Monthly Traffic Safety Analysis

4,383 CRASHES IN
IOWA, IA
SEPTEMBER 2022

All metrics benchmarked againstSeptember 2021

In September 2022, there were 4,383 total crashes, a 3.4% decrease from the 4,536 crashes recorded in September 2021. While overall crashes and fatalities declined, the number of people injured increased by 4.7%, rising from 1,513 to 1,584. One of the most significant changes was a 21.3% year-over-year increase in crashes attributed to drivers failing to yield the right of way from a stop sign.

4,383

-3.4%was 4,536

Total Crash Events

33

-13.2%was 38

Persons Killed

1,584

4.7%was 1,513

Persons Injured

31

-11.4%was 35

Fatal Crash Events

Note: "Persons Killed" (33) counts individual fatalities across all crash events. "Fatal" in the severity table below (31) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Iowa Crash Data · ArcGIS Open Data · 2022-09-01 to 2022-09-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall crash volume in September 2022 showed a slight year-over-year decline, with total crashes falling by 3.4% from 4,536 to 4,383. This downward trend included a 13.2% decrease in fatalities, from 38 to 33. In contrast, the number of people injured in crashes rose by 4.7% compared to the same period last year, from 1,513 to 1,584.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 2-50.0%

0

Cyclists Killed

Prior: 3-100.0%

31

Motorists Killed

Prior: 33-6.1%

1

Other Killed

Prior: 0%

38

Pedestrians Injured

Prior: 372.7%

52

Cyclists Injured

Prior: 4126.8%

1,487

Motorists Injured

Prior: 1,4244.4%

7

Other Injured

Prior: 11-36.4%

Source: Iowa Crash Data · ArcGIS Open Data · 2022-09-01 to 2022-09-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The time of day with the most crashes remained consistent, with the 3 PM hour being the peak period in both September 2022 (396 crashes) and September 2021 (404 crashes). However, the peak day for crashes shifted from Thursday in the prior year (847 crashes) to Friday in the current year (897 crashes). Fridays saw a notable 24.4% increase in crash volume year-over-year, rising from 721 incidents.

Source: Iowa Crash Data · ArcGIS Open Data · 2022-09-01 to 2022-09-30 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2022-09-01 to 2022-09-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The proportion of fatal crashes decreased slightly, from 0.8% of all crashes in September 2021 to 0.7% in September 2022. Crashes resulting in serious injuries also saw a proportional decrease, accounting for 2.4% of incidents compared to 2.8% the previous year. However, the overall share of crashes resulting in any level of injury rose from 29.3% to 30.4% year-over-year, while the share of no-injury crashes declined from 70.0% to 68.9%.

Severity is per crash event (most severe injury). 31 fatal crash events resulted in 33 persons killed.

Outcome by Severity (Crash Events)

Fatal31fatal crashes0.7%
-11.4%prior 35
Serious Injury104serious injury crashes2.4%
-17.5%prior 126
Minor Injury489minor injury crashes11.2%
-0.6%prior 492
Possible Injury741possible injury crashes16.9%
4.5%prior 709
No Injury3,018no injury crashes68.9%
-4.9%prior 3,174

Source: Iowa Crash Data · ArcGIS Open Data · 2022-09-01 to 2022-09-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2022-09-01 to 2022-09-30 · Most severe injury per crash record

Top Contributing Factors

Following too closely remained the leading contributing factor in both periods, though its count decreased by 5.5% from 548 to 518 crashes. Crashes involving animals, the second-most common factor, also saw a notable 14.9% decline in count from 516 to 439. Conversely, crashes attributed to 'Failure to Yield Right of Way: From stop sign' increased by 21.3%, rising from 235 incidents in the prior year to 285 in the current period.

