Yearly Traffic Safety Analysis

115 CRASHES IN
IOWA, IA
2020

All metrics benchmarked against2019

In 2020, Decatur County recorded 115 total crashes, a 5.0% decrease from the 121 crashes documented in 2019. Despite the overall reduction in collisions, the number of individuals injured saw a substantial year-over-year increase. The total number of injuries rose from 29 in 2019 to 46 in 2020, representing a 58.6% increase.

115

▼ -5.0%was 121

Total Crash Events

1

Persons Killed

46

▲ 58.6%was 29

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 crash trends in Decatur County showed a mixed pattern from 2019 to 2020. The total number of crashes decreased by 5.0%, from 121 to 115. However, the severity of outcomes worsened, with total injuries increasing by 58.6% from 29 to 46. The number of fatalities remained constant, with one person killed in each year.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 0→%

0

Motorists Killed

Prior: 1↓-100.0%

0

Pedestrians Injured

Prior: 1↓-100.0%

46

Motorists Injured

Prior: 27↑70.4%

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 peak days for crashes remained similar year-over-year, with Friday being a high-volume day in both 2019 (23 crashes) and 2020 (22 crashes). A significant shift occurred in the peak hour of crashes, moving from the 7 p.m. hour in 2019 (10 crashes) to the 6 a.m. hour in 2020 (13 crashes). Collisions during the 6 a.m. hour more than doubled, increasing from 6 incidents in 2019.

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 total number of fatal crashes was unchanged at one for both 2019 and 2020, the overall severity of crashes increased. The number of serious injury crashes quadrupled, rising from one in 2019 to four in 2020. Consequently, the proportion of crashes resulting in any level of injury (Fatal, Serious, Minor, or Possible) grew from 26.4% of all crashes in 2019 to 27.9% in 2020.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.9%
→0.0%prior 1
Serious Injury4serious injury crashes3.5%
↑300.0%prior 1
Minor Injury11minor injury crashes9.6%
↑22.2%prior 9
Possible Injury16possible injury crashes13.9%
↓-5.9%prior 17
No Injury83no injury crashes72.2%
↓-10.8%prior 93

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 slightly from 44 incidents in 2019 to 41 in 2020. 'Lost Control' was the second most frequent factor in both periods, with its count declining from 20 to 18. A notable increase was observed in crashes attributed to 'Ran off road - straight,' which rose from 7 incidents in 2019 to 11 in 2020, a 57.1% increase in count.

Officer-Reported Primary Contributing Cause

Animal41 (35.7%)↓-6.8%prior 44
Lost Control18 (15.7%)↓-10.0%prior 20
Ran off road - straight11 (9.6%)↑57.1%prior 7
Driving too fast for conditions8 (7%)
Other (explain in narrative): Other5 (4.3%)→0.0%prior 5
Ran off road - left4 (3.5%)↓-20.0%prior 5
Driver Distraction: Other interior distraction4 (3.5%)
Other (explain in narrative): No improper action3 (2.6%)
Operating vehicle in an reckless, erratic, careless, negligent manner3 (2.6%)
Driver Distraction: Inattentive/lost in thought2 (1.7%)

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 shift in crash conditions between the two periods. Collisions on dry roads decreased from 66 in 2019 to 51 in 2020, and crashes in clear weather fell from 58 to 44. Conversely, crashes on icy or frosty roads increased substantially, from 2 incidents in 2019 to 13 in 2020. Similarly, the number of crashes occurring in cloudy weather rose from 17 to 22.

Weather

Clear44 (47.8%)
↓-24.1%prior 58
Cloudy22 (23.9%)
↑29.4%prior 17
Snow9 (9.8%)
Freezing rain/drizzle7 (7.6%)
Rain5 (5.4%)
↓-28.6%prior 7
Fog, smoke, smog4 (4.3%)
Blowing Snow1 (1.1%)

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

Lighting

Daylight50 (54.3%)
↓-15.3%prior 59
Dark - roadway not lighted29 (31.5%)
↑7.4%prior 27
Dusk6 (6.5%)
Dawn3 (3.3%)
Dark - roadway lighted3 (3.3%)
Dark - unknown roadway lighting1 (1.1%)

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

Road Surface

Dry51 (55.4%)
↓-22.7%prior 66
Ice/frost13 (14.1%)
Wet9 (9.8%)
↓-25.0%prior 12
Snow8 (8.7%)
→0.0%prior 8
Gravel6 (6.5%)
Slush5 (5.4%)

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

Vehicles & Demographics

Ford vehicles were most frequently involved in crashes in 2020 with 28 units, overtaking Chevrolet, which had a combined total of 27 units ('CHEVROLET' and 'CHEV') down from 40 in 2019. The age distribution of persons involved also shifted; involvement for the 26-34 age group decreased from 42 individuals in 2019 to 36 in 2020. Meanwhile, the number of persons in the 16-20 age group increased from 17 to 21, and the 35-44 age group increased from 32 to 36.

Top Vehicle Makes (146 vehicles)

1
FORD28 (19.2%)
↑55.6%prior 18
2
CHEVROLET17 (11.6%)
↓-22.7%prior 22
3
CHEV10 (6.8%)
↓-44.4%prior 18
4
TOYOTA10 (6.8%)
5
FREIGHTLINER7 (4.8%)
6
DODGE7 (4.8%)
→0.0%prior 7
7
NISSAN6 (4.1%)
8
GMC4 (2.7%)
↓-42.9%prior 7
9
BUICK4 (2.7%)
10
KENWORTH4 (2.7%)
↓-20.0%prior 5

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

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

Sex Distribution (131 persons with recorded sex)

Male86 (65.6%)
↓-18.1%prior 105
Female45 (34.4%)
↑18.4%prior 38

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: 115
  • Total persons involved: 222
  • Total vehicles involved: 146

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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