Monthly Traffic Safety Analysis

4,536 CRASHES IN
IOWA, IA
SEPTEMBER 2021

All metrics benchmarked againstSeptember 2020

In September 2021, Iowa recorded 4,536 total traffic crashes, a 9.5% increase from the 4,143 crashes reported in September 2020. While overall collisions rose, the number of fatalities slightly decreased from 41 to 38 year-over-year. The most significant trend was the overall rise in crash volume across the state.

4,536

9.5%was 4,143

Total Crash Events

38

-7.3%was 41

Persons Killed

1,513

-1.6%was 1,538

Persons Injured

35

-12.5%was 40

Fatal Crash Events

Note: "Persons Killed" (38) counts individual fatalities across all crash events. "Fatal" in the severity table below (35) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Iowa Crash Data · ArcGIS Open Data · 2021-09-01 to 2021-09-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Crash trends in September 2021 showed a notable increase in total collisions compared to the same month in the prior year. Total crashes rose by 9.5%, from 4,143 to 4,536. Despite this increase in crash volume, both total injuries and fatalities saw slight decreases, falling by 1.6% and 7.3% respectively.

Vulnerable Road User Casualties

2

Pedestrians Killed

Prior: 5-60.0%

3

Cyclists Killed

Prior: 0%

33

Motorists Killed

Prior: 36-8.3%

0

Other Killed

Prior: 00.0%

37

Pedestrians Injured

Prior: 39-5.1%

41

Cyclists Injured

Prior: 2657.7%

1,424

Motorists Injured

Prior: 1,470-3.1%

11

Other Injured

Prior: 3266.7%

Source: Iowa Crash Data · ArcGIS Open Data · 2021-09-01 to 2021-09-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes shifted between September 2020 and September 2021. The peak day for crashes moved from Tuesday (743 crashes) in the prior year to Thursday (847 crashes) in the current period. While the peak hour for collisions remained at 3 p.m. year-over-year, the number of crashes during this hour increased from 348 to 404.

Source: Iowa Crash Data · ArcGIS Open Data · 2021-09-01 to 2021-09-30 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2021-09-01 to 2021-09-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

While total crashes increased, the severity of those crashes showed a slight downward trend year-over-year. The fatal crash rate decreased from 0.97 per 100 crashes in September 2020 to 0.77 in September 2021, with fatal crashes dropping from 40 to 35. The proportion of crashes resulting in possible injury also decreased from 17.0% to 15.6% of all incidents. Conversely, the share of crashes with no reported injuries increased from 68.2% to 70.0%.

Severity is per crash event (most severe injury). 35 fatal crash events resulted in 38 persons killed.

Outcome by Severity (Crash Events)

Fatal35fatal crashes0.8%
-12.5%prior 40
Serious Injury126serious injury crashes2.8%
3.3%prior 122
Minor Injury492minor injury crashes10.8%
8.8%prior 452
Possible Injury709possible injury crashes15.6%
0.9%prior 703
No Injury3,174no injury crashes70%
12.3%prior 2,826

Source: Iowa Crash Data · ArcGIS Open Data · 2021-09-01 to 2021-09-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2021-09-01 to 2021-09-30 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factors shifted between the two periods. In September 2021, 'Followed too close' became the primary factor with 548 incidents, an increase of 98 crashes (a 21.8% count increase) from 450 in the prior year when it was ranked second. 'Animal' involvement, the top factor in 2020 with 503 crashes, saw a slight increase to 516 crashes but moved to the second position. Other notable changes include an increase in crashes attributed to 'Ran Traffic Signal,' which rose from 124 to 157 incidents, and a decrease in 'Ran off road - left' crashes from 271 to 228.

