Yearly Traffic Safety Analysis

274 CRASHES IN
IOWA, IA
2020

All metrics benchmarked against2019

In 2020, Poweshiek County recorded 274 total vehicle crashes, a 15.4% decrease from the 324 crashes documented in 2019. This overall reduction in collisions was accompanied by a significant drop in crash severity. The most notable year-over-year change was the elimination of traffic fatalities, which fell from 3 in the prior year to 0 in the current period.

274

▼ -15.4%was 324

Total Crash Events

0

▼ -100.0%was 3

Persons Killed

79

▼ -24.8%was 105

Persons Injured

0

▼ -100.0%was 3

Fatal Crash Events

Note: "Persons Killed" (0) counts individual fatalities across all crash events. "Fatal" in the severity table below (0) 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 Poweshiek County indicates a significant downward trend year-over-year. Total crashes fell by 15.4%, from 324 in 2019 to 274 in 2020. This positive trend extended to personal injuries, which decreased by 24.8% from 105 to 79, and fatalities, which were reduced from 3 to 0.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

0

Motorists Killed

Prior: 3↓-100.0%

1

Pedestrians Injured

Prior: 0→%

78

Motorists Injured

Prior: 103↓-24.3%

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 showed a slight shift between the two periods. In 2020, Friday was the peak day for crashes with 56 incidents, shifting from Monday (57 incidents) in the prior year. The peak hour for collisions also moved slightly later in the day, from the 3 p.m. hour (31 crashes) in 2019 to the 4 p.m. hour (23 crashes) 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

Crash severity decreased notably in 2020 compared to 2019. Fatal crashes were eliminated, dropping from 3 incidents to 0. While the number of serious injury crashes remained constant at 5 for both years, minor injury crashes saw a substantial 46.9% decrease, falling from 32 to 17. Consequently, the proportion of crashes resulting in no injuries increased from 75.9% in 2019 to 77.0% in 2020.

Outcome by Severity (Crash Events)

Serious Injury5serious injury crashes1.8%
→0.0%prior 5
Minor Injury17minor injury crashes6.2%
↓-46.9%prior 32
Possible Injury41possible injury crashes15%
↑7.9%prior 38
No Injury211no injury crashes77%
↓-14.2%prior 246

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, increasing slightly from 47 crashes in 2019 to 50 in 2020. Crashes attributed to "Driving too fast for conditions" saw a 22.2% decrease in count, dropping from 45 to 35 incidents. Conversely, crashes where a driver "Lost Control" increased in count by 30.4%, from 23 to 30 incidents, making it the third most common factor in 2020.

Officer-Reported Primary Contributing Cause

Animal50 (18.2%)↑6.4%prior 47
Driving too fast for conditions35 (12.8%)↓-22.2%prior 45
Lost Control30 (10.9%)↑30.4%prior 23
Ran off road - straight29 (10.6%)↓-14.7%prior 34
Followed too close19 (6.9%)↑46.2%prior 13
FTYROW: From stop sign17 (6.2%)↓-5.6%prior 18
Ran off road - left15 (5.5%)→0.0%prior 15
Other (explain in narrative): Other7 (2.6%)↓-56.3%prior 16
Other (explain in narrative): No improper action6 (2.2%)→0.0%prior 6
Operating vehicle in an reckless, erratic, careless, negligent manner6 (2.2%)→0.0%prior 6

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 under clear weather and on dry roads remained the most frequent scenarios in both years, though their counts decreased in line with the overall trend. A notable shift occurred in lighting conditions, where crashes on dark, unlighted roadways increased from 53 to 71 incidents. In contrast, crashes on roads with snow or ice decreased from a combined 79 incidents in 2019 to 58 in 2020.

Weather

Clear124 (52.5%)
↓-17.9%prior 151
Cloudy45 (19.1%)
↓-11.8%prior 51
Snow35 (14.8%)
↑25.0%prior 28
Rain14 (5.9%)
↑16.7%prior 12
Freezing rain/drizzle10 (4.2%)
↑25.0%prior 8
Blowing Snow3 (1.3%)
↓-87.5%prior 24
Severe Winds3 (1.3%)
Fog, smoke, smog2 (0.8%)

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

Lighting

Daylight140 (59.3%)
↓-26.7%prior 191
Dark - roadway not lighted71 (30.1%)
↑34.0%prior 53
Dark - roadway lighted11 (4.7%)
↓-50.0%prior 22
Dawn7 (3.0%)
↑16.7%prior 6
Dusk6 (2.5%)
→0.0%prior 6
Dark - unknown roadway lighting1 (0.4%)

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

Road Surface

Dry141 (59.7%)
↓-10.8%prior 158
Snow32 (13.6%)
↓-22.0%prior 41
Ice/frost26 (11.0%)
↓-31.6%prior 38
Wet22 (9.3%)
↓-18.5%prior 27
Gravel13 (5.5%)
↑85.7%prior 7
Slush2 (0.8%)

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

Vehicles & Demographics

The most common vehicle makes involved in crashes, Ford and Chevrolet, remained consistent across both years, though the total number of vehicles involved decreased. An analysis of persons involved shows a reduction across most age groups. The 26-34 age group saw a notable drop from 121 individuals involved in crashes in 2019 to 91 in 2020, and the 21-25 age group saw a similar decrease from 81 to 59.

Top Vehicle Makes (395 vehicles)

1
FORD55 (13.9%)
↓-19.1%prior 68
2
CHEV43 (10.9%)
↓-36.8%prior 68
3
CHEVROLET24 (6.1%)
↓-36.8%prior 38
4
DODG19 (4.8%)
↓-20.8%prior 24
5
JEEP16 (4.1%)
↑77.8%prior 9
6
FREIGHTLINER13 (3.3%)
↓-13.3%prior 15
7
VOLVO13 (3.3%)
↑30.0%prior 10
8
TOYO11 (2.8%)
↓-38.9%prior 18
9
GMC11 (2.8%)
↓-26.7%prior 15
10
DODGE11 (2.8%)
↓-31.3%prior 16

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

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

Sex Distribution (363 persons with recorded sex)

Male232 (63.9%)
↓-12.8%prior 266
Female131 (36.1%)
↓-31.1%prior 190

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: 274
  • Total persons involved: 520
  • Total vehicles involved: 395

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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