Yearly Traffic Safety Analysis

520 CRASHES IN
IOWA, IA
2020

All metrics benchmarked against2019

In Wapello County, total traffic crashes decreased from 566 in 2019 to 520 in 2020, an 8.1% reduction. While overall collisions and fatalities declined, the number of crashes attributed to driving under the influence (DUI) increased by 50%, from 22 in the prior year to 33 in the current period. Fatalities decreased from 5 to 4, and total injuries saw a marginal decline from 204 to 201.

520

▼ -8.1%was 566

Total Crash Events

4

▼ -20.0%was 5

Persons Killed

201

▼ -1.5%was 204

Persons Injured

4

▼ -20.0%was 5

Fatal Crash Events

Note: "Persons Killed" (4) counts individual fatalities across all crash events. "Fatal" in the severity table below (4) 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 data for Wapello County indicates a downward trend in collisions year-over-year. The total number of crashes fell by 8.1%, from 566 in 2019 to 520 in 2020. This decline was accompanied by a slight reduction in both fatalities (from 5 to 4) and total injuries (from 204 to 201).

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

0

Cyclists Killed

Prior: 0→0.0%

4

Motorists Killed

Prior: 5↓-20.0%

3

Pedestrians Injured

Prior: 3→0.0%

2

Cyclists Injured

Prior: 2→0.0%

196

Motorists Injured

Prior: 198↓-1.0%

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 timing of crashes showed some shifts between the two periods. The peak day for crashes moved from Tuesday (97 crashes) in 2019 to Wednesday (93 crashes) in 2020. However, the peak hour for collisions remained consistent at the 3 p.m. hour in both years, with 49 crashes in 2019 and 44 in 2020.

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 shifted year-over-year. While fatal crashes decreased from 5 to 4, and the corresponding fatality rate dropped from 0.88% to 0.77%, the number of serious injury crashes increased from 7 to 11. This represented a proportional increase in serious injury crashes from 1.2% of all collisions in 2019 to 2.1% in 2020. Crashes resulting in no injury decreased as a share of the total, from 71.0% to 66.9%.

Outcome by Severity (Crash Events)

Fatal4fatal crashes0.8%
↓-20.0%prior 5
Serious Injury11serious injury crashes2.1%
↑57.1%prior 7
Minor Injury55minor injury crashes10.6%
↑7.8%prior 51
Possible Injury102possible injury crashes19.6%
↑1.0%prior 101
No Injury348no injury crashes66.9%
↓-13.4%prior 402

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 for crashes saw significant changes between 2019 and 2020. While collisions involving an animal remained the top factor in both years (88 in 2019 vs. 90 in 2020), the second-ranked factor changed. Crashes attributed to 'Lost Control' decreased by 50%, from 50 incidents in 2019 to 25 in 2020. Conversely, crashes where a driver 'Ran Stop Sign' increased in count by 45.8%, from 24 to 35, becoming the second-most cited factor in 2020.

Officer-Reported Primary Contributing Cause

Animal90 (17.3%)↑2.3%prior 88
Ran Stop Sign35 (6.7%)↑45.8%prior 24
Other (explain in narrative): Other33 (6.3%)↑22.2%prior 27
Followed too close31 (6%)↓-16.2%prior 37
FTYROW: From stop sign29 (5.6%)↓-32.6%prior 43
Driving too fast for conditions27 (5.2%)↓-32.5%prior 40
Lost Control25 (4.8%)↓-50.0%prior 50
Ran off road - straight25 (4.8%)↑4.2%prior 24
Ran off road - left23 (4.4%)↓-8.0%prior 25
Operating vehicle in an reckless, erratic, careless, negligent manner19 (3.7%)↓-9.5%prior 21

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

Road & Environmental Conditions

Crash conditions were broadly similar year-over-year, with most incidents in both periods occurring in clear weather and on dry roads. A notable change was observed in road surface conditions, where crashes on ice or frost-covered roads decreased by 55.3%, from 38 incidents in 2019 to 17 in 2020. Crashes in daylight conditions decreased from 327 to 289, consistent with the overall drop in collisions.

Weather

Clear340 (76.9%)
↓-1.4%prior 345
Cloudy50 (11.3%)
↓-38.3%prior 81
Rain22 (5.0%)
↑10.0%prior 20
Snow22 (5.0%)
↓-12.0%prior 25
Freezing rain/drizzle6 (1.4%)
↓-60.0%prior 15
Fog, smoke, smog1 (0.2%)
Blowing Snow1 (0.2%)
↓-83.3%prior 6

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

Lighting

Daylight289 (65.4%)
↓-11.6%prior 327
Dark - roadway lighted72 (16.3%)
↓-14.3%prior 84
Dark - roadway not lighted50 (11.3%)
↓-13.8%prior 58
Dusk20 (4.5%)
↑122.2%prior 9
Dawn8 (1.8%)
↓-46.7%prior 15
Dark - unknown roadway lighting3 (0.7%)

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

Road Surface

Dry350 (79.2%)
↓-1.4%prior 355
Wet42 (9.5%)
↓-10.6%prior 47
Snow25 (5.7%)
↓-28.6%prior 35
Ice/frost17 (3.8%)
↓-55.3%prior 38
Gravel4 (0.9%)
Mud, dirt2 (0.5%)
Slush1 (0.2%)
↓-87.5%prior 8
Water (standing or moving)1 (0.2%)

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

Vehicles & Demographics

The makes of vehicles involved in crashes remained consistent, with Ford and Chevrolet being the most frequent in both years. The number of persons involved in crashes from the 26-34 age group increased slightly from 214 to 220, bucking the overall downward trend seen in most other age brackets. For instance, the 16-20 age group saw a decrease from 168 persons involved to 160.

Top Vehicle Makes (866 vehicles)

1
FORD126 (14.5%)
↓-13.1%prior 145
2
CHEV125 (14.4%)
↓-10.1%prior 139
3
CHEVROLET83 (9.6%)
↑23.9%prior 67
4
DODG52 (6%)
↓-13.3%prior 60
5
TOYT50 (5.8%)
↓-12.3%prior 57
6
JEEP32 (3.7%)
→0.0%prior 32
7
DODGE30 (3.5%)
↑11.1%prior 27
8
GMC28 (3.2%)
↓-17.6%prior 34
9
TOYOTA21 (2.4%)
↓-34.4%prior 32
10
NISS20 (2.3%)
↑5.3%prior 19

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

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

Sex Distribution (776 persons with recorded sex)

Male455 (58.6%)
↓-6.2%prior 485
Female321 (41.4%)
↓-13.9%prior 373

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: 520
  • Total persons involved: 1,219
  • Total vehicles involved: 866

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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