Yearly Traffic Safety Analysis

111 CRASHES IN
IOWA, IA
2021

All metrics benchmarked against2020

In Monroe County, total traffic crashes decreased by 8.3% from 121 in 2020 to 111 in 2021. While the number of fatal crashes dropped from one to zero, the total number of injuries reported increased by 60.9%, from 23 to 37, during the same period. The most significant contributing factor in both years remained collisions with animals.

111

▼ -8.3%was 121

Total Crash Events

0

▼ -100.0%was 1

Persons Killed

37

▲ 60.9%was 23

Persons Injured

0

▼ -100.0%was 1

Fatal Crash Events

Note: "Persons Killed" (0) counts individual fatalities across all crash events. "Fatal" in the severity table below (0) 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

Overall, traffic collisions in Monroe County saw a modest decline in 2021, with total crashes falling to 111 from 121 in the prior year. This decrease in crash volume was accompanied by a significant 60.9% increase in the number of people injured, which rose from 23 to 37. The number of fatalities fell from one in 2020 to zero in 2021.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

0

Motorists Killed

Prior: 1↓-100.0%

1

Pedestrians Injured

Prior: 0→%

36

Motorists Injured

Prior: 23↑56.5%

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 showed some shifts between 2020 and 2021. The most common day for crashes changed from Thursday (29 crashes) in 2020 to Monday (24 crashes) in 2021. However, the peak hour for collisions remained consistent, with the 5 p.m. hour having the highest frequency in both years, accounting for 13 crashes in 2020 and 15 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

In 2021, Monroe County recorded zero fatal crashes, a decrease from one fatal crash in 2020. Despite a lower overall crash total, the proportion of injury-related crashes increased, with the total number of injured persons rising from 23 to 37. Crashes resulting in minor injuries more than doubled from 6 incidents in 2020 to 14 in 2021, and their share of all crashes increased from 5.0% to 12.6%.

Outcome by Severity (Crash Events)

Serious Injury3serious injury crashes2.7%
→0.0%prior 3
Minor Injury14minor injury crashes12.6%
↑133.3%prior 6
Possible Injury13possible injury crashes11.7%
↑8.3%prior 12
No Injury81no injury crashes73%
↓-18.2%prior 99

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 animals remained the top contributing factor in both periods, though the count of these incidents decreased from 51 in 2020 to 43 in 2021. The count of crashes attributed to 'Followed too close' increased from 6 to 10, making it the second-most cited factor in 2021. Conversely, incidents where a driver 'Ran Stop Sign' saw a notable decrease, falling from 6 crashes in 2020 to just one in 2021.

Officer-Reported Primary Contributing Cause

Animal43 (38.7%)↓-15.7%prior 51
Followed too close10 (9%)↑66.7%prior 6
Lost Control8 (7.2%)→0.0%prior 8
Ran off road - left5 (4.5%)→0.0%prior 5
Other (explain in narrative): Other5 (4.5%)↓-28.6%prior 7
Driving too fast for conditions4 (3.6%)
Other (explain in narrative): No improper action3 (2.7%)
Failed to keep in proper lane3 (2.7%)
Operating vehicle in an reckless, erratic, careless, negligent manner3 (2.7%)
FTYROW: From stop sign3 (2.7%)↓-57.1%prior 7

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 in 2021 occurred more frequently during clear weather and daylight conditions compared to 2020. The proportion of crashes in daylight increased from 41.3% to 47.7% of all crashes year-over-year. Notably, there was a significant reduction in crashes occurring in dark, unlighted roadway conditions, with the count of these incidents falling from 26 in 2020 to 13 in 2021. The share of crashes on dry road surfaces remained relatively stable across both years.

Weather

Clear63 (77.8%)
↑3.3%prior 61
Cloudy12 (14.8%)
↓-14.3%prior 14
Rain5 (6.2%)
↓-28.6%prior 7
Fog, smoke, smog1 (1.2%)

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

Lighting

Daylight53 (65.4%)
↑6.0%prior 50
Dark - roadway not lighted13 (16.0%)
↓-50.0%prior 26
Dawn9 (11.1%)
↑50.0%prior 6
Dusk4 (4.9%)
Dark - roadway lighted2 (2.5%)

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

Road Surface

Dry62 (76.5%)
↓-6.1%prior 66
Wet9 (11.1%)
↓-25.0%prior 12
Ice/frost4 (4.9%)
Gravel3 (3.7%)
↓-50.0%prior 6
Snow2 (2.5%)
Slush1 (1.2%)

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

Vehicles & Demographics

Chevrolet and Ford were the top two vehicle makes involved in crashes in both 2020 and 2021. Chevrolet involvements decreased from 46 to 43, while Ford involvements increased from 30 to 32. There was a notable shift in the age distribution of persons involved in crashes; the 35-44 age group became the most represented with 46 individuals in 2021, an increase from 36 in 2020. Meanwhile, the 26-34 age group's involvement decreased from 43 to 25.

Top Vehicle Makes (163 vehicles)

1
FORD32 (19.6%)
↑6.7%prior 30
2
CHEV30 (18.4%)
↓-14.3%prior 35
3
DODG19 (11.7%)
↑35.7%prior 14
4
CHEVROLET13 (8%)
↑18.2%prior 11
5
BUIC6 (3.7%)
6
JEEP5 (3.1%)
↓-50.0%prior 10
7
TOYOTA4 (2.5%)
↓-20.0%prior 5
8
DODGE4 (2.5%)
9
PONT3 (1.8%)
10
TOYO3 (1.8%)

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

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

Sex Distribution (124 persons with recorded sex)

Male76 (61.3%)
↓-16.5%prior 91
Female48 (38.7%)
↓-36.0%prior 75

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: 111
  • Total persons involved: 207
  • Total vehicles involved: 163

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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