Yearly Traffic Safety Analysis

304 CRASHES IN
IOWA, IA
2021

All metrics benchmarked against2020

In Harrison County, total traffic crashes remained stable, decreasing slightly from 307 in 2020 to 304 in 2021, a change of less than 1%. Despite the consistent number of collisions, the severity of outcomes worsened significantly. The most notable year-over-year shift was a sharp rise in traffic fatalities, which increased from 1 to 4, and a 22% increase in total injuries, from 100 to 122.

304

▼ -1.0%was 307

Total Crash Events

4

▲ 300.0%was 1

Persons Killed

122

▲ 22.0%was 100

Persons Injured

4

▲ 300.0%was 1

Fatal Crash Events

Note: "Persons Killed" (4) counts individual fatalities across all crash events. "Fatal" in the severity table below (4) 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 crash volume in Harrison County was stable year-over-year, with 304 crashes in 2021 compared to 307 in 2020. This represents a minor decrease of just 3 incidents, or approximately 1%. However, this stability in total crashes masks a significant increase in crash severity, with more injuries and fatalities recorded in the current period.

Vulnerable Road User Casualties

4

Motorists Killed

Prior: 0→%

122

Motorists Injured

Prior: 99↑23.2%

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 peak day for crashes remained Friday in both 2021 (48 crashes) and 2020 (57 crashes). However, the peak hour for collisions shifted from the morning commute at 7 a.m. in the prior period (24 crashes) to the evening at 7 p.m. in the current period (22 crashes). This reflects a change in daily crash patterns, with evening hours seeing a higher concentration of incidents in 2021 compared to the previous year.

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 in 2021 compared to 2020. The number of fatal crashes rose from 1 to 4, and the proportion of crashes resulting in a fatality increased from 0.3% to 1.3%. The share of serious injury crashes also grew from 5.2% (16 crashes) to 6.6% (20 crashes). Correspondingly, the proportion of crashes with no injuries decreased from 75.9% in 2020 to 66.8% in 2021.

Outcome by Severity (Crash Events)

Fatal4fatal crashes1.3%
↑300.0%prior 1
Serious Injury20serious injury crashes6.6%
↑25.0%prior 16
Minor Injury32minor injury crashes10.5%
↑23.1%prior 26
Possible Injury45possible injury crashes14.8%
↑45.2%prior 31
No Injury203no injury crashes66.8%
↓-12.9%prior 233

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 increasing from 61 crashes in 2020 to 74 in 2021. 'Lost Control' was the second-ranked factor in both years, though its count decreased from 40 to 36 incidents. 'Driving too fast for conditions' moved into the top three factors, increasing from 27 to 31 incidents, while 'Followed too close' saw a significant drop from 30 crashes in 2020 to just 12 in 2021.

Officer-Reported Primary Contributing Cause

Animal74 (24.3%)↑21.3%prior 61
Lost Control36 (11.8%)↓-10.0%prior 40
Driving too fast for conditions31 (10.2%)↑14.8%prior 27
Ran off road - straight29 (9.5%)↑52.6%prior 19
Ran off road - left12 (3.9%)↓-14.3%prior 14
Followed too close12 (3.9%)↓-60.0%prior 30
FTYROW: From stop sign11 (3.6%)↑37.5%prior 8
Other (explain in narrative): Other10 (3.3%)↑42.9%prior 7
Exceeded authorized speed9 (3%)
Improper Backing8 (2.6%)

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Driving conditions for crashes remained broadly similar year-over-year, with clear weather and dry road surfaces predominating in both 2021 and 2020. Crashes in clear weather accounted for 172 incidents in 2021 versus 185 in 2020. The proportion of crashes occurring on adverse road surfaces (such as wet, snow, or ice) saw a slight decrease, accounting for 18.8% of crashes in 2021 compared to 21.2% in 2020. Lighting conditions also showed little change, with daylight being the most common condition in both periods.

Weather

Clear172 (70.8%)
↓-7.0%prior 185
Cloudy34 (14.0%)
↑9.7%prior 31
Snow13 (5.3%)
↓-13.3%prior 15
Rain10 (4.1%)
↓-9.1%prior 11
Blowing Snow5 (2.1%)
Severe Winds4 (1.6%)
Fog, smoke, smog3 (1.2%)
↓-40.0%prior 5
Freezing rain/drizzle2 (0.8%)
↓-71.4%prior 7

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

Lighting

Daylight152 (62.6%)
↓-9.5%prior 168
Dark - roadway not lighted68 (28.0%)
↑9.7%prior 62
Dark - roadway lighted8 (3.3%)
↓-61.9%prior 21
Dusk7 (2.9%)
Dawn6 (2.5%)
↑20.0%prior 5
Dark - unknown roadway lighting2 (0.8%)

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

Road Surface

Dry176 (72.1%)
↓-6.9%prior 189
Wet24 (9.8%)
↓-11.1%prior 27
Snow15 (6.1%)
→0.0%prior 15
Ice/frost15 (6.1%)
↑15.4%prior 13
Gravel11 (4.5%)
↑57.1%prior 7
Slush2 (0.8%)
↓-75.0%prior 8
Mud, dirt1 (0.4%)

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, remained consistent across both years. The number of Fords involved increased from 69 to 79, while the combined count for Chevrolet models decreased from 96 to 81. Analysis of persons involved shows a demographic shift, with the 26-34 and 35-44 age groups being most represented in 2021 (94 and 93 persons, respectively). This contrasts with 2020, when the 45-54 age group had the highest involvement (91 persons).

Top Vehicle Makes (410 vehicles)

1
FORD79 (19.3%)
↑14.5%prior 69
2
CHEV42 (10.2%)
↓-26.3%prior 57
3
CHEVROLET39 (9.5%)
→0.0%prior 39
4
DODGE22 (5.4%)
↑69.2%prior 13
5
HONDA16 (3.9%)
↑45.5%prior 11
6
GMC14 (3.4%)
↓-17.6%prior 17
7
TOYOTA14 (3.4%)
↑55.6%prior 9
8
TOYT13 (3.2%)
↑160.0%prior 5
9
DODG13 (3.2%)
↓-31.6%prior 19
10
KIA12 (2.9%)
↑50.0%prior 8

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

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

Sex Distribution (320 persons with recorded sex)

Male215 (67.2%)
↓-21.5%prior 274
Female105 (32.8%)
↓-15.3%prior 124

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: 304
  • Total persons involved: 568
  • Total vehicles involved: 410

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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