Yearly Traffic Safety Analysis

288 CRASHES IN
IOWA, IA
2023

All metrics benchmarked against2022

In 2023, Harrison County recorded 288 total crashes, a 9.5% increase from the 263 crashes documented in 2022. While the number of fatal crashes remained unchanged, the most notable year-over-year shift was a significant rise in the severity of non-fatal incidents. Total injuries increased by 30.6% from 72 to 94, and crashes resulting in serious injuries more than doubled from 5 to 11.

288

▲ 9.5%was 263

Total Crash Events

▲ 40.0%was 5

Persons Killed

▲ 30.6%was 72

Persons Injured

Fatal Crash Events

Note: "Persons Killed" (7) 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

Crash data for Harrison County indicates an upward trend in both frequency and severity in 2023 compared to the prior year. Total crashes increased by 9.5%, rising from 263 to 288 incidents. This was accompanied by a more pronounced increase in negative outcomes, as total injuries rose by 30.6% and the number of fatalities grew from 5 to 7.

Vulnerable Road User Casualties

Motorists Killed

Prior: 5↑40.0%

Motorists Injured

Prior: 72↑30.6%

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 shifted between the two periods. The most frequent day for crashes changed from Monday in 2022, with 42 incidents, to Saturday in 2023, with 54 incidents. While the peak hour for collisions remained 6 p.m. in both years, the number of crashes during that hour increased from 18 to 24. The highest volume month for crashes also shifted from June in 2022 to a tie between August and November 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

While the number of fatal crashes was stable at 4 for both 2023 and 2022, the overall severity of crashes worsened. The count of serious injury crashes more than doubled from 5 to 11, and minor injury crashes increased from 25 to 33. Consequently, the proportion of crashes resulting in no injuries decreased, accounting for 70.8% of all incidents in 2023 compared to 73.4% in 2022.

Severity is per crash event (most severe injury). 4 fatal crash events resulted in 7 persons killed.

Outcome by Severity (Crash Events)

Fatal4fatal crashes1.4%

→0.0%prior 4

Serious Injury11serious injury crashes3.8%

↑120.0%prior 5

Minor Injury33minor injury crashes11.5%

↑32.0%prior 25

Possible Injury36possible injury crashes12.5%

→0.0%prior 36

No Injury204no injury crashes70.8%

↑5.7%prior 193

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

The top contributing factor remained consistent, with 'Animal' cited in 53 crashes in 2023 versus 52 in 2022. However, the count of crashes attributed to other leading causes increased notably. Incidents involving 'Lost Control' rose by 36.4%, from 33 to 45 crashes. Crashes due to 'Followed too close' increased from 13 to 20, and incidents where a driver failed to yield from a stop sign nearly doubled from 8 to 15.

Officer-Reported Primary Contributing Cause

Animal53 (18.4%)↑1.9%prior 52

Lost Control45 (15.6%)↑36.4%prior 33

Ran off road - straight27 (9.4%)↑17.4%prior 23

Ran off road - left24 (8.3%)↑33.3%prior 18

Followed too close20 (6.9%)↑53.8%prior 13

Driving too fast for conditions18 (6.3%)↑20.0%prior 15

FTYROW: From stop sign15 (5.2%)↑87.5%prior 8

Driver Distraction: Other interior distraction8 (2.8%)

Failed to keep in proper lane7 (2.4%)

Ran Stop Sign7 (2.4%)

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 were largely consistent year-over-year, with the majority of incidents in both 2023 and 2022 occurring in 'Clear' weather and on 'Dry' road surfaces. Most crashes in both periods also happened during 'Daylight' hours. A notable shift was observed in lighting conditions, as crashes on dark, unlighted roadways decreased from 55 incidents in 2022 to 39 in 2023.

Weather

Clear175 (73.2%)

↑8.0%prior 162

Cloudy31 (13.0%)

↑10.7%prior 28

Snow15 (6.3%)

↑7.1%prior 14

Rain9 (3.8%)

↑28.6%prior 7

Freezing rain/drizzle5 (2.1%)

Fog, smoke, smog1 (0.4%)

Severe Winds1 (0.4%)

Sleet, hail1 (0.4%)

Blowing Snow1 (0.4%)

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

Lighting

Daylight176 (73.3%)

↑22.2%prior 144

Dark - roadway not lighted39 (16.3%)

↓-29.1%prior 55

Dark - roadway lighted16 (6.7%)

↑60.0%prior 10

Dawn5 (2.1%)

↓-50.0%prior 10

Dusk2 (0.8%)

Dark - unknown roadway lighting2 (0.8%)

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

Road Surface

Dry178 (74.2%)

↑3.5%prior 172

Ice/frost19 (7.9%)

↑18.8%prior 16

Wet16 (6.7%)

↑23.1%prior 13

Snow13 (5.4%)

↑8.3%prior 12

Gravel8 (3.3%)

↑60.0%prior 5

Slush4 (1.7%)

Mud, dirt2 (0.8%)

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

Vehicles & Demographics

Chevrolet and Ford were the two most common vehicle makes involved in crashes in both periods. The representation of persons involved in crashes showed significant changes across specific age groups. The number of individuals aged 16-20 involved in crashes grew from 49 in 2022 to 72 in 2023. Similarly, the 35-44 age group saw its involvement increase from 70 individuals to 106 over the same period.

Top Vehicle Makes (392 vehicles)

FORD67 (17.1%)

↑19.6%prior 56

CHEV48 (12.2%)

↓-11.1%prior 54

CHEVROLET24 (6.1%)

↓-14.3%prior 28

DODG17 (4.3%)

↑112.5%prior 8

TOYT14 (3.6%)

↑180.0%prior 5

NISS12 (3.1%)

↑9.1%prior 11

KIA11 (2.8%)

↑120.0%prior 5

JEEP11 (2.8%)

↓-35.3%prior 17

TOYOTA11 (2.8%)

↑37.5%prior 8

GMC11 (2.8%)

↑83.3%prior 6

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

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

Sex Distribution (372 persons with recorded sex)

Male253 (68.0%)

↑13.5%prior 223

Female119 (32.0%)

↑4.4%prior 114

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: 288
Total persons involved: 569
Total vehicles involved: 392

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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288 CRASHES INIOWA, IA2023