Yearly Traffic Safety Analysis

1,723 CRASHES IN
IOWA, IA
2020

All metrics benchmarked against2019

In Black Hawk County, total traffic crashes decreased by 25.8% from 2,322 in 2019 to 1,723 in 2020. This significant drop in overall incidents was accompanied by a 31.9% reduction in total injuries, from 808 to 550. The most notable change was a substantial reduction in crashes attributed to adverse road conditions, with incidents on snow, ice, or slush-covered roads falling from 558 to 180.

1,723

▼ -25.8%was 2,322

Total Crash Events

9

▼ -18.2%was 11

Persons Killed

550

▼ -31.9%was 808

Persons Injured

9

▼ -10.0%was 10

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 · 2020-01-01 to 2020-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Traffic crashes in Black Hawk County showed a significant downward trend year-over-year. The total number of crashes fell by 599 incidents, from 2,322 in 2019 to 1,723 in 2020. This decline was also reflected in crash outcomes, with total fatalities decreasing from 11 to 9 and total injuries dropping from 808 to 550.

Vulnerable Road User Casualties

2

Pedestrians Killed

Prior: 1↑100.0%

2

Cyclists Killed

Prior: 1↑100.0%

5

Motorists Killed

Prior: 9↓-44.4%

16

Pedestrians Injured

Prior: 13↑23.1%

14

Cyclists Injured

Prior: 20↓-30.0%

520

Motorists Injured

Prior: 775↓-32.9%

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The time and day of crashes saw some shifts between the two periods. The peak day for crashes moved from Friday (408 crashes) in 2019 to Thursday (282 crashes) in 2020. While the 3 p.m. hour remained the peak time for collisions in both years, the number of crashes during that hour decreased from 218 to 142.

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

While the total number of fatal crashes decreased from 10 to 9, the fatal crash rate as a percentage of all crashes increased slightly from 0.43% in 2019 to 0.52% in 2020. Similarly, the share of crashes resulting in serious injuries rose from 1.8% to 2.1%. Conversely, the proportion of crashes involving minor injuries decreased from 8.6% to 7.7% of the total.

Outcome by Severity (Crash Events)

Fatal9fatal crashes0.5%
↓-10.0%prior 10
Serious Injury37serious injury crashes2.1%
↓-11.9%prior 42
Minor Injury133minor injury crashes7.7%
↓-33.5%prior 200
Possible Injury326possible injury crashes18.9%
↓-23.1%prior 424
No Injury1,218no injury crashes70.7%
↓-26.0%prior 1,646

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factors shifted between periods, with incidents attributed to "Driving too fast for conditions" seeing a 55.7% decrease in count, from 185 in 2019 to 82 in 2020. Crashes involving "Followed too close" also dropped by 48.2%, from 166 to 86. Consequently, while these were top-three factors in 2019, they were surpassed in the 2020 rankings by "Animal" (151 crashes) and "FTYROW: From stop sign" (98 crashes).

Officer-Reported Primary Contributing Cause

Other (explain in narrative): Other193 (11.2%)↓-16.5%prior 231
Animal151 (8.8%)↓-7.4%prior 163
FTYROW: From stop sign98 (5.7%)↓-38.0%prior 158
Ran off road - left92 (5.3%)↓-43.9%prior 164
Followed too close86 (5%)↓-48.2%prior 166
Driving too fast for conditions82 (4.8%)↓-55.7%prior 185
Ran Stop Sign80 (4.6%)↓-39.4%prior 132
FTYROW: Making left turn67 (3.9%)↓-26.4%prior 91
Driver Distraction: Other interior distraction66 (3.8%)↑1.5%prior 65
Lost Control65 (3.8%)↓-15.6%prior 77

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

There was a notable shift in crash conditions year-over-year, with a much lower proportion of incidents occurring on adverse road surfaces. Crashes on roads with snow, ice, or slush accounted for 24.0% of all incidents in 2019 but only 10.4% in 2020. Correspondingly, the share of crashes on dry roads increased from 59.1% to 73.4%. The proportion of crashes in daylight decreased from 64.5% to 59.2%, while crashes on lighted, dark roadways increased as a share of the total from 15.0% to 18.6%.

Weather

Clear1,177 (72.3%)
↓-18.7%prior 1,448
Cloudy242 (14.9%)
↓-30.1%prior 346
Rain76 (4.7%)
↓-37.7%prior 122
Snow67 (4.1%)
↓-54.1%prior 146
Freezing rain/drizzle44 (2.7%)
↓-25.4%prior 59
Blowing Snow8 (0.5%)
↓-81.8%prior 44
Fog, smoke, smog8 (0.5%)
↓-20.0%prior 10
Sleet, hail2 (0.1%)
↓-66.7%prior 6
Severe Winds2 (0.1%)
↓-87.5%prior 16
Other (explain in narrative)1 (0.1%)
↓-83.3%prior 6

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · Weather condition at time of crash

Lighting

Daylight1,020 (62.5%)
↓-31.9%prior 1,497
Dark - roadway lighted320 (19.6%)
↓-8.0%prior 348
Dark - roadway not lighted205 (12.6%)
↓-9.3%prior 226
Dusk42 (2.6%)
↓-32.3%prior 62
Dawn27 (1.7%)
↓-34.1%prior 41
Dark - unknown roadway lighting17 (1.0%)
↓-46.9%prior 32

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · Lighting condition field

Road Surface

Dry1,265 (77.6%)
↓-7.9%prior 1,373
Wet166 (10.2%)
↓-33.1%prior 248
Snow83 (5.1%)
↓-68.2%prior 261
Ice/frost80 (4.9%)
↓-68.8%prior 256
Slush17 (1.0%)
↓-58.5%prior 41
Gravel13 (0.8%)
↑8.3%prior 12
Other (explain in narrative)5 (0.3%)
Water (standing or moving)1 (0.1%)

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · Road surface condition field

Vehicles & Demographics

The makes of vehicles involved in crashes remained consistent, though their numbers declined in line with the overall trend. Ford and Chevrolet were the top two makes in both 2019 and 2020, with Ford-involved vehicles decreasing from 718 to 515 and Chevrolet-involved vehicles dropping from a combined 851 to 608. The age distribution of persons involved in crashes also remained relatively stable, with the 26-34 age group representing the largest share in both periods (15.5% in 2019 and 15.2% in 2020).

Top Vehicle Makes (3,010 vehicles)

1
FORD515 (17.1%)
↓-28.3%prior 718
2
CHEV411 (13.7%)
↓-32.8%prior 612
3
CHEVROLET197 (6.5%)
↓-17.6%prior 239
4
DODG134 (4.5%)
↓-22.1%prior 172
5
TOYT133 (4.4%)
↓-46.8%prior 250
6
NR111 (3.7%)
↓-19.0%prior 137
7
JEEP105 (3.5%)
↓-32.3%prior 155
8
NISS91 (3%)
↓-38.1%prior 147
9
HOND88 (2.9%)
↓-31.3%prior 128
10
GMC83 (2.8%)
↓-25.2%prior 111

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · Vehicle unit records

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

Sex Distribution (2,622 persons with recorded sex)

Male1,474 (56.2%)
↓-28.8%prior 2,069
Female1,148 (43.8%)
↓-31.9%prior 1,685

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · 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: 2020-01-01 through 2020-12-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2020-01-01 through 2020-12-31 (366 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 1,723
  • Total persons involved: 3,965
  • Total vehicles involved: 3,010

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: 2020." Published September 9, 2026. Reporting period: 2020-01-01 to 2020-12-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/2020-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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