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CRASH INTELLIGENCE REPORT · IOWA, IA · 2015
Purpose: Machine-readable JSON endpoint for AI agents, LLMs, researchers, and programmatic consumers. Returns all underlying crash data and AI-generated commentary without HTML.
Authentication: None required. Public endpoint.
GET: https://thatcarhitme.com/api/crash-data/reports/data/iowa/statewide/2015-annual-report
Yearly Traffic Safety Analysis
128 CRASHES IN
IOWA, IA
2015
In 2015, Monroe County recorded 128 traffic crashes, resulting in 2 fatalities and 36 injuries. The single most prominent statistical finding from the data is the high incidence of collisions involving animals, which was cited as the primary contributing factor in 46 crashes, accounting for 35.9% of all incidents in the county.
128
Total Crash Events
2
Persons Killed
36
Persons Injured
2
Fatal Crash Events
Note: "Persons Killed" (2) counts individual fatalities across all crash events. "Fatal" in the severity table below (2) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Aggregate counts from crash, person, and vehicle records
Vulnerable Road User Casualties
In 2015, crashes in Monroe County resulted in 2 motorists killed and 35 motorists injured. No cyclists were killed or injured. One pedestrian was injured, but there were no pedestrian fatalities. The data clearly indicates that vehicle occupants constituted the entirety of fatalities and the vast majority of injuries.
0
Pedestrians Killed
2
Motorists Killed
1
Pedestrians Injured
35
Motorists Injured
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
Crash occurrences in Monroe County were most frequent on Mondays, which saw 25 incidents, closely followed by Thursdays with 24. The most common time for crashes was the 9 p.m. hour, with 11 incidents recorded. While more crashes happened during daylight hours (52 incidents), a significant number also occurred in dark conditions, including 28 on unlit roadways and 8 on lit roadways.
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash date field aggregated by weekday
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The vast majority of crashes, 100 out of 128, resulted in no injuries, accounting for 78.1% of all incidents. Injury-sustaining crashes included 4 with serious injuries, 4 with minor injuries, and 18 with possible injuries. Two separate crashes were fatal, resulting in a total of 2 fatalities for the year.
Outcome by Severity (Crash Events)
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factor to crashes was overwhelmingly animals, cited in 46 incidents, or 35.9% of the total. The next most common factor was losing control of the vehicle, which accounted for 12 crashes (9.4%). Following this, several factors were each responsible for 7 crashes (5.5% each), including following too closely, running a stop sign, running off a straight road, and failure to yield the right-of-way from a stop sign.
Officer-Reported Primary Contributing Cause
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
A majority of crashes occurred in favorable conditions, with 70 incidents happening in clear weather and 63 on dry road surfaces. Daylight was the most frequent lighting condition, present for 52 crashes. However, adverse conditions were also a factor, with 11 crashes on wet roads, 6 during rain, and a combined 7 on roads with snow or ice. Crashes in low light were also notable, with 38 incidents occurring in dark conditions.
Weather
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Weather condition at time of crash
Lighting
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Lighting condition field
Road Surface
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Road surface condition field
Vehicles & Demographics
The most frequently involved vehicle makes in crashes were Chevrolet (47 vehicles), Ford (32), and Dodge (15), combining abbreviated and full names from the data. Analysis of persons involved shows the 35-44 age group was the most represented, with 37 individuals. Other highly represented groups include those aged 45-54 (33 people), 16-20 (31 people), and both the 21-25 and 26-34 age brackets (30 people each).
Top Vehicle Makes (184 vehicles)
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Vehicle unit records
6 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (176 persons with recorded sex)
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Person-level records linked to crash events
Major Cause
The most frequently cited major cause for crashes was interaction with an animal, accounting for 46 of 128 incidents (35.9%). Losing control of the vehicle was the second leading cause, with 12 incidents (9.4%). Other significant causes, each contributing to 7 crashes (5.5%), were following too closely, running a stop sign, and failing to yield the right-of-way from a stop sign.
Major Cause
Showing top 9 of 28 reported. 19 additional (25 total) not shown: Made improper turn, Driving too fast for conditions, Driver Distraction: Inattentive/lost in thought, Other (explain in narrative): Vision obstructed, Ran off road - left, Swerving/Evasive Action, Failed to keep in proper lane, Operator inexperience, Other (explain in narrative): No improper action, Driver Distraction: Talking on a hands free device, Ran Traffic Signal, Passing: On wrong side, Passing: Where prohibited by signs/markings, Driver Distraction: Other interior distraction, Driver Distraction: Reaching for object(s)/fallen object(s), Failed to yield to emergency vehicle, FTYROW: Other (explain in narrative), Disregarded RR Signal, Driver Distraction: Passenger.
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records
First Harmful Event
The initial event in crashes was almost evenly split between a collision with another vehicle in traffic (47 incidents) and a collision with an animal (46 incidents). These two events together initiated 72.7% of all crashes. Collisions with fixed objects were less common, with the most frequent being running into a ditch, which occurred in 10 crashes.
First Harmful Event
Showing top 9 of 16 reported. 7 additional (7 total) not shown: Collision with: Struck/struck by object/cargo/person from other vehicle, Collision with fixed object: Curb/island/raised median, Miscellaneous events: Eluding law enforcement, Collision with fixed object: Tree, Collision with fixed object: Bridge/bridge rail parapet, Collision with: Non-motorist (see non-motorist section - NOT a unit), Collision with: Other non-fixed object (explain in narrative).
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records
Roadway Junction / Feature
Crashes were more likely to occur on non-junction road segments than at intersections. The data shows 48 crashes happened on straight or curved sections of road with no special feature. In contrast, 31 crashes occurred at intersections, with four-way intersections being the most common type, accounting for 21 of these incidents.
