Yearly Traffic Safety Analysis

125 CRASHES IN
IOWA, IA
2020

All metrics benchmarked against2019

In 2020, Page County recorded 125 total crashes, a 12% decrease from the 142 crashes reported in 2019. Despite the overall reduction in collisions, the number of fatalities rose from 2 to 3, and total injuries increased from 40 to 45. This divergence, with fewer crashes resulting in more severe outcomes, represents the most significant year-over-year shift in the data.

125

▼ -12.0%was 142

Total Crash Events

3

▲ 50.0%was 2

Persons Killed

45

▲ 12.5%was 40

Persons Injured

3

▲ 50.0%was 2

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

Overall traffic crashes in Page County showed a downward trend, decreasing by 12% from 142 incidents in 2019 to 125 in 2020. However, the severity of these crashes increased, as total fatalities rose from 2 to 3 and the number of people injured grew from 40 to 45 over the same period.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 0→%

2

Motorists Killed

Prior: 2→0.0%

0

Pedestrians Injured

Prior: 1↓-100.0%

45

Motorists Injured

Prior: 38↑18.4%

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 between the two periods. In 2020, the peak day for crashes was Thursday with 25 incidents, a change from Friday (28 incidents) in the prior year. The peak hour also moved dramatically, from 9 a.m. in 2019 (14 crashes) to 7 p.m. in 2020 (11 crashes), indicating a shift from morning to evening collision patterns.

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 increased in 2020 compared to the prior year. The fatal crash rate rose from 1.4% to 2.4%, with fatal incidents increasing from 2 to 3. While the share of serious injury crashes fell from 3.5% to 1.6%, the proportion of minor injury crashes grew from 9.9% to 16.0%. Consequently, the percentage of crashes resulting in no injuries decreased from 72.5% in 2019 to 68.0% in 2020.

Outcome by Severity (Crash Events)

Fatal3fatal crashes2.4%
↑50.0%prior 2
Serious Injury2serious injury crashes1.6%
↓-60.0%prior 5
Minor Injury20minor injury crashes16%
↑42.9%prior 14
Possible Injury15possible injury crashes12%
↓-16.7%prior 18
No Injury85no injury crashes68%
↓-17.5%prior 103

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 animals remained the leading contributing factor in both periods, though the count decreased from 25 in 2019 to 22 in 2020. 'Failure to yield from a stop sign' held its position as the second-most common factor, with incidents increasing from 11 to 12. Notably, crashes attributed to 'Ran off road - straight' increased from 3 incidents to 10, while crashes from 'Lost Control' doubled from 5 to 10. Conversely, 'Driving too fast for conditions' incidents fell from 10 to 7.

Officer-Reported Primary Contributing Cause

Animal22 (17.6%)↓-12.0%prior 25
FTYROW: From stop sign12 (9.6%)↑9.1%prior 11
Ran off road - straight10 (8%)
Lost Control10 (8%)↑100.0%prior 5
Followed too close7 (5.6%)↓-22.2%prior 9
Driving too fast for conditions7 (5.6%)↓-30.0%prior 10
Driver Distraction: Other interior distraction5 (4%)↓-16.7%prior 6
Swerving/Evasive Action5 (4%)
Ran Stop Sign5 (4%)
Failed to keep in proper lane4 (3.2%)

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 on dry roads made up a larger share of the total in 2020 (68.8%) compared to 2019 (60.6%), while collisions on adverse surfaces like snow, ice, or wet pavement decreased from 24.6% to 16.0% of all incidents. There was a notable shift in lighting conditions, with the share of crashes in unlit dark areas rising from 12.0% in 2019 to 18.4% in 2020. The proportion of crashes in clear weather remained relatively stable.

Weather

Clear83 (73.5%)
↓-5.7%prior 88
Cloudy20 (17.7%)
↓-9.1%prior 22
Freezing rain/drizzle5 (4.4%)
Other (explain in narrative)2 (1.8%)
Rain2 (1.8%)
↓-60.0%prior 5
Snow1 (0.9%)
↓-85.7%prior 7

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

Lighting

Daylight74 (65.5%)
↓-16.9%prior 89
Dark - roadway not lighted23 (20.4%)
↑35.3%prior 17
Dark - roadway lighted5 (4.4%)
↓-68.8%prior 16
Dawn4 (3.5%)
Dark - unknown roadway lighting4 (3.5%)
Dusk3 (2.7%)

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

Road Surface

Dry86 (76.1%)
→0.0%prior 86
Ice/frost9 (8.0%)
↑28.6%prior 7
Gravel7 (6.2%)
Wet7 (6.2%)
↓-12.5%prior 8
Snow4 (3.5%)
↓-78.9%prior 19

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

Vehicles & Demographics

The top two vehicle makes involved in crashes swapped rankings; Ford became the most common make in 2020 with 40 vehicles, while Chevrolet, the top make in 2019, dropped to second. Analysis of persons involved shows a significant demographic shift, with the 16-20 age group's involvement increasing from 30 individuals in 2019 to 45 in 2020. Conversely, involvement for the 65+ age group decreased from 49 to 35 people.

Top Vehicle Makes (186 vehicles)

1
FORD40 (21.5%)
↑8.1%prior 37
2
CHEV25 (13.4%)
↓-41.9%prior 43
3
CHEVROLET13 (7%)
↓-45.8%prior 24
4
DODG12 (6.5%)
↓-14.3%prior 14
5
JEEP9 (4.8%)
↑12.5%prior 8
6
DODGE7 (3.8%)
↓-50.0%prior 14
7
BUIC6 (3.2%)
↑20.0%prior 5
8
GMC6 (3.2%)
9
CHRY6 (3.2%)
↑20.0%prior 5
10
PONT5 (2.7%)
↓-28.6%prior 7

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

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

Sex Distribution (168 persons with recorded sex)

Male96 (57.1%)
↓-23.2%prior 125
Female72 (42.9%)
→0.0%prior 72

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: 125
  • Total persons involved: 260
  • Total vehicles involved: 186

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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