Yearly Traffic Safety Analysis

365 CRASHES IN
IOWA, IA
2015

In 2015, Plymouth County recorded 365 traffic crashes, resulting in 4 fatalities and 153 injuries. A significant portion of these incidents, 46.6% (170 crashes), involved a single vehicle. The leading contributing factor cited in crashes was encounters with animals, accounting for 17.3% of all incidents.

365

Total Crash Events

4

Persons Killed

153

Persons Injured

3

Fatal Crash Events

Note: "Persons Killed" (4) 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 · 2015-01-01 to 2015-12-31 · Aggregate counts from crash, person, and vehicle records

Vulnerable Road User Casualties

Motor vehicle occupants represented all 4 fatalities and the vast majority of injuries, with 151 motorists injured in 2015. There were no pedestrian fatalities or injuries reported. Two cyclists were injured in crashes, but no cyclist fatalities occurred.

0

Cyclists Killed

4

Motorists Killed

2

Cyclists Injured

151

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 Plymouth County peaked midweek, with Wednesday recording the highest number of incidents (59). The most frequent time for crashes was the 3 p.m. hour, which saw 38 incidents. The majority of crashes, 232 out of 365, occurred during daylight hours.

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 majority of crashes in 2015, approximately 69.9% (255 incidents), resulted in no injuries. Injury-related crashes, including serious, minor, and possible injuries, accounted for 107 incidents. There were 3 fatal crashes recorded, which resulted in a total of 4 fatalities, indicating at least one crash involved multiple deaths.

Severity is per crash event (most severe injury). 3 fatal crash events resulted in 4 persons killed.

Outcome by Severity (Crash Events)

Fatal3fatal crashes0.8%
Serious Injury14serious injury crashes3.8%
Minor Injury47minor injury crashes12.9%
Possible Injury46possible injury crashes12.6%
No Injury255no injury crashes69.9%

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 most frequently cited contributing factor in Plymouth County crashes was 'Animal', involved in 63 incidents (17.3%). This was followed by 'Lost Control' with 46 crashes (12.6%) and 'Driving too fast for conditions' with 26 crashes (7.1%). Failure to yield the right-of-way from a stop sign and running off the road were also significant factors, each contributing to 24 crashes.

Officer-Reported Primary Contributing Cause

Animal63 (17.3%)
Lost Control46 (12.6%)
Driving too fast for conditions26 (7.1%)
Ran off road - straight24 (6.6%)
FTYROW: From stop sign24 (6.6%)
Ran off road - left23 (6.3%)
Followed too close18 (4.9%)
Other (explain in narrative): Other15 (4.1%)
FTYROW: At uncontrolled intersection12 (3.3%)
Ran Stop Sign11 (3%)

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 63.6% (232) happening in daylight and 54.5% (199) on dry road surfaces. Clear weather was reported for 187 crashes, or 51.2% of the total. Regarding adverse conditions, 43 crashes occurred on icy or frosty roads, and 53 crashes took place on unlighted roadways after dark.

Weather

Clear187 (60.7%)
Cloudy68 (22.1%)
Snow25 (8.1%)
Freezing rain/drizzle10 (3.2%)
Rain9 (2.9%)
Severe Winds4 (1.3%)
Blowing Snow3 (1.0%)
Sleet, hail1 (0.3%)
Fog, smoke, smog1 (0.3%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Weather condition at time of crash

Lighting

Daylight232 (74.1%)
Dark - roadway not lighted53 (16.9%)
Dark - roadway lighted17 (5.4%)
Dawn7 (2.2%)
Dusk3 (1.0%)
Dark - unknown roadway lighting1 (0.3%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Lighting condition field

Road Surface

Dry199 (64.2%)
Ice/frost43 (13.9%)
Snow38 (12.3%)
Wet17 (5.5%)
Gravel8 (2.6%)
Slush3 (1.0%)
Sand2 (0.6%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Road surface condition field

Vehicles & Demographics

Analysis of persons involved in crashes shows the 16-20 age group was the most represented, with 133 individuals, followed by the 26-34 age group with 114 individuals. Among the 547 vehicles involved, Chevrolet was the most frequent make (130 vehicles), followed by Ford (93 vehicles). Dodge (38 vehicles), Pontiac (27 vehicles), and Toyota (27 vehicles) were also commonly involved.

