Yearly Traffic Safety Analysis

1,636 CRASHES IN
IOWA, IA
2020

All metrics benchmarked against2019

In Johnson County, total crashes decreased from 2,606 in 2019 to 1,636 in 2020, a 37.2% reduction. This significant drop in collisions was accompanied by a decrease in both total injuries, from 693 to 517, and fatalities, from 9 to 3, year-over-year. The most notable shift was this substantial overall reduction in crash volume across nearly all categories, though the proportion of crashes resulting in serious injuries increased.

1,636

▼ -37.2%was 2,606

Total Crash Events

3

▼ -66.7%was 9

Persons Killed

517

▼ -25.4%was 693

Persons Injured

3

▼ -57.1%was 7

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

Crash data for Johnson County shows a significant downward trend year-over-year. Total crashes fell by 37.2%, from 2,606 in 2019 to 1,636 in 2020. This trend extended to crash outcomes, with total injuries declining by 25.4% (from 693 to 517) and total fatalities decreasing from 9 to 3.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

0

Cyclists Killed

Prior: 1↓-100.0%

3

Motorists Killed

Prior: 8↓-62.5%

0

Other Killed

Prior: 0→0.0%

14

Pedestrians Injured

Prior: 18↓-22.2%

18

Cyclists Injured

Prior: 34↓-47.1%

483

Motorists Injured

Prior: 640↓-24.5%

2

Other Injured

Prior: 1↑100.0%

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

The temporal patterns of crashes shifted between the two periods. In 2020, the peak day for crashes was Wednesday with 276 incidents, a change from Friday (503 crashes) in 2019. The peak hour also shifted earlier, from 5 p.m. in 2019 (245 crashes) to 4 p.m. in 2020 (164 crashes), alongside a general decrease in crash counts during traditional commute times.

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 fell from 7 to 3 year-over-year, the severity mix of non-fatal crashes changed. The proportion of crashes resulting in serious injuries increased from 1.2% (32 crashes) in 2019 to 2.6% (42 crashes) in 2020. Conversely, crashes resulting in only possible injury decreased as a share of all incidents from 14.3% to 13.3%, and no-injury crashes fell from a 76.8% share to 73.8%.

Outcome by Severity (Crash Events)

Fatal3fatal crashes0.2%
↓-57.1%prior 7
Serious Injury42serious injury crashes2.6%
↑31.3%prior 32
Minor Injury167minor injury crashes10.2%
↓-13.5%prior 193
Possible Injury217possible injury crashes13.3%
↓-41.7%prior 372
No Injury1,207no injury crashes73.8%
↓-39.7%prior 2,002

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 factors remained consistent, though their counts dropped significantly in line with the overall trend. 'Followed too close' was the top factor in both years, but its count fell by 53% from 474 crashes in 2019 to 223 in 2020. Similarly, crashes attributed to 'Driving too fast for conditions' decreased by 45.6% from 237 to 129 incidents. 'Ran off road - left' moved up in the rankings to become the third most common factor in 2020 with 114 incidents.

Officer-Reported Primary Contributing Cause

Followed too close223 (13.6%)↓-53.0%prior 474
Driving too fast for conditions129 (7.9%)↓-45.6%prior 237
Ran off road - left114 (7%)↓-18.0%prior 139
Animal100 (6.1%)↓-39.0%prior 164
Other (explain in narrative): Other96 (5.9%)↓-41.1%prior 163
Lost Control68 (4.2%)↓-26.1%prior 92
FTYROW: From stop sign54 (3.3%)↓-46.5%prior 101
FTYROW: Making left turn53 (3.2%)↓-42.4%prior 92
Ran off road - straight53 (3.2%)↓-5.4%prior 56
Other (explain in narrative): No improper action52 (3.2%)↓-29.7%prior 74

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 distribution of crashes by environmental conditions remained broadly similar year-over-year, despite the large drop in total incidents. Crashes on dry road surfaces accounted for 68.5% of the total in 2020, nearly identical to the 68.3% share in 2019. Similarly, the proportion of crashes occurring in daylight was stable, at 66.9% in 2020 versus 69.5% in 2019. While the absolute number of crashes in adverse weather like snow (down from 161 to 84) and rain (down from 148 to 102) decreased, their share of the total did not change significantly.

Weather

Clear1,028 (65.4%)
↓-34.2%prior 1,563
Cloudy277 (17.6%)
↓-50.1%prior 555
Rain102 (6.5%)
↓-31.1%prior 148
Snow84 (5.3%)
↓-47.8%prior 161
Freezing rain/drizzle56 (3.6%)
↑16.7%prior 48
Blowing Snow9 (0.6%)
↓-65.4%prior 26
Fog, smoke, smog6 (0.4%)
↓-40.0%prior 10
Severe Winds5 (0.3%)
↓-28.6%prior 7
Other (explain in narrative)4 (0.3%)
Sleet, hail1 (0.1%)

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

Lighting

Daylight1,094 (69.5%)
↓-39.6%prior 1,812
Dark - roadway lighted211 (13.4%)
↓-33.9%prior 319
Dark - roadway not lighted167 (10.6%)
↓-40.6%prior 281
Dusk48 (3.1%)
↓-28.4%prior 67
Dawn40 (2.5%)
↓-20.0%prior 50
Dark - unknown roadway lighting13 (0.8%)
↑44.4%prior 9

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

Road Surface

Dry1,121 (71.2%)
↓-37.1%prior 1,781
Wet213 (13.5%)
↓-31.7%prior 312
Ice/frost111 (7.0%)
↓-36.2%prior 174
Snow84 (5.3%)
↓-59.8%prior 209
Slush25 (1.6%)
↓-26.5%prior 34
Gravel14 (0.9%)
↑40.0%prior 10
Other (explain in narrative)5 (0.3%)
Mud, dirt2 (0.1%)

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

Vehicles & Demographics

The demographics of vehicles and persons involved in crashes showed consistency between 2019 and 2020. The most common vehicle makes involved in collisions remained Ford, Chevrolet, and Toyota in both years, though the total count for each make decreased substantially. The age distribution of individuals involved in crashes also saw minimal change; for example, the 26-34 age group represented 16.7% of persons in 2020, compared to 16.3% in 2019.

Top Vehicle Makes (2,980 vehicles)

1
FORD425 (14.3%)
↓-40.5%prior 714
2
CHEV256 (8.6%)
↓-41.8%prior 440
3
TOYT208 (7%)
↓-50.4%prior 419
4
CHEVROLET185 (6.2%)
↓-12.3%prior 211
5
HOND126 (4.2%)
↓-55.5%prior 283
6
TOYOTA122 (4.1%)
↓-35.8%prior 190
7
NR101 (3.4%)
↓-22.9%prior 131
8
JEEP94 (3.2%)
↓-40.5%prior 158
9
DODG88 (3%)
↓-20.0%prior 110
10
GMC87 (2.9%)
↓-6.5%prior 93

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

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

Sex Distribution (2,695 persons with recorded sex)

Male1,571 (58.3%)
↓-37.0%prior 2,494
Female1,124 (41.7%)
↓-42.4%prior 1,951

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: 1,636
  • Total persons involved: 3,897
  • Total vehicles involved: 2,980

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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