Yearly Traffic Safety Analysis

230 CRASHES IN
IOWA, IA
2020

All metrics benchmarked against2019

In Adair County, total crashes remained stable at 230 in 2020 compared to 2019. However, injuries increased by 12.66%, rising from 79 in 2019 to 89 in 2020. A significant shift was observed in DUI-related crashes, which decreased by 50%, from 12 in 2019 to 6 in 2020.

230

Total Crash Events

6

Persons Killed

89

▲ 12.7%was 79

Persons Injured

5

▼ -16.7%was 6

Fatal Crash Events

Note: "Persons Killed" (6) counts individual fatalities across all crash events. "Fatal" in the severity table below (5) 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 crash volume in Adair County remained stable year-over-year, with 230 crashes reported in both 2019 and 2020. Fatalities also remained constant at 6 for both periods. However, total injuries saw an increase of 12.66%, rising from 79 in 2019 to 89 in 2020.

Vulnerable Road User Casualties

6

Motorists Killed

Prior: 5↑20.0%

89

Motorists Injured

Prior: 78↑14.1%

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 in Adair County showed some shifts year-over-year. The peak day for crashes moved from Sunday in 2019, with 46 incidents, to Saturday in 2020, with 39 incidents. Similarly, the peak crash hour shifted from 4 PM in 2019 (18 crashes) to 5 PM in 2020 (17 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

The fatal crash rate in Adair County decreased slightly from 2.61% in 2019 to 2.17% in 2020. While serious injury crashes (severity A) decreased from 12 to 7, minor injury crashes (severity B) increased from 21 to 37 year-over-year. Overall, total injuries rose by 12.66%, from 79 in 2019 to 89 in 2020.

Severity is per crash event (most severe injury). 5 fatal crash events resulted in 6 persons killed.

Outcome by Severity (Crash Events)

Fatal5fatal crashes2.2%
↓-16.7%prior 6
Serious Injury7serious injury crashes3%
↓-41.7%prior 12
Minor Injury37minor injury crashes16.1%
↑76.2%prior 21
Possible Injury21possible injury crashes9.1%
↓-36.4%prior 33
No Injury160no injury crashes69.6%
↑1.3%prior 158

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

Animal-related incidents remained the leading contributing factor, increasing by 7 crashes from 51 in 2019 to 58 in 2020. Crashes attributed to 'Lost Control' saw a slight increase of 1, from 31 to 32, moving it to the second-highest factor. Conversely, 'Ran off road - straight' crashes decreased by 6, from 34 to 28. Notably, crashes involving 'Driving too fast for conditions' increased by 50%, rising from 10 to 15 incidents.

Officer-Reported Primary Contributing Cause

Animal58 (25.2%)↑13.7%prior 51
Lost Control32 (13.9%)↑3.2%prior 31
Ran off road - straight28 (12.2%)↓-17.6%prior 34
Driving too fast for conditions15 (6.5%)↑50.0%prior 10
Ran off road - left8 (3.5%)↓-33.3%prior 12
Followed too close7 (3%)↓-46.2%prior 13
FTYROW: Making left turn6 (2.6%)
Failed to keep in proper lane6 (2.6%)
Operating vehicle in an reckless, erratic, careless, negligent manner6 (2.6%)↓-33.3%prior 9
Exceeded authorized speed5 (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

Adverse weather conditions showed notable shifts; crashes in freezing rain/drizzle increased significantly from 4 in 2019 to 12 in 2020, while crashes during severe winds decreased from 9 to 4. Regarding road surface, wet road crashes decreased from 42 to 25, but crashes on snowy surfaces increased from 16 to 23. Daylight crashes decreased from 118 to 103, with dusk crashes increasing from 4 to 7.

Weather

Clear105 (56.5%)
↓-7.1%prior 113
Cloudy25 (13.4%)
→0.0%prior 25
Rain17 (9.1%)
↑30.8%prior 13
Snow14 (7.5%)
↓-30.0%prior 20
Freezing rain/drizzle12 (6.5%)
Blowing Snow6 (3.2%)
Severe Winds4 (2.2%)
↓-55.6%prior 9
Fog, smoke, smog3 (1.6%)
↓-57.1%prior 7

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

Lighting

Daylight103 (55.7%)
↓-12.7%prior 118
Dark - roadway not lighted60 (32.4%)
→0.0%prior 60
Dusk7 (3.8%)
Dawn7 (3.8%)
↑16.7%prior 6
Dark - roadway lighted6 (3.2%)
↓-40.0%prior 10
Dark - unknown roadway lighting2 (1.1%)

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

Road Surface

Dry108 (58.7%)
↓-4.4%prior 113
Wet25 (13.6%)
↓-40.5%prior 42
Snow23 (12.5%)
↑43.8%prior 16
Ice/frost13 (7.1%)
↓-7.1%prior 14
Gravel12 (6.5%)
Slush1 (0.5%)
↓-80.0%prior 5
Other (explain in narrative)1 (0.5%)
Mud, dirt1 (0.5%)

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

Vehicles & Demographics

Ford remained the most frequently involved vehicle make, with its count increasing from 40 in 2019 to 52 in 2020. Chevrolet-branded vehicles (Chevrolet and Chev combined) remained stable at 54 incidents. In terms of person demographics, individuals aged 16-20 involved in crashes increased from 34 to 46, while those aged 26-34 decreased from 101 to 91.

Top Vehicle Makes (303 vehicles)

1
FORD52 (17.2%)
↑30.0%prior 40
2
CHEVROLET29 (9.6%)
↑38.1%prior 21
3
CHEV25 (8.3%)
↓-24.2%prior 33
4
FREIGHTLINER19 (6.3%)
↑18.8%prior 16
5
KENWORTH12 (4%)
↑20.0%prior 10
6
RAM11 (3.6%)
↑57.1%prior 7
7
DODG11 (3.6%)
↑37.5%prior 8
8
TOYOTA11 (3.6%)
↑10.0%prior 10
9
DODGE11 (3.6%)
↓-26.7%prior 15
10
JEEP10 (3.3%)
↑42.9%prior 7

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

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

Sex Distribution (258 persons with recorded sex)

Male187 (72.5%)
→0.0%prior 187
Female71 (27.5%)
↓-21.1%prior 90

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: 230
  • Total persons involved: 461
  • Total vehicles involved: 303

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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