Yearly Traffic Safety Analysis

819 CRASHES IN
IOWA, IA
2021

All metrics benchmarked against2020

In Des Moines County, total traffic crashes increased from 761 in 2020 to 819 in 2021, a rise of approximately 7.6%. This period also saw total injuries increase by 14.4% from 180 to 206. A notable shift in contributing factors was observed, with crashes attributed to failure to yield while making a left turn increasing by 84.6%, from 26 incidents in 2020 to 48 in 2021.

819

▲ 7.6%was 761

Total Crash Events

3

▲ 50.0%was 2

Persons Killed

206

▲ 14.4%was 180

Persons Injured

3

▲ 50.0%was 2

Fatal Crash Events

Note: "Persons Killed" (3) counts individual fatalities across all crash events. "Fatal" in the severity table below (3) 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 for Des Moines County indicates an upward trend from 2020 to 2021. Total crashes rose by 7.6%, from 761 to 819 incidents. This increase was accompanied by a 14.4% rise in total injuries, from 180 to 206, and an increase in fatalities from 2 to 3.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 0→%

1

Cyclists Killed

Prior: 1→0.0%

1

Motorists Killed

Prior: 1→0.0%

5

Pedestrians Injured

Prior: 7↓-28.6%

7

Cyclists Injured

Prior: 5↑40.0%

194

Motorists Injured

Prior: 168↑15.5%

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 temporal patterns of crashes in Des Moines County shifted between 2020 and 2021. The most common day for crashes changed from Tuesday (123 crashes) in 2020 to Friday (142 crashes) in 2021. The peak hour for collisions also shifted earlier, from the 3 p.m. hour in 2020 (61 crashes) to the 1 p.m. hour in 2021 (62 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

The severity of crashes saw a slight increase from 2020 to 2021. The number of fatal crashes rose from 2 to 3, and the fatal crash rate increased from 0.26% to 0.37%. Serious injury crashes also increased in both count (from 14 to 17) and as a proportion of all crashes (from 1.8% to 2.1%). Conversely, the share of crashes resulting in possible injuries decreased from 13.7% in 2020 to 12.3% in 2021.

Outcome by Severity (Crash Events)

Fatal3fatal crashes0.4%
↑50.0%prior 2
Serious Injury17serious injury crashes2.1%
↑21.4%prior 14
Minor Injury64minor injury crashes7.8%
↑8.5%prior 59
Possible Injury101possible injury crashes12.3%
↓-2.9%prior 104
No Injury634no injury crashes77.4%
↑8.9%prior 582

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

While collisions with animals remained the top contributing factor in both periods, the count decreased slightly from 128 in 2020 to 123 in 2021. Significant shifts occurred in other driver-related factors. Crashes involving 'Failure to Yield Right of Way: Making left turn' saw a substantial increase, rising by 84.6% from 26 incidents in 2020 to 48 in 2021. 'Followed too close' also increased in count from 42 to 56. Conversely, crashes attributed to 'Failure to Yield Right of Way: From stop sign' decreased by 34.1%, from 44 incidents in 2020 to 29 in 2021.

Officer-Reported Primary Contributing Cause

Animal123 (15%)↓-3.9%prior 128
Other (explain in narrative): Other84 (10.3%)↑33.3%prior 63
Followed too close56 (6.8%)↑33.3%prior 42
FTYROW: Making left turn48 (5.9%)↑84.6%prior 26
Driver Distraction: Other interior distraction45 (5.5%)↑18.4%prior 38
Driving too fast for conditions42 (5.1%)↑27.3%prior 33
Ran off road - left41 (5%)↓-2.4%prior 42
Lost Control33 (4%)↑37.5%prior 24
FTYROW: From stop sign29 (3.5%)↓-34.1%prior 44
Other (explain in narrative): No improper action23 (2.8%)↑4.5%prior 22

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 proportion of crashes occurring in clear weather and on dry roads remained relatively stable between 2020 and 2021. However, there was an increase in crashes during rainy conditions, which rose from 39 incidents (5.1% of total) in 2020 to 57 incidents (7.0% of total) in 2021. Crashes on wet road surfaces similarly increased from 77 to 96. Conversely, incidents in dark, unlighted conditions decreased from 77 in 2020 to 51 in 2021, and crashes on icy or frosty roads fell from 33 to 22.

Weather

Clear476 (66.9%)
↑5.1%prior 453
Cloudy128 (18.0%)
↑6.7%prior 120
Rain57 (8.0%)
↑46.2%prior 39
Snow33 (4.6%)
↑22.2%prior 27
Freezing rain/drizzle7 (1.0%)
↓-30.0%prior 10
Blowing Snow3 (0.4%)
Severe Winds3 (0.4%)
Sleet, hail2 (0.3%)
Other (explain in narrative)2 (0.3%)
Fog, smoke, smog1 (0.1%)

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

Lighting

Daylight499 (70.0%)
↑19.4%prior 418
Dark - roadway lighted122 (17.1%)
↓-1.6%prior 124
Dark - roadway not lighted51 (7.2%)
↓-33.8%prior 77
Dusk25 (3.5%)
→0.0%prior 25
Dawn14 (2.0%)
↑133.3%prior 6
Dark - unknown roadway lighting2 (0.3%)
↓-60.0%prior 5

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

Road Surface

Dry523 (73.1%)
↑5.2%prior 497
Wet96 (13.4%)
↑24.7%prior 77
Snow51 (7.1%)
↑155.0%prior 20
Ice/frost22 (3.1%)
↓-33.3%prior 33
Gravel11 (1.5%)
↓-45.0%prior 20
Slush7 (1.0%)
↑40.0%prior 5
Mud, dirt3 (0.4%)
Water (standing or moving)2 (0.3%)

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 remained consistent, with Ford and Chevrolet variants appearing as the most frequent in both 2020 and 2021. An analysis of persons involved in crashes shows notable shifts in age demographics. The number of individuals in the 35-44 age group involved in crashes increased from 204 in 2020 to 262 in 2021. The 65+ age group also saw an increase in involvement, rising from 168 persons in 2020 to 193 in 2021.

Top Vehicle Makes (1,398 vehicles)

1
FORD220 (15.7%)
↑12.8%prior 195
2
CHEV141 (10.1%)
↓-21.2%prior 179
3
CHEVROLET126 (9%)
↑18.9%prior 106
4
DODG62 (4.4%)
↓-11.4%prior 70
5
KIA62 (4.4%)
↑47.6%prior 42
6
GMC59 (4.2%)
↑13.5%prior 52
7
JEEP47 (3.4%)
↓-11.3%prior 53
8
TOYO45 (3.2%)
↑40.6%prior 32
9
NR42 (3%)
↓-16.0%prior 50
10
DODGE42 (3%)
↑68.0%prior 25

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

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

Sex Distribution (1,093 persons with recorded sex)

Male601 (55.0%)
↑4.9%prior 573
Female492 (45.0%)
↑9.1%prior 451

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: 819
  • Total persons involved: 1,735
  • Total vehicles involved: 1,398

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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