Yearly Traffic Safety Analysis

98 CRASHES IN
IOWA, IA
2021

All metrics benchmarked against2020

In Hancock County, total vehicle crashes decreased from 107 in 2020 to 98 in 2021, representing an 8.4% decline. During this period, fatalities fell from two to one, and total injuries dropped from 65 to 54. The most significant year-over-year change was a sharp reduction in crashes attributed to a driver losing control, which fell by 66.7% from 21 incidents in 2020 to 7 in 2021.

98

▼ -8.4%was 107

Total Crash Events

1

▼ -50.0%was 2

Persons Killed

54

▼ -16.9%was 65

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

Overall traffic safety trends in Hancock County showed improvement from 2020 to 2021. Total crashes decreased by 8.4%, falling from 107 to 98. This positive trend extended to crash outcomes, with total injuries declining by 16.9% from 65 to 54, and fatalities decreasing from two to one.

Vulnerable Road User Casualties

1

Motorists Killed

Prior: 2↓-50.0%

54

Motorists Injured

Prior: 65↓-16.9%

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 periods. In 2021, the peak day for crashes was Thursday with 19 incidents, a change from 2020 when Friday was the peak day with 25 incidents. The busiest time of day also shifted slightly, with the peak hour moving from 4 p.m. in 2020 (12 crashes) to 5 p.m. in 2021 (8 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

Crash severity improved from 2020 to 2021. While both years recorded one fatal crash, the total number of fatalities decreased from two to one. The proportion of crashes resulting in any injury fell from 42.1% (45 of 107 crashes) in 2020 to 36.7% (36 of 98 crashes) in 2021. This was driven by a significant drop in minor injury crashes, which decreased from 24 to 8, even as possible injury crashes rose from 16 to 23.

Outcome by Severity (Crash Events)

Fatal1fatal crashes1%
→0.0%prior 1
Serious Injury5serious injury crashes5.1%
→0.0%prior 5
Minor Injury8minor injury crashes8.2%
↓-66.7%prior 24
Possible Injury23possible injury crashes23.5%
↑43.8%prior 16
No Injury61no injury crashes62.2%
→0.0%prior 61

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

The leading contributing factors for crashes changed between 2020 and 2021. The most frequent factor in 2020, 'Lost Control,' saw its count drop by 66.7% from 21 incidents to just 7 in 2021. In 2021, the most cited factor was 'Other (explain in narrative): Other' with 11 incidents. Meanwhile, crashes involving 'Followed too close' more than doubled, increasing from 3 incidents in 2020 to 7 in 2021.

Officer-Reported Primary Contributing Cause

Other (explain in narrative): Other11 (11.2%)↑120.0%prior 5
Ran off road - straight8 (8.2%)↑33.3%prior 6
Animal7 (7.1%)↑16.7%prior 6
Driving too fast for conditions7 (7.1%)↓-22.2%prior 9
Followed too close7 (7.1%)
Lost Control7 (7.1%)↓-66.7%prior 21
Driver Distraction: Other interior distraction6 (6.1%)→0.0%prior 6
Ran off road - left5 (5.1%)
FTYROW: At uncontrolled intersection4 (4.1%)
FTYROW: From driveway3 (3.1%)

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 were more likely to occur in clear conditions in 2021 compared to the prior year. In 2021, 82.7% of crashes happened in clear weather, up from 65.4% in 2020. Correspondingly, crashes on non-dry road surfaces like snow, ice, or wet pavement decreased, accounting for 21.4% of crashes in 2021 versus 33.6% in 2020. The proportion of crashes occurring in daylight versus dark or low-light conditions remained relatively stable across both years.

Weather

Clear81 (84.4%)
↑15.7%prior 70
Cloudy5 (5.2%)
↓-66.7%prior 15
Snow3 (3.1%)
Rain2 (2.1%)
Freezing rain/drizzle2 (2.1%)
Fog, smoke, smog1 (1.0%)
Severe Winds1 (1.0%)
Blowing Snow1 (1.0%)

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

Lighting

Daylight63 (64.9%)
↓-7.4%prior 68
Dark - roadway not lighted14 (14.4%)
↓-36.4%prior 22
Dawn8 (8.2%)
Dark - roadway lighted7 (7.2%)
↑40.0%prior 5
Dusk5 (5.2%)

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

Road Surface

Dry72 (74.2%)
↑9.1%prior 66
Snow8 (8.2%)
↓-20.0%prior 10
Ice/frost7 (7.2%)
↓-46.2%prior 13
Wet5 (5.2%)
↓-16.7%prior 6
Gravel4 (4.1%)
↓-42.9%prior 7
Sand1 (1.0%)

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

Vehicles & Demographics

The top vehicle makes involved in crashes, Ford and Chevrolet, remained consistent in both rank and volume between 2020 and 2021. However, the demographics of persons involved in crashes shifted. The number of males involved decreased substantially from 106 in 2020 to 70 in 2021, while the number of females was stable. The 16-20 age group became the most represented group in 2021 with 43 individuals, an increase from 38 in the prior year, despite an overall decrease in the total number of people involved in crashes.

Top Vehicle Makes (157 vehicles)

1
FORD34 (21.7%)
↓-5.6%prior 36
2
CHEVROLET19 (12.1%)
↑90.0%prior 10
3
CHEV18 (11.5%)
↓-28.0%prior 25
4
DODG10 (6.4%)
↑42.9%prior 7
5
GMC8 (5.1%)
↓-11.1%prior 9
6
PONT6 (3.8%)
7
HOND5 (3.2%)
8
CHRY4 (2.5%)
9
DODGE4 (2.5%)
10
TOYT4 (2.5%)

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

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

Sex Distribution (120 persons with recorded sex)

Male70 (58.3%)
↓-34.0%prior 106
Female50 (41.7%)
↑4.2%prior 48

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: 98
  • Total persons involved: 209
  • Total vehicles involved: 157

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