Top Vehicle Makes (547 vehicles)

1
FORD93 (17%)
2
CHEV80 (14.6%)
3
CHEVROLET50 (9.1%)
4
DODG26 (4.8%)
5
GMC24 (4.4%)
6
PONT17 (3.1%)
7
TOYT16 (2.9%)
8
CHRY14 (2.6%)
9
PETERBILT13 (2.4%)
10
DODGE12 (2.2%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Vehicle unit records

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

Sex Distribution (505 persons with recorded sex)

Male290 (57.4%)
Female215 (42.6%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Person-level records linked to crash events

Major Cause

The leading major cause attributed to crashes was 'Animal', cited in 63 incidents, or 17.3% of the total. 'Lost Control' was the second most common cause, contributing to 46 crashes (12.6%). Other significant causes included 'Driving too fast for conditions' (26 crashes) and failure to yield from a stop sign (24 crashes).

Major Cause

1
Animal63 (17.7%)
2
Lost Control46 (13%)
3
Driving too fast for conditions26 (7.3%)
4
Ran off road - straight24 (6.8%)
5
FTYROW: From stop sign24 (6.8%)
6
Ran off road - left23 (6.5%)
7
Followed too close18 (5.1%)
8
Other (explain in narrative): Other15 (4.2%)
9
FTYROW: At uncontrolled intersection12 (3.4%)

Showing top 9 of 42 reported. 33 additional (104 total) not shown: Ran Stop Sign, FTYROW: Making left turn, Operating vehicle in an reckless, erratic, careless, negligent manner, Driver Distraction: Other interior distraction, Ran Traffic Signal, Driver Distraction: Exterior distraction, FTYROW: From driveway, Other (explain in narrative): No improper action, Improper or erratic lane changing, Improper Backing, Driver Distraction: Inattentive/lost in thought, FTYROW: From parked position, Made improper turn, Driver Distraction: Reaching for object(s)/fallen object(s), Crossed centerline (undivided), Swerving/Evasive Action, Driver Distraction: Talking on a hand-held device, Other (explain in narrative): Vision obstructed, Passing: Other passing (explain in narrative), Passing: With insufficient distance/inadequate visibility, Driver Distraction: Passenger, Exceeded authorized speed, FTYROW: Other (explain in narrative), Cargo/equipment loss or shift, FTYROW: From yield sign, Failure to signal intentions, Driver Distraction: Talking on a hands free device, Aggressive driving/road rage, Driver Distraction: Manual operation of an electronic communication device, Ran off road - right, Driver Distraction: Adjusting devices (radio, climate), Disregarded RR Signal, Towing Improperly.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

First Harmful Event

The most common first harmful event was a collision with another vehicle in traffic, which occurred in 156 crashes (42.7%). Events characteristic of run-off-road crashes were also frequent, including collisions with an animal (62 crashes), vehicle overturns or rollovers (43 crashes), and collisions with a ditch (36 crashes). These non-collision and single-vehicle events collectively represent a significant portion of total incidents.

First Harmful Event

1
Collision with: Vehicle in traffic156 (43.5%)
2
Collision with: Animal62 (17.3%)
3
Non-collision events: Overturn/rollover43 (12%)
4
Collision with fixed object: Ditch36 (10%)
5
Collision with: Parked motor vehicle7 (1.9%)
6
Collision with fixed object: Utility pole/light support6 (1.7%)
7
Collision with fixed object: Embankment4 (1.1%)
8
Collision with: Re-entering roadway4 (1.1%)
9
Collision with fixed object: Bridge/bridge rail parapet4 (1.1%)

Showing top 9 of 30 reported. 21 additional (37 total) not shown: Collision with fixed object: Tree, Collision with: Non-motorist (see non-motorist section - NOT a unit), Collision with fixed object: Other post/pole/support (explain in narrative), Non-collision events: Other non-collision (explain in narrative), Non-collision events: Non-contact vehicle (phantom), Collision with: Struck/struck by object/cargo/person from other vehicle, Collision with: Other non-fixed object (explain in narrative), Collision with fixed object: Curb/island/raised median, Non-collision events: Jackknife, Collision with fixed object: Mailbox, Other (explain in narrative), Miscellaneous events: Fire/explosion, Collision with fixed object: Building, Non-collision events: Vehicle went airborne, Collision with fixed object: Culvert/pipe opening, Collision with fixed object: Guardrail - face, Collision with fixed object: Guardrail - end, Collision with fixed object: Ground, Collision with fixed object: Fire hydrant, Collision with: Railway vehicle/train, Collision with fixed object: Traffic sign support.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Roadway Junction / Feature

A plurality of crashes, 165 incidents (45.2%), occurred at non-junction locations along a road segment. Four-way intersections were the most common type of junction for crashes, accounting for 79 incidents. T-intersections were the site of another 26 crashes, with all intersection-related crashes combined making up 110 of the total incidents.

