Monthly Traffic Safety Analysis

4,370 CRASHES IN
IOWA, IA
JANUARY 2022

All metrics benchmarked againstJanuary 2021

In January 2022, there were 4,370 total crashes in Iowa, a 2.6% decrease from the 4,486 crashes recorded in January 2021. While overall crashes and injuries declined, the number of fatal crashes increased from 14 to 17. A notable year-over-year shift occurred in major urban centers, with crashes in Des Moines increasing by 23.4% while incidents in Davenport decreased by 27.4%.

4,370

▼ -2.6%was 4,486

Total Crash Events

17

▲ 6.3%was 16

Persons Killed

1,153

▼ -2.8%was 1,186

Persons Injured

17

▲ 21.4%was 14

Fatal Crash Events

Note: "Persons Killed" (17) counts individual fatalities across all crash events. "Fatal" in the severity table below (17) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-01-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall traffic crashes decreased by 2.6% in January 2022 compared to the same month in the prior year, falling from 4,486 to 4,370. This downward trend was also reflected in total injuries, which declined by 2.8% from 1,186 to 1,153. However, total fatalities increased by one, from 16 in January 2021 to 17 in January 2022.

Vulnerable Road User Casualties

2

Pedestrians Killed

Prior: 1↑100.0%

0

Cyclists Killed

Prior: 0→0.0%

15

Motorists Killed

Prior: 15→0.0%

31

Pedestrians Injured

Prior: 21↑47.6%

2

Cyclists Injured

Prior: 2→0.0%

1,120

Motorists Injured

Prior: 1,161↓-3.5%

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-01-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes showed some year-over-year shifts. While Friday remained the day with the highest number of crashes in both January 2022 (793 crashes) and January 2021 (845 crashes), the peak hour for collisions shifted two hours earlier, from 5 p.m. in 2021 to 3 p.m. in 2022. Crashes on Mondays saw a notable increase from 645 to 730, while Tuesday crashes decreased from 705 to 563.

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-01-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-01-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The severity of crashes shifted slightly year-over-year, with incidents becoming marginally more severe despite a drop in total volume. The number of fatal crashes increased from 14 to 17, causing the fatal crash rate to rise from 0.31% to 0.39% of all crashes. While the count of serious injury crashes decreased from 67 to 63, the number of minor injury crashes increased from 301 to 330.

Outcome by Severity (Crash Events)

Fatal17fatal crashes0.4%
↑21.4%prior 14
Serious Injury63serious injury crashes1.4%
↓-6.0%prior 67
Minor Injury330minor injury crashes7.6%
↑9.6%prior 301
Possible Injury653possible injury crashes14.9%
↓-3.0%prior 673
No Injury3,307no injury crashes75.7%
↓-3.6%prior 3,431

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-01-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-01-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factors remained consistent, with 'Driving too fast for conditions' being the top cause in both January 2021 (549 crashes) and January 2022 (532 crashes). Crashes involving animals, the second-ranked factor, saw a significant count decrease of 15.5%, from 497 to 420. Conversely, crashes due to 'Followed too close' increased in count by 13.6% (from 287 to 326), and 'Ran Traffic Signal' incidents grew by 13.2% (from 152 to 172).

Officer-Reported Primary Contributing Cause

Driving too fast for conditions532 (12.2%)↓-3.1%prior 549
Animal420 (9.6%)↓-15.5%prior 497
Ran off road - left396 (9.1%)↑2.1%prior 388
Followed too close326 (7.5%)↑13.6%prior 287
Other (explain in narrative): Other297 (6.8%)↑12.5%prior 264
Lost Control260 (5.9%)↓-16.1%prior 310
FTYROW: From stop sign200 (4.6%)↑12.4%prior 178
Ran off road - straight193 (4.4%)↓-5.9%prior 205
Ran Traffic Signal172 (3.9%)↑13.2%prior 152
FTYROW: Making left turn169 (3.9%)↑11.9%prior 151

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-01-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Environmental conditions during crashes were notably different year-over-year, indicating January 2022 had more favorable weather. The number of crashes occurring in clear weather increased from 1,981 to 2,591, raising its share of total crashes from 44.2% to 59.3%. Similarly, crashes on dry roads increased from 1,818 to 2,021. Consequently, crashes in adverse conditions like snow (580 down to 463) and on wet surfaces (552 down to 294) decreased.

