Yearly Traffic Safety Analysis

322 CRASHES IN
IOWA, IA
2021

All metrics benchmarked against2020

In Henry County, total traffic crashes increased by 15.4% from 279 in 2020 to 322 in 2021. The most significant year-over-year change was the increase in total fatalities, which rose from one person in 2020 to five in 2021. The number of injuries also saw a slight increase from 92 to 98 during the same period.

322

▲ 15.4%was 279

Total Crash Events

5

▲ 400.0%was 1

Persons Killed

98

▲ 6.5%was 92

Persons Injured

3

▲ 200.0%was 1

Fatal Crash Events

Note: "Persons Killed" (5) 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

Traffic safety trends in Henry County worsened from 2020 to 2021. Total crashes rose by 15.4%, from 279 to 322 incidents. This increase was accompanied by a rise in both injuries, from 92 to 98, and a significant increase in fatalities, from one to five.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 0→0.0%

5

Motorists Killed

Prior: 1↑400.0%

2

Cyclists Injured

Prior: 2→0.0%

96

Motorists Injured

Prior: 89↑7.9%

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 shifted between the two years. In 2021, the peak day for crashes was Thursday with 57 incidents, a change from Friday (46 incidents) in the prior year. The peak hour also shifted earlier, from 5 p.m. (19 crashes) in 2020 to 3 p.m. (28 crashes) 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 from 2020 to 2021. The number of fatal crashes rose from one to three, and the total number of individuals killed increased from one to five. While crashes involving serious injuries decreased slightly from 12 to 11, those resulting in possible injuries increased from 28 to 36. The proportion of crashes with no injuries remained stable at approximately 74% in both years.

Severity is per crash event (most severe injury). 3 fatal crash events resulted in 5 persons killed.

Outcome by Severity (Crash Events)

Fatal3fatal crashes0.9%
↑200.0%prior 1
Serious Injury11serious injury crashes3.4%
↓-8.3%prior 12
Minor Injury31minor injury crashes9.6%
→0.0%prior 31
Possible Injury36possible injury crashes11.2%
↑28.6%prior 28
No Injury241no injury crashes74.8%
↑16.4%prior 207

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 remained the leading contributing factor in both years, with an identical count of 106 crashes. The count for 'Lost Control' also remained unchanged at 23 crashes. However, crashes attributed to 'Driving too fast for conditions' increased from 16 in 2020 to 20 in 2021, and incidents involving 'Failure to yield right of way from a stop sign' rose from 16 to 19. The top five contributing factors were consistent across both years, with minor shifts in their respective counts.

Officer-Reported Primary Contributing Cause

Animal106 (32.9%)→0.0%prior 106
Lost Control23 (7.1%)→0.0%prior 23
Driving too fast for conditions20 (6.2%)↑25.0%prior 16
FTYROW: From stop sign19 (5.9%)↑18.8%prior 16
Ran off road - straight15 (4.7%)↑15.4%prior 13
Other (explain in narrative): Other13 (4%)↑44.4%prior 9
Followed too close11 (3.4%)↓-15.4%prior 13
Operating vehicle in an reckless, erratic, careless, negligent manner10 (3.1%)↑42.9%prior 7
Other (explain in narrative): No improper action9 (2.8%)→0.0%prior 9
Ran off road - left8 (2.5%)→0.0%prior 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

Crashes increased across most reported conditions, consistent with the overall rise in incidents. Collisions in clear weather rose from 131 to 163, and those in daylight increased from 118 to 166. Crashes on dry road surfaces increased from 140 to 168. Notably, incidents on roads with ice or frost more than doubled, increasing from 5 in 2020 to 12 in 2021.

Weather

Clear163 (69.1%)
↑24.4%prior 131
Cloudy47 (19.9%)
↑34.3%prior 35
Rain13 (5.5%)
↑44.4%prior 9
Snow4 (1.7%)
↓-63.6%prior 11
Blowing Snow3 (1.3%)
Freezing rain/drizzle2 (0.8%)
Fog, smoke, smog2 (0.8%)
Severe Winds1 (0.4%)
Sleet, hail1 (0.4%)

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

Lighting

Daylight166 (70.3%)
↑40.7%prior 118
Dark - roadway not lighted45 (19.1%)
↓-15.1%prior 53
Dark - roadway lighted14 (5.9%)
↑40.0%prior 10
Dawn6 (2.5%)
↑20.0%prior 5
Dusk3 (1.3%)
↓-70.0%prior 10
Dark - unknown roadway lighting2 (0.8%)

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

Road Surface

Dry168 (70.9%)
↑20.0%prior 140
Wet25 (10.5%)
↑19.0%prior 21
Gravel18 (7.6%)
↑28.6%prior 14
Snow14 (5.9%)
↑27.3%prior 11
Ice/frost12 (5.1%)
↑140.0%prior 5

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

Vehicles & Demographics

Comparing vehicle involvement, Chevrolet-branded vehicles (including 'CHEV' and 'CHEVROLET') were involved in 116 crashes in 2021, up from 74 in 2020, making it the most frequent make. Ford vehicles were involved in 71 crashes in 2021, a slight increase from 68 in 2020. Analysis of driver age shows a notable increase in persons aged 35-44 involved in crashes, rising from 80 in 2020 to 104 in 2021, while involvement for the 26-34 age group decreased from 94 to 73.

Top Vehicle Makes (459 vehicles)

1
CHEV79 (17.2%)
↑68.1%prior 47
2
FORD71 (15.5%)
↑4.4%prior 68
3
CHEVROLET37 (8.1%)
↑37.0%prior 27
4
GMC24 (5.2%)
↑41.2%prior 17
5
DODG19 (4.1%)
↓-26.9%prior 26
6
JEEP15 (3.3%)
↑25.0%prior 12
7
TOYT13 (2.8%)
→0.0%prior 13
8
NISS12 (2.6%)
↑140.0%prior 5
9
HOND12 (2.6%)
↑50.0%prior 8
10
KIA10 (2.2%)
↓-9.1%prior 11

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

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

Sex Distribution (364 persons with recorded sex)

Male226 (62.1%)
↑7.6%prior 210
Female138 (37.9%)
↓-2.1%prior 141

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: 322
  • Total persons involved: 613
  • Total vehicles involved: 459

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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