Yearly Traffic Safety Analysis

340 CRASHES IN
IOWA, IA
2020

All metrics benchmarked against2019

In 2020, Cedar County recorded 340 total vehicle crashes, a 13.7% decrease from the 394 crashes reported in 2019. Despite the overall reduction in collisions, the number of fatalities increased significantly, rising from 1 in 2019 to 5 in 2020. Total injuries, however, saw a decrease from 88 to 67 over the same period.

340

▼ -13.7%was 394

Total Crash Events

5

▲ 400.0%was 1

Persons Killed

67

▼ -23.9%was 88

Persons Injured

3

▲ 200.0%was 1

Fatal Crash Events

Note: "Persons Killed" (5) 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

The overall trend in Cedar County shows a notable decrease in traffic collisions year-over-year. Total crashes fell by 13.7%, from 394 in 2019 to 340 in 2020. This downward trend was also reflected in the number of injuries, which decreased by 23.9%, but was contrasted by a sharp rise in fatalities from 1 to 5.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

0

Cyclists Killed

Prior: 0→0.0%

5

Motorists Killed

Prior: 1↑400.0%

3

Pedestrians Injured

Prior: 1↑200.0%

1

Cyclists Injured

Prior: 1→0.0%

63

Motorists Injured

Prior: 86↓-26.7%

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 in Cedar County shifted between 2019 and 2020. The peak day for collisions moved from Thursday (75 crashes) in 2019 to Wednesday (59 crashes) in 2020. A more significant change occurred in the peak hour, which shifted from the 7 AM morning commute in 2019 (34 crashes) to the 6 PM evening hour in 2020 (27 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 severity of outcomes worsened in 2020. The number of fatal crashes tripled from 1 in 2019 to 3 in 2020, and the fatal crash rate increased from 0.25 to 0.88 per 100 crashes. The total number of injury-related crashes declined from 72 to 57, with minor injury crashes seeing the largest drop. However, the count of serious injury crashes remained unchanged at 9 incidents for both years.

Severity is per crash event (most severe injury). 3 fatal crash events resulted in 5 persons killed.

Outcome by Severity (Crash Events)

Fatal3fatal crashes0.9%
↑200.0%prior 1
Serious Injury9serious injury crashes2.6%
→0.0%prior 9
Minor Injury26minor injury crashes7.6%
↓-33.3%prior 39
Possible Injury22possible injury crashes6.5%
↓-8.3%prior 24
No Injury280no injury crashes82.4%
↓-12.8%prior 321

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 primary contributing factors for crashes in Cedar County remained consistent year-over-year, though their counts decreased. Collisions involving an animal were the leading cause in both periods, with 93 incidents in 2020, a slight decrease from 94 in 2019. Significant reductions were seen in other top factors: crashes from 'Ran off road - straight' fell by 35.8% from 53 to 34, and those from 'Driving too fast for conditions' dropped by 29.8% from 47 to 33. The top three factors maintained their rank order across both years.

Officer-Reported Primary Contributing Cause

Animal93 (27.4%)↓-1.1%prior 94
Ran off road - straight34 (10%)↓-35.8%prior 53
Driving too fast for conditions33 (9.7%)↓-29.8%prior 47
Lost Control29 (8.5%)↓-19.4%prior 36
Ran off road - left18 (5.3%)↓-5.3%prior 19
Followed too close14 (4.1%)↓-22.2%prior 18
Other (explain in narrative): Other12 (3.5%)↓-20.0%prior 15
FTYROW: From stop sign11 (3.2%)↑22.2%prior 9
Improper or erratic lane changing9 (2.6%)↑28.6%prior 7
Driver Distraction: Other interior distraction8 (2.4%)↑14.3%prior 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

Crashes in clear weather and on dry roads remained the most common scenario in both 2019 and 2020, with their proportions staying relatively stable. However, there was a notable decrease in crashes occurring in adverse weather conditions. Collisions in snow dropped from 54 incidents in 2019 to 26 in 2020. Similarly, crashes on snow or ice-covered roads fell from a combined 70 incidents to 57.

Weather

Clear149 (59.8%)
↓-12.4%prior 170
Cloudy30 (12.0%)
↓-30.2%prior 43
Snow26 (10.4%)
↓-51.9%prior 54
Rain16 (6.4%)
↓-23.8%prior 21
Freezing rain/drizzle16 (6.4%)
Fog, smoke, smog5 (2.0%)
↓-28.6%prior 7
Blowing Snow4 (1.6%)
↓-42.9%prior 7
Severe Winds2 (0.8%)
Sleet, hail1 (0.4%)

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

Lighting

Daylight157 (61.8%)
↓-21.5%prior 200
Dark - roadway not lighted70 (27.6%)
↓-11.4%prior 79
Dark - roadway lighted10 (3.9%)
↓-16.7%prior 12
Dawn7 (2.8%)
↑16.7%prior 6
Dusk5 (2.0%)
↓-37.5%prior 8
Dark - unknown roadway lighting5 (2.0%)

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

Road Surface

Dry149 (59.6%)
↓-15.3%prior 176
Ice/frost31 (12.4%)
↑14.8%prior 27
Wet26 (10.4%)
↓-36.6%prior 41
Snow26 (10.4%)
↓-39.5%prior 43
Gravel14 (5.6%)
↓-17.6%prior 17
Sand1 (0.4%)
Slush1 (0.4%)
Water (standing or moving)1 (0.4%)
Mud, dirt1 (0.4%)

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 and Ford leading in both years, though their total counts decreased in 2020. In 2020, 85 Chevrolet and 69 Ford vehicles were involved in crashes, down from 104 and 95 respectively in 2019. Analysis of persons involved shows a shift in age demographics; the proportion of individuals aged 16-20 increased from 12.8% in 2019 to 16.5% in 2020, while the representation of the 26-34 age group decreased from 22.6% to 16.0%.

Top Vehicle Makes (483 vehicles)

1
FORD69 (14.3%)
↓-27.4%prior 95
2
CHEV52 (10.8%)
↓-14.8%prior 61
3
CHEVROLET33 (6.8%)
↓-23.3%prior 43
4
FREIGHTLINER26 (5.4%)
↓-7.1%prior 28
5
DODG19 (3.9%)
↓-9.5%prior 21
6
TOYOTA18 (3.7%)
↑80.0%prior 10
7
TOYT14 (2.9%)
↑27.3%prior 11
8
PETERBILT14 (2.9%)
↑55.6%prior 9
9
JEEP13 (2.7%)
↓-13.3%prior 15
10
DODGE13 (2.7%)
↑18.2%prior 11

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

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

Sex Distribution (444 persons with recorded sex)

Male291 (65.5%)
↓-16.4%prior 348
Female153 (34.5%)
↓-15.9%prior 182

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: 340
  • Total persons involved: 671
  • Total vehicles involved: 483

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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