Roadway Junction / Feature

1
Non-intersection: Non-junction/no special feature165 (53.4%)
2
Intersection: Four-way intersection79 (25.6%)
3
Intersection: T-intersection26 (8.4%)
4
Non-intersection: Driveway access (related, not in)9 (2.9%)
5
Non-intersection: Driveway access (within)7 (2.3%)
6
Non-intersection: Crossover-related6 (1.9%)
7
Non-intersection: Railroad grade crossing4 (1.3%)
8
Intersection: Five points or more3 (1%)
9
Non-intersection: Alley3 (1%)

Showing top 9 of 15 reported. 6 additional (7 total) not shown: Interchange-related: Off-ramp, Intersection: Other intersection (explain in narrative), Non-intersection: Other non-intersection (explain in narrative), Intersection: Intersection with ramp, Interchange-related: Off-ramp, diverge area, Non-intersection: Bike lanes.

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, accounting for 254 of the 547 vehicles. Sport utility vehicles (110 vehicles) and light trucks or pickups (101 vehicles) were also frequently involved. Tractor/semi-trailers were involved in 29 crashes, while motorcycles were involved in 2.

Vehicle Type

"Other" combines 10 smaller categories (13 records): Farm tractor (2), Motorcycle (2), School bus (seats > 15) (2), Other heavy truck (> 10000 lbs) (cannot classify) (1), Maintenance/construction vehicle (1), Farm equipment (explain in narrative) (1), Cargo/panel van (1), Train (1), Truck/trailer (1), All-terrain vehicle (ATV) (1).

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Vehicle unit records

Traffic Control Device

The data indicates that the majority of vehicles involved in crashes were in areas with no traffic controls present, accounting for 360 vehicles. Stop signs were the most common form of traffic control noted, present for 75 vehicles involved in crashes. Traffic signals were a factor for 32 vehicles involved in incidents.

Traffic Control Device

"Other" combines 1 smaller categories (2 records): Flashing traffic control signal (2).

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 impact, recorded as the most damaged area for 144 vehicles. Side impacts were also very common, with various points on the driver and passenger sides accounting for a combined 155 vehicles. Rear impacts were noted as the primary damage area for 59 vehicles.

Most Damaged Area

"Other" combines 9 smaller categories (128 records): Front - driver side corner (25), Driver side - middle (24), Passenger side - rear (23), Passenger side - front (20), Rear - driver side corner (13), Rear - passenger side corner (12), Other (explain in narrative) (5), Non-collision/no damage (4), Undercarriage (2).

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Vehicle unit records

Impairment (Alcohol / Drugs)

A total of 16 crashes involved a driver flagged for impairment, representing 4.4% of all crashes in the county for the year. Of these, alcohol was suspected in 12 cases and drugs were suspected in 4 cases. These counts should be considered a minimum as impairment is often under-reported.

Crashes by City

Within Plymouth County, the city of Le Mars accounted for the largest number of crashes with 129 incidents. The town of Hinton recorded the second-highest volume with 17 crashes, followed by Kingsley with 7 crashes. A substantial number of crashes occurred outside of any incorporated city limits.

Crashes by City

1
LE MARS129 (76.3%)
2
HINTON17 (10.1%)
3
KINGSLEY7 (4.1%)
4
AKRON5 (3%)
5
REMSEN3 (1.8%)
6
SIOUX CITY3 (1.8%)
7
MERRILL2 (1.2%)
8
CRAIG1 (0.6%)
9
STRUBLE1 (0.6%)

Showing top 9 of 10 reported. 1 additional (1 total) not shown: WESTFIELD.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Paved vs Unpaved Road

The vast majority of crashes, 342 incidents, occurred on paved roadways. Crashes on unpaved surfaces like gravel or dirt roads accounted for 19 incidents, representing 5.3% of crashes where the surface type was specified. This highlights the role of the county's secondary road network in overall crash statistics.

