Yearly Traffic Safety Analysis

109 CRASHES IN
IOWA, IA
2021

All metrics benchmarked against2020

In 2021, Worth County recorded 109 total crashes, a 23.9% increase from the 88 crashes reported in 2020. The most significant year-over-year change was the emergence of 3 fatal crashes resulting in 3 fatalities, whereas no fatal crashes occurred in the prior year. The total number of injuries remained relatively stable, increasing from 18 to 19.

109

▲ 23.9%was 88

Total Crash Events

3

Persons Killed

19

▲ 5.6%was 18

Persons Injured

3

Fatal Crash Events

Note: "Persons Killed" (3) counts individual fatalities across all crash events. "Fatal" in the severity table below (3) 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 Worth County showed an upward trajectory from 2020 to 2021. The total number of crashes increased by 23.9%, rising from 88 to 109 incidents. While total injuries saw a slight increase from 18 to 19, the county experienced 3 fatalities in 2021 after recording none in the previous year.

Vulnerable Road User Casualties

3

Motorists Killed

Prior: 0→%

19

Motorists Injured

Prior: 18↑5.6%

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 in Worth County shifted between 2020 and 2021. The peak day for crashes moved from Tuesday (19 crashes) in 2020 to Wednesday (19 crashes) in 2021. A more pronounced change occurred in the peak hour, which shifted from the 6 p.m. hour in 2020 (10 crashes) to the 3 p.m. hour in 2021 (11 crashes).

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

In 2021, Worth County experienced a significant shift in crash severity with the occurrence of 3 fatal crashes, accounting for 2.8% of all incidents, compared to zero in 2020. The number of serious injury crashes and minor injury crashes held steady at 2 and 9 incidents, respectively, though their proportion of total crashes declined. Overall, the share of crashes resulting in any level of injury decreased slightly from 17.0% in 2020 to 15.6% in 2021.

Outcome by Severity (Crash Events)

Fatal3fatal crashes2.8%
Serious Injury2serious injury crashes1.8%
→0.0%prior 2
Minor Injury9minor injury crashes8.3%
→0.0%prior 9
Possible Injury6possible injury crashes5.5%
↑50.0%prior 4
No Injury89no injury crashes81.7%
↑21.9%prior 73

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 leading contributing factor in both periods, with the count increasing from 32 incidents in 2020 to 40 in 2021. The second most common factor shifted from 'Driving too fast for conditions' in 2020 (12 incidents) to 'Lost Control' in 2021 (12 incidents). Notably, crashes attributed to 'Driving too fast for conditions' decreased from 12 to 5, while incidents of 'Ran Stop Sign' increased from 1 to 5.

Officer-Reported Primary Contributing Cause

Animal40 (36.7%)↑25.0%prior 32
Lost Control12 (11%)↑50.0%prior 8
Ran off road - straight8 (7.3%)↑14.3%prior 7
Other (explain in narrative): Other6 (5.5%)
Driving too fast for conditions5 (4.6%)↓-58.3%prior 12
Ran Stop Sign5 (4.6%)
Swerving/Evasive Action3 (2.8%)
Driver Distraction: Other interior distraction3 (2.8%)
Passing: Other passing (explain in narrative)3 (2.8%)
Ran off road - left3 (2.8%)

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 proportion of crashes occurring in daylight increased significantly, from 48.5% of incidents with known lighting in 2020 to 68.3% in 2021. Correspondingly, the share of crashes on dry road surfaces rose from 58.8% to 69.5% over the same period. The percentage of crashes happening during adverse weather conditions like snow or rain remained relatively stable, accounting for 15.6% of crashes in 2021 compared to 17.6% in 2020.

Weather

Clear55 (67.1%)
↑22.2%prior 45
Cloudy10 (12.2%)
↑42.9%prior 7
Snow5 (6.1%)
Blowing Snow4 (4.9%)
Freezing rain/drizzle3 (3.7%)
Fog, smoke, smog3 (3.7%)
Rain2 (2.4%)

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

Lighting

Daylight56 (68.3%)
↑69.7%prior 33
Dark - roadway not lighted21 (25.6%)
↓-22.2%prior 27
Dark - roadway lighted3 (3.7%)
Dawn1 (1.2%)
Dusk1 (1.2%)

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

Road Surface

Dry57 (69.5%)
↑42.5%prior 40
Ice/frost12 (14.6%)
↓-25.0%prior 16
Wet6 (7.3%)
Snow5 (6.1%)
↓-16.7%prior 6
Gravel2 (2.4%)

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

Vehicles & Demographics

Ford and Chevrolet remained the top two vehicle makes involved in crashes, with the number of Ford vehicles increasing from 24 to 29 and Chevrolet vehicles from 16 to 24 year-over-year. Dodge replaced Honda as the third most frequently involved vehicle make in 2021. Regarding demographics, the 26-34 age group saw the most significant growth, with 40 individuals involved in crashes in 2021, up from 26 in 2020. The rank order of the top three most involved age groups remained consistent between the two years.

Top Vehicle Makes (147 vehicles)

1
FORD29 (19.7%)
↑20.8%prior 24
2
CHEVROLET13 (8.8%)
↑85.7%prior 7
3
CHEV11 (7.5%)
↑22.2%prior 9
4
DODGE8 (5.4%)
5
NISS6 (4.1%)
6
DODG5 (3.4%)
7
FRET4 (2.7%)
8
INTERNATIONA4 (2.7%)
9
CHRY4 (2.7%)
10
TOYO4 (2.7%)

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

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

Sex Distribution (121 persons with recorded sex)

Male78 (64.5%)
↑14.7%prior 68
Female43 (35.5%)
↑13.2%prior 38

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: 109
  • Total persons involved: 182
  • Total vehicles involved: 147

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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