Roadway Junction / Feature
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records
Vehicle Type
Passenger cars were the most common vehicle type involved in crashes, with 71 units, followed by four-tire light trucks or pickups (47) and sport utility vehicles (33). These three categories comprised 82.1% of the 184 vehicles involved in incidents. Notably, 9 tractor-trailers and 4 motorcycles were also involved in crashes during this period.
Vehicle Type
"Other" combines 6 smaller categories (7 records): Single-unit truck (>= 3 axles) (2), Train (1), Golf cart (1), Motor home/recreational vehicle (1), Other light truck (<=10000 lbs) (1), Cargo/panel van (1).
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Vehicle unit records
Traffic Control Device
A significant majority of crashes, 109 incidents, occurred in areas where no traffic controls were present. For crashes that did happen at controlled locations, stop signs were the most common traffic control device, noted in 22 incidents. Crashes at locations with traffic signals (6 incidents) or railway crossing devices (7 incidents) were less frequent.
Traffic Control Device
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Vehicle unit records
Most Damaged Area
The front of the vehicle was the most common area of initial impact, recorded as the most damaged area for 38 vehicles. Rear impacts were noted in 16 cases, suggesting a notable share of rear-end type collisions. Impacts to the front-driver side corner (14 vehicles) and various points along the driver and passenger sides were also frequently reported.
Most Damaged Area
"Other" combines 8 smaller categories (34 records): Driver side - middle (6), Passenger side - middle (6), Passenger side - rear (6), Rear - driver side corner (6), Driver side - rear (5), Rear - passenger side corner (2), Other (explain in narrative) (2), Non-collision/no damage (1).
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Vehicle unit records
Crashes by City
Within Monroe County, the city of Albia recorded the highest number of crashes with 48 incidents. The town of Lovilia reported 7 crashes. A large number of crashes in the county occurred outside of any specific city's limits and are therefore not included in this municipal breakdown.
Crashes by City
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records
Paved vs Unpaved Road
Of the crashes where the road surface type was specified, 111 occurred on paved roads. A smaller but significant number, 16 crashes, took place on unpaved surfaces such as gravel or dirt roads. This represents 12.6% of the 127 crashes with available surface data, highlighting the role of the county's secondary road network in traffic incidents.
Paved vs Unpaved Road
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records
Driver Condition
While most drivers were recorded as 'apparently normal,' the data specifies conditions for a subset of individuals. Among these, driving under the influence of alcohol was the most cited condition, noted for 5 drivers. Additionally, 2 drivers were identified as being asleep or fatigued at the time of their crash.
Driver Condition
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records
Property Damage
The estimated property damage for the majority of crashes fell into the '$1,500 - $7,500' range, which applied to 106 of the 128 incidents (82.8%). More severe damage was less common, with 16 crashes estimated between $7,500 and $25,000, and only 3 crashes exceeding $25,000 in property damage.
Property Damage
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records
Manner of Collision
Single-vehicle incidents were the most common manner of collision, accounting for 58 of the 128 total crashes (45.3%). Among multi-vehicle crashes, broadside collisions were the most frequent type, with 26 incidents (20.3%), followed by rear-end collisions, which occurred 15 times (11.7%).
Manner of Collision
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records
Pre-Crash Driver Action
The most common action drivers were taking immediately before a crash was simply moving straight ahead, which was the case in 110 instances. The next most frequent pre-crash action was turning left, recorded for 11 vehicles. Backing and being stopped in traffic were also noted, with 7 and 6 instances respectively.
Pre-Crash Driver Action
Showing top 9 of 14 reported. 5 additional (6 total) not shown: Other (explain in narrative), Negotiating a curve, Entering traffic lane (merging), Overtaking/passing, Entering a parked position.
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Vehicle unit records
Person Type
Of the 223 people involved in crashes, the overwhelming majority were drivers, accounting for 212 individuals (95.1%). Passengers made up a small fraction of the total, with 10 individuals (4.5%). Only one pedestrian was involved in a crash during this period.
Person Type
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records
Person Injury Severity
Out of 223 individuals involved in crashes, 38 people were either injured or killed. This includes 2 fatalities and 36 individuals who sustained injuries ranging from possible to serious. The remaining 185 people involved in these incidents were not reported as injured.
Person Injury Severity
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records
Occupant Safety Equipment
Based on the limited available data for safety equipment usage, 22 occupants were reported as using a shoulder and lap belt. Of the 26 individuals for whom restraint use was documented, 3 were reported as using no safety equipment. One person was recorded as wearing a DOT-compliant helmet.
Occupant Safety Equipment
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Person-level records linked to crash events
Vehicles Per Crash
Single-vehicle crashes were the most common type of incident, accounting for 76 of the 128 total crashes (59.4%). Two-vehicle collisions were the next most frequent, with 49 incidents (38.3%). Multi-vehicle pile-ups involving three or more vehicles were rare, with only three such crashes recorded.
Vehicles Per Crash
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records
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: 2015-01-01 through 2015-12-31
- Report generated: September 9, 2026
Data Coverage
- Reporting period: 2015-01-01 through 2015-12-31 (365 days)
- Geographic scope: iowa, IA
- Total crash records analyzed: 128
- Total persons involved: 223
- Total vehicles involved: 184
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: 2015." Published September 9, 2026. Reporting period: 2015-01-01 to 2015-12-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/2015-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
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Iowa Crash Data · ArcGIS
Period: 2015-01-01 – 2015-12-31
Generated: September 9, 2026 · All rights reserved