Yearly Traffic Safety Analysis

730 CRASHES IN
IOWA, IA
2021

All metrics benchmarked against2020

In 2021, Marshall County recorded 730 total crashes, a 16.4% increase from the 627 crashes documented in 2020. This period saw a notable rise in traffic fatalities, which increased from 3 in the prior year to 8 in the current year. Concurrently, the total number of injuries rose from 203 to 242.

730

16.4%was 627

Total Crash Events

8

166.7%was 3

Persons Killed

242

19.2%was 203

Persons Injured

8

166.7%was 3

Fatal Crash Events

Note: "Persons Killed" (8) counts individual fatalities across all crash events. "Fatal" in the severity table below (8) 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 trends in Marshall County showed an increase year-over-year, with total collisions rising by 16.4% from 627 in 2020 to 730 in 2021. This upward trend was also reflected in crash outcomes, as total injuries increased by 19.2% and fatalities more than doubled, rising from 3 to 8.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Cyclists Killed

Prior: 00.0%

8

Motorists Killed

Prior: 3166.7%

0

Other Killed

Prior: 00.0%

5

Pedestrians Injured

Prior: 2150.0%

3

Cyclists Injured

Prior: 30.0%

233

Motorists Injured

Prior: 19817.7%

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

While Friday remained the peak day for crashes in both 2020 (113 incidents) and 2021 (136 incidents), the peak hour shifted two hours earlier. In 2021, the 3 p.m. hour saw the most crashes with 76, compared to the 5 p.m. peak of 51 crashes in 2020. Crash volume in December 2021 (102) was substantially higher than in December 2020 (55).

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 increased from 2020 to 2021, with fatal crashes rising from 3 to 8 and the corresponding fatal crash rate increasing from 0.48% to 1.1%. While the count of serious injury crashes decreased from 19 to 15, crashes resulting in minor or possible injuries increased in total from 156 to 177. The proportion of non-injury crashes remained stable at 72.6% in 2021, compared to 71.6% in 2020.

Outcome by Severity (Crash Events)

Fatal8fatal crashes1.1%
166.7%prior 3
Serious Injury15serious injury crashes2.1%
-21.1%prior 19
Minor Injury79minor injury crashes10.8%
17.9%prior 67
Possible Injury98possible injury crashes13.4%
10.1%prior 89
No Injury530no injury crashes72.6%
18.0%prior 449

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, increasing from 110 incidents in 2020 to 120 in 2021. 'Lost Control' became the second most frequent factor, with incidents rising by 47.8% from 46 to 68. In contrast, 'Failure to yield from a stop sign' incidents decreased from 57 to 53. Other factors with notable increases in count include 'Followed too close' (from 25 to 43) and 'Driving too fast for conditions' (from 21 to 36).

Officer-Reported Primary Contributing Cause

Animal120 (16.4%)9.1%prior 110
Lost Control68 (9.3%)47.8%prior 46
FTYROW: From stop sign53 (7.3%)-7.0%prior 57
Followed too close43 (5.9%)72.0%prior 25
Other (explain in narrative): Other42 (5.8%)35.5%prior 31
Driving too fast for conditions36 (4.9%)71.4%prior 21
FTYROW: Making left turn32 (4.4%)128.6%prior 14
Ran off road - left28 (3.8%)21.7%prior 23
Ran Stop Sign26 (3.6%)36.8%prior 19
Ran off road - straight24 (3.3%)-7.7%prior 26

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

Road & Environmental Conditions

Most crashes in both periods occurred during daylight hours on dry roads. In 2021, crashes in daylight increased in both absolute count (from 330 to 408) and as a share of all crashes (from 52.6% to 55.9%). The proportion of crashes occurring on adverse road surfaces such as ice, snow, or wet pavement remained consistent, accounting for 17.8% of incidents in 2021 compared to 18.7% in 2020.

Weather

Clear458 (73.0%)
22.1%prior 375
Cloudy94 (15.0%)
2.2%prior 92
Freezing rain/drizzle23 (3.7%)
130.0%prior 10
Snow17 (2.7%)
0.0%prior 17
Rain12 (1.9%)
-29.4%prior 17
Severe Winds11 (1.8%)
Blowing Snow7 (1.1%)
-46.2%prior 13
Fog, smoke, smog5 (0.8%)

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

Lighting

Daylight408 (64.6%)
23.6%prior 330
Dark - roadway not lighted101 (16.0%)
21.7%prior 83
Dark - roadway lighted100 (15.8%)
4.2%prior 96
Dawn10 (1.6%)
42.9%prior 7
Dusk9 (1.4%)
-30.8%prior 13
Dark - unknown roadway lighting4 (0.6%)

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

Road Surface

Dry485 (77.0%)
22.8%prior 395
Ice/frost52 (8.3%)
92.6%prior 27
Wet36 (5.7%)
-25.0%prior 48
Snow33 (5.2%)
10.0%prior 30
Gravel13 (2.1%)
-23.5%prior 17
Slush9 (1.4%)
-25.0%prior 12
Mud, dirt1 (0.2%)
Other (explain in narrative)1 (0.2%)

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

Vehicles & Demographics

Ford and Chevrolet remained the top two vehicle makes involved in crashes, with both seeing an increase in total incidents from 2020 to 2021; Fords increased from 160 to 175, and Chevrolets rose from 209 to 239. An analysis of persons involved in crashes shows a demographic shift, with the 65+ age group's involvement increasing from 137 individuals (9.5% of total) in 2020 to 174 (11.7% of total) in 2021.

Top Vehicle Makes (1,177 vehicles)

1
FORD175 (14.9%)
9.4%prior 160
2
CHEV154 (13.1%)
6.9%prior 144
3
CHEVROLET85 (7.2%)
30.8%prior 65
4
HOND51 (4.3%)
13.3%prior 45
5
DODG48 (4.1%)
-9.4%prior 53
6
GMC47 (4%)
30.6%prior 36
7
TOYT44 (3.7%)
15.8%prior 38
8
DODGE43 (3.7%)
34.4%prior 32
9
JEEP42 (3.6%)
44.8%prior 29
10
HONDA38 (3.2%)
58.3%prior 24

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

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

Sex Distribution (921 persons with recorded sex)

Male550 (59.7%)
10.2%prior 499
Female371 (40.3%)
0.5%prior 369

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: 730
  • Total persons involved: 1,486
  • Total vehicles involved: 1,177

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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