Yearly Traffic Safety Analysis

177 CRASHES IN
IOWA, IA
2021

All metrics benchmarked against2020

In Emmet County, total traffic crashes increased by 15.7%, rising from 153 incidents in 2020 to 177 in 2021. While the overall number of injuries decreased from 35 to 29, the most significant year-over-year change was a sharp rise in crash severity. The number of fatalities increased from one in 2020 to four in 2021, corresponding to an increase in fatal crashes from one to four.

177

▲ 15.7%was 153

Total Crash Events

4

▲ 300.0%was 1

Persons Killed

29

▼ -17.1%was 35

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

Crash data for Emmet County indicates a rising trend in collision frequency from 2020 to 2021. The total number of crashes grew by 15.7%, from 153 to 177. While the number of reported injuries declined by 17.1% (from 35 to 29), the number of fatalities increased from one to four during the same period.

Vulnerable Road User Casualties

4

Motorists Killed

Prior: 0→%

29

Motorists Injured

Prior: 33↓-12.1%

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 timing of crashes in Emmet County shifted between 2020 and 2021. The peak day for incidents moved from Thursday (31 crashes) in 2020 to a tie between Wednesday and Friday (28 crashes each) in 2021. A more pronounced change occurred in the peak hour, which shifted from the 5 p.m. evening commute hour in 2020 (15 crashes) to the 6 a.m. morning hour in 2021 (12 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 significantly in 2021 compared to the prior year. The number of fatal crashes increased from one to four, and the fatal crash rate rose from 0.65 to 2.26 per 100 crashes. While the proportion of crashes resulting in minor or possible injuries decreased from a combined 22.2% in 2020 to 14.7% in 2021, the current year saw the emergence of two serious injury crashes, a category not present in the prior year's data. Consequently, the share of crashes with no reported injuries increased from 77.1% to 81.9%.

Outcome by Severity (Crash Events)

Fatal4fatal crashes2.3%
↑300.0%prior 1
Serious Injury2serious injury crashes1.1%
Minor Injury15minor injury crashes8.5%
↓-11.8%prior 17
Possible Injury11possible injury crashes6.2%
↓-35.3%prior 17
No Injury145no injury crashes81.9%
↑22.9%prior 118

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 2020 and 2021, though the count of such incidents decreased from 48 to 44. The top three factors were consistent across both years, with "Lost Control" increasing from 13 to 14 crashes and "Other (explain in narrative): Other" decreasing from 14 to 13. Notably, crashes caused by "Followed too close" decreased by 40%, from 10 incidents in 2020 to 6 in 2021, while incidents attributed to "Driving too fast for conditions" remained unchanged at nine.

Officer-Reported Primary Contributing Cause

Animal44 (24.9%)↓-8.3%prior 48
Lost Control14 (7.9%)↑7.7%prior 13
Other (explain in narrative): Other13 (7.3%)↓-7.1%prior 14
Driving too fast for conditions9 (5.1%)→0.0%prior 9
Ran off road - left8 (4.5%)
Ran off road - straight6 (3.4%)
Followed too close6 (3.4%)↓-40.0%prior 10
FTYROW: At uncontrolled intersection5 (2.8%)↓-16.7%prior 6
FTYROW: From driveway5 (2.8%)
Driver Distraction: Other interior distraction5 (2.8%)→0.0%prior 5

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

Road & Environmental Conditions

Crashes were more likely to occur in clear weather and on dry roads in 2021 compared to 2020. The proportion of crashes in clear weather increased from 52.9% to 60.5%, while those on dry road surfaces rose from 51.0% to 61.0%. Regarding lighting, the proportion of crashes in daylight remained stable at approximately 52%, but crashes in dark conditions (both lighted and unlighted roadways) increased from a combined 20.2% of crashes in 2020 to 24.9% in 2021.

Weather

Clear107 (72.8%)
↑32.1%prior 81
Cloudy19 (12.9%)
↑18.8%prior 16
Freezing rain/drizzle6 (4.1%)
Snow5 (3.4%)
Rain4 (2.7%)
↓-33.3%prior 6
Fog, smoke, smog3 (2.0%)
Blowing Snow2 (1.4%)
↓-60.0%prior 5
Other (explain in narrative)1 (0.7%)

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

Lighting

Daylight92 (61.7%)
↑16.5%prior 79
Dark - roadway not lighted27 (18.1%)
↑42.1%prior 19
Dark - roadway lighted17 (11.4%)
↑41.7%prior 12
Dawn8 (5.4%)
Dusk3 (2.0%)
Dark - unknown roadway lighting2 (1.3%)

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

Road Surface

Dry108 (73.0%)
↑38.5%prior 78
Wet11 (7.4%)
→0.0%prior 11
Snow11 (7.4%)
↑57.1%prior 7
Ice/frost10 (6.8%)
↓-33.3%prior 15
Gravel5 (3.4%)
Mud, dirt2 (1.4%)
Slush1 (0.7%)

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

Vehicles & Demographics

The makes of vehicles involved in crashes remained broadly consistent year-over-year, with Chevrolet, Ford, and GMC being the most common in both 2021 and 2020. However, analysis of the age of persons involved reveals notable demographic shifts. The number of individuals aged 65 and older involved in crashes increased from 41 to 51, and their share of all persons involved grew from 12.9% to 17.2%. Conversely, the 26-34 age group saw a significant decrease in involvement, dropping from 47 individuals in 2020 to 29 in 2021.

Top Vehicle Makes (264 vehicles)

1
CHEV49 (18.6%)
↑16.7%prior 42
2
FORD37 (14%)
↓-7.5%prior 40
3
CHEVROLET32 (12.1%)
↑18.5%prior 27
4
GMC17 (6.4%)
↑21.4%prior 14
5
TOYO12 (4.5%)
6
DODG9 (3.4%)
→0.0%prior 9
7
JEEP9 (3.4%)
8
NR9 (3.4%)
↑80.0%prior 5
9
PONT8 (3%)
↑33.3%prior 6
10
BUIC8 (3%)
↑33.3%prior 6

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

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

Sex Distribution (190 persons with recorded sex)

Male113 (59.5%)
↑1.8%prior 111
Female77 (40.5%)
↓-9.4%prior 85

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: 177
  • Total persons involved: 297
  • Total vehicles involved: 264

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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