Officer-Reported Primary Contributing Cause

Followed too close518 (11.8%)-5.5%prior 548
Animal439 (10%)-14.9%prior 516
Other (explain in narrative): Other307 (7%)-11.8%prior 348
FTYROW: From stop sign285 (6.5%)21.3%prior 235
Lost Control225 (5.1%)3.7%prior 217
Ran off road - left208 (4.7%)-8.8%prior 228
FTYROW: Making left turn201 (4.6%)5.8%prior 190
Ran Traffic Signal167 (3.8%)6.4%prior 157
Driver Distraction: Other interior distraction151 (3.4%)-12.2%prior 172
Operating vehicle in an reckless, erratic, careless, negligent manner138 (3.1%)-13.8%prior 160

Source: Iowa Crash Data · ArcGIS Open Data · 2022-09-01 to 2022-09-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The majority of crashes in both periods occurred in clear weather on dry roads. However, there was an increase in the proportion of crashes under adverse conditions in September 2022 compared to the prior year. Crashes during rainy weather increased their share of the total from 2.9% to 4.0%. Similarly, incidents on wet road surfaces rose from 4.8% to 6.5% of all crashes.

Weather

Clear3,297 (82.3%)
-6.0%prior 3,509
Cloudy502 (12.5%)
9.6%prior 458
Rain174 (4.3%)
33.8%prior 130
Fog, smoke, smog15 (0.4%)
150.0%prior 6
Other (explain in narrative)7 (0.2%)
40.0%prior 5
Freezing rain/drizzle6 (0.1%)
Severe Winds2 (0.0%)
Blowing sand, soil, dirt2 (0.0%)
Sleet, hail2 (0.0%)

Source: Iowa Crash Data · ArcGIS Open Data · 2022-09-01 to 2022-09-30 · Weather condition at time of crash

Lighting

Daylight3,036 (75.7%)
-1.9%prior 3,096
Dark - roadway lighted461 (11.5%)
2.4%prior 450
Dark - roadway not lighted330 (8.2%)
-10.1%prior 367
Dusk95 (2.4%)
-7.8%prior 103
Dawn69 (1.7%)
-16.9%prior 83
Dark - unknown roadway lighting18 (0.4%)
-14.3%prior 21

Source: Iowa Crash Data · ArcGIS Open Data · 2022-09-01 to 2022-09-30 · Lighting condition field

Road Surface

Dry3,594 (89.5%)
-5.2%prior 3,793
Wet286 (7.1%)
30.0%prior 220
Gravel119 (3.0%)
20.2%prior 99
Other (explain in narrative)10 (0.2%)
Mud, dirt5 (0.1%)

Source: Iowa Crash Data · ArcGIS Open Data · 2022-09-01 to 2022-09-30 · Road surface condition field

Vehicles & Demographics

The top vehicle makes involved in crashes remained consistent, with Ford and Chevrolet models being the most frequent in both periods. The number of Ford vehicles involved was nearly unchanged, decreasing from 1,237 to 1,221. The number of people involved in crashes increased across all major age brackets despite fewer total crashes, with the largest percentage increase seen in the 35-44 age group, which grew by 8.3% from 1,333 to 1,444 individuals.

Top Vehicle Makes (7,716 vehicles)

1
FORD1,221 (15.8%)
-1.3%prior 1,237
2
CHEV1,055 (13.7%)
14.3%prior 923
3
CHEVROLET373 (4.8%)
-37.0%prior 592
4
TOYT370 (4.8%)
26.7%prior 292
5
HOND320 (4.1%)
30.6%prior 245
6
JEEP316 (4.1%)
23.9%prior 255
7
DODG307 (4%)
26.3%prior 243
8
GMC271 (3.5%)
1.5%prior 267
9
NISS261 (3.4%)
34.5%prior 194
10
KIA208 (2.7%)
0.0%prior 208

Source: Iowa Crash Data · ArcGIS Open Data · 2022-09-01 to 2022-09-30 · Vehicle unit records

1,285 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (6,936 persons with recorded sex)

Male3,884 (56.0%)
11.2%prior 3,492
Female3,052 (44.0%)
11.6%prior 2,734

Source: Iowa Crash Data · ArcGIS Open Data · 2022-09-01 to 2022-09-30 · 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: 2022-09-01 through 2022-09-30
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2022-09-01 through 2022-09-30 (30 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 4,383
  • Total persons involved: 10,296
  • Total vehicles involved: 7,716

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 2022." Published September 9, 2026. Reporting period: 2022-09-01 to 2022-09-30. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/september-2022-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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