Yearly Traffic Safety Analysis

213 CRASHES IN
IOWA, IA
2023

All metrics benchmarked against2022

In Grundy County, total crashes increased by 10.9% from 192 in 2022 to 213 in 2023. The most significant year-over-year change was the increase in fatalities, which rose from zero in the prior period to four in the current period. Overall injuries also increased by 50%, from 60 to 90.

213

▲ 10.9%was 192

Total Crash Events

4

Persons Killed

90

▲ 50.0%was 60

Persons Injured

1

Fatal Crash Events

Note: "Persons Killed" (4) 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 trends in Grundy County showed an increase year-over-year. Total crashes rose by 10.9%, from 192 in 2022 to 213 in 2023. This was accompanied by a 50% increase in total injuries, from 60 to 90, and a rise in fatalities from zero to four.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

0

Cyclists Killed

Prior: 0→0.0%

4

Motorists Killed

Prior: 0→%

1

Pedestrians Injured

Prior: 0→%

1

Cyclists Injured

Prior: 0→%

88

Motorists Injured

Prior: 60↑46.7%

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 temporal patterns of crashes showed some shifts between the two periods. While Thursday remained the peak day for crashes in both 2022 (37 crashes) and 2023 (39 crashes), the peak hour shifted from 3 PM in the prior year to 5 PM in the current year. Notably, Saturday crashes saw a significant increase, rising from 20 in 2022 to 36 in 2023.

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 worsened in 2023, primarily driven by the occurrence of one fatal crash which resulted in four fatalities, compared to zero fatal crashes in 2022. While the number of crashes classified as 'Serious Injury' decreased from 8 to 6, the counts for 'Minor Injury' (23 to 31) and 'Possible Injury' (18 to 30) both increased. Consequently, the proportion of crashes resulting in no injury decreased from 74.5% in 2022 to 68.1% in 2023.

Severity is per crash event (most severe injury). 1 fatal crash events resulted in 4 persons killed.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.5%
Serious Injury6serious injury crashes2.8%
↓-25.0%prior 8
Minor Injury31minor injury crashes14.6%
↑34.8%prior 23
Possible Injury30possible injury crashes14.1%
↑66.7%prior 18
No Injury145no injury crashes68.1%
↑1.4%prior 143

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 such incidents rising by 24.6% from 69 crashes in 2022 to 86 in 2023. 'Lost Control' and 'Ran off road - left' also remained high-ranking factors, with counts of 19 and 17 respectively in 2023, similar to the prior year. Notably, crashes attributed to 'Operating vehicle in a reckless, erratic, careless, negligent manner' and 'Driver Distraction: Other interior distraction' both tripled in count, from 2 to 6 incidents each.

Officer-Reported Primary Contributing Cause

Animal86 (40.4%)↑24.6%prior 69
Lost Control19 (8.9%)↑11.8%prior 17
Ran off road - left17 (8%)→0.0%prior 17
Driving too fast for conditions9 (4.2%)↓-10.0%prior 10
Other (explain in narrative): Other7 (3.3%)↓-12.5%prior 8
Ran Stop Sign6 (2.8%)↑20.0%prior 5
Driver Distraction: Other interior distraction6 (2.8%)
Operating vehicle in an reckless, erratic, careless, negligent manner6 (2.8%)
Driver Distraction: Inattentive/lost in thought5 (2.3%)
Driver Distraction: Exterior distraction4 (1.9%)

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 on dry roads remained relatively stable year-over-year. However, there was a notable shift in lighting conditions, with crashes in dark, lighted areas doubling from 7 in 2022 to 14 in 2023. Crashes associated with winter weather decreased, with incidents on snow-covered roads falling from 15 to 6 and crashes during snowfall dropping from 18 to 12.

Weather

Clear84 (63.6%)
↑15.1%prior 73
Cloudy21 (15.9%)
↓-22.2%prior 27
Snow12 (9.1%)
↓-33.3%prior 18
Rain7 (5.3%)
Fog, smoke, smog3 (2.3%)
Severe Winds3 (2.3%)
Freezing rain/drizzle2 (1.5%)

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

Lighting

Daylight84 (62.7%)
↓-5.6%prior 89
Dark - roadway not lighted32 (23.9%)
↑10.3%prior 29
Dark - roadway lighted14 (10.4%)
↑100.0%prior 7
Dawn2 (1.5%)
↓-60.0%prior 5
Dusk2 (1.5%)

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

Road Surface

Dry88 (66.2%)
↑4.8%prior 84
Ice/frost15 (11.3%)
↓-16.7%prior 18
Wet13 (9.8%)
↑44.4%prior 9
Gravel8 (6.0%)
↑60.0%prior 5
Snow6 (4.5%)
↓-60.0%prior 15
Slush3 (2.3%)

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

Vehicles & Demographics

Ford and Chevrolet vehicles were the most common makes involved in crashes during both periods. The number of Fords involved increased from 46 to 53, while the combined count for Chevrolet ('CHEV' and 'CHEVROLET') decreased from 70 to 58. Analysis of persons involved in crashes shows a notable increase in the 55-64 age group, which grew from 36 individuals in 2022 to 66 in 2023. The 26-34 age group also saw an increase in involvement, from 53 to 65 persons.

Top Vehicle Makes (276 vehicles)

1
FORD53 (19.2%)
↑15.2%prior 46
2
CHEV49 (17.8%)
↓-10.9%prior 55
3
JEEP15 (5.4%)
↑15.4%prior 13
4
TOYO13 (4.7%)
↑44.4%prior 9
5
CHEVROLET9 (3.3%)
↓-40.0%prior 15
6
BUIC9 (3.3%)
7
KIA9 (3.3%)
↑28.6%prior 7
8
CHRY8 (2.9%)
↑14.3%prior 7
9
DODG8 (2.9%)
↓-11.1%prior 9
10
NISS7 (2.5%)
↓-22.2%prior 9

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

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

Sex Distribution (260 persons with recorded sex)

Male154 (59.2%)
↑4.1%prior 148
Female106 (40.8%)
↑1.9%prior 104

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 10, 2026

Data Coverage

  • Reporting period: 2023-01-01 through 2023-12-31 (365 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 213
  • Total persons involved: 466
  • Total vehicles involved: 276

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 10, 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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