Yearly Traffic Safety Analysis

77 CRASHES IN
IOWA, IA
2020

All metrics benchmarked against2019

In Shelby County, total vehicle crashes decreased by 31.9% from 113 in 2019 to 77 in 2020. This downturn was accompanied by a significant reduction in crash severity. The most notable year-over-year shift was the 80% drop in fatalities, which fell from 5 in 2019 to 1 in 2020.

77

▼ -31.9%was 113

Total Crash Events

1

▼ -80.0%was 5

Persons Killed

30

▼ -43.4%was 53

Persons Injured

1

▼ -80.0%was 5

Fatal Crash Events

Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) 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

Traffic crashes in Shelby County showed a significant downward trend year-over-year. The total number of crashes fell by 31.9%, from 113 to 77. Similarly, the number of people injured decreased by 43.4% from 53 to 30, and fatalities dropped from 5 to 1.

Vulnerable Road User Casualties

1

Motorists Killed

Prior: 5↓-80.0%

30

Motorists Injured

Prior: 53↓-43.4%

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 timing of crashes shifted between the two periods. In 2020, the peak day for crashes was Wednesday with 20 incidents, a change from 2019 when Friday was the peak day with 21 crashes. The peak hour for collisions also moved later in the afternoon, from 2 p.m. in 2019 (11 crashes) to 3 p.m. in 2020 (12 crashes).

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

Crash severity decreased notably from 2019 to 2020. The fatal crash rate fell from 4.4% of all crashes (5 incidents) in the prior period to 1.3% (1 incident) in the current period. The proportion of crashes resulting in no injuries increased from 61.1% in 2019 to 70.1% in 2020, while the share of crashes involving any level of injury (possible, minor, or serious) declined.

Outcome by Severity (Crash Events)

Fatal1fatal crashes1.3%
↓-80.0%prior 5
Serious Injury5serious injury crashes6.5%
→0.0%prior 5
Minor Injury8minor injury crashes10.4%
↓-55.6%prior 18
Possible Injury9possible injury crashes11.7%
↓-43.8%prior 16
No Injury54no injury crashes70.1%
↓-21.7%prior 69

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

The ranking of top contributing factors changed significantly year-over-year. Collisions involving an animal, the top factor in 2019 with 18 incidents, decreased by 66.7% in count to 6 incidents in 2020. Conversely, 'Driving too fast for conditions' became the leading factor in 2020 with 9 crashes, a 200% increase in count from just 3 incidents in 2019. 'Lost Control' and 'FTYROW: From stop sign' also saw their incident counts decrease from 12 to 8 and 11 to 8, respectively.

Officer-Reported Primary Contributing Cause

Driving too fast for conditions9 (11.7%)
FTYROW: From stop sign8 (10.4%)↓-27.3%prior 11
Lost Control8 (10.4%)↓-33.3%prior 12
Other (explain in narrative): Other6 (7.8%)↓-50.0%prior 12
Animal6 (7.8%)↓-66.7%prior 18
Ran off road - left5 (6.5%)↓-50.0%prior 10
Made improper turn4 (5.2%)
Ran off road - straight3 (3.9%)
Ran Stop Sign3 (3.9%)
FTYROW: Making left turn3 (3.9%)

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 proportion of crashes occurring in clear and dry conditions was higher in 2020 than in 2019. Crashes during daylight hours accounted for 70.1% of the total in 2020, up from 64.6% in the prior year. Similarly, incidents on dry road surfaces made up 66.2% of crashes in 2020 versus 62.8% in 2019, indicating a relative decrease in the share of crashes happening under adverse conditions.

Weather

Clear51 (73.9%)
↓-23.9%prior 67
Cloudy9 (13.0%)
↓-55.0%prior 20
Snow3 (4.3%)
Blowing Snow2 (2.9%)
Freezing rain/drizzle1 (1.4%)
Fog, smoke, smog1 (1.4%)
Blowing sand, soil, dirt1 (1.4%)
Rain1 (1.4%)

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

Lighting

Daylight54 (74.0%)
↓-26.0%prior 73
Dark - roadway lighted7 (9.6%)
↓-22.2%prior 9
Dark - roadway not lighted7 (9.6%)
↓-56.3%prior 16
Dawn3 (4.1%)
Dusk2 (2.7%)

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

Road Surface

Dry51 (69.9%)
↓-28.2%prior 71
Snow8 (11.0%)
↑60.0%prior 5
Gravel6 (8.2%)
→0.0%prior 6
Wet4 (5.5%)
↓-42.9%prior 7
Ice/frost2 (2.7%)
↓-80.0%prior 10
Slush1 (1.4%)
Mud, dirt1 (1.4%)

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

Vehicles & Demographics

Ford and Chevrolet remained the top two vehicle makes involved in collisions for both years, though the total number of vehicles for each make decreased in 2020. The age demographics of persons involved in crashes also shifted. The 55-64 age group, which was the most represented in 2019 with 49 individuals, saw its involvement drop to 20 individuals in 2020. In 2020, the 26-34 age group was the most common (30 persons), followed closely by the 65+ age group (29 persons).

Top Vehicle Makes (132 vehicles)

1
FORD27 (20.5%)
↓-40.0%prior 45
2
CHEV22 (16.7%)
↓-21.4%prior 28
3
CHEVROLET7 (5.3%)
↓-46.2%prior 13
4
GMC6 (4.5%)
5
BUIC6 (4.5%)
↓-40.0%prior 10
6
DODG5 (3.8%)
↓-37.5%prior 8
7
HYUN4 (3%)
8
BUICK4 (3%)
9
NISS4 (3%)
10
DODGE4 (3%)
↓-42.9%prior 7

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

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

Sex Distribution (116 persons with recorded sex)

Male76 (65.5%)
↓-24.0%prior 100
Female40 (34.5%)
↓-40.3%prior 67

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: 77
  • Total persons involved: 182
  • Total vehicles involved: 132

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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