Yearly Traffic Safety Analysis

176 CRASHES IN
IOWA, IA
2021

All metrics benchmarked against2020

In Jackson County, total traffic crashes increased by 20.5% from 146 in 2020 to 176 in 2021. During this period, the number of fatalities rose from 3 to 5, and total injuries increased from 59 to 69. A notable year-over-year shift was the increase in crashes involving suspected driving under the influence (DUI), which rose from 4 incidents in 2020 to 11 in 2021.

176

▲ 20.5%was 146

Total Crash Events

5

▲ 66.7%was 3

Persons Killed

69

▲ 16.9%was 59

Persons Injured

4

▲ 33.3%was 3

Fatal Crash Events

Note: "Persons Killed" (5) 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

The overall trend in Jackson County shows an increase in traffic incidents from 2020 to 2021. Total crashes rose by 20.5% from 146 to 176. Similarly, the number of people injured increased by 16.9% from 59 to 69, and fatalities increased by 66.7% from 3 to 5.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 2↓-100.0%

5

Motorists Killed

Prior: 1↑400.0%

0

Other Killed

Prior: 0→0.0%

1

Pedestrians Injured

Prior: 1→0.0%

67

Motorists Injured

Prior: 57↑17.5%

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

Temporal patterns shifted between the two periods. In 2021, the peak day for crashes was Friday with 36 incidents, a change from 2020 when Monday was the peak day with 30 crashes. The peak hour also moved from the evening to the morning, shifting from 5 p.m. (12 crashes) in 2020 to 7 a.m. (14 crashes) 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

The severity of crashes saw mixed changes year-over-year. The number of fatal crashes increased from 3 in 2020 to 4 in 2021, and the total number of fatalities rose from 3 to 5. However, the count of serious injury crashes decreased from 8 in 2020 to 4 in 2021. Crashes resulting in minor injuries increased from 15 to 21, while no-injury crashes grew from 98 to 124.

Severity is per crash event (most severe injury). 4 fatal crash events resulted in 5 persons killed.

Outcome by Severity (Crash Events)

Fatal4fatal crashes2.3%
↑33.3%prior 3
Serious Injury4serious injury crashes2.3%
↓-50.0%prior 8
Minor Injury21minor injury crashes11.9%
↑40.0%prior 15
Possible Injury23possible injury crashes13.1%
↑4.5%prior 22
No Injury124no injury crashes70.5%
↑26.5%prior 98

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 showed some shifts between 2020 and 2021. "Lost Control" remained the top cited factor in both years, with its count remaining stable at 21 in 2021 compared to 22 in 2020. Incidents involving an "Animal" increased from 12 to 17, and crashes attributed to "Driving too fast for conditions" grew from 7 to 11. Conversely, crashes where a driver failed to yield the right of way from a stop sign decreased from 12 to 11.

Officer-Reported Primary Contributing Cause

Lost Control21 (11.9%)↓-4.5%prior 22
Ran off road - straight19 (10.8%)↑35.7%prior 14
Animal17 (9.7%)↑41.7%prior 12
Other (explain in narrative): Other13 (7.4%)↑18.2%prior 11
FTYROW: From stop sign11 (6.3%)↓-8.3%prior 12
Driving too fast for conditions11 (6.3%)↑57.1%prior 7
Followed too close8 (4.5%)↑14.3%prior 7
Ran Stop Sign6 (3.4%)
FTYROW: Making left turn6 (3.4%)
Ran off road - left5 (2.8%)↓-37.5%prior 8

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 different environmental conditions remained largely consistent from 2020 to 2021. Crashes in clear weather accounted for 63.6% of incidents in 2021 (112 crashes), compared to 63.0% in 2020 (92 crashes). Similarly, crashes on dry road surfaces made up 65.9% of the total in 2021 (116 crashes), nearly identical to the 69.2% share in 2020 (101 crashes). The proportion of crashes occurring in daylight also held steady, at 60.2% in 2021 versus 63.0% in the prior year.

Weather

Clear112 (68.3%)
↑21.7%prior 92
Cloudy33 (20.1%)
→0.0%prior 33
Rain7 (4.3%)
→0.0%prior 7
Freezing rain/drizzle6 (3.7%)
Snow5 (3.0%)
↓-16.7%prior 6
Other (explain in narrative)1 (0.6%)

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

Lighting

Daylight106 (64.6%)
↑15.2%prior 92
Dark - roadway not lighted30 (18.3%)
↑20.0%prior 25
Dark - roadway lighted18 (11.0%)
↑12.5%prior 16
Dusk6 (3.7%)
↓-14.3%prior 7
Dawn3 (1.8%)
Dark - unknown roadway lighting1 (0.6%)

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

Road Surface

Dry116 (70.7%)
↑14.9%prior 101
Ice/frost13 (7.9%)
↑62.5%prior 8
Wet12 (7.3%)
↓-14.3%prior 14
Snow11 (6.7%)
↑83.3%prior 6
Gravel10 (6.1%)
→0.0%prior 10
Slush2 (1.2%)

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 remained consistent, with Chevrolet and Ford leading in both periods. In 2021, 76 Chevrolet and 60 Ford vehicles were involved in crashes, up from 51 and 36 respectively in 2020. Analysis of person data shows a notable increase in the involvement of individuals aged 65 and older, which rose from 39 persons in 2020 to 59 in 2021. Conversely, the number of persons aged 21-25 involved in crashes decreased from 40 to 32.

Top Vehicle Makes (278 vehicles)

1
FORD60 (21.6%)
↑66.7%prior 36
2
CHEV52 (18.7%)
↑67.7%prior 31
3
CHEVROLET24 (8.6%)
↑20.0%prior 20
4
TOYT13 (4.7%)
↑160.0%prior 5
5
DODG11 (4%)
↓-45.0%prior 20
6
GMC9 (3.2%)
↓-35.7%prior 14
7
DODGE8 (2.9%)
8
JEEP8 (2.9%)
↓-11.1%prior 9
9
CHRY7 (2.5%)
↑40.0%prior 5
10
HOND7 (2.5%)

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

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

Sex Distribution (229 persons with recorded sex)

Male131 (57.2%)
↓-7.7%prior 142
Female98 (42.8%)
↑36.1%prior 72

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: 176
  • Total persons involved: 353
  • Total vehicles involved: 278

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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