Yearly Traffic Safety Analysis

132 CRASHES IN
IOWA, IA
2020

All metrics benchmarked against2019

In Fremont County, the total number of traffic crashes remained nearly stable, with 132 incidents in 2020 compared to 131 in 2019. Despite the consistent crash volume, there was a significant 27.4% decrease in the number of people injured, which fell from 73 to 53. However, the number of fatalities rose from 3 to 4 year-over-year.

132

▲ 0.8%was 131

Total Crash Events

4

▲ 33.3%was 3

Persons Killed

53

▼ -27.4%was 73

Persons Injured

4

▲ 33.3%was 3

Fatal Crash Events

Note: "Persons Killed" (4) 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 crash trends in Fremont County were stable year-over-year, with total incidents rising by only one, from 131 in 2019 to 132 in 2020. While total crashes held steady, outcomes worsened in terms of fatalities, which increased from 3 to 4. In contrast, the number of people injured saw a marked improvement, declining from 73 to 53.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

4

Motorists Killed

Prior: 3↑33.3%

3

Pedestrians Injured

Prior: 1↑200.0%

50

Motorists Injured

Prior: 72↓-30.6%

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 slightly between the two periods. The peak day for collisions moved from Thursday (22 crashes) in 2019 to Friday (24 crashes) in 2020. The busiest hour also shifted earlier, from 5 p.m. in 2019, which saw 14 crashes, to 4 p.m. in 2020 with 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

While total crashes were stable, the severity of outcomes changed. The number of fatal crashes increased from 3 in 2019 to 4 in 2020, and the fatal crash rate rose from 2.29 to 3.03 per 100 crashes. Conversely, non-fatal injury crashes became less frequent; crashes resulting in serious injuries fell from 10 to 8, and those with possible injuries dropped from 17 to 11. Consequently, the proportion of crashes with no injuries increased from 62.6% to 68.2% of all incidents.

Outcome by Severity (Crash Events)

Fatal4fatal crashes3%
↑33.3%prior 3
Serious Injury8serious injury crashes6.1%
↓-20.0%prior 10
Minor Injury19minor injury crashes14.4%
→0.0%prior 19
Possible Injury11possible injury crashes8.3%
↓-35.3%prior 17
No Injury90no injury crashes68.2%
↑9.8%prior 82

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' became the leading contributing factor in 2020, with the count of such incidents rising from 15 to 23, a 53.3% increase from 2019. The number of crashes attributed to 'Driving too fast for conditions' also doubled, from 8 incidents to 16. In contrast, crashes due to 'Followed too close' decreased from 10 to 7, and incidents involving 'Ran Stop Sign' fell from 7 to 4.

Officer-Reported Primary Contributing Cause

Animal23 (17.4%)↑53.3%prior 15
Lost Control18 (13.6%)↑12.5%prior 16
Driving too fast for conditions16 (12.1%)↑100.0%prior 8
Ran off road - straight14 (10.6%)↑27.3%prior 11
Followed too close7 (5.3%)↓-30.0%prior 10
Operating vehicle in an reckless, erratic, careless, negligent manner5 (3.8%)→0.0%prior 5
Ran Stop Sign4 (3%)↓-42.9%prior 7
Ran off road - left4 (3%)↓-42.9%prior 7
Ran Traffic Signal4 (3%)
FTYROW: Making left turn3 (2.3%)↓-50.0%prior 6

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

Road & Environmental Conditions

There was a notable shift in lighting conditions for crashes, with incidents on dark, unlighted roadways increasing from 23 in 2019 to 35 in 2020. Crashes on icy or frosty road surfaces also increased from 9 to 14 year-over-year. Conversely, crashes on dry roads decreased from 87 to 81, and collisions in clear weather dropped from 83 to 72.

Weather

Clear72 (63.7%)
↓-13.3%prior 83
Cloudy13 (11.5%)
↓-27.8%prior 18
Freezing rain/drizzle8 (7.1%)
↑14.3%prior 7
Snow6 (5.3%)
Rain6 (5.3%)
↑20.0%prior 5
Blowing Snow2 (1.8%)
Fog, smoke, smog2 (1.8%)
Sleet, hail2 (1.8%)
Other (explain in narrative)1 (0.9%)
Blowing sand, soil, dirt1 (0.9%)

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

Lighting

Daylight69 (60.5%)
↓-10.4%prior 77
Dark - roadway not lighted35 (30.7%)
↑52.2%prior 23
Dark - roadway lighted4 (3.5%)
↓-63.6%prior 11
Dawn2 (1.8%)
Dusk2 (1.8%)
↓-71.4%prior 7
Dark - unknown roadway lighting2 (1.8%)

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

Road Surface

Dry81 (70.4%)
↓-6.9%prior 87
Ice/frost14 (12.2%)
↑55.6%prior 9
Wet9 (7.8%)
↓-40.0%prior 15
Snow8 (7.0%)
↓-20.0%prior 10
Other (explain in narrative)1 (0.9%)
Slush1 (0.9%)
Gravel1 (0.9%)

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 crashes, though both saw a decrease in counts from the prior year. The age demographics of people involved in crashes shifted significantly; the number of individuals in the 16-20 age group fell from 45 in 2019 to 25 in 2020. Meanwhile, involvement of the 35-44 age group increased substantially, from 26 persons in 2019 to 45 in 2020.

Top Vehicle Makes (183 vehicles)

1
FORD27 (14.8%)
↓-3.6%prior 28
2
CHEVROLET18 (9.8%)
↓-25.0%prior 24
3
CHEV16 (8.7%)
↓-15.8%prior 19
4
TOYOTA10 (5.5%)
↑100.0%prior 5
5
FREIGHTLINER10 (5.5%)
↑25.0%prior 8
6
GMC9 (4.9%)
↑50.0%prior 6
7
DODGE9 (4.9%)
↑12.5%prior 8
8
DODG7 (3.8%)
→0.0%prior 7
9
KENWORTH6 (3.3%)
10
PETERBILT6 (3.3%)

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

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

Sex Distribution (172 persons with recorded sex)

Male119 (69.2%)
↑1.7%prior 117
Female53 (30.8%)
↓-23.2%prior 69

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: 132
  • Total persons involved: 266
  • Total vehicles involved: 183

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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