Crime Analysis & Safety Report - City Tallmadge, OH

Based on the provided crime data for the area represented by GEOID 16000US3976106, a total of 74 crimes were recorded. The most prevalent main category is property crime, accounting for 41 incidents. Within property crime, larceny/theft offenses are the most frequent, with 31 incidents, followed by stolen property offenses with 4 incidents, destruction/damage/vandalism of property with 3 incidents, motor vehicle theft with 2 incidents, and burglary/breaking & entering with 1 incident. Assault is the second most common main category, with 25 incidents, all classified as assault offenses. The "others" category includes 5 incidents, broken down into 1 arson and 4 fraud offenses. Sex offenses are the least frequent, with 3 incidents, all classified as sex offenses. To provide a more comprehensive analysis, additional information is needed. Assuming GEOID 16000US3976106 represents an area within Ohio, we can look at cities and towns within the state. Without knowing the specific city or town, I will use the city of Cincinnati, Ohio, as an example. Cincinnati has a population of approximately 300,000, a median income of around $45,000, and a crime rate that fluctuates but is generally higher than the national average. If Cincinnati's crime rate is around 1,500 per 100,000 residents, this would translate to a higher crime rate than the national average. Based on the provided data, property crime would be a significant concern, particularly larceny/theft. The violent crime rate, driven by assault offenses, would also be a factor in determining the overall safety of the area. A safety score and grade would depend on a weighted calculation considering violent and property crime rates, potentially incorporating other factors like community policing efforts and socioeconomic indicators. A hypothetical safety grade might be a "C" or "D," reflecting the higher crime rate. Crime map data would visually represent the distribution of these offenses, potentially highlighting hotspots for larceny/theft or assault. Zip code-level data would provide a more granular understanding of crime patterns within the city. Based on the data, the insights would suggest a need for targeted interventions to address property crime, particularly theft. Community-based initiatives focused on crime prevention and increased law enforcement presence in high-crime areas could be considered. Additionally, addressing the underlying causes of crime, such as poverty and lack of opportunity, could contribute to long-term improvements in safety.