Yearly Traffic Safety Analysis

1,776 CRASHES IN
IOWA, IA
2020

All metrics benchmarked against2019

In 2020, Dubuque County recorded 1,776 vehicle crashes, a 17.4% decrease from the 2,149 crashes reported in 2019. This overall decline was accompanied by a significant reduction in traffic fatalities, which fell from 8 to 3 year-over-year. The total number of injuries also decreased by 19.7% from 633 to 508.

1,776

▼ -17.4%was 2,149

Total Crash Events

3

▼ -62.5%was 8

Persons Killed

508

▼ -19.7%was 633

Persons Injured

3

▼ -62.5%was 8

Fatal Crash Events

Note: "Persons Killed" (3) counts individual fatalities across all crash events. "Fatal" in the severity table below (3) 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 safety trends in Dubuque County showed a notable improvement from 2019 to 2020. Total crashes decreased by 17.4%, from 2,149 to 1,776. Similarly, the number of injuries fell by 19.7% from 633 to 508, and fatalities saw a 62.5% reduction from 8 to 3.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 2↓-100.0%

0

Cyclists Killed

Prior: 0→0.0%

3

Motorists Killed

Prior: 6↓-50.0%

0

Other Killed

Prior: 0→0.0%

17

Pedestrians Injured

Prior: 16↑6.3%

6

Cyclists Injured

Prior: 12↓-50.0%

484

Motorists Injured

Prior: 605↓-20.0%

1

Other Injured

Prior: 0→%

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

Year-over-year temporal patterns show a shift in the busiest day for crashes, moving from Thursday (377 crashes) in 2019 to Friday (290 crashes) in 2020. The peak hour for collisions remained consistent at 5 PM in both periods, though the number of crashes during this hour decreased from 213 to 138. The monthly distribution of crashes also changed, with a sharp decline in incidents during April 2020, which saw only 57 crashes compared to 164 in April 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

The severity of crashes decreased from 2019 to 2020, with the fatal crash rate falling from 0.37% to 0.17% of all incidents. The total number of fatal crashes dropped from 8 to 3. The proportion of serious injury crashes also saw a slight decline from 1.3% to 1.1% of all incidents, while the share of crashes resulting in minor injuries increased slightly from 7.7% to 8.3%.

Outcome by Severity (Crash Events)

Fatal3fatal crashes0.2%
↓-62.5%prior 8
Serious Injury20serious injury crashes1.1%
↓-28.6%prior 28
Minor Injury147minor injury crashes8.3%
↓-10.9%prior 165
Possible Injury255possible injury crashes14.4%
↓-19.8%prior 318
No Injury1,351no injury crashes76.1%
↓-17.1%prior 1,630

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

The leading contributing factor in both periods was 'Ran off road - left,' though its count decreased by 19% from 542 incidents in 2019 to 439 in 2020. Crashes involving animals, the second-ranked factor, increased in count by 23.7% from 215 to 266. Notably, incidents of 'Failure to yield right of way from a stop sign' dropped by 44.9% (from 118 to 65), while 'Ran Traffic Signal' incidents rose by 6.8% (from 103 to 110), entering the top three factors for 2020.

Officer-Reported Primary Contributing Cause

Ran off road - left439 (24.7%)↓-19.0%prior 542
Animal266 (15%)↑23.7%prior 215
Ran Traffic Signal110 (6.2%)↑6.8%prior 103
Lost Control91 (5.1%)↓-10.8%prior 102
Ran Stop Sign69 (3.9%)↓-41.0%prior 117
FTYROW: From stop sign65 (3.7%)↓-44.9%prior 118
Made improper turn61 (3.4%)↓-12.9%prior 70
FTYROW: Making left turn61 (3.4%)↓-10.3%prior 68
Other (explain in narrative): No improper action59 (3.3%)↓-9.2%prior 65
Ran off road - straight54 (3%)↑45.9%prior 37

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

In 2020, a greater proportion of crashes occurred under clear weather (57.1% vs. 49.7%) and on dry road surfaces (68.7% vs. 62.1%) compared to 2019. Correspondingly, the share of crashes on wet roads decreased from 13.7% to 10.2%. While the majority of incidents in both years happened during daylight, the proportion of daylight crashes fell from 66.7% in 2019 to 58.2% in 2020, while crashes in lighted dark conditions increased proportionally from 13.7% to 17.4%.

Weather

Clear1,015 (64.9%)
↓-5.1%prior 1,069
Cloudy305 (19.5%)
↓-44.3%prior 548
Snow102 (6.5%)
↓-37.4%prior 163
Rain97 (6.2%)
↓-10.2%prior 108
Freezing rain/drizzle25 (1.6%)
↓-45.7%prior 46
Sleet, hail7 (0.4%)
Fog, smoke, smog5 (0.3%)
↓-68.8%prior 16
Blowing Snow4 (0.3%)
↓-71.4%prior 14
Severe Winds1 (0.1%)
Other (explain in narrative)1 (0.1%)

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

Lighting

Daylight1,034 (66.0%)
↓-27.9%prior 1,434
Dark - roadway lighted309 (19.7%)
↑4.7%prior 295
Dark - roadway not lighted148 (9.5%)
↑7.2%prior 138
Dusk43 (2.7%)
↓-25.9%prior 58
Dawn29 (1.9%)
↓-31.0%prior 42
Dark - unknown roadway lighting3 (0.2%)

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

Road Surface

Dry1,221 (78.0%)
↓-8.5%prior 1,334
Wet182 (11.6%)
↓-38.1%prior 294
Snow93 (5.9%)
↓-41.5%prior 159
Slush37 (2.4%)
↓-14.0%prior 43
Ice/frost28 (1.8%)
↓-78.1%prior 128
Gravel3 (0.2%)
Oil1 (0.1%)

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

Vehicles & Demographics

The most common vehicle makes involved in crashes remained consistent, with Chevrolet, Ford, and Toyota leading in both 2019 and 2020, though the total number of vehicles for each make decreased. The age demographics of persons involved in crashes also showed relative stability year-over-year. For instance, the 16-20 age group represented 12.4% of individuals in both periods, while the 26-34 age group saw its share of involvement decrease slightly from 16.1% in 2019 to 14.6% in 2020.

Top Vehicle Makes (3,042 vehicles)

1
FORD440 (14.5%)
↓-21.1%prior 558
2
CHEV397 (13.1%)
↓-22.3%prior 511
3
CHEVROLET260 (8.5%)
↓-16.9%prior 313
4
TOYT133 (4.4%)
↓-31.4%prior 194
5
JEEP130 (4.3%)
↓-24.9%prior 173
6
DODG113 (3.7%)
↓-26.6%prior 154
7
GMC111 (3.6%)
↓-19.0%prior 137
8
HOND107 (3.5%)
↓-28.7%prior 150
9
KIA98 (3.2%)
↓-3.0%prior 101
10
DODGE85 (2.8%)
↓-12.4%prior 97

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

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

Sex Distribution (2,760 persons with recorded sex)

Male1,598 (57.9%)
↓-17.7%prior 1,942
Female1,162 (42.1%)
↓-25.4%prior 1,557

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: 1,776
  • Total persons involved: 4,037
  • Total vehicles involved: 3,042

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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