Yearly Traffic Safety Analysis

105 CRASHES IN
IOWA, IA
2020

All metrics benchmarked against2019

In 2020, Calhoun County recorded 105 total vehicle crashes, a 3.7% decrease from the 109 crashes reported in 2019. While the total number of crashes remained relatively stable, the number of people injured fell by 52.5%, from 40 in 2019 to 19 in 2020. The number of fatalities also decreased from two to one during the same period.

105

▼ -3.7%was 109

Total Crash Events

1

▼ -50.0%was 2

Persons Killed

19

▼ -52.5%was 40

Persons Injured

1

▼ -50.0%was 2

Fatal Crash Events

Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) 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 crash trends in Calhoun County showed a slight decrease between 2019 and 2020. The total number of crashes fell by 3.7% from 109 to 105. More significantly, the number of resulting injuries saw a substantial 52.5% reduction from 40 to 19, and fatalities were halved from two to one.

Vulnerable Road User Casualties

1

Motorists Killed

Prior: 2↓-50.0%

19

Motorists Injured

Prior: 39↓-51.3%

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 2019 and 2020. The day with the most crashes moved from Saturday (21 incidents) in 2019 to Friday (17 incidents) in 2020. The peak hour for crashes also shifted earlier, from 5 p.m. in 2019 to 3 p.m. in 2020, though both hours recorded 10 crashes. Crashes in 2020 were more evenly distributed across the week, with a notable increase in incidents during the morning hours between 5 a.m. and 9 a.m., which saw 25 crashes compared to 7 in the prior year.

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

Crash severity decreased in 2020 compared to the previous year. The fatal crash rate was nearly halved, dropping from 1.83% in 2019 to 0.95% in 2020, with one fatal crash instead of two. The proportion of crashes resulting in any injury also declined from 27.5% to 18.1%. This was driven primarily by a significant drop in minor injury crashes, which fell from 15 incidents (13.8% of total) in 2019 to 6 incidents (5.7% of total) in 2020.

Outcome by Severity (Crash Events)

Fatal1fatal crashes1%
↓-50.0%prior 2
Serious Injury2serious injury crashes1.9%
→0.0%prior 2
Minor Injury6minor injury crashes5.7%
↓-60.0%prior 15
Possible Injury10possible injury crashes9.5%
↓-9.1%prior 11
No Injury86no injury crashes81.9%
↑8.9%prior 79

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 leading contributing factor in both periods, though the count decreased slightly from 35 incidents in 2019 to 32 in 2020. The rankings of other major factors shifted; 'Driving too fast for conditions' saw a significant drop in count, from 7 crashes in 2019 to 2 in 2020. Conversely, incidents of 'Ran off road - straight' increased from 7 to 8, and 'Ran off road - left' increased from 5 to 7. 'Lost Control' remained a consistent factor, with its count decreasing from 9 to 8.

Officer-Reported Primary Contributing Cause

Animal32 (30.5%)↓-8.6%prior 35
Lost Control8 (7.6%)↓-11.1%prior 9
Ran off road - straight8 (7.6%)↑14.3%prior 7
Ran off road - left7 (6.7%)↑40.0%prior 5
Other (explain in narrative): Other4 (3.8%)
Ran Stop Sign4 (3.8%)
Other (explain in narrative): No improper action4 (3.8%)↓-20.0%prior 5
Followed too close3 (2.9%)
FTYROW: From stop sign3 (2.9%)
FTYROW: Making left turn3 (2.9%)

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

Road & Environmental Conditions

Driving conditions for crashes remained broadly similar year-over-year, with a majority of incidents in both 2020 and 2019 occurring in clear weather (56 and 51 crashes, respectively) and during daylight hours (56 and 55 crashes). There was a slight decrease in the proportion of crashes occurring on non-dry road surfaces. In 2020, 24 crashes happened on surfaces described as icy, snowy, wet, or gravel, compared to 29 such crashes in 2019. Crashes on icy or frosty roads were nearly unchanged, with 14 in 2020 versus 13 in 2019.

Weather

Clear56 (68.3%)
↑9.8%prior 51
Cloudy10 (12.2%)
↓-23.1%prior 13
Fog, smoke, smog4 (4.9%)
Freezing rain/drizzle4 (4.9%)
Snow3 (3.7%)
Rain2 (2.4%)
↓-60.0%prior 5
Blowing Snow2 (2.4%)
Sleet, hail1 (1.2%)

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

Lighting

Daylight56 (69.1%)
↑1.8%prior 55
Dark - roadway not lighted16 (19.8%)
↑23.1%prior 13
Dawn5 (6.2%)
→0.0%prior 5
Dark - roadway lighted2 (2.5%)
Dusk2 (2.5%)

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

Road Surface

Dry58 (70.7%)
↑11.5%prior 52
Ice/frost14 (17.1%)
↑7.7%prior 13
Snow4 (4.9%)
Wet3 (3.7%)
↓-57.1%prior 7
Gravel2 (2.4%)
↓-60.0%prior 5
Slush1 (1.2%)

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

Vehicles & Demographics

The top vehicle makes involved in crashes were consistent, with Chevrolet and Ford accounting for the most vehicles in both years. In 2020, a combined 38 Chevrolet and 25 Ford vehicles were involved in crashes, compared to 40 Chevrolet and 23 Ford vehicles in 2019. An analysis of persons involved in crashes shows a shift in age demographics. The representation of the 16-20 age group decreased from 31 individuals in 2019 to 19 in 2020, while the 35-44 age group saw its involvement increase from 25 to 33 individuals.

Top Vehicle Makes (147 vehicles)

1
FORD25 (17%)
↑8.7%prior 23
2
CHEV24 (16.3%)
↓-17.2%prior 29
3
CHEVROLET14 (9.5%)
↑27.3%prior 11
4
DODG8 (5.4%)
↓-27.3%prior 11
5
FREIGHTLINER7 (4.8%)
↑40.0%prior 5
6
GMC5 (3.4%)
7
BUIC5 (3.4%)
8
CHRY5 (3.4%)
9
DODGE5 (3.4%)
10
TOYT4 (2.7%)

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

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

Sex Distribution (136 persons with recorded sex)

Male79 (58.1%)
↓-11.2%prior 89
Female57 (41.9%)
↑7.5%prior 53

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 10, 2026

Data Coverage

  • Reporting period: 2020-01-01 through 2020-12-31 (366 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 105
  • Total persons involved: 197
  • Total vehicles involved: 147

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 10, 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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