Monthly Traffic Safety Analysis

4,143 CRASHES IN
IOWA, IA
SEPTEMBER 2020

All metrics benchmarked againstSeptember 2019

In September 2020, Iowa recorded 4,143 traffic crashes, a 7.9% decrease from the 4,500 crashes reported in September 2019. Despite the overall reduction in collisions, total fatalities increased slightly from 39 to 41. The most notable shift was a 15.7% year-over-year increase in crashes involving driving under the influence (DUI), which rose from 140 to 162 incidents.

4,143

▼ -7.9%was 4,500

Total Crash Events

41

▲ 5.1%was 39

Persons Killed

1,538

▼ -9.6%was 1,702

Persons Injured

40

▲ 2.6%was 39

Fatal Crash Events

Note: "Persons Killed" (41) counts individual fatalities across all crash events. "Fatal" in the severity table below (40) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Iowa Crash Data · ArcGIS Open Data · 2020-09-01 to 2020-09-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend in traffic collisions showed a decrease year-over-year. Total crashes fell by 7.9% from 4,500 in September 2019 to 4,143 in September 2020. Correspondingly, the number of people injured in these incidents declined by 9.6% from 1,702 to 1,538. However, this downward trend did not extend to fatalities, which rose from 39 to 41.

Vulnerable Road User Casualties

5

Pedestrians Killed

Prior: 3↑66.7%

0

Cyclists Killed

Prior: 1↓-100.0%

36

Motorists Killed

Prior: 35↑2.9%

0

Other Killed

Prior: 0→0.0%

39

Pedestrians Injured

Prior: 29↑34.5%

26

Cyclists Injured

Prior: 52↓-50.0%

1,470

Motorists Injured

Prior: 1,612↓-8.8%

3

Other Injured

Prior: 9↓-66.7%

Source: Iowa Crash Data · ArcGIS Open Data · 2020-09-01 to 2020-09-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The peak time for crashes remained the 3 p.m. hour in both periods, although the volume of crashes during this hour decreased from 411 to 348. A significant shift occurred in the peak day of the week for crashes, moving from Friday (776 crashes) in September 2019 to Tuesday (743 crashes) in September 2020. Collisions on Mondays saw a substantial drop from 773 to 505, while crashes on Tuesdays increased from 592 to 743.

Source: Iowa Crash Data · ArcGIS Open Data · 2020-09-01 to 2020-09-30 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2020-09-01 to 2020-09-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The severity of crashes worsened slightly year-over-year. The fatal crash rate increased from 0.87 per 100 crashes in September 2019 to 0.97 in September 2020, with the absolute number of fatal crashes rising from 39 to 40. The proportion of crashes resulting in a serious injury also grew, moving from 2.5% of all crashes (113 incidents) to 2.9% (122 incidents).

Severity is per crash event (most severe injury). 40 fatal crash events resulted in 41 persons killed.

Outcome by Severity (Crash Events)

Fatal40fatal crashes1%
↑2.6%prior 39
Serious Injury122serious injury crashes2.9%
↑8.0%prior 113
Minor Injury452minor injury crashes10.9%
↓-2.6%prior 464
Possible Injury703possible injury crashes17%
↓-14.1%prior 818
No Injury2,826no injury crashes68.2%
↓-7.8%prior 3,066

Source: Iowa Crash Data · ArcGIS Open Data · 2020-09-01 to 2020-09-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2020-09-01 to 2020-09-30 · Most severe injury per crash record

Top Contributing Factors

Collisions with an animal became the leading contributing factor in September 2020, with the count of such incidents increasing by 18.9% from 423 to 503. This displaced "Followed too close" as the top factor, which saw its incident count fall by 26.2% from 610 to 450. Notably, crashes attributed to exceeding the authorized speed limit saw a 90.9% increase in count, rising from 44 incidents in the prior year to 84 in the current period.

