Yearly Traffic Safety Analysis

236 CRASHES IN
IOWA, IA
2020

All metrics benchmarked against2019

In Floyd County, total vehicle crashes decreased by 14.8% from 277 in 2019 to 236 in 2020. While overall collisions and injuries declined, the number of fatalities remained stable at one death in each period. The most significant year-over-year shift was in contributing factors, with crashes attributed to animals increasing by nearly 30% while those linked to driving too fast for conditions fell by 76%.

236

▼ -14.8%was 277

Total Crash Events

1

Persons Killed

67

▼ -5.6%was 71

Persons Injured

1

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 Floyd County showed a downward trend from 2019 to 2020. The total number of crashes fell from 277 to 236, and total injuries decreased from 71 to 67. However, the number of crash-related fatalities held steady at one death recorded in both 2019 and 2020.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

1

Cyclists Killed

Prior: 0→%

0

Motorists Killed

Prior: 1↓-100.0%

1

Pedestrians Injured

Prior: 0→%

0

Cyclists Injured

Prior: 1↓-100.0%

66

Motorists Injured

Prior: 70↓-5.7%

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, Friday was the peak day for crashes with 47 incidents, a change from 2019 when Tuesday was the peak with 49 crashes. The peak hour for collisions also shifted slightly, moving from 4 p.m. in 2019 (19 crashes) to 5 p.m. in 2020 (19 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 the number of fatal crashes was unchanged at one incident in both years, the fatal crash rate increased from 0.36% in 2019 to 0.42% in 2020 due to the lower overall crash total. The proportion of crashes resulting in minor injuries grew from 5.4% of all crashes in 2019 to 8.5% in 2020. Conversely, the share of crashes involving possible injuries decreased from 11.9% to 10.6% year-over-year.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.4%
→0.0%prior 1
Serious Injury5serious injury crashes2.1%
↓-16.7%prior 6
Minor Injury20minor injury crashes8.5%
↑33.3%prior 15
Possible Injury25possible injury crashes10.6%
↓-24.2%prior 33
No Injury185no injury crashes78.4%
↓-16.7%prior 222

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 were the leading contributing factor in both years, but their count increased by 29.7%, from 74 crashes in 2019 to 96 in 2020. In contrast, crashes attributed to 'driving too fast for conditions' saw a major 76% reduction in count, falling from 25 incidents in 2019 to just 6 in 2020. Similarly, crashes from failing to yield at a stop sign were halved, dropping from 18 in 2019 to 9 in 2020.

Officer-Reported Primary Contributing Cause

Animal96 (40.7%)↑29.7%prior 74
Lost Control11 (4.7%)↓-15.4%prior 13
Ran off road - left10 (4.2%)↓-37.5%prior 16
Followed too close10 (4.2%)↓-9.1%prior 11
FTYROW: From stop sign9 (3.8%)↓-50.0%prior 18
Ran Stop Sign9 (3.8%)↓-40.0%prior 15
Driver Distraction: Inattentive/lost in thought8 (3.4%)
Improper Backing7 (3%)
Operating vehicle in an reckless, erratic, careless, negligent manner7 (3%)
Other (explain in narrative): Other6 (2.5%)↓-33.3%prior 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

Crashes occurred under substantially better road conditions in 2020 compared to the prior year. Collisions on roads with snow or ice dropped significantly, from a combined 59 incidents in 2019 to 16 in 2020. Consequently, the number of crashes on dry roads accounted for a larger share of the total in 2020, even as their absolute count fell from 129 to 109.

Weather

Clear106 (72.6%)
↓-26.4%prior 144
Cloudy32 (21.9%)
↑3.2%prior 31
Snow4 (2.7%)
↓-69.2%prior 13
Blowing Snow1 (0.7%)
↓-87.5%prior 8
Freezing rain/drizzle1 (0.7%)
↓-83.3%prior 6
Rain1 (0.7%)
↓-85.7%prior 7
Severe Winds1 (0.7%)

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

Lighting

Daylight105 (71.9%)
↓-29.5%prior 149
Dark - roadway lighted20 (13.7%)
↓-28.6%prior 28
Dark - roadway not lighted16 (11.0%)
↓-48.4%prior 31
Dawn4 (2.7%)
Dusk1 (0.7%)

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

Road Surface

Dry109 (74.7%)
↓-15.5%prior 129
Wet12 (8.2%)
↓-29.4%prior 17
Snow9 (6.2%)
↓-71.0%prior 31
Ice/frost7 (4.8%)
↓-75.0%prior 28
Gravel5 (3.4%)
Slush2 (1.4%)
Mud, dirt1 (0.7%)
Sand1 (0.7%)

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

Vehicles & Demographics

The top vehicle makes involved in crashes, Chevrolet and Ford, remained the same across both periods, though the number of crashes involving them declined in 2020. Ford-involved crashes fell from 79 to 51, and Chevrolet-involved crashes dropped from 102 to 72. Demographically, the most notable change was a decrease in the number of persons aged 26-34 involved in crashes, which fell from 100 in 2019 to 77 in 2020.

Top Vehicle Makes (338 vehicles)

1
CHEV54 (16%)
↓-26.0%prior 73
2
FORD51 (15.1%)
↓-35.4%prior 79
3
CHEVROLET18 (5.3%)
↓-37.9%prior 29
4
DODG17 (5%)
↓-41.4%prior 29
5
GMC13 (3.8%)
6
CHRY12 (3.6%)
↓-33.3%prior 18
7
PONT11 (3.3%)
↑10.0%prior 10
8
JEEP10 (3%)
↓-41.2%prior 17
9
BUIC10 (3%)
→0.0%prior 10
10
TOYT9 (2.7%)
↓-30.8%prior 13

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

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

Sex Distribution (305 persons with recorded sex)

Male171 (56.1%)
↓-26.0%prior 231
Female134 (43.9%)
↓-19.3%prior 166

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: 236
  • Total persons involved: 519
  • Total vehicles involved: 338

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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