Yearly Traffic Safety Analysis

58 CRASHES IN
IOWA, IA
2021

All metrics benchmarked against2020

In 2021, Van Buren County recorded 58 total crashes, the same number as in 2020. Despite the stable crash volume, the number of reported injuries increased by 36% from 25 to 34. The most significant change was a 400% increase in crashes resulting in serious injuries, which rose from 1 in 2020 to 5 in 2021.

58

Total Crash Events

0

Persons Killed

34

36.0%was 25

Persons Injured

0

Fatal Crash Events

Note: "Persons Killed" (0) counts individual fatalities across all crash events. "Fatal" in the severity table below (0) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall number of crashes in Van Buren County remained stable year-over-year, with 58 incidents reported in both 2021 and 2020. However, the total number of injuries resulting from these crashes rose by 36%, increasing from 25 in 2020 to 34 in 2021. Fatalities remained at zero for both periods.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

34

Motorists Injured

Prior: 2536.0%

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · 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 years. While Tuesday remained the peak day for crashes in both 2021 (12 crashes) and 2020 (11 crashes), the peak hour shifted earlier from 5 p.m. in 2020 (7 crashes) to 3 p.m. in 2021 (9 crashes). In 2021, Monday and Tuesday were the busiest days, whereas in 2020, crashes were more distributed across Tuesday, Thursday, and Friday.

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Although the total number of crashes was unchanged, the severity of those crashes increased in 2021. There were no fatal crashes in either period. However, the number of crashes resulting in serious injuries increased from 1 in 2020 to 5 in 2021. The count of minor injury crashes also rose from 12 to 16, while the proportion of crashes with no injuries decreased from 63.8% in 2020 to 55.2% in 2021.

Outcome by Severity (Crash Events)

Serious Injury5serious injury crashes8.6%
400.0%prior 1
Minor Injury16minor injury crashes27.6%
33.3%prior 12
Possible Injury5possible injury crashes8.6%
-37.5%prior 8
No Injury32no injury crashes55.2%
-13.5%prior 37

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Most severe injury per crash record

Top Contributing Factors

The ranking of top contributing factors shifted between 2020 and 2021. In 2021, "Lost Control" was the leading factor with 13 incidents, a slight increase from 12 in the prior year. Crashes involving an "Animal," which was the top factor in 2020 with 16 incidents, saw a 50% decrease in count to 8 incidents in 2021. Conversely, crashes attributed to "Failure to Yield Right of Way from a stop sign" increased from 1 incident in 2020 to 6 in 2021.

Officer-Reported Primary Contributing Cause

Lost Control13 (22.4%)8.3%prior 12
Animal8 (13.8%)-50.0%prior 16
FTYROW: From stop sign6 (10.3%)
Ran off road - straight5 (8.6%)-28.6%prior 7
Ran Stop Sign4 (6.9%)
FTYROW: From parked position3 (5.2%)
Ran off road - left3 (5.2%)
Driver Distraction: Other interior distraction2 (3.4%)
Other (explain in narrative): Other2 (3.4%)-60.0%prior 5
Improper Backing1 (1.7%)

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The majority of crashes in both periods occurred in clear weather and daylight on dry roads. In 2021, there was a notable increase in crashes on dry road surfaces, rising from 33 to 46 incidents. Correspondingly, crashes on adverse road surfaces like wet or snow-covered roads decreased from a combined 15 incidents in 2020 to just 3 in 2021. Crashes occurring during snowy weather conditions, which accounted for 5 incidents in 2020, were not reported in 2021.

Weather

Clear40 (75.5%)
25.0%prior 32
Cloudy12 (22.6%)
100.0%prior 6
Fog, smoke, smog1 (1.9%)

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Weather condition at time of crash

Lighting

Daylight35 (66.0%)
2.9%prior 34
Dark - roadway not lighted12 (22.6%)
9.1%prior 11
Dusk4 (7.5%)
Dark - unknown roadway lighting1 (1.9%)
Dawn1 (1.9%)

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Lighting condition field

Road Surface

Dry46 (86.8%)
39.4%prior 33
Gravel3 (5.7%)
Wet3 (5.7%)
-66.7%prior 9
Ice/frost1 (1.9%)

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Road surface condition field

Vehicles & Demographics

Ford and Chevrolet vehicles were the most frequently involved in crashes in both periods. In 2021, Chevrolet (21 vehicles, combining 'CHEV' and 'CHEVROLET' entries) surpassed Ford (12 vehicles) as the most common make, a reversal from 2020 when Ford led with 18 vehicles to Chevrolet's 17. Regarding driver and passenger demographics, the 35-44 age group saw a notable increase in involvement, from 12 individuals in 2020 to 21 in 2021. Meanwhile, the 65+ age group's involvement decreased from 22 to 18 persons.

Top Vehicle Makes (84 vehicles)

1
CHEV12 (14.3%)
50.0%prior 8
2
FORD12 (14.3%)
-33.3%prior 18
3
CHEVROLET9 (10.7%)
0.0%prior 9
4
GMC7 (8.3%)
5
DODGE5 (6%)
6
DODG4 (4.8%)
7
BUICK3 (3.6%)
8
HOND3 (3.6%)
9
TOYOTA3 (3.6%)
10
YAM2 (2.4%)

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Vehicle unit records

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

Sex Distribution (71 persons with recorded sex)

Male45 (63.4%)
-8.2%prior 49
Female26 (36.6%)
13.0%prior 23

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · 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: 2021-01-01 through 2021-12-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2021-01-01 through 2021-12-31 (365 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 58
  • Total persons involved: 115
  • Total vehicles involved: 84

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: 2021." Published September 9, 2026. Reporting period: 2021-01-01 to 2021-12-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/2021-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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