Yearly Traffic Safety Analysis

199 CRASHES IN
IOWA, IA
2020

All metrics benchmarked against2019

In 2020, Washington County recorded 199 total crashes, an 8.3% decrease from the 217 crashes reported in 2019. Despite the overall reduction in collisions, the total number of people injured increased by 17.6%, rising from 74 in 2019 to 87 in 2020. While total fatalities decreased from 4 to 2 year-over-year, the number of serious injury crashes more than doubled from 4 to 10.

199

▼ -8.3%was 217

Total Crash Events

2

▼ -50.0%was 4

Persons Killed

87

▲ 17.6%was 74

Persons Injured

1

▼ -66.7%was 3

Fatal Crash Events

Note: "Persons Killed" (2) 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 Washington County showed a downward trend, decreasing by 8.3% from 217 incidents in 2019 to 199 in 2020. While the number of fatal crashes fell from 3 to 1 and total fatalities were halved from 4 to 2, the number of people injured in crashes increased by 17.6% over the same period, from 74 to 87.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

0

Cyclists Killed

Prior: 0→0.0%

2

Motorists Killed

Prior: 4↓-50.0%

1

Pedestrians Injured

Prior: 0→%

2

Cyclists Injured

Prior: 0→%

84

Motorists Injured

Prior: 74↑13.5%

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 significantly between the two periods. In 2020, the peak day for crashes was Wednesday with 37 incidents, and the peak hour was 5 p.m. with 20 incidents. This contrasts with 2019, when crashes peaked on Mondays (41 incidents) and during the 7 a.m. morning commute hour, which saw 22 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 total number of crashes decreased, the proportion of crashes resulting in an injury increased in 2020. The fatal crash count dropped from 3 in 2019 to 1 in 2020, with the rate falling from 1.4% to 0.5% of all crashes. However, the share of serious injury crashes rose from 1.8% (4 crashes) to 5.0% (10 crashes), and the share of minor injury crashes increased from 11.1% (24 crashes) to 16.1% (32 crashes).

Severity is per crash event (most severe injury). 1 fatal crash events resulted in 2 persons killed.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.5%
↓-66.7%prior 3
Serious Injury10serious injury crashes5%
↑150.0%prior 4
Minor Injury32minor injury crashes16.1%
↑33.3%prior 24
Possible Injury33possible injury crashes16.6%
↓-10.8%prior 37
No Injury123no injury crashes61.8%
↓-17.4%prior 149

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 involving an animal remained the leading contributing factor in both periods, with 25 incidents in 2020 compared to 24 in 2019. A notable shift occurred in stop sign-related incidents; crashes attributed to 'Ran Stop Sign' increased in count from 6 to 17, while those coded as 'FTYROW: From stop sign' decreased from 19 to 7. The count of crashes involving 'Driving too fast for conditions' also rose from 13 to 18, making it the second-most cited factor in 2020.

Officer-Reported Primary Contributing Cause

Animal25 (12.6%)↑4.2%prior 24
Driving too fast for conditions18 (9%)↑38.5%prior 13
Ran Stop Sign17 (8.5%)↑183.3%prior 6
Lost Control15 (7.5%)↓-16.7%prior 18
Ran off road - left14 (7%)↓-30.0%prior 20
Followed too close14 (7%)↓-6.7%prior 15
Driver Distraction: Other interior distraction12 (6%)↑71.4%prior 7
FTYROW: From stop sign7 (3.5%)↓-63.2%prior 19
Exceeded authorized speed6 (3%)
FTYROW: Making left turn5 (2.5%)↓-58.3%prior 12

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 proportion of crashes occurring in clear weather was higher in 2020, accounting for 71.9% of incidents compared to 60.4% in 2019. There was a notable shift in lighting conditions, with the share of crashes in daylight decreasing from 69.6% to 58.3% year-over-year. Concurrently, the proportion of crashes occurring on dark, unlighted roadways increased from 13.4% (29 crashes) in 2019 to 22.1% (44 crashes) in 2020.

Weather

Clear143 (73.7%)
↑9.2%prior 131
Cloudy20 (10.3%)
↓-51.2%prior 41
Rain11 (5.7%)
↓-8.3%prior 12
Snow9 (4.6%)
↑28.6%prior 7
Freezing rain/drizzle6 (3.1%)
↓-14.3%prior 7
Fog, smoke, smog2 (1.0%)
Blowing Snow1 (0.5%)
↓-85.7%prior 7
Severe Winds1 (0.5%)
Sleet, hail1 (0.5%)

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

Lighting

Daylight116 (60.4%)
↓-23.2%prior 151
Dark - roadway not lighted44 (22.9%)
↑51.7%prior 29
Dark - roadway lighted13 (6.8%)
→0.0%prior 13
Dawn8 (4.2%)
↓-27.3%prior 11
Dusk8 (4.2%)
Dark - unknown roadway lighting3 (1.6%)

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

Road Surface

Dry136 (70.1%)
↓-2.9%prior 140
Wet18 (9.3%)
↓-14.3%prior 21
Ice/frost15 (7.7%)
↓-28.6%prior 21
Gravel14 (7.2%)
↑75.0%prior 8
Slush6 (3.1%)
Snow4 (2.1%)
↓-71.4%prior 14
Other (explain in narrative)1 (0.5%)

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 remained consistent, with Chevrolet, Ford, and Dodge being the most frequent in both 2020 and 2019, although the total number of vehicles involved decreased from 352 to 304. A notable demographic shift occurred among persons involved in collisions. The 16-20 age group saw its involvement increase from 42 individuals in 2019 to 64 in 2020, becoming the most represented age bracket. Conversely, the number of individuals aged 65 and older involved in crashes decreased from 73 to 50 over the same period.

Top Vehicle Makes (304 vehicles)

1
FORD44 (14.5%)
↓-21.4%prior 56
2
CHEV36 (11.8%)
↓-34.5%prior 55
3
CHEVROLET24 (7.9%)
↑20.0%prior 20
4
DODG14 (4.6%)
↑7.7%prior 13
5
DODGE12 (3.9%)
↑20.0%prior 10
6
TOYT11 (3.6%)
↓-8.3%prior 12
7
GMC10 (3.3%)
↓-9.1%prior 11
8
HOND9 (3%)
↑12.5%prior 8
9
FREIGHTLINER9 (3%)
↑50.0%prior 6
10
BUIC9 (3%)
↓-10.0%prior 10

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

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

Sex Distribution (280 persons with recorded sex)

Male187 (66.8%)
↑1.6%prior 184
Female93 (33.2%)
↓-34.5%prior 142

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: 199
  • Total persons involved: 431
  • Total vehicles involved: 304

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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