Yearly Traffic Safety Analysis

297 CRASHES IN
IOWA, IA
2023

All metrics benchmarked against2022

In 2023, Buena Vista County recorded 297 total crashes, a 6% decrease from the 316 crashes reported in 2022. Despite this overall reduction in collisions, the number of fatalities increased from one in the prior year to three in the current year. This rise in fatalities, alongside a drop in total crashes, represents the most significant year-over-year shift in the data.

297

▼ -6.0%was 316

Total Crash Events

3

▲ 200.0%was 1

Persons Killed

96

▼ -5.9%was 102

Persons Injured

2

▲ 100.0%was 1

Fatal Crash Events

Note: "Persons Killed" (3) 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

Overall, traffic crashes in Buena Vista County showed a downward trend, decreasing by 6% from 316 in 2022 to 297 in 2023. However, this trend did not extend to crash severity, as total fatalities increased from one to three. The total number of injuries saw a slight decrease from 102 to 96.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

0

Cyclists Killed

Prior: 0→0.0%

3

Motorists Killed

Prior: 1↑200.0%

3

Pedestrians Injured

Prior: 2↑50.0%

2

Cyclists Injured

Prior: 2→0.0%

91

Motorists Injured

Prior: 98↓-7.1%

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. The peak day for crashes moved from Friday (56 crashes) in 2022 to Tuesday (51 crashes) in 2023. While the 5 PM hour remained a peak time for collisions in both years, 2023 saw an additional peak emerge at the 3 PM hour, which recorded 28 crashes, matching the 5 PM total.

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

The severity of crashes increased in 2023, with fatal crashes rising from one to two and total fatalities increasing from one to three. Consequently, the fatal crash rate more than doubled, from 0.3% to 0.7% of all crashes. In contrast, the count of serious injury crashes fell sharply from six in 2022 to one in 2023. The overall proportion of crashes involving any level of injury remained stable at approximately 27% for both years.

Severity is per crash event (most severe injury). 2 fatal crash events resulted in 3 persons killed.

Outcome by Severity (Crash Events)

Fatal2fatal crashes0.7%
↑100.0%prior 1
Serious Injury1serious injury crashes0.3%
↓-83.3%prior 6
Minor Injury42minor injury crashes14.1%
↑5.0%prior 40
Possible Injury38possible injury crashes12.8%
↓-7.3%prior 41
No Injury214no injury crashes72.1%
↓-6.1%prior 228

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, though the count decreased slightly from 53 in 2022 to 49 in 2023. The number of crashes attributed to 'Followed too close' increased from 14 to 20, and incidents of 'Ran Stop Sign' rose from 8 to 13. Conversely, crashes due to 'Lost Control' fell from a count of 21 to 15, and incidents where drivers failed to yield from a stop sign decreased from 19 to 12.

Officer-Reported Primary Contributing Cause

Animal49 (16.5%)↓-7.5%prior 53
Other (explain in narrative): Other22 (7.4%)↓-15.4%prior 26
Followed too close20 (6.7%)↑42.9%prior 14
Driver Distraction: Other interior distraction17 (5.7%)↑54.5%prior 11
Lost Control15 (5.1%)↓-28.6%prior 21
Improper Backing14 (4.7%)↑27.3%prior 11
Made improper turn13 (4.4%)↓-18.8%prior 16
Ran Stop Sign13 (4.4%)↑62.5%prior 8
FTYROW: From stop sign12 (4%)↓-36.8%prior 19
Operating vehicle in an reckless, erratic, careless, negligent manner11 (3.7%)↑37.5%prior 8

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Environmental conditions during crashes were remarkably consistent year-over-year. In both 2023 and 2022, approximately 60% of crashes occurred in daylight and 69% on dry road surfaces. The proportion of crashes happening on adverse surfaces like wet, icy, or snowy roads was also stable at nearly 20%. This indicates no significant shift in the role environmental conditions played in crashes between the two periods.

Weather

Clear210 (77.5%)
↓-1.4%prior 213
Cloudy36 (13.3%)
↓-14.3%prior 42
Rain12 (4.4%)
↑71.4%prior 7
Snow6 (2.2%)
↓-50.0%prior 12
Freezing rain/drizzle3 (1.1%)
Sleet, hail2 (0.7%)
Fog, smoke, smog1 (0.4%)
Other (explain in narrative)1 (0.4%)

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

Lighting

Daylight175 (64.3%)
↓-8.4%prior 191
Dark - roadway not lighted51 (18.8%)
↓-8.9%prior 56
Dark - roadway lighted26 (9.6%)
↑4.0%prior 25
Dawn10 (3.7%)
Dusk8 (2.9%)
↓-27.3%prior 11
Dark - unknown roadway lighting2 (0.7%)

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

Road Surface

Dry206 (75.5%)
↓-5.5%prior 218
Wet32 (11.7%)
↑60.0%prior 20
Ice/frost14 (5.1%)
↓-33.3%prior 21
Snow12 (4.4%)
↓-40.0%prior 20
Gravel7 (2.6%)
↓-12.5%prior 8
Sand1 (0.4%)
Slush1 (0.4%)

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

Vehicles & Demographics

The top vehicle makes involved in crashes, primarily Chevrolet and Ford, remained consistent in rank and volume between 2022 and 2023. An analysis of persons involved reveals a demographic shift, with the number of individuals aged 16-20 decreasing from 96 to 72. Conversely, the number of individuals aged 65 and older involved in crashes increased from 55 in 2022 to 77 in 2023.

Top Vehicle Makes (471 vehicles)

1
CHEV87 (18.5%)
↓-1.1%prior 88
2
FORD73 (15.5%)
↓-8.8%prior 80
3
DODG29 (6.2%)
↑16.0%prior 25
4
CHEVROLET28 (5.9%)
↑12.0%prior 25
5
GMC28 (5.9%)
↑7.7%prior 26
6
JEEP25 (5.3%)
↑78.6%prior 14
7
TOYT20 (4.2%)
↑53.8%prior 13
8
NISS15 (3.2%)
↑36.4%prior 11
9
HOND14 (3%)
↓-12.5%prior 16
10
NR11 (2.3%)
↑22.2%prior 9

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

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

Sex Distribution (425 persons with recorded sex)

Male255 (60.0%)
↓-5.6%prior 270
Female170 (40.0%)
↓-9.6%prior 188

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: 297
  • Total persons involved: 634
  • Total vehicles involved: 471

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