Yearly Traffic Safety Analysis

322 CRASHES IN
IOWA, IA
2021

All metrics benchmarked against2020

In 2021, Poweshiek County recorded 322 total crashes, an increase from the 274 crashes documented in 2020, representing a 17.5% rise. The total number of people injured also increased from 79 to 94. Notably, after recording zero traffic fatalities in the prior year, there were two fatalities resulting from two separate fatal crashes in 2021.

322

▲ 17.5%was 274

Total Crash Events

2

Persons Killed

94

▲ 19.0%was 79

Persons Injured

2

Fatal Crash Events

Note: "Persons Killed" (2) counts individual fatalities across all crash events. "Fatal" in the severity table below (2) 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 Poweshiek County showed a notable increase year-over-year. Total crashes rose by 17.5%, from 274 in 2020 to 322 in 2021. This upward trend was also reflected in the number of people injured, which increased by 19.0% from 79 to 94.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

0

Cyclists Killed

Prior: 0→0.0%

2

Motorists Killed

Prior: 0→%

2

Pedestrians Injured

Prior: 1↑100.0%

1

Cyclists Injured

Prior: 0→%

91

Motorists Injured

Prior: 78↑16.7%

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 saw some shifts between the two periods. In 2021, the peak day for crashes was Monday with 57 incidents, a change from Friday (56 incidents) in 2020. The peak hour for crashes also shifted later in the day, from the 4 p.m. hour in 2020 (23 crashes) to the 6 p.m. hour in 2021 (22 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

Crash severity worsened in 2021 compared to the previous year, with the county recording two fatal crashes after having none in 2020. The proportion of serious injury crashes increased from 1.8% to 2.8% of all incidents, and minor injury crashes grew from 6.2% to 9.0%. Conversely, crashes resulting in possible injuries decreased as a share of the total, from 15.0% in 2020 to 11.2% in 2021.

Outcome by Severity (Crash Events)

Fatal2fatal crashes0.6%
Serious Injury9serious injury crashes2.8%
↑80.0%prior 5
Minor Injury29minor injury crashes9%
↑70.6%prior 17
Possible Injury36possible injury crashes11.2%
↓-12.2%prior 41
No Injury246no injury crashes76.4%
↑16.6%prior 211

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 remained consistent, though their counts shifted. Collisions involving an 'Animal' remained the top factor, with the count of such incidents increasing by 46% from 50 in 2020 to 73 in 2021. 'Driving too fast for conditions' and 'Lost Control' remained the second and third most common factors, with their counts staying relatively stable at 31 and 29 respectively. Crashes attributed to 'Failure to yield from a stop sign' also saw an increase, rising from 17 to 21 incidents.

Officer-Reported Primary Contributing Cause

Animal73 (22.7%)↑46.0%prior 50
Driving too fast for conditions31 (9.6%)↓-11.4%prior 35
Lost Control29 (9%)↓-3.3%prior 30
Ran off road - straight26 (8.1%)↓-10.3%prior 29
FTYROW: From stop sign21 (6.5%)↑23.5%prior 17
Followed too close20 (6.2%)↑5.3%prior 19
FTYROW: Making left turn14 (4.3%)↑133.3%prior 6
Ran off road - left14 (4.3%)↓-6.7%prior 15
Other (explain in narrative): Other10 (3.1%)↑42.9%prior 7
Other (explain in narrative): No improper action8 (2.5%)↑33.3%prior 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

A larger proportion of crashes in 2021 occurred during favorable conditions compared to 2020. Crashes in clear weather increased from representing 45.3% to 52.8% of the total, while those on dry road surfaces rose from 51.5% to 58.1%. Correspondingly, the share of crashes happening in snowy conditions fell from 12.8% to 5.0%. Crashes during daylight hours also constituted a larger share of the total, increasing from 51.1% in 2020 to 55.6% in 2021.

Weather

Clear170 (65.1%)
↑37.1%prior 124
Cloudy46 (17.6%)
↑2.2%prior 45
Snow16 (6.1%)
↓-54.3%prior 35
Rain14 (5.4%)
→0.0%prior 14
Freezing rain/drizzle6 (2.3%)
↓-40.0%prior 10
Blowing Snow6 (2.3%)
Fog, smoke, smog3 (1.1%)

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

Lighting

Daylight179 (68.6%)
↑27.9%prior 140
Dark - roadway not lighted52 (19.9%)
↓-26.8%prior 71
Dark - roadway lighted14 (5.4%)
↑27.3%prior 11
Dawn9 (3.4%)
↑28.6%prior 7
Dusk4 (1.5%)
↓-33.3%prior 6
Dark - unknown roadway lighting3 (1.1%)

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

Road Surface

Dry187 (71.6%)
↑32.6%prior 141
Wet26 (10.0%)
↑18.2%prior 22
Snow22 (8.4%)
↓-31.3%prior 32
Ice/frost12 (4.6%)
↓-53.8%prior 26
Gravel7 (2.7%)
↓-46.2%prior 13
Slush7 (2.7%)

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 vehicles being the most frequent in both years. Ford vehicle involvements increased from 55 to 73. Analysis of persons involved shows a shift in age demographics; the number of individuals in the 55-64 age group involved in crashes increased from 61 to 99, and the 21-25 age group grew from 59 to 78. Meanwhile, the 65+ age group saw a decrease in involvement from 70 to 59 persons.

Top Vehicle Makes (491 vehicles)

1
FORD73 (14.9%)
↑32.7%prior 55
2
CHEV71 (14.5%)
↑65.1%prior 43
3
CHEVROLET33 (6.7%)
↑37.5%prior 24
4
DODGE16 (3.3%)
↑45.5%prior 11
5
TOYOTA16 (3.3%)
↑60.0%prior 10
6
HONDA15 (3.1%)
7
TOYO15 (3.1%)
↑36.4%prior 11
8
KIA15 (3.1%)
↑87.5%prior 8
9
JEEP13 (2.6%)
↓-18.8%prior 16
10
GMC13 (2.6%)
↑18.2%prior 11

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

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

Sex Distribution (411 persons with recorded sex)

Male268 (65.2%)
↑15.5%prior 232
Female143 (34.8%)
↑9.2%prior 131

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: 322
  • Total persons involved: 612
  • Total vehicles involved: 491

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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