, from 16 incidents in 2022 to 9 in 2023.

Officer-Reported Primary Contributing Cause

Animal84 (32.6%)↑42.4%prior 59
Lost Control33 (12.8%)↑43.5%prior 23
Ran off road - straight19 (7.4%)↑11.8%prior 17
Driver Distraction: Other interior distraction13 (5%)↑116.7%prior 6
Driving too fast for conditions12 (4.7%)↑71.4%prior 7
Other (explain in narrative): Other12 (4.7%)↓-7.7%prior 13
FTYROW: From stop sign9 (3.5%)↓-43.8%prior 16
Ran Stop Sign8 (3.1%)↑33.3%prior 6
Followed too close8 (3.1%)↑33.3%prior 6
FTYROW: Making left turn7 (2.7%)

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 year-over-year increase in crashes occurred primarily under favorable conditions. Crashes on dry roads rose from 119 to 147, and those in daylight increased from 99 to 116. The proportion of crashes under these conditions remained largely consistent, with dry roads accounting for 55.6% of crashes in 2022 and 57.0% in 2023. There were no significant shifts in the proportion of crashes occurring during adverse weather or on hazardous road surfaces.

Weather

Clear130 (68.1%)
↑18.2%prior 110
Cloudy37 (19.4%)
↑32.1%prior 28
Snow9 (4.7%)
↑28.6%prior 7
Rain6 (3.1%)
↓-25.0%prior 8
Freezing rain/drizzle4 (2.1%)
Fog, smoke, smog2 (1.0%)
Other (explain in narrative)1 (0.5%)
Severe Winds1 (0.5%)
Blowing Snow1 (0.5%)

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

Lighting

Daylight116 (60.7%)
↑17.2%prior 99
Dark - roadway not lighted42 (22.0%)
↑20.0%prior 35
Dark - roadway lighted15 (7.9%)
↓-6.3%prior 16
Dawn10 (5.2%)
↑66.7%prior 6
Dusk5 (2.6%)
↓-16.7%prior 6
Dark - unknown roadway lighting3 (1.6%)

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

Road Surface

Dry147 (77.0%)
↑23.5%prior 119
Wet17 (8.9%)
↑21.4%prior 14
Ice/frost10 (5.2%)
↑11.1%prior 9
Snow8 (4.2%)
↓-27.3%prior 11
Gravel6 (3.1%)
↓-40.0%prior 10
Slush2 (1.0%)
Other (explain in narrative)1 (0.5%)

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

Vehicles & Demographics

Comparing vehicle involvement, crashes involving Ford vehicles decreased from 66 to 54, while those involving Chevrolet vehicles increased from 69 to 86. Analysis of persons involved shows a notable increase in the 16-20 age group, which grew from 47 individuals in 2022 to 77 in 2023. The 65+ age group also saw increased involvement, rising from 64 to 86 persons.

Top Vehicle Makes (348 vehicles)

1
CHEV57 (16.4%)
↑5.6%prior 54
2
FORD54 (15.5%)
↓-18.2%prior 66
3
CHEVROLET29 (8.3%)
↑93.3%prior 15
4
GMC20 (5.7%)
↑11.1%prior 18
5
JEEP17 (4.9%)
↑30.8%prior 13
6
TOYT16 (4.6%)
↑77.8%prior 9
7
DODG14 (4%)
↓-17.6%prior 17
8
NISS13 (3.7%)
↑116.7%prior 6
9
BUIC12 (3.4%)
↑33.3%prior 9
10
HOND8 (2.3%)
↑14.3%prior 7

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

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

Sex Distribution (323 persons with recorded sex)

Male196 (60.7%)
↑25.6%prior 156
Female127 (39.3%)
↑2.4%prior 124

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: 258
  • Total persons involved: 517
  • Total vehicles involved: 348

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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