Yearly Traffic Safety Analysis

2,151 CRASHES IN
IOWA, IA
2021

All metrics benchmarked against2020

In Black Hawk County, total crashes increased by 24.8%, rising from 1,723 in 2020 to 2,151 in 2021. This rise in collisions was accompanied by a 39.5% increase in total injuries, which grew from 550 to 767. The number of fatalities, however, remained unchanged at nine for both periods.

2,151

▲ 24.8%was 1,723

Total Crash Events

9

Persons Killed

767

▲ 39.5%was 550

Persons Injured

9

Fatal Crash Events

Note: "Persons Killed" (9) counts individual fatalities across all crash events. "Fatal" in the severity table below (9) 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 data from Black Hawk County indicates a rising trend, with total collisions increasing by 428 incidents, or 24.8%, from 2020 to 2021. While the number of fatalities held steady at nine, the number of people injured in crashes saw a significant increase of 39.5% year-over-year, climbing from 550 to 767.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 2↓-50.0%

0

Cyclists Killed

Prior: 2↓-100.0%

8

Motorists Killed

Prior: 5↑60.0%

0

Other Killed

Prior: 0→0.0%

16

Pedestrians Injured

Prior: 16→0.0%

18

Cyclists Injured

Prior: 14↑28.6%

731

Motorists Injured

Prior: 520↑40.6%

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 daily and hourly patterns of crashes showed some shifts between the two years. The peak day for crashes moved from Thursday (282 crashes) in 2020 to Friday (383 crashes) in 2021. The 3 p.m. hour remained the peak time for collisions in both periods, but the volume of crashes during this hour increased from 142 in 2020 to 220 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

While the number of fatal crashes remained constant at nine in both 2020 and 2021, the fatal crash rate per 100 crashes decreased from 0.52 to 0.42 due to the overall increase in collisions. The number of crashes resulting in minor injuries grew from 133 to 196, and their share of all crashes increased from 7.7% to 9.1%. Similarly, possible injury crashes rose from 326 to 433, representing a proportional increase from 18.9% to 20.1% of all incidents.

Outcome by Severity (Crash Events)

Fatal9fatal crashes0.4%
→0.0%prior 9
Serious Injury38serious injury crashes1.8%
↑2.7%prior 37
Minor Injury196minor injury crashes9.1%
↑47.4%prior 133
Possible Injury433possible injury crashes20.1%
↑32.8%prior 326
No Injury1,475no injury crashes68.6%
↑21.1%prior 1,218

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 were largely consistent, with 'Other' and 'Animal' ranking as the top two causes in both 2020 and 2021. However, the count for several factors increased significantly; crashes attributed to 'Followed too close' rose from 86 to 136, a 58% increase in count, while those citing 'Ran Traffic Signal' increased from 65 to 88. Crashes involving animals remained relatively stable, with 151 incidents in 2020 and 157 in 2021.

Officer-Reported Primary Contributing Cause

Other (explain in narrative): Other301 (14%)↑56.0%prior 193
Animal157 (7.3%)↑4.0%prior 151
Followed too close136 (6.3%)↑58.1%prior 86
FTYROW: From stop sign117 (5.4%)↑19.4%prior 98
Ran off road - left104 (4.8%)↑13.0%prior 92
Driving too fast for conditions102 (4.7%)↑24.4%prior 82
Ran Stop Sign102 (4.7%)↑27.5%prior 80
FTYROW: Making left turn93 (4.3%)↑38.8%prior 67
Ran Traffic Signal88 (4.1%)↑35.4%prior 65
Driver Distraction: Other interior distraction81 (3.8%)↑22.7%prior 66

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 crashes across various conditions remained broadly similar year-over-year, with the majority of incidents in both 2021 (69.0%) and 2020 (68.3%) occurring in clear weather. There was a notable shift in lighting conditions, as the proportion of crashes in daylight increased from 59.2% in 2020 to 65.1% in 2021. Conversely, the share of crashes on unlit dark roadways decreased from 11.9% to 8.2%.

Weather

Clear1,483 (73.5%)
↑26.0%prior 1,177
Cloudy305 (15.1%)
↑26.0%prior 242
Rain81 (4.0%)
↑6.6%prior 76
Snow70 (3.5%)
↑4.5%prior 67
Freezing rain/drizzle39 (1.9%)
↓-11.4%prior 44
Blowing Snow19 (0.9%)
↑137.5%prior 8
Fog, smoke, smog7 (0.3%)
↓-12.5%prior 8
Severe Winds6 (0.3%)
Other (explain in narrative)4 (0.2%)
Sleet, hail3 (0.1%)

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

Lighting

Daylight1,401 (69.3%)
↑37.4%prior 1,020
Dark - roadway lighted355 (17.6%)
↑10.9%prior 320
Dark - roadway not lighted176 (8.7%)
↓-14.1%prior 205
Dusk46 (2.3%)
↑9.5%prior 42
Dawn29 (1.4%)
↑7.4%prior 27
Dark - unknown roadway lighting14 (0.7%)
↓-17.6%prior 17

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

Road Surface

Dry1,498 (74.2%)
↑18.4%prior 1,265
Wet197 (9.8%)
↑18.7%prior 166
Snow144 (7.1%)
↑73.5%prior 83
Ice/frost133 (6.6%)
↑66.3%prior 80
Slush25 (1.2%)
↑47.1%prior 17
Gravel17 (0.8%)
↑30.8%prior 13
Other (explain in narrative)4 (0.2%)
↓-20.0%prior 5

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

Vehicles & Demographics

The most common vehicle makes involved in crashes, Ford and Chevrolet, maintained their top rankings in both 2020 and 2021, with their counts increasing in line with the overall rise in collisions. An analysis of persons involved shows a general increase across all age groups. Notably, the number of individuals aged 16-20 involved in crashes rose from 496 to 652, and those aged 65 and older increased from 353 to 496.

Top Vehicle Makes (3,880 vehicles)

1
FORD600 (15.5%)
↑16.5%prior 515
2
CHEV475 (12.2%)
↑15.6%prior 411
3
CHEVROLET357 (9.2%)
↑81.2%prior 197
4
TOYT161 (4.1%)
↑21.1%prior 133
5
JEEP153 (3.9%)
↑45.7%prior 105
6
DODG123 (3.2%)
↓-8.2%prior 134
7
GMC123 (3.2%)
↑48.2%prior 83
8
NR120 (3.1%)
↑8.1%prior 111
9
TOYOTA118 (3%)
↑93.4%prior 61
10
KIA116 (3%)
↑96.6%prior 59

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

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

Sex Distribution (3,186 persons with recorded sex)

Male1,721 (54.0%)
↑16.8%prior 1,474
Female1,465 (46.0%)
↑27.6%prior 1,148

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: 2,151
  • Total persons involved: 4,792
  • Total vehicles involved: 3,880

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