Yearly Traffic Safety Analysis

502 CRASHES IN
IOWA, IA
2020

All metrics benchmarked against2019

In Marion County, total crashes decreased by 18.6% from 617 in 2019 to 502 in 2020. Despite the overall reduction in collisions and a 23.4% drop in injuries, the most notable year-over-year shift was a significant increase in crash severity. The number of fatalities more than doubled, rising from 2 in 2019 to 5 in 2020.

502

▼ -18.6%was 617

Total Crash Events

5

▲ 150.0%was 2

Persons Killed

131

▼ -23.4%was 171

Persons Injured

4

▲ 100.0%was 2

Fatal Crash Events

Note: "Persons Killed" (5) counts individual fatalities across all crash events. "Fatal" in the severity table below (4) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, traffic crashes in Marion County saw a notable decline in 2020 compared to the previous year. Total crashes fell by 18.6% from 617 to 502, and the number of people injured decreased by 23.4% from 171 to 131. However, this downward trend in volume was contrasted by a sharp rise in fatalities, which increased from 2 to 5.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

1

Cyclists Killed

Prior: 0→%

4

Motorists Killed

Prior: 2↑100.0%

6

Pedestrians Injured

Prior: 5↑20.0%

2

Cyclists Injured

Prior: 1↑100.0%

123

Motorists Injured

Prior: 165↓-25.5%

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · 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 shifts between 2019 and 2020. Friday remained the peak day for crashes in both periods, with 87 incidents in 2020 compared to 128 in 2019. However, the peak hour for collisions moved earlier in the day, shifting from the 5 p.m. hour (56 crashes) in 2019 to the 3 p.m. hour (45 crashes) in 2020.

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

While total crashes decreased, their severity profile worsened in 2020. The number of fatal crashes doubled from 2 to 4, and the corresponding fatal crash rate increased from 0.32% to 0.8% of all collisions. The proportion of crashes resulting in serious injuries decreased slightly from 3.1% to 2.6%, while minor injury crashes saw their share of total incidents increase from 7.9% to 10.0%.

Severity is per crash event (most severe injury). 4 fatal crash events resulted in 5 persons killed.

Outcome by Severity (Crash Events)

Fatal4fatal crashes0.8%
↑100.0%prior 2
Serious Injury13serious injury crashes2.6%
↓-31.6%prior 19
Minor Injury50minor injury crashes10%
↑2.0%prior 49
Possible Injury47possible injury crashes9.4%
↓-35.6%prior 73
No Injury388no injury crashes77.3%
↓-18.1%prior 474

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · Most severe injury per crash record

Top Contributing Factors

Collisions involving an animal remained the leading contributing factor in both years, though the count of such incidents decreased from 196 in 2019 to 164 in 2020. "Lost Control" also remained a top factor, with its count falling from 47 to 37 incidents. "Followed too close" ranked third in 2020 with 28 crashes, a decrease from 36 crashes in the prior year. Crashes attributed to failure to yield from a stop sign saw a notable reduction, falling from 37 incidents in 2019 to 20 in 2020.

Officer-Reported Primary Contributing Cause

Animal164 (32.7%)↓-16.3%prior 196
Lost Control37 (7.4%)↓-21.3%prior 47
Followed too close28 (5.6%)↓-22.2%prior 36
Other (explain in narrative): Other25 (5%)↓-35.9%prior 39
Operating vehicle in an reckless, erratic, careless, negligent manner23 (4.6%)↑53.3%prior 15
Driving too fast for conditions22 (4.4%)↓-12.0%prior 25
FTYROW: From stop sign20 (4%)↓-45.9%prior 37
Ran off road - straight16 (3.2%)↓-33.3%prior 24
Ran off road - left15 (3%)↓-21.1%prior 19
Other (explain in narrative): No improper action12 (2.4%)↑71.4%prior 7

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The distribution of crashes across different environmental conditions remained broadly similar between the two periods. Crashes in daylight accounted for 52.0% of incidents in 2020, a slight proportional increase from 50.4% in 2019. The share of crashes occurring on dry road surfaces also grew, from 52.7% in 2019 to 56.6% in 2020, with a corresponding decrease in the proportion of crashes on adverse surfaces like wet, snow, or ice.

Weather

Clear259 (69.1%)
↓-9.4%prior 286
Cloudy75 (20.0%)
↓-31.8%prior 110
Snow16 (4.3%)
↑14.3%prior 14
Rain12 (3.2%)
↓-25.0%prior 16
Freezing rain/drizzle8 (2.1%)
↓-46.7%prior 15
Blowing Snow3 (0.8%)
↓-57.1%prior 7
Fog, smoke, smog2 (0.5%)

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · Weather condition at time of crash

Lighting

Daylight261 (70.0%)
↓-16.1%prior 311
Dark - roadway not lighted70 (18.8%)
↓-17.6%prior 85
Dark - roadway lighted27 (7.2%)
↓-20.6%prior 34
Dusk8 (2.1%)
↓-50.0%prior 16
Dawn7 (1.9%)
↓-50.0%prior 14

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · Lighting condition field

Road Surface

Dry284 (75.9%)
↓-12.6%prior 325
Wet27 (7.2%)
↓-20.6%prior 34
Snow22 (5.9%)
↓-33.3%prior 33
Ice/frost18 (4.8%)
↓-48.6%prior 35
Gravel17 (4.5%)
↓-34.6%prior 26
Slush6 (1.6%)

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · Road surface condition field

Vehicles & Demographics

Ford and Chevrolet were the top two vehicle makes involved in crashes in both years, though their total counts decreased in 2020. In 2020, 164 Fords and 158 Chevrolets (combining 'CHEV' and 'CHEVROLET' entries) were involved, down from 186 and 189, respectively, in 2019. The age demographics of persons involved in crashes also shifted, with the 16-20 age group becoming the most represented cohort in 2020 with 168 individuals. This contrasts with 2019, where the 35-44 age group was the largest with 213 individuals.

Top Vehicle Makes (728 vehicles)

1
FORD164 (22.5%)
↓-11.8%prior 186
2
CHEV107 (14.7%)
↓-15.1%prior 126
3
CHEVROLET51 (7%)
↓-19.0%prior 63
4
DODG34 (4.7%)
↓-47.7%prior 65
5
JEEP31 (4.3%)
↓-3.1%prior 32
6
TOYT26 (3.6%)
↓-18.8%prior 32
7
GMC24 (3.3%)
↓-20.0%prior 30
8
HOND23 (3.2%)
↑27.8%prior 18
9
NISS18 (2.5%)
↓-5.3%prior 19
10
DODGE16 (2.2%)
↓-27.3%prior 22

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · Vehicle unit records

76 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (682 persons with recorded sex)

Male420 (61.6%)
↓-15.5%prior 497
Female262 (38.4%)
↓-28.8%prior 368

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · 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: 2020-01-01 through 2020-12-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2020-01-01 through 2020-12-31 (366 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 502
  • Total persons involved: 1,028
  • Total vehicles involved: 728

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: 2020." Published September 9, 2026. Reporting period: 2020-01-01 to 2020-12-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/2020-annual-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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