Yearly Traffic Safety Analysis

68 CRASHES IN
IOWA, IA
2021

All metrics benchmarked against2020

In Taylor County, total crashes increased from 59 in 2020 to 68 in 2021, a 15.3% rise. Despite the increase in collisions, the number of reported injuries fell by 50%, from 34 in the prior year to 17 in the current year. The number of fatalities remained unchanged at one in both periods.

68

▲ 15.3%was 59

Total Crash Events

1

Persons Killed

17

▼ -50.0%was 34

Persons Injured

1

Fatal Crash Events

Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) 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

Crash trends in Taylor County show an increase in total collisions, rising 15.3% from 59 in 2020 to 68 in 2021. However, the outcomes of these crashes became less severe, with total injuries decreasing by 50% from 34 to 17. The number of fatalities remained stable at one death in both years.

Vulnerable Road User Casualties

1

Motorists Killed

Prior: 1→0.0%

17

Motorists Injured

Prior: 34↓-50.0%

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 shifted between the two periods. The peak day for crashes moved from Wednesday (15 crashes) in 2020 to Thursday (18 crashes) in 2021. Similarly, the peak hour for collisions shifted from 7 p.m. in the prior year to 3 p.m. in the current year, though both peak hours saw 9 crashes each.

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

While the number of fatal crashes remained constant at one for both years, the fatal crash rate per 100 crashes decreased from 1.69 to 1.47. The proportion of crashes resulting in any injury dropped from 37.3% (22 crashes) in 2020 to 20.6% (14 crashes) in 2021. Correspondingly, no-injury crashes increased from comprising 61.0% of all incidents in 2020 to 77.9% in 2021.

Outcome by Severity (Crash Events)

Fatal1fatal crashes1.5%
→0.0%prior 1
Serious Injury5serious injury crashes7.4%
↓-28.6%prior 7
Minor Injury1minor injury crashes1.5%
↓-88.9%prior 9
Possible Injury8possible injury crashes11.8%
↑33.3%prior 6
No Injury53no injury crashes77.9%
↑47.2%prior 36

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 involving animals remained the top contributing factor in both periods, with the count increasing from 24 crashes in 2020 to 30 in 2021. 'Lost Control' was the second-most cited factor in both years, though its count decreased from 7 to 5. Notably, crashes attributed to 'Failure to Yield Right of Way from a stop sign' increased from 1 to 4, and incidents of 'Followed too close' doubled from 2 to 4.

Officer-Reported Primary Contributing Cause

Animal30 (44.1%)↑25.0%prior 24
Lost Control5 (7.4%)↓-28.6%prior 7
FTYROW: From stop sign4 (5.9%)
Followed too close4 (5.9%)
Made improper turn3 (4.4%)
Operating vehicle in an reckless, erratic, careless, negligent manner3 (4.4%)
Ran Stop Sign2 (2.9%)
Failed to keep in proper lane2 (2.9%)
Driving too fast for conditions2 (2.9%)
FTYROW: Making left turn1 (1.5%)

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

Road & Environmental Conditions

Crashes in daylight conditions accounted for a larger share of incidents for which lighting was recorded, rising from 61% in 2020 to 70% in 2021. Conversely, the share of crashes occurring in dark, unlighted conditions decreased from 34% to 18%. The proportion of crashes on non-dry road surfaces saw an increase from 29.3% to 35.0%.

Weather

Clear28 (70.0%)
↓-6.7%prior 30
Cloudy9 (22.5%)
Blowing sand, soil, dirt1 (2.5%)
Freezing rain/drizzle1 (2.5%)
Rain1 (2.5%)

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

Lighting

Daylight28 (70.0%)
↑12.0%prior 25
Dark - roadway not lighted7 (17.5%)
↓-50.0%prior 14
Dawn3 (7.5%)
Dark - roadway lighted1 (2.5%)
Dusk1 (2.5%)

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

Road Surface

Dry26 (65.0%)
↓-10.3%prior 29
Gravel4 (10.0%)
Snow3 (7.5%)
Wet3 (7.5%)
Slush1 (2.5%)
Other (explain in narrative)1 (2.5%)
Mud, dirt1 (2.5%)
Ice/frost1 (2.5%)

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

Vehicles & Demographics

Ford remained the most common vehicle make involved in crashes, with its count increasing from 20 to 22 vehicles. In contrast, the combined involvement of Chevrolet vehicles (CHEV and CHEVROLET) decreased from 21 to 15. Analysis of persons involved shows a notable shift in age distribution; the number of individuals aged 21-25 involved in crashes dropped from 22 to 7. Conversely, the 65+ age group saw an increase in involvement, from 14 individuals in 2020 to 20 in 2021.

Top Vehicle Makes (97 vehicles)

1
FORD22 (22.7%)
↑10.0%prior 20
2
CHEV10 (10.3%)
↓-23.1%prior 13
3
GMC5 (5.2%)
4
CHEVROLET5 (5.2%)
↓-37.5%prior 8
5
DODG4 (4.1%)
↓-33.3%prior 6
6
KIA4 (4.1%)
7
NISS3 (3.1%)
8
TOYT3 (3.1%)
9
JEEP3 (3.1%)
10
ISUZ2 (2.1%)

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

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

Sex Distribution (73 persons with recorded sex)

Male43 (58.9%)
↓-10.4%prior 48
Female30 (41.1%)
↓-3.2%prior 31

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: 68
  • Total persons involved: 126
  • Total vehicles involved: 97

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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