Yearly Traffic Safety Analysis

1,005 CRASHES IN
IOWA, IA
2021

All metrics benchmarked against2020

In 2021, Cerro Gordo County recorded 1,005 vehicle crashes, a 17.7% increase from the 854 crashes documented in 2020. This rise was accompanied by a significant increase in crash severity. The most notable year-over-year change was in crash-related fatalities, which rose from 2 in 2020 to 8 in 2021.

1,005

17.7%was 854

Total Crash Events

8

300.0%was 2

Persons Killed

313

29.9%was 241

Persons Injured

8

300.0%was 2

Fatal Crash Events

Note: "Persons Killed" (8) counts individual fatalities across all crash events. "Fatal" in the severity table below (8) 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 crash trends in Cerro Gordo County showed a notable increase from 2020 to 2021. The total number of crashes rose by 151 incidents from 854 to 1,005. This was accompanied by a rise in total injuries from 241 to 313 and an increase in fatalities from 2 to 8.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 10.0%

2

Cyclists Killed

Prior: 0%

5

Motorists Killed

Prior: 1400.0%

0

Other Killed

Prior: 00.0%

7

Pedestrians Injured

Prior: 475.0%

11

Cyclists Injured

Prior: 5120.0%

294

Motorists Injured

Prior: 23226.7%

1

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 largely consistent year-over-year. Friday was the peak day for crashes in both 2021 (161 crashes) and 2020 (147 crashes). The peak hour for collisions shifted slightly earlier, from 6 p.m. in 2020 (73 crashes) to 5 p.m. in 2021 (80 crashes), with both periods showing elevated crash volumes during the evening commute.

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 worsened in 2021 compared to the prior year. The number of fatal crashes increased from 2 to 8, raising the fatal crash rate from 0.2% to 0.8% of all incidents. While the proportion of serious injury crashes remained stable at 1.3%, the share of minor injury crashes grew from 7.3% in 2020 to 8.5% in 2021. Consequently, the proportion of crashes with no injuries decreased from 76.7% to 74.6%.

Outcome by Severity (Crash Events)

Fatal8fatal crashes0.8%
300.0%prior 2
Serious Injury13serious injury crashes1.3%
18.2%prior 11
Minor Injury85minor injury crashes8.5%
37.1%prior 62
Possible Injury149possible injury crashes14.8%
20.2%prior 124
No Injury750no injury crashes74.6%
14.5%prior 655

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 an animal remained the leading contributing factor in both periods, with the count of such incidents increasing from 154 in 2020 to 168 in 2021. The number of crashes attributed to 'Followed too close' saw a significant rise, jumping from 58 to 99 incidents, making it the second-most cited factor in 2021. Conversely, crashes where 'Driving too fast for conditions' was a factor decreased in count from 59 to 49. Crashes involving 'Failure to yield from a stop sign' also increased from 57 to 67 incidents.

Officer-Reported Primary Contributing Cause

Animal168 (16.7%)9.1%prior 154
Followed too close99 (9.9%)70.7%prior 58
Other (explain in narrative): Other85 (8.5%)39.3%prior 61
FTYROW: From stop sign67 (6.7%)17.5%prior 57
Driving too fast for conditions49 (4.9%)-16.9%prior 59
Ran off road - left40 (4%)8.1%prior 37
Lost Control33 (3.3%)26.9%prior 26
Ran Stop Sign32 (3.2%)77.8%prior 18
FTYROW: Making left turn31 (3.1%)14.8%prior 27
Driver Distraction: Other interior distraction31 (3.1%)10.7%prior 28

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 distribution of environmental conditions during crashes was largely unchanged between 2020 and 2021. Crashes in clear weather and daylight conditions continued to make up the majority of incidents, with their share of total crashes remaining stable. Similarly, crashes on dry road surfaces represented about 65% of all incidents in 2021, a slight proportional increase from 63% in the prior year, with no significant shifts in the proportions of adverse condition crashes.

Weather

Clear589 (68.5%)
22.5%prior 481
Cloudy182 (21.2%)
22.1%prior 149
Rain24 (2.8%)
20.0%prior 20
Snow24 (2.8%)
-44.2%prior 43
Freezing rain/drizzle22 (2.6%)
69.2%prior 13
Blowing Snow9 (1.0%)
0.0%prior 9
Fog, smoke, smog5 (0.6%)
Severe Winds4 (0.5%)
Other (explain in narrative)1 (0.1%)

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

Lighting

Daylight603 (69.9%)
19.9%prior 503
Dark - roadway lighted122 (14.1%)
16.2%prior 105
Dark - roadway not lighted108 (12.5%)
38.5%prior 78
Dusk15 (1.7%)
-44.4%prior 27
Dawn14 (1.6%)
75.0%prior 8
Dark - unknown roadway lighting1 (0.1%)

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

Road Surface

Dry652 (75.6%)
21.2%prior 538
Wet83 (9.6%)
33.9%prior 62
Ice/frost63 (7.3%)
28.6%prior 49
Snow51 (5.9%)
-19.0%prior 63
Gravel9 (1.0%)
50.0%prior 6
Slush5 (0.6%)
-16.7%prior 6

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

Vehicles & Demographics

Analysis of vehicle makes involved in crashes shows that Chevrolet (356 vehicles) and Ford (324 vehicles) remained the top two makes in 2021, consistent with their rankings in 2020. The demographic distribution of persons involved in crashes saw a notable shift in the 55-64 age group, whose count increased from 220 individuals in 2020 to 300 in 2021. Other age groups saw increases in involvement that were more proportional to the overall rise in crashes.

Top Vehicle Makes (1,706 vehicles)

1
FORD324 (19%)
27.6%prior 254
2
CHEV211 (12.4%)
-0.9%prior 213
3
CHEVROLET145 (8.5%)
54.3%prior 94
4
TOYT72 (4.2%)
7.5%prior 67
5
JEEP69 (4%)
91.7%prior 36
6
GMC61 (3.6%)
29.8%prior 47
7
NR55 (3.2%)
41.0%prior 39
8
DODG54 (3.2%)
1.9%prior 53
9
HOND49 (2.9%)
28.9%prior 38
10
NISS48 (2.8%)
-2.0%prior 49

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

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

Sex Distribution (1,371 persons with recorded sex)

Male759 (55.4%)
7.4%prior 707
Female612 (44.6%)
8.5%prior 564

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: 1,005
  • Total persons involved: 2,141
  • Total vehicles involved: 1,706

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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