Yearly Traffic Safety Analysis

177 CRASHES IN
IOWA, IA
2020

All metrics benchmarked against2019

In 2020, Franklin County recorded 177 total traffic crashes, a 14.1% decrease from the 206 crashes reported in 2019. While overall crashes and fatalities declined, the number of crashes involving a driver under the influence of alcohol or drugs (DUI) increased from 3 in 2019 to 11 in 2020.

177

▼ -14.1%was 206

Total Crash Events

1

▼ -50.0%was 2

Persons Killed

49

▼ -5.8%was 52

Persons Injured

1

▼ -50.0%was 2

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

Overall, traffic crashes in Franklin County saw a downward trend from 2019 to 2020. Total crashes fell by 14.1% from 206 to 177. Fatalities were halved from 2 to 1, and total injuries decreased slightly from 52 to 49.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 0→0.0%

1

Motorists Killed

Prior: 2↓-50.0%

1

Cyclists Injured

Prior: 2↓-50.0%

48

Motorists Injured

Prior: 50↓-4.0%

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 shifted between the two periods. In 2020, the peak day for crashes was Wednesday with 36 incidents, and the peak hour was 4 p.m. with 16 incidents. This contrasts with 2019, when the peak day was Friday (35 crashes) and the peak hour was 9 a.m. (17 crashes), indicating a shift from a morning peak to an afternoon peak.

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 saw a mixed change year-over-year. The number of fatal crashes decreased from 2 in 2019 to 1 in 2020, and the fatal crash rate per 100 crashes fell from 0.97 to 0.56. However, the proportion of crashes involving any level of injury (Fatal, Serious, Minor, or Possible) increased from 28.6% of all crashes in 2019 to 33.9% in 2020.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.6%
↓-50.0%prior 2
Serious Injury2serious injury crashes1.1%
↓-33.3%prior 3
Minor Injury15minor injury crashes8.5%
↓-6.3%prior 16
Possible Injury24possible injury crashes13.6%
↑20.0%prior 20
No Injury135no injury crashes76.3%
↓-18.2%prior 165

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 with animals remained the top contributing factor in both years, though the count decreased from 61 in 2019 to 47 in 2020. The second-leading factor in 2019, 'Driving too fast for conditions,' saw its count drop from 20 to 8. Conversely, crashes attributed to 'FTYROW: From stop sign' more than doubled, increasing from 3 incidents in 2019 to 7 in 2020.

Officer-Reported Primary Contributing Cause

Animal47 (26.6%)↓-23.0%prior 61
Lost Control19 (10.7%)↑5.6%prior 18
Other (explain in narrative): Other16 (9%)↑14.3%prior 14
Driving too fast for conditions8 (4.5%)↓-60.0%prior 20
Ran off road - left8 (4.5%)↓-11.1%prior 9
Ran off road - straight8 (4.5%)↓-38.5%prior 13
FTYROW: From stop sign7 (4%)
Other (explain in narrative): No improper action6 (3.4%)
Driver Distraction: Other interior distraction6 (3.4%)
FTYROW: At uncontrolled intersection5 (2.8%)↓-66.7%prior 15

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 environmental conditions showed notable changes. Crashes on roads with ice, frost, or snow decreased from a combined 53 incidents in 2019 to 30 in 2020. While daylight remained the most common lighting condition, crashes in the dark on unlighted roadways increased from 28 in 2019 to 36 in 2020.

Weather

Clear86 (63.2%)
↑1.2%prior 85
Cloudy16 (11.8%)
↓-30.4%prior 23
Rain8 (5.9%)
Snow8 (5.9%)
↓-33.3%prior 12
Blowing Snow7 (5.1%)
↑40.0%prior 5
Severe Winds4 (2.9%)
↓-20.0%prior 5
Freezing rain/drizzle4 (2.9%)
↓-69.2%prior 13
Fog, smoke, smog2 (1.5%)
Blowing sand, soil, dirt1 (0.7%)

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

Lighting

Daylight80 (58.8%)
↓-23.8%prior 105
Dark - roadway not lighted36 (26.5%)
↑28.6%prior 28
Dark - roadway lighted13 (9.6%)
↑44.4%prior 9
Dawn5 (3.7%)
Dusk2 (1.5%)
↓-66.7%prior 6

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

Road Surface

Dry85 (62.5%)
↑16.4%prior 73
Ice/frost19 (14.0%)
↓-29.6%prior 27
Wet15 (11.0%)
↑15.4%prior 13
Snow11 (8.1%)
↓-57.7%prior 26
Gravel5 (3.7%)
Mud, dirt1 (0.7%)

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

Vehicles & Demographics

The makes of vehicles involved in crashes remained consistent, with Ford and Chevrolet models being the most frequent in both 2019 and 2020. The age distribution of persons involved in crashes shifted; the 21-25 age group's share of involvement increased from 8.6% in 2019 to 11.8% in 2020. In contrast, the representation of the 65+ age group decreased from 13.4% to 9.4% of all persons involved.

Top Vehicle Makes (264 vehicles)

1
FORD40 (15.2%)
↓-32.2%prior 59
2
CHEV28 (10.6%)
↓-15.2%prior 33
3
CHEVROLET18 (6.8%)
↓-40.0%prior 30
4
FREIGHTLINER14 (5.3%)
↑55.6%prior 9
5
DODGE13 (4.9%)
↑44.4%prior 9
6
DODG13 (4.9%)
↑44.4%prior 9
7
JEEP12 (4.5%)
↑71.4%prior 7
8
NR11 (4.2%)
9
GMC10 (3.8%)
↑11.1%prior 9
10
CHRY9 (3.4%)
↑28.6%prior 7

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

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

Sex Distribution (236 persons with recorded sex)

Male145 (61.4%)
↓-13.2%prior 167
Female91 (38.6%)
↑3.4%prior 88

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: 177
  • Total persons involved: 372
  • Total vehicles involved: 264

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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