Yearly Traffic Safety Analysis

101 CRASHES IN
IOWA, IA
2020

All metrics benchmarked against2019

In 2020, Davis County recorded 101 total crashes, an 11.0% increase from the 91 crashes documented in 2019. While the number of fatalities remained unchanged at one, the number of people injured rose from 30 to 35. The most significant year-over-year change was a 250% increase in crashes resulting in a serious injury, which grew from 2 incidents in 2019 to 7 in 2020.

101

▲ 11.0%was 91

Total Crash Events

1

Persons Killed

35

▲ 16.7%was 30

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

Overall traffic crash trends in Davis County moved upward between 2019 and 2020. The total number of crashes increased by 11.0%, rising from 91 to 101. This was accompanied by a 16.7% rise in total injuries from 30 to 35, while fatalities held steady with one death reported in each year.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

1

Motorists Killed

Prior: 1→0.0%

1

Pedestrians Injured

Prior: 0→%

34

Motorists Injured

Prior: 28↑21.4%

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 time of day when crashes were most likely to occur remained consistent, with the 5 p.m. hour being the peak time in both 2019 and 2020, each recording 11 crashes. However, the peak day for crashes shifted from Friday (17 crashes) in 2019 to Monday (18 crashes) in 2020. The day with the fewest crashes also changed, from Wednesday in the prior period to Thursday in the current period.

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 remained stable at one incident in both 2019 and 2020, the severity of non-fatal injury crashes worsened. Crashes resulting in serious injuries increased significantly, from 2 incidents (2.2% of all crashes) in 2019 to 7 incidents (6.9%) in 2020. Consequently, the share of crashes with no reported injuries decreased from 80.2% in the prior year to 75.2% in the current year.

Outcome by Severity (Crash Events)

Fatal1fatal crashes1%
→0.0%prior 1
Serious Injury7serious injury crashes6.9%
↑250.0%prior 2
Minor Injury8minor injury crashes7.9%
↑60.0%prior 5
Possible Injury9possible injury crashes8.9%
↓-10.0%prior 10
No Injury76no injury crashes75.2%
↑4.1%prior 73

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, with an identical count of 35 incidents in 2019 and 2020. The count of crashes attributed to 'Driving too fast for conditions' more than doubled, increasing from 3 to 7 incidents year-over-year. Crashes involving a driver who 'Lost Control' also increased from 7 in the prior period to 10 in the current period.

Officer-Reported Primary Contributing Cause

Animal35 (34.7%)→0.0%prior 35
Lost Control10 (9.9%)↑42.9%prior 7
Driving too fast for conditions7 (6.9%)
Ran off road - straight6 (5.9%)→0.0%prior 6
FTYROW: From stop sign5 (5%)→0.0%prior 5
Followed too close4 (4%)
Other (explain in narrative): Other3 (3%)
Ran off road - left3 (3%)
Ran Traffic Signal2 (2%)
Passing: Other passing (explain in narrative)2 (2%)

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 on dry roads saw a notable increase, rising from 38 in 2019 to 52 in 2020. In contrast, incidents on icy or frosty road surfaces dropped sharply from 11 crashes in the prior period to only 1 in the current period. Crashes occurring in clear weather increased in both count (from 43 to 54) and as a proportion of all crashes, while incidents in daylight conditions increased in count but remained proportionally stable.

Weather

Clear54 (79.4%)
↑25.6%prior 43
Snow6 (8.8%)
Cloudy5 (7.4%)
↓-44.4%prior 9
Freezing rain/drizzle2 (2.9%)
Fog, smoke, smog1 (1.5%)

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

Lighting

Daylight43 (63.2%)
↑10.3%prior 39
Dark - roadway not lighted19 (27.9%)
↑18.8%prior 16
Dawn3 (4.4%)
Dusk2 (2.9%)
Dark - roadway lighted1 (1.5%)

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

Road Surface

Dry52 (76.5%)
↑36.8%prior 38
Snow8 (11.8%)
↑60.0%prior 5
Gravel4 (5.9%)
Ice/frost1 (1.5%)
↓-90.9%prior 11
Mud, dirt1 (1.5%)
Slush1 (1.5%)
Wet1 (1.5%)
↓-83.3%prior 6

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 for both periods. The most significant demographic shift occurred in the 26-34 age group, where the number of people involved in crashes nearly tripled from 15 in 2019 to 42 in 2020. The 16-20 age group also saw a substantial increase in crash involvement, rising from 19 individuals to 31.

Top Vehicle Makes (139 vehicles)

1
FORD23 (16.5%)
↓-8.0%prior 25
2
CHEV22 (15.8%)
↑10.0%prior 20
3
DODG16 (11.5%)
↑60.0%prior 10
4
GMC9 (6.5%)
5
CHEVROLET8 (5.8%)
↓-42.9%prior 14
6
DODGE5 (3.6%)
→0.0%prior 5
7
TOYOTA4 (2.9%)
8
CHRYSLER4 (2.9%)
9
TOYT3 (2.2%)
10
BUIC3 (2.2%)

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 (131 persons with recorded sex)

Male88 (67.2%)
↑15.8%prior 76
Female43 (32.8%)
↓-2.3%prior 44

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: 101
  • Total persons involved: 218
  • Total vehicles involved: 139

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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