Yearly Traffic Safety Analysis

116 CRASHES IN
IOWA, IA
2021

All metrics benchmarked against2020

In Montgomery County, total traffic crashes increased by 3.6%, from 112 in 2020 to 116 in 2021. Despite the slight rise in total incidents, there was a significant improvement in crash severity. The most notable year-over-year change was the reduction in traffic fatalities, which dropped from 3 in 2020 to zero in 2021.

116

▲ 3.6%was 112

Total Crash Events

0

▼ -100.0%was 3

Persons Killed

30

▼ -16.7%was 36

Persons Injured

0

▼ -100.0%was 2

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 crash trends were mixed for Montgomery County. The total number of crashes saw a slight increase of 3.6%, rising from 112 in 2020 to 116 in 2021. However, the severity of these incidents decreased, with total injuries falling by 16.7% from 36 to 30, and fatalities being eliminated entirely from 3 to 0.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 3↓-100.0%

30

Motorists Injured

Prior: 35↓-14.3%

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 showed some shifts between the two periods. The peak day for crashes moved from Monday, with 23 incidents in 2020, to Friday, with 21 incidents in 2021. The peak hour for collisions, however, remained consistent at 5 p.m. in both years, though the number of crashes during that hour fell from 15 in 2020 to 12 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

Crash severity outcomes improved significantly in 2021 compared to the prior year. The number of fatal crashes dropped from 2 to 0, and total fatalities fell from 3 to 0. The number of crashes resulting in serious injuries also decreased from 5 in 2020 to 1 in 2021, representing a drop in the share of serious injury crashes from 4.5% to 0.9% of the total.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes0.9%
↓-80.0%prior 5
Minor Injury7minor injury crashes6%
↓-36.4%prior 11
Possible Injury16possible injury crashes13.8%
↑45.5%prior 11
No Injury92no injury crashes79.3%
↑10.8%prior 83

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 with animals remained the leading contributing factor in both years, though the count of such incidents decreased from 28 in 2020 to 23 in 2021. Notably, crashes attributed to 'Lost Control' fell from 13 incidents in 2020 to just 1 in 2021. Conversely, incidents involving 'Ran Stop Sign' doubled from 4 to 8, and crashes related to 'Driver Distraction: Other interior distraction' increased from 4 to 9.

Officer-Reported Primary Contributing Cause

Animal23 (19.8%)↓-17.9%prior 28
Driver Distraction: Other interior distraction9 (7.8%)
FTYROW: From stop sign8 (6.9%)↑60.0%prior 5
Ran Stop Sign8 (6.9%)
Improper Backing6 (5.2%)
FTYROW: Making left turn6 (5.2%)
Driving too fast for conditions6 (5.2%)→0.0%prior 6
Operating vehicle in an reckless, erratic, careless, negligent manner6 (5.2%)
FTYROW: At uncontrolled intersection5 (4.3%)
Followed too close4 (3.4%)

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 were more likely to occur in favorable conditions compared to 2020. The number of incidents on dry road surfaces increased from 67 to 77, while crashes on snow or ice-covered roads decreased from 12 to 7. Similarly, crashes in clear weather rose from 57 to 72, whereas snow-related weather crashes fell from 6 to 2. The distribution of crashes by lighting conditions remained relatively stable, with daylight being the predominant condition in both years.

Weather

Clear72 (72.0%)
↑26.3%prior 57
Cloudy18 (18.0%)
↓-18.2%prior 22
Rain5 (5.0%)
Snow2 (2.0%)
↓-66.7%prior 6
Fog, smoke, smog1 (1.0%)
Severe Winds1 (1.0%)
Blowing Snow1 (1.0%)

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

Lighting

Daylight67 (66.3%)
↓-1.5%prior 68
Dark - roadway not lighted16 (15.8%)
↑45.5%prior 11
Dusk8 (7.9%)
Dark - roadway lighted8 (7.9%)
↓-20.0%prior 10
Dawn1 (1.0%)
Dark - unknown roadway lighting1 (1.0%)

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

Road Surface

Dry77 (77.0%)
↑14.9%prior 67
Wet12 (12.0%)
↑71.4%prior 7
Ice/frost5 (5.0%)
Gravel3 (3.0%)
↓-50.0%prior 6
Snow2 (2.0%)
↓-75.0%prior 8
Sand1 (1.0%)

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

Vehicles & Demographics

An analysis of vehicles involved shows that Chevrolet models became the most common make in 2021 crashes with 48 vehicles, overtaking Ford, which was the top make in 2020 with 34 vehicles. Regarding driver and passenger demographics, the number of individuals aged 65 and older involved in crashes increased from 29 to 37 year-over-year. Conversely, the 26-34 age group saw a decrease in involvement, from 39 persons in 2020 to 34 in 2021.

Top Vehicle Makes (193 vehicles)

1
CHEVROLET26 (13.5%)
↑136.4%prior 11
2
FORD25 (13%)
↓-26.5%prior 34
3
CHEV22 (11.4%)
↓-15.4%prior 26
4
DODGE11 (5.7%)
→0.0%prior 11
5
JEEP11 (5.7%)
↑22.2%prior 9
6
DODG11 (5.7%)
↑57.1%prior 7
7
GMC7 (3.6%)
8
CHRY7 (3.6%)
↑40.0%prior 5
9
BUICK4 (2.1%)
10
NISS4 (2.1%)
↓-60.0%prior 10

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 (155 persons with recorded sex)

Female80 (51.6%)
↑35.6%prior 59
Male75 (48.4%)
↓-17.6%prior 91

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: 116
  • Total persons involved: 244
  • Total vehicles involved: 193

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

ThatCarHitMe.com · An Injuria.ai Company