Yearly Traffic Safety Analysis

668 CRASHES IN
IOWA, IA
2021

All metrics benchmarked against2020

In Clinton County, total traffic crashes increased by 11.7% from 598 in 2020 to 668 in 2021. This rise was accompanied by an increase in fatalities from 4 to 5 and a 13.9% increase in total injuries from 231 to 263. The most significant year-over-year shift was a 50% increase in the number of serious injury crashes, which rose from 18 to 27.

668

11.7%was 598

Total Crash Events

5

25.0%was 4

Persons Killed

263

13.9%was 231

Persons Injured

5

66.7%was 3

Fatal Crash Events

Note: "Persons Killed" (5) counts individual fatalities across all crash events. "Fatal" in the severity table below (5) 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

Overall traffic safety trends in Clinton County worsened from 2020 to 2021. The total number of crashes increased by 70 incidents, representing an 11.7% rise. This negative trend extended to crash severity, with both fatalities and total injuries increasing year-over-year.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Cyclists Killed

Prior: 00.0%

5

Motorists Killed

Prior: 425.0%

0

Other Killed

Prior: 00.0%

4

Pedestrians Injured

Prior: 6-33.3%

6

Cyclists Injured

Prior: 7-14.3%

251

Motorists Injured

Prior: 21815.1%

2

Other Injured

Prior: 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 remained broadly consistent between the two periods. Friday was the peak day for crashes in both 2021 (119 crashes) and 2020 (110 crashes). The peak hour for collisions shifted slightly, moving from the 3 p.m. hour in 2020 (53 crashes) to the 4 p.m. hour in 2021 (51 crashes), with the afternoon commute remaining the most common time for incidents.

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 from 2020 to 2021. The number of fatal crashes rose from 3 to 5, and the number of fatalities increased from 4 to 5. The count of serious injury crashes saw a substantial 50% increase, from 18 incidents in 2020 to 27 in 2021, raising its share of all crashes from 3.0% to 4.0%. Conversely, the count of minor injury crashes decreased slightly from 83 to 79.

Outcome by Severity (Crash Events)

Fatal5fatal crashes0.7%
66.7%prior 3
Serious Injury27serious injury crashes4%
50.0%prior 18
Minor Injury79minor injury crashes11.8%
-4.8%prior 83
Possible Injury113possible injury crashes16.9%
21.5%prior 93
No Injury444no injury crashes66.5%
10.7%prior 401

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 by 19.1% from 89 to 106 incidents. A significant change occurred with 'Lost Control' crashes, which increased in count by 85.3% from 34 to 63, making it the second-most cited factor in 2021 after being fifth in 2020. Conversely, crashes attributed to 'Followed too close' decreased by 45.8% in count, from 48 incidents in 2020 to 26 in 2021.

Officer-Reported Primary Contributing Cause

Animal106 (15.9%)19.1%prior 89
Lost Control63 (9.4%)85.3%prior 34
FTYROW: From stop sign45 (6.7%)18.4%prior 38
Other (explain in narrative): Other45 (6.7%)15.4%prior 39
Ran Stop Sign40 (6%)25.0%prior 32
Ran off road - straight34 (5.1%)30.8%prior 26
Ran off road - left34 (5.1%)47.8%prior 23
Operating vehicle in an reckless, erratic, careless, negligent manner33 (4.9%)73.7%prior 19
Followed too close26 (3.9%)-45.8%prior 48
Driver Distraction: Other interior distraction23 (3.4%)76.9%prior 13

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 conditions under which crashes occurred were largely similar year-over-year. Crashes in clear weather and daylight continued to be the most common scenarios in both periods, with their proportions remaining stable. There was a slight increase in the share of crashes occurring on adverse road surfaces (wet, ice, or snow), which accounted for 20.4% of crashes in 2021 compared to 17.9% in 2020.

Weather

Clear432 (74.1%)
8.5%prior 398
Cloudy83 (14.2%)
23.9%prior 67
Snow24 (4.1%)
26.3%prior 19
Rain21 (3.6%)
-8.7%prior 23
Freezing rain/drizzle9 (1.5%)
-43.8%prior 16
Blowing Snow8 (1.4%)
Fog, smoke, smog3 (0.5%)
Sleet, hail2 (0.3%)
Severe Winds1 (0.2%)

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

Lighting

Daylight357 (61.2%)
9.5%prior 326
Dark - roadway not lighted107 (18.4%)
4.9%prior 102
Dark - roadway lighted82 (14.1%)
10.8%prior 74
Dusk23 (3.9%)
64.3%prior 14
Dawn12 (2.1%)
9.1%prior 11
Dark - unknown roadway lighting2 (0.3%)

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

Road Surface

Dry431 (73.9%)
4.9%prior 411
Wet50 (8.6%)
0.0%prior 50
Ice/frost50 (8.6%)
72.4%prior 29
Snow29 (5.0%)
163.6%prior 11
Gravel14 (2.4%)
-26.3%prior 19
Slush6 (1.0%)
-25.0%prior 8
Other (explain in narrative)2 (0.3%)
Mud, dirt1 (0.2%)

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

Vehicles & Demographics

The makes of vehicles involved in crashes showed little change, with Ford and Chevrolet remaining the most frequently recorded in both 2020 and 2021. An analysis of persons involved in crashes shows a slight shift in age demographics; the share of individuals in the 16-20 age group decreased from 11.9% to 10.5%, while the share of those in the 0-15 age group increased from 1.6% to 2.8%.

Top Vehicle Makes (1,059 vehicles)

1
FORD180 (17%)
1.1%prior 178
2
CHEV121 (11.4%)
-8.3%prior 132
3
CHEVROLET97 (9.2%)
-5.8%prior 103
4
GMC48 (4.5%)
4.3%prior 46
5
JEEP41 (3.9%)
28.1%prior 32
6
DODGE38 (3.6%)
72.7%prior 22
7
DODG37 (3.5%)
19.4%prior 31
8
TOYT32 (3%)
33.3%prior 24
9
TOYOTA31 (2.9%)
34.8%prior 23
10
NISS26 (2.5%)
85.7%prior 14

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

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

Sex Distribution (802 persons with recorded sex)

Male465 (58.0%)
-8.3%prior 507
Female337 (42.0%)
-7.2%prior 363

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: 668
  • Total persons involved: 1,413
  • Total vehicles involved: 1,059

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

ThatCarHitMe.com · An Injuria.ai Company