Weather

Clear2,591 (65.0%)
↑30.8%prior 1,981
Cloudy628 (15.8%)
↓-26.2%prior 851
Snow463 (11.6%)
↓-20.2%prior 580
Blowing Snow130 (3.3%)
↓-40.9%prior 220
Freezing rain/drizzle110 (2.8%)
↓-52.6%prior 232
Other (explain in narrative)23 (0.6%)
↑21.1%prior 19
Severe Winds16 (0.4%)
↓-30.4%prior 23
Fog, smoke, smog12 (0.3%)
↓-87.4%prior 95
Rain6 (0.2%)
↓-70.0%prior 20
Sleet, hail6 (0.2%)
↓-45.5%prior 11

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-01-31 · Weather condition at time of crash

Lighting

Daylight2,363 (59.1%)
↑7.5%prior 2,198
Dark - roadway lighted831 (20.8%)
↓-9.5%prior 918
Dark - roadway not lighted587 (14.7%)
↓-12.0%prior 667
Dusk110 (2.8%)
↓-19.1%prior 136
Dawn84 (2.1%)
↓-27.0%prior 115
Dark - unknown roadway lighting20 (0.5%)
↓-16.7%prior 24

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-01-31 · Lighting condition field

Road Surface

Dry2,021 (50.5%)
↑11.2%prior 1,818
Snow845 (21.1%)
↓-0.2%prior 847
Ice/frost668 (16.7%)
↓-2.2%prior 683
Wet294 (7.4%)
↓-46.7%prior 552
Slush122 (3.1%)
↓-0.8%prior 123
Gravel33 (0.8%)
↑57.1%prior 21
Other (explain in narrative)10 (0.3%)
↑11.1%prior 9
Sand5 (0.1%)
Mud, dirt1 (0.0%)

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-01-31 · Road surface condition field

Vehicles & Demographics

The top vehicle makes involved in crashes, including Ford and Chevrolet, remained consistent in ranking and volume between January 2021 and January 2022. However, the demographics of persons involved in crashes showed a notable shift. The number of individuals in the 26-34 age group decreased from 1,635 to 1,461. Conversely, the number of persons aged 65 and older involved in crashes saw a significant increase, rising from 720 to 920 year-over-year.

Top Vehicle Makes (7,460 vehicles)

1
FORD1,245 (16.7%)
↓-0.7%prior 1,254
2
CHEV825 (11.1%)
↓-4.8%prior 867
3
CHEVROLET548 (7.3%)
↓-12.3%prior 625
4
JEEP323 (4.3%)
↑8.8%prior 297
5
TOYT315 (4.2%)
↑16.2%prior 271
6
NR251 (3.4%)
↑5.5%prior 238
7
DODG245 (3.3%)
↓-0.8%prior 247
8
GMC234 (3.1%)
↓-4.1%prior 244
9
TOYOTA213 (2.9%)
↑12.7%prior 189
10
HOND208 (2.8%)
↑9.5%prior 190

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-01-31 · Vehicle unit records

1,519 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (6,557 persons with recorded sex)

Male3,915 (59.7%)
↓-1.4%prior 3,969
Female2,642 (40.3%)
↑3.0%prior 2,566

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-01-31 · 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: 2022-01-01 through 2022-01-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2022-01-01 through 2022-01-31 (31 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 4,370
  • Total persons involved: 9,760
  • Total vehicles involved: 7,460

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 2022." Published September 9, 2026. Reporting period: 2022-01-01 to 2022-01-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/january-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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