Paved vs Unpaved Road

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Roadway Contributing Factor

In cases where a roadway factor was noted as a contributor, adverse surface conditions such as wet or icy pavement were the most common, cited in 78 crashes. A slippery, loose, or worn surface was a factor in 4 additional crashes. Most crashes did not have an apparent roadway factor cited as a primary contributor.

Roadway Contributing Factor

1
Surface condition (e.g.wet, icy)78 (90.7%)
2
Slippery, loose or worn surface4 (4.7%)
3
Traffic backup, regular congestion2 (2.3%)
4
Ruts/holes/bumps1 (1.2%)
5
Shoulders (none, low, soft, high)1 (1.2%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Driver Condition

Among drivers where a condition other than 'apparently normal' was recorded, being asleep or fatigued was noted in 10 instances, as was driving under the influence of alcohol. Emotional state and medical conditions were each cited as a factor for 4 drivers. These figures represent a subset of all drivers, as most were recorded as being in normal condition.

Driver Condition

1
Asleep/fatigued10 (33.3%)
2
Under the influence of alcohol10 (33.3%)
3
Emotional (e.g. depressed, angry)4 (13.3%)
4
Medical condition (seizure, reaction)4 (13.3%)
5
Under the influence of drugs/meds1 (3.3%)
6
Visually impaired1 (3.3%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Property Damage

The most common estimated property damage cost per crash was in the $1,500 to $7,500 range, which applied to 261 incidents. A smaller number of crashes, 83, resulted in damages estimated between $7,500 and $25,000. High-damage crashes, with costs exceeding $25,000, accounted for 7 incidents, or 1.9% of the total.

Property Damage

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Manner of Collision

Nearly half of all crashes, 170 incidents (46.6%), were single-vehicle, non-collision events such as running off the road or overturning. Among multi-vehicle crashes, broadside collisions were the most frequent type, with 63 incidents (17.3%). Rear-end collisions were also common, accounting for 62 crashes (17.0%).

Manner of Collision

"Other" combines 3 smaller categories (7 records): Sideswipe, opposite direction (3), Angle, oncoming left turn (3), Rear to rear (1).

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Pre-Crash Driver Action

The most common pre-crash action for vehicles involved was moving essentially straight, which was the case for 365 of the 547 vehicles. Turning left was the next most frequent maneuver, recorded for 38 vehicles. Backing and being stopped in traffic were each the pre-crash action for 19 vehicles.

Pre-Crash Driver Action

1
Movement essentially straight365 (71.6%)
2
Turning left38 (7.5%)
3
Backing19 (3.7%)
4
Stopped in traffic19 (3.7%)
5
Legally Parked18 (3.5%)
6
Turning right11 (2.2%)
7
Other (explain in narrative)10 (2%)
8
Slowing/stopping (deceleration)8 (1.6%)
9
Changing lanes7 (1.4%)

Showing top 9 of 17 reported. 8 additional (15 total) not shown: Overtaking/passing, Negotiating a curve, Entering traffic lane (merging), Entering a parked position, Leaving traffic lane, Making U-turn, Starting in road, Accelerating in road.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Vehicle unit records

Person Type

Of the 707 people involved in crashes, the vast majority, 661 individuals (93.5%), were drivers. Passengers accounted for 44 of the people involved, while 2 were bicyclists. No pedestrians were recorded in any crash incidents.

Person Type

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Person Injury Severity

Across all 707 individuals involved in crashes, 4 sustained fatal injuries and 153 sustained some level of injury. This includes 18 serious injuries, 76 minor injuries, and 59 possible injuries. In total, 22.2% of all persons involved in crashes were either killed or injured.

Person Injury Severity

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Occupant Safety Equipment

Among the 139 vehicle occupants for whom safety equipment use was recorded, 109 were using a shoulder and lap belt. However, 27 individuals, or 19.4% of this subset, were recorded as using no safety equipment at all. Data on restraint use was not available for the majority of occupants.

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, accounting for 193 incidents, or 52.9% of the total. Two-vehicle collisions were also frequent, with 161 incidents. Crashes involving three or more vehicles were rare, with only 10 such events recorded during the year.

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: 365
  • Total persons involved: 707
  • Total vehicles involved: 547

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

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