Yearly Traffic Safety Analysis

293 CRASHES IN
IOWA, IA
2021

All metrics benchmarked against2020

In 2021, Buena Vista County recorded 293 total crashes, representing a 31.4% increase from the 223 crashes documented in 2020. This rise in collisions was accompanied by an increase in injuries from 67 to 92. The most significant year-over-year change was the occurrence of 3 traffic fatalities in 2021, whereas none were recorded in the prior year.

293

▲ 31.4%was 223

Total Crash Events

3

Persons Killed

92

▲ 37.3%was 67

Persons Injured

2

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 · 2021-01-01 to 2021-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Traffic safety metrics in Buena Vista County indicated a worsening trend from 2020 to 2021. Total crashes increased by 31.4%, rising from 223 to 293 incidents. Concurrently, the number of people injured in these crashes grew by 37.3% from 67 to 92, and the county went from zero traffic fatalities in 2020 to three in 2021.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

0

Cyclists Killed

Prior: 0→0.0%

3

Motorists Killed

Prior: 0→%

1

Pedestrians Injured

Prior: 1→0.0%

4

Cyclists Injured

Prior: 2↑100.0%

87

Motorists Injured

Prior: 64↑35.9%

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 timing of crashes showed consistent patterns between the two periods. Friday remained the peak day for crashes, with counts increasing from 47 in 2020 to 57 in 2021. Similarly, the 3 p.m. hour was the most frequent time for a crash in both years, rising from 19 to 25 incidents. Crashes occurring on Mondays also saw a notable increase, from 36 in 2020 to 56 in 2021.

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

Crash severity increased notably in 2021, with the county recording 2 fatal crashes and 3 fatalities, compared to zero in 2020. While the absolute number of crashes involving any injury rose from 66 to 77, their share of all crashes decreased slightly from 29.7% to 26.3%. Crashes resulting in no injuries made up 73% of all incidents in 2021, a slight increase from 70.4% in 2020.

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%
Serious Injury6serious injury crashes2%
→0.0%prior 6
Minor Injury34minor injury crashes11.6%
↑13.3%prior 30
Possible Injury37possible injury crashes12.6%
↑23.3%prior 30
No Injury214no injury crashes73%
↑36.3%prior 157

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

Collisions with animals were the leading contributing factor in both years, with the count of such incidents increasing by 51.4% from 35 in 2020 to 53 in 2021. Crashes attributed to a driver running a stop sign grew from 12 to 19 incidents year-over-year. The most dramatic shift was in crashes due to following too closely, which increased by 350% from 4 incidents in 2020 to 18 in 2021, becoming the third-most-cited factor.

Officer-Reported Primary Contributing Cause

Animal53 (18.1%)↑51.4%prior 35
Ran Stop Sign19 (6.5%)↑58.3%prior 12
Followed too close18 (6.1%)
Other (explain in narrative): Other16 (5.5%)→0.0%prior 16
Operating vehicle in an reckless, erratic, careless, negligent manner14 (4.8%)↑180.0%prior 5
Driver Distraction: Other interior distraction14 (4.8%)↓-6.7%prior 15
Lost Control14 (4.8%)↑27.3%prior 11
Improper Backing13 (4.4%)↑116.7%prior 6
Driving too fast for conditions13 (4.4%)↓-23.5%prior 17
FTYROW: From stop sign11 (3.8%)↓-31.3%prior 16

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

Road & Environmental Conditions

Most crashes in both 2021 and 2020 occurred under favorable conditions, with clear weather and daylight being the most common settings. Crashes on dry roads accounted for approximately 66% of the total in both years, showing no proportional change. However, incidents on roads with ice or frost increased in count from 15 in 2020 to 25 in 2021, representing a rise in share from 6.7% to 8.5% of all crashes.

Weather

Clear191 (74.3%)
↑21.7%prior 157
Cloudy42 (16.3%)
↑75.0%prior 24
Rain7 (2.7%)
Freezing rain/drizzle5 (1.9%)
Snow5 (1.9%)
↓-58.3%prior 12
Fog, smoke, smog4 (1.6%)
Blowing Snow2 (0.8%)
Other (explain in narrative)1 (0.4%)

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

Lighting

Daylight176 (67.4%)
↑25.7%prior 140
Dark - roadway not lighted42 (16.1%)
↓-4.5%prior 44
Dark - roadway lighted25 (9.6%)
↑66.7%prior 15
Dusk12 (4.6%)
Dawn5 (1.9%)
Dark - unknown roadway lighting1 (0.4%)

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

Road Surface

Dry193 (74.5%)
↑32.2%prior 146
Ice/frost25 (9.7%)
↑66.7%prior 15
Wet24 (9.3%)
↑33.3%prior 18
Gravel9 (3.5%)
↓-30.8%prior 13
Snow8 (3.1%)
↓-42.9%prior 14

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

Vehicles & Demographics

Top Vehicle Makes (481 vehicles)

1
FORD82 (17%)
↑20.6%prior 68
2
CHEV74 (15.4%)
↑57.4%prior 47
3
CHEVROLET24 (5%)
↑9.1%prior 22
4
GMC21 (4.4%)
↑75.0%prior 12
5
DODG21 (4.4%)
↓-4.5%prior 22
6
TOYOTA18 (3.7%)
↑157.1%prior 7
7
TOYT17 (3.5%)
↑30.8%prior 13
8
DODGE15 (3.1%)
↑36.4%prior 11
9
HOND14 (2.9%)
↑27.3%prior 11
10
KIA13 (2.7%)
↑44.4%prior 9

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

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

Sex Distribution (373 persons with recorded sex)

Male225 (60.3%)
↑20.3%prior 187
Female148 (39.7%)
↑15.6%prior 128

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: 293
  • Total persons involved: 593
  • Total vehicles involved: 481

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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