Yearly Traffic Safety Analysis

196 CRASHES IN
IOWA, IA
2020

All metrics benchmarked against2019

In Mills County, total vehicle crashes decreased from 258 in 2019 to 196 in 2020, a 24% reduction. Despite this overall decline in collisions and a 46.1% drop in injuries from 115 to 62, the number of fatalities more than doubled, rising from 2 in 2019 to 5 in 2020.

196

▼ -24.0%was 258

Total Crash Events

5

▲ 150.0%was 2

Persons Killed

62

▼ -46.1%was 115

Persons Injured

3

▲ 50.0%was 2

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 shows a significant year-over-year decrease in the number of crashes and injuries. Total crashes fell by 24%, from 258 to 196, and total injuries dropped by 46.1% from 115 to 62. However, this positive trend did not extend to crash fatalities, which increased by 150% from 2 to 5.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

0

Cyclists Killed

Prior: 0→0.0%

5

Motorists Killed

Prior: 2↑150.0%

1

Pedestrians Injured

Prior: 0→%

2

Cyclists Injured

Prior: 0→%

59

Motorists Injured

Prior: 115↓-48.7%

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

Temporal crash patterns shifted between the two periods. In 2020, the peak day for crashes was Friday with 38 incidents, a change from 2019 when Tuesday was the peak day with 42 crashes. The busiest hour also shifted from the 5 p.m. evening commute hour in 2019 (19 crashes) to the midday 12 p.m. hour in 2020 (14 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. The number of fatal crashes increased from 2 in 2019 to 3 in 2020, and the fatal crash rate rose from 0.8% to 1.5% of all crashes. Conversely, crashes resulting in serious injuries decreased, falling from 13 incidents (5.0% of total) in 2019 to 8 incidents (4.1% of total) in 2020.

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

Outcome by Severity (Crash Events)

Fatal3fatal crashes1.5%
↑50.0%prior 2
Serious Injury8serious injury crashes4.1%
↓-38.5%prior 13
Minor Injury28minor injury crashes14.3%
↓-12.5%prior 32
Possible Injury21possible injury crashes10.7%
↓-40.0%prior 35
No Injury136no injury crashes69.4%
↓-22.7%prior 176

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 an animal remained the top contributing factor in both years, though the count decreased from 43 in 2019 to 39 in 2020. A notable shift occurred with 'Lost Control,' which saw its count increase by 42.1% from 19 crashes in 2019 to 27 in 2020, making it the second-leading factor. In contrast, crashes attributed to 'Driving too fast for conditions' fell by 47.6%, from 21 incidents in 2019 to 11 in 2020.

Officer-Reported Primary Contributing Cause

Animal39 (19.9%)↓-9.3%prior 43
Lost Control27 (13.8%)↑42.1%prior 19
Ran off road - straight15 (7.7%)→0.0%prior 15
Driving too fast for conditions11 (5.6%)↓-47.6%prior 21
FTYROW: From stop sign10 (5.1%)↓-16.7%prior 12
Other (explain in narrative): Other10 (5.1%)↓-56.5%prior 23
Followed too close8 (4.1%)↓-11.1%prior 9
Ran off road - left7 (3.6%)↓-36.4%prior 11
Exceeded authorized speed6 (3.1%)↑20.0%prior 5
FTYROW: Making left turn4 (2%)↓-20.0%prior 5

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 proportion of crashes occurring in favorable conditions increased year-over-year. In 2020, 66.3% of crashes happened in clear weather, up from 59.3% in 2019. Similarly, crashes on dry road surfaces accounted for 70.9% of the total in 2020, compared to 62.8% in 2019. The share of crashes occurring in daylight remained stable at approximately 56% for both periods.

Weather

Clear130 (72.6%)
↓-15.0%prior 153
Cloudy22 (12.3%)
↓-55.1%prior 49
Snow13 (7.3%)
↑18.2%prior 11
Rain10 (5.6%)
↓-23.1%prior 13
Fog, smoke, smog2 (1.1%)
Freezing rain/drizzle1 (0.6%)
Blowing Snow1 (0.6%)
↓-80.0%prior 5

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

Lighting

Daylight110 (61.8%)
↓-24.1%prior 145
Dark - roadway not lighted42 (23.6%)
↓-27.6%prior 58
Dark - roadway lighted11 (6.2%)
↓-21.4%prior 14
Dawn10 (5.6%)
↓-16.7%prior 12
Dusk5 (2.8%)
→0.0%prior 5

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

Road Surface

Dry139 (77.7%)
↓-14.2%prior 162
Snow15 (8.4%)
↓-31.8%prior 22
Wet11 (6.1%)
↓-62.1%prior 29
Gravel8 (4.5%)
↓-27.3%prior 11
Ice/frost5 (2.8%)
↓-28.6%prior 7
Slush1 (0.6%)

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

Vehicles & Demographics

Ford and Chevrolet remained the top two vehicle makes involved in crashes in both 2019 and 2020, with their involvement counts decreasing in line with the overall trend. The age demographics of persons involved in crashes showed a shift; the 35-44 age group was most represented in 2019 with 94 individuals, whereas the 45-54 age group was most represented in 2020 with 65 individuals. The number of people involved in crashes decreased across all reported age groups.

Top Vehicle Makes (289 vehicles)

1
FORD48 (16.6%)
↓-17.2%prior 58
2
CHEV27 (9.3%)
↓-18.2%prior 33
3
TOYOTA16 (5.5%)
↑33.3%prior 12
4
CHEVROLET16 (5.5%)
↓-59.0%prior 39
5
KIA14 (4.8%)
→0.0%prior 14
6
GMC14 (4.8%)
↑16.7%prior 12
7
JEEP11 (3.8%)
↑37.5%prior 8
8
DODGE10 (3.5%)
↓-16.7%prior 12
9
DODG9 (3.1%)
↓-50.0%prior 18
10
NISS8 (2.8%)
↓-33.3%prior 12

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

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

Sex Distribution (252 persons with recorded sex)

Male157 (62.3%)
↓-27.3%prior 216
Female95 (37.7%)
↓-28.6%prior 133

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: 196
  • Total persons involved: 421
  • Total vehicles involved: 289

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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