Yearly Traffic Safety Analysis

226 CRASHES IN
IOWA, IA
2023

All metrics benchmarked against2022

In Washington County, the total number of traffic crashes remained unchanged year-over-year, with 226 incidents recorded in both 2023 and 2022. While the overall crash volume was stable, there was a decrease in crash severity and specific contributing factors. Notably, total fatalities decreased from 3 in 2022 to 2 in 2023, and crashes involving a driver under the influence fell from 13 to 8.

226

Total Crash Events

2

▼ -33.3%was 3

Persons Killed

79

▼ -1.3%was 80

Persons Injured

2

▼ -33.3%was 3

Fatal Crash Events

Note: "Persons Killed" (2) counts individual fatalities across all crash events. "Fatal" in the severity table below (2) 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

The overall crash trend in Washington County was stable between 2022 and 2023, with the total number of crashes holding steady at 226 for both years. Despite the consistent crash volume, the outcomes showed a slight improvement. Total injuries decreased marginally from 80 to 79, and fatalities fell from 3 to 2.

Vulnerable Road User Casualties

2

Motorists Killed

Prior: 3↓-33.3%

79

Motorists Injured

Prior: 78↑1.3%

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 in Washington County showed a notable shift in the peak time of day. While Friday remained the most frequent day for crashes in both 2023 (48 incidents) and 2022 (40 incidents), the peak hour for collisions moved from 5 p.m. in 2022 (26 crashes) to 1 p.m. in 2023 (21 crashes). This indicates a change from an evening commute peak to an early afternoon peak year-over-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

Crash severity in Washington County saw a decrease in fatal outcomes but a shift in injury types. The number of fatal crashes fell from 3 in 2022 to 2 in 2023, with the corresponding fatal crash rate dropping from 1.33 to 0.88 per 100 crashes. While the count of serious injury crashes increased slightly from 9 to 10, there was a significant rise in 'possible injury' crashes from 16 to 33. Consequently, the proportion of crashes resulting in no injuries decreased from 71.7% in 2022 to 65.5% in 2023.

Outcome by Severity (Crash Events)

Fatal2fatal crashes0.9%
↓-33.3%prior 3
Serious Injury10serious injury crashes4.4%
↑11.1%prior 9
Minor Injury33minor injury crashes14.6%
↓-8.3%prior 36
Possible Injury33possible injury crashes14.6%
↑106.3%prior 16
No Injury148no injury crashes65.5%
↓-8.6%prior 162

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 leading contributing factors for crashes shifted between 2022 and 2023. While collisions involving an 'Animal' remained the most common cause in both years, the count decreased from 26 to 22. A significant change was observed in 'Ran off road - straight' crashes, which increased from 5 incidents in 2022 to 18 in 2023, becoming the second-leading factor. Conversely, incidents of 'Ran Stop Sign' decreased from 23 to 15, and crashes attributed to 'Followed too close' dropped from 18 to 16.

Officer-Reported Primary Contributing Cause

Animal22 (9.7%)↓-15.4%prior 26
Ran off road - straight18 (8%)↑260.0%prior 5
Followed too close16 (7.1%)↓-11.1%prior 18
Lost Control16 (7.1%)↑23.1%prior 13
FTYROW: From stop sign16 (7.1%)↓-15.8%prior 19
Ran Stop Sign15 (6.6%)↓-34.8%prior 23
Ran off road - left13 (5.8%)↑62.5%prior 8
FTYROW: Making left turn12 (5.3%)↑140.0%prior 5
Driver Distraction: Other interior distraction12 (5.3%)↑33.3%prior 9
Driving too fast for conditions9 (4%)↓-30.8%prior 13

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 conditions under which crashes occurred remained broadly similar year-over-year. In both 2023 and 2022, the majority of incidents happened in clear weather (151 and 147 crashes, respectively) and during daylight hours (154 and 147 crashes). Crashes on dry road surfaces were the most common in both periods, accounting for 171 incidents in 2023 compared to 165 in 2022. The total number of crashes occurring on wet, snowy, or icy roads was nearly identical, with 37 in 2023 and 38 in 2022.

Weather

Clear151 (70.2%)
↑2.7%prior 147
Cloudy40 (18.6%)
↑8.1%prior 37
Rain7 (3.3%)
↑16.7%prior 6
Snow7 (3.3%)
↓-22.2%prior 9
Freezing rain/drizzle5 (2.3%)
→0.0%prior 5
Fog, smoke, smog4 (1.9%)
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

Daylight154 (71.3%)
↑4.8%prior 147
Dark - roadway not lighted34 (15.7%)
↑6.3%prior 32
Dark - roadway lighted15 (6.9%)
↓-25.0%prior 20
Dusk8 (3.7%)
→0.0%prior 8
Dawn4 (1.9%)
Dark - unknown roadway lighting1 (0.5%)

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

Road Surface

Dry171 (79.2%)
↑3.6%prior 165
Wet19 (8.8%)
↑46.2%prior 13
Ice/frost9 (4.2%)
↓-25.0%prior 12
Snow9 (4.2%)
↓-30.8%prior 13
Gravel6 (2.8%)
↑20.0%prior 5
Slush2 (0.9%)

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

Vehicles & Demographics

An analysis of vehicles and persons involved shows shifts in both make and age demographics. In 2023, Ford became the most frequently involved vehicle make with 73 vehicles, an increase from 56 in 2022, surpassing Chevrolet (which had 69 vehicles in 2022 and 61 in 2023). Regarding persons involved, there was a significant increase in the 21-25 age group, which grew from 41 individuals in 2022 to 66 in 2023. Meanwhile, involvement for the 65+ age group, the largest cohort in 2023, decreased slightly from 86 to 81 persons.

Top Vehicle Makes (362 vehicles)

1
FORD73 (20.2%)
↑30.4%prior 56
2
CHEV61 (16.9%)
↓-11.6%prior 69
3
DODG17 (4.7%)
↑41.7%prior 12
4
HOND16 (4.4%)
↑6.7%prior 15
5
BUIC14 (3.9%)
↓-6.7%prior 15
6
TOYT14 (3.9%)
→0.0%prior 14
7
NISS13 (3.6%)
↑62.5%prior 8
8
CHEVROLET12 (3.3%)
↓-50.0%prior 24
9
JEEP11 (3%)
→0.0%prior 11
10
GMC10 (2.8%)
↓-44.4%prior 18

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

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

Sex Distribution (332 persons with recorded sex)

Male188 (56.6%)
↓-7.4%prior 203
Female144 (43.4%)
↓-3.4%prior 149

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: 226
  • Total persons involved: 483
  • Total vehicles involved: 362

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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