Monthly Traffic Safety Analysis

4,486 CRASHES IN
IOWA, IA
JANUARY 2021

All metrics benchmarked againstJanuary 2020

In January 2021, there were 4,486 total crashes statewide, a 14.6% decrease from the 5,253 crashes recorded in January 2020. This overall reduction in collisions was accompanied by a significant year-over-year shift in contributing factors, most notably a 41% drop in crashes attributed to 'Driving too fast for conditions,' which fell from 930 incidents to 549.

4,486

▼ -14.6%was 5,253

Total Crash Events

16

▼ -33.3%was 24

Persons Killed

1,186

▼ -11.3%was 1,337

Persons Injured

14

▼ -36.4%was 22

Fatal Crash Events

Note: "Persons Killed" (16) counts individual fatalities across all crash events. "Fatal" in the severity table below (14) 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 2021-01-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Traffic safety metrics showed a general improvement in January 2021 compared to the same month in the prior year. The total number of crashes fell by 767, from 5,253 to 4,486. Similarly, total fatalities decreased from 24 to 16, and total injuries dropped from 1,337 to 1,186.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 5↓-80.0%

0

Cyclists Killed

Prior: 1↓-100.0%

15

Motorists Killed

Prior: 18↓-16.7%

0

Other Killed

Prior: 0→0.0%

21

Pedestrians Injured

Prior: 37↓-43.2%

2

Cyclists Injured

Prior: 8↓-75.0%

1,161

Motorists Injured

Prior: 1,291↓-10.1%

2

Other Injured

Prior: 1↑100.0%

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-01-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes remained consistent year-over-year. Friday was the peak day for crashes in both January 2021 (845 crashes) and January 2020 (1,240 crashes). The 5 p.m. hour was the peak hour in both periods, accounting for 363 crashes in the current period and 438 in the prior period.

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-01-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-01-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

While total crashes declined, the severity distribution saw some shifts. The fatal crash rate decreased from 0.42% to 0.31% of all crashes. However, the proportion of crashes resulting in serious injuries increased from 1.1% (57 incidents) in the prior period to 1.5% (67 incidents) in the current period. The share of crashes with no injuries increased slightly from 76.0% to 76.5%.

Severity is per crash event (most severe injury). 14 fatal crash events resulted in 16 persons killed.

Outcome by Severity (Crash Events)

Fatal14fatal crashes0.3%
↓-36.4%prior 22
Serious Injury67serious injury crashes1.5%
↑17.5%prior 57
Minor Injury301minor injury crashes6.7%
↓-16.9%prior 362
Possible Injury673possible injury crashes15%
↓-17.9%prior 820
No Injury3,431no injury crashes76.5%
↓-14.1%prior 3,992

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-01-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-01-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factors changed slightly between the two periods. 'Driving too fast for conditions' remained the top factor but saw its count decrease by 41%, from 930 incidents to 549. Collisions involving an 'Animal' increased from 469 to 497, moving from the third-ranked factor to the second. 'Ran off road - left' decreased from 495 to 388 incidents, becoming the third most common factor.

Officer-Reported Primary Contributing Cause

Driving too fast for conditions549 (12.2%)↓-41.0%prior 930
Animal497 (11.1%)↑6.0%prior 469
Ran off road - left388 (8.6%)↓-21.6%prior 495
Lost Control310 (6.9%)↓-8.3%prior 338
Followed too close287 (6.4%)↓-22.0%prior 368
Other (explain in narrative): Other264 (5.9%)→0.0%prior 264
Ran off road - straight205 (4.6%)↓-4.7%prior 215
FTYROW: From stop sign178 (4%)↓-12.3%prior 203
Ran Traffic Signal152 (3.4%)↓-14.1%prior 177
FTYROW: Making left turn151 (3.4%)↓-16.6%prior 181

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-01-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

There was a notable shift in the conditions under which crashes occurred. The proportion of crashes on dry roads increased from 31.1% to 40.5% year-over-year, while the share of crashes on roads with snow or ice decreased. Crashes in clear weather constituted 44.2% of the total in January 2021, up from 34.7% in January 2020, while the share of crashes during snowy weather decreased from 18.0% to 12.9%.

Weather

Clear1,981 (49.1%)
↑8.7%prior 1,822
Cloudy851 (21.1%)
↓-33.7%prior 1,283
Snow580 (14.4%)
↓-38.5%prior 943
Freezing rain/drizzle232 (5.8%)
↓-50.8%prior 472
Blowing Snow220 (5.5%)
↑67.9%prior 131
Fog, smoke, smog95 (2.4%)
↑31.9%prior 72
Severe Winds23 (0.6%)
↓-4.2%prior 24
Rain20 (0.5%)
↓-66.1%prior 59
Other (explain in narrative)19 (0.5%)
↑72.7%prior 11
Sleet, hail11 (0.3%)
↓-50.0%prior 22

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

Lighting

Daylight2,198 (54.2%)
↓-17.3%prior 2,659
Dark - roadway lighted918 (22.6%)
↓-16.2%prior 1,095
Dark - roadway not lighted667 (16.4%)
↓-10.7%prior 747
Dusk136 (3.4%)
↓-11.1%prior 153
Dawn115 (2.8%)
↓-24.3%prior 152
Dark - unknown roadway lighting24 (0.6%)
↓-35.1%prior 37

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

Road Surface

Dry1,818 (44.8%)
↑11.1%prior 1,636
Snow847 (20.9%)
↓-23.1%prior 1,101
Ice/frost683 (16.8%)
↓-42.0%prior 1,177
Wet552 (13.6%)
↓-12.9%prior 634
Slush123 (3.0%)
↓-53.1%prior 262
Gravel21 (0.5%)
↓-8.7%prior 23
Other (explain in narrative)9 (0.2%)
↓-10.0%prior 10
Mud, dirt2 (0.0%)
↓-60.0%prior 5
Sand2 (0.0%)

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

Vehicles & Demographics

The makes of vehicles involved in crashes remained consistent, with Chevrolet (1,492 vehicles) and Ford (1,254 vehicles) being the most common in January 2021, maintaining their top two positions from the prior year. The age distribution of persons involved in crashes also showed little change; the 26-34 age group was the largest cohort in both periods, accounting for 16.8% of persons in the current period compared to 16.1% in the prior period.

Top Vehicle Makes (7,431 vehicles)

1
FORD1,254 (16.9%)
↓-12.7%prior 1,437
2
CHEV867 (11.7%)
↓-24.0%prior 1,141
3
CHEVROLET625 (8.4%)
↑24.3%prior 503
4
JEEP297 (4%)
↓-15.4%prior 351
5
TOYT271 (3.6%)
↓-31.4%prior 395
6
DODG247 (3.3%)
↓-33.1%prior 369
7
GMC244 (3.3%)
↓-15.0%prior 287
8
NR238 (3.2%)
↓-15.6%prior 282
9
DODGE207 (2.8%)
↑10.7%prior 187
10
HOND190 (2.6%)
↓-32.6%prior 282

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

1,498 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (6,535 persons with recorded sex)

Male3,969 (60.7%)
↓-15.2%prior 4,679
Female2,566 (39.3%)
↓-21.1%prior 3,253

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-01-31 · 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 2021-01-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2021-01-01 through 2021-01-31 (31 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 4,486
  • Total persons involved: 9,739
  • Total vehicles involved: 7,431

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: January 2021." Published September 9, 2026. Reporting period: 2021-01-01 to 2021-01-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/january-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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