Officer-Reported Primary Contributing Cause

Followed too close548 (12.1%)21.8%prior 450
Animal516 (11.4%)2.6%prior 503
Other (explain in narrative): Other348 (7.7%)43.2%prior 243
FTYROW: From stop sign235 (5.2%)6.3%prior 221
Ran off road - left228 (5%)-15.9%prior 271
Lost Control217 (4.8%)-3.6%prior 225
FTYROW: Making left turn190 (4.2%)-2.6%prior 195
Driver Distraction: Other interior distraction172 (3.8%)39.8%prior 123
Operating vehicle in an reckless, erratic, careless, negligent manner160 (3.5%)35.6%prior 118
Ran Traffic Signal157 (3.5%)26.6%prior 124

Source: Iowa Crash Data · ArcGIS Open Data · 2021-09-01 to 2021-09-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes in September 2021 occurred under more favorable conditions compared to the same month in 2020. The proportion of crashes happening in clear weather increased from 64.0% to 77.3% of the total. Correspondingly, crashes during rain fell from a 10.8% share to 2.9%. A similar trend was observed for road surface conditions, with the percentage of crashes on wet surfaces decreasing from 16.3% in 2020 to 4.8% in 2021.

Weather

Clear3,509 (85.3%)
32.3%prior 2,652
Cloudy458 (11.1%)
-24.2%prior 604
Rain130 (3.2%)
-71.0%prior 448
Fog, smoke, smog6 (0.1%)
-68.4%prior 19
Other (explain in narrative)5 (0.1%)
Blowing sand, soil, dirt4 (0.1%)
Freezing rain/drizzle1 (0.0%)
-90.9%prior 11
Severe Winds1 (0.0%)

Source: Iowa Crash Data · ArcGIS Open Data · 2021-09-01 to 2021-09-30 · Weather condition at time of crash

Lighting

Daylight3,096 (75.1%)
14.5%prior 2,705
Dark - roadway lighted450 (10.9%)
-9.1%prior 495
Dark - roadway not lighted367 (8.9%)
0.3%prior 366
Dusk103 (2.5%)
-1.9%prior 105
Dawn83 (2.0%)
15.3%prior 72
Dark - unknown roadway lighting21 (0.5%)
90.9%prior 11

Source: Iowa Crash Data · ArcGIS Open Data · 2021-09-01 to 2021-09-30 · Lighting condition field

Road Surface

Dry3,793 (92.0%)
27.2%prior 2,982
Wet220 (5.3%)
-67.4%prior 675
Gravel99 (2.4%)
23.8%prior 80
Other (explain in narrative)4 (0.1%)
-33.3%prior 6
Mud, dirt4 (0.1%)
-50.0%prior 8
Oil2 (0.0%)
Snow1 (0.0%)

Source: Iowa Crash Data · ArcGIS Open Data · 2021-09-01 to 2021-09-30 · Road surface condition field

Vehicles & Demographics

The demographic profile of vehicles and persons involved in crashes remained largely stable year-over-year. The most common vehicle makes involved in collisions were consistent, with Ford and Chevrolet models leading in both September 2020 and September 2021. Similarly, the age distribution of all persons involved in crashes saw minimal change; the 26-34 age group constituted the largest single cohort in both periods, representing 14.7% of individuals in 2020 and 15.0% in 2021.

Top Vehicle Makes (7,978 vehicles)

1
FORD1,237 (15.5%)
8.5%prior 1,140
2
CHEV923 (11.6%)
1.8%prior 907
3
CHEVROLET592 (7.4%)
6.7%prior 555
4
TOYT292 (3.7%)
2.5%prior 285
5
TOYOTA269 (3.4%)
59.2%prior 169
6
GMC267 (3.3%)
9.9%prior 243
7
JEEP255 (3.2%)
0.0%prior 255
8
HOND245 (3.1%)
10.9%prior 221
9
DODG243 (3%)
-12.6%prior 278
10
NR232 (2.9%)
0.0%prior 232

Source: Iowa Crash Data · ArcGIS Open Data · 2021-09-01 to 2021-09-30 · Vehicle unit records

1,272 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (6,226 persons with recorded sex)

Male3,492 (56.1%)
-5.9%prior 3,712
Female2,734 (43.9%)
3.1%prior 2,653

Source: Iowa Crash Data · ArcGIS Open Data · 2021-09-01 to 2021-09-30 · 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: 2021-09-01 through 2021-09-30
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2021-09-01 through 2021-09-30 (30 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 4,536
  • Total persons involved: 9,544
  • Total vehicles involved: 7,978

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: September 2021." Published September 9, 2026. Reporting period: 2021-09-01 to 2021-09-30. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/september-2021-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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