Yearly Traffic Safety Analysis

278 CRASHES IN
IOWA, IA
2023

All metrics benchmarked against2022

In 2023, Poweshiek County recorded 278 total crashes, an 11% decrease from the 312 crashes reported in 2022. Despite the overall reduction in collisions, the number of fatalities more than doubled, increasing from 2 in the prior year to 5 in the current year. This resulted in a corresponding increase in fatal crashes from 2 to 4.

278

▼ -10.9%was 312

Total Crash Events

5

▲ 150.0%was 2

Persons Killed

101

▼ -11.4%was 114

Persons Injured

4

▲ 100.0%was 2

Fatal Crash Events

Note: "Persons Killed" (5) 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

Overall traffic collisions in Poweshiek County showed a downward trend year-over-year, with total crashes falling by 10.9% from 312 in 2022 to 278 in 2023. Similarly, the number of people injured decreased by 11.4% from 114 to 101. However, this was contrasted by a sharp rise in fatalities, which increased from 2 to 5 during the same period.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

5

Motorists Killed

Prior: 2↑150.0%

1

Pedestrians Injured

Prior: 2↓-50.0%

100

Motorists Injured

Prior: 110↓-9.1%

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. In 2023, the peak day for crashes was Friday with 48 incidents, and the peak hour was 1 p.m. with 24 incidents. This represents a change from 2022, when Monday was the peak day with 55 crashes and 11 a.m. was the peak hour with 28 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

While total crashes decreased, the severity of crashes increased year-over-year. The number of fatal crashes doubled from 2 in 2022 to 4 in 2023, and the fatal crash rate rose from 0.64 to 1.44 per 100 crashes. The count of serious injury crashes also increased from 10 to 12. Conversely, crashes resulting in minor or possible injuries saw a decrease in count, from 32 to 28 and 38 to 29, respectively.

Severity is per crash event (most severe injury). 4 fatal crash events resulted in 5 persons killed.

Outcome by Severity (Crash Events)

Fatal4fatal crashes1.4%
↑100.0%prior 2
Serious Injury12serious injury crashes4.3%
↑20.0%prior 10
Minor Injury28minor injury crashes10.1%
↓-12.5%prior 32
Possible Injury29possible injury crashes10.4%
↓-23.7%prior 38
No Injury205no injury crashes73.7%
↓-10.9%prior 230

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, with the count increasing from 62 in 2022 to 67 in 2023. However, several other leading factors saw significant decreases; crashes attributed to 'Lost Control' fell from 38 to 16, and those from 'Ran off road - straight' decreased from 30 to 17. Notably, incidents involving an inattentive or distracted driver increased from 3 to 10, while crashes due to 'Driving too fast for conditions' dropped from 20 to 7.

Officer-Reported Primary Contributing Cause

Animal67 (24.1%)↑8.1%prior 62
Ran off road - straight17 (6.1%)↓-43.3%prior 30
Lost Control16 (5.8%)↓-57.9%prior 38
Ran off road - left14 (5%)↓-22.2%prior 18
Other (explain in narrative): Other13 (4.7%)↑8.3%prior 12
FTYROW: From stop sign11 (4%)↑10.0%prior 10
Driver Distraction: Other interior distraction10 (3.6%)↑42.9%prior 7
Driver Distraction: Inattentive/lost in thought10 (3.6%)
Improper or erratic lane changing9 (3.2%)↑28.6%prior 7
Made improper turn8 (2.9%)↑33.3%prior 6

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 majority of crashes in both years occurred in clear weather and on dry roads. However, there was a notable year-over-year decrease in crashes happening under adverse winter conditions. Collisions on snowy or icy roads dropped from a combined 48 incidents in 2022 to just 11 in 2023. Similarly, crashes during snowfall decreased from 22 to 9.

Weather

Clear164 (75.2%)
↓-3.0%prior 169
Cloudy24 (11.0%)
↓-36.8%prior 38
Rain15 (6.9%)
↓-6.3%prior 16
Snow9 (4.1%)
↓-59.1%prior 22
Severe Winds3 (1.4%)
Fog, smoke, smog2 (0.9%)
Sleet, hail1 (0.5%)

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

Lighting

Daylight151 (68.3%)
↓-20.1%prior 189
Dark - roadway not lighted36 (16.3%)
↓-14.3%prior 42
Dark - roadway lighted14 (6.3%)
↓-12.5%prior 16
Dusk13 (5.9%)
Dawn5 (2.3%)
↓-16.7%prior 6
Dark - unknown roadway lighting2 (0.9%)

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

Road Surface

Dry176 (80.7%)
↑5.4%prior 167
Wet26 (11.9%)
↓-13.3%prior 30
Snow11 (5.0%)
↓-59.3%prior 27
Gravel5 (2.3%)
↓-44.4%prior 9

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

Vehicles & Demographics

The most common vehicle makes involved in crashes remained consistent, with Ford (72 vehicles) and Chevrolet (65 vehicles combined) leading in 2023, though counts for both were down from 94 and 90, respectively, in 2022. The age demographics of individuals involved in crashes showed notable shifts. The proportion of people in the 26-34 age group increased from 13.1% to 17.9% of all persons involved, and the 55-64 age group's share grew from 10.5% to 15.6%. Conversely, the 35-44 age group's representation decreased from 20.2% to 14.9%.

Top Vehicle Makes (414 vehicles)

1
FORD72 (17.4%)
↓-23.4%prior 94
2
CHEV46 (11.1%)
↓-30.3%prior 66
3
JEEP22 (5.3%)
↓-12.0%prior 25
4
CHEVROLET19 (4.6%)
↓-20.8%prior 24
5
TOYO17 (4.1%)
↑88.9%prior 9
6
GMC15 (3.6%)
→0.0%prior 15
7
FREIGHTLINER15 (3.6%)
↓-21.1%prior 19
8
HOND13 (3.1%)
↑44.4%prior 9
9
RAM12 (2.9%)
↓-7.7%prior 13
10
DODG11 (2.7%)
↓-8.3%prior 12

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

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

Sex Distribution (394 persons with recorded sex)

Male261 (66.2%)
↓-2.2%prior 267
Female133 (33.8%)
↓-13.6%prior 154

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: 278
  • Total persons involved: 597
  • Total vehicles involved: 414

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

ThatCarHitMe.com · An Injuria.ai Company