Officer-Reported Primary Contributing Cause

Animal503 (12.1%)↑18.9%prior 423
Followed too close450 (10.9%)↓-26.2%prior 610
Ran off road - left271 (6.5%)↓-2.2%prior 277
Other (explain in narrative): Other243 (5.9%)↓-22.9%prior 315
Lost Control225 (5.4%)↑7.7%prior 209
FTYROW: From stop sign221 (5.3%)↓-12.6%prior 253
FTYROW: Making left turn195 (4.7%)↓-11.8%prior 221
Other (explain in narrative): No improper action131 (3.2%)↑4.0%prior 126
Ran Traffic Signal124 (3%)↓-15.6%prior 147
Driver Distraction: Other interior distraction123 (3%)↓-5.4%prior 130

Source: Iowa Crash Data · ArcGIS Open Data · 2020-09-01 to 2020-09-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The proportion of crashes occurring in daylight conditions decreased from 69.8% in September 2019 to 65.3% in September 2020. There was a corresponding increase in the share of crashes during adverse conditions. Crashes in the rain accounted for 10.8% of all incidents (448 crashes), up from 9.0% (405 crashes) in the prior year. Similarly, the percentage of collisions on wet road surfaces increased from 15.8% to 16.3%.

Weather

Clear2,652 (70.9%)
↓-6.9%prior 2,849
Cloudy604 (16.1%)
↓-30.9%prior 874
Rain448 (12.0%)
↑10.6%prior 405
Fog, smoke, smog19 (0.5%)
↓-26.9%prior 26
Freezing rain/drizzle11 (0.3%)
↑37.5%prior 8
Blowing sand, soil, dirt3 (0.1%)
Other (explain in narrative)3 (0.1%)
Severe Winds2 (0.1%)

Source: Iowa Crash Data · ArcGIS Open Data · 2020-09-01 to 2020-09-30 · Weather condition at time of crash

Lighting

Daylight2,705 (72.1%)
↓-13.9%prior 3,142
Dark - roadway lighted495 (13.2%)
↑6.7%prior 464
Dark - roadway not lighted366 (9.7%)
↓-3.2%prior 378
Dusk105 (2.8%)
↑20.7%prior 87
Dawn72 (1.9%)
↓-25.8%prior 97
Dark - unknown roadway lighting11 (0.3%)
↓-26.7%prior 15

Source: Iowa Crash Data · ArcGIS Open Data · 2020-09-01 to 2020-09-30 · Lighting condition field

Road Surface

Dry2,982 (79.5%)
↓-11.2%prior 3,358
Wet675 (18.0%)
↓-4.9%prior 710
Gravel80 (2.1%)
↑2.6%prior 78
Mud, dirt8 (0.2%)
Other (explain in narrative)6 (0.2%)
↓-45.5%prior 11

Source: Iowa Crash Data · ArcGIS Open Data · 2020-09-01 to 2020-09-30 · Road surface condition field

Vehicles & Demographics

Ford and Chevrolet remained the top two vehicle makes involved in crashes, though their counts declined in line with the overall trend. In September 2020, 1,140 Fords and a combined 1,462 Chevrolet vehicles were involved in crashes, down from 1,322 and 1,516 respectively. The 26-34 age group was the most frequently involved demographic in both periods, with 1,448 persons in September 2020 compared to 1,631 in the prior year. The relative distribution of persons involved by age group remained largely consistent.

Top Vehicle Makes (7,193 vehicles)

1
FORD1,140 (15.8%)
↓-13.8%prior 1,322
2
CHEV907 (12.6%)
↓-9.9%prior 1,007
3
CHEVROLET555 (7.7%)
↑9.0%prior 509
4
TOYT285 (4%)
↓-23.4%prior 372
5
DODG278 (3.9%)
↓-12.6%prior 318
6
JEEP255 (3.5%)
↓-10.2%prior 284
7
GMC243 (3.4%)
↓-4.0%prior 253
8
NR232 (3.2%)
↓-9.4%prior 256
9
HOND221 (3.1%)
↓-19.6%prior 275
10
NISS191 (2.7%)
↓-12.8%prior 219

Source: Iowa Crash Data · ArcGIS Open Data · 2020-09-01 to 2020-09-30 · Vehicle unit records

1,353 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (6,365 persons with recorded sex)

Male3,712 (58.3%)
↓-8.1%prior 4,041
Female2,653 (41.7%)
↓-16.8%prior 3,190

Source: Iowa Crash Data · ArcGIS Open Data · 2020-09-01 to 2020-09-30 · 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: 2020-09-01 through 2020-09-30
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2020-09-01 through 2020-09-30 (30 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 4,143
  • Total persons involved: 9,830
  • Total vehicles involved: 7,193

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: September 2020." Published September 9, 2026. Reporting period: 2020-09-01 to 2020-09-30. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/september-2020-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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