Introduction
This blog post will briefly show you how data analytics can be used to reduce drug-resistant infections and tackle crime in Thunder Bay. Data analytics is the process of analyzing data systematically to gain insight into underlying trends and understand relationships. What’s great about data analytics and Thunder Bay is that the city is rich with potential for data analytics due to its history of data collection and collaboration with different levels of government and its long-term vision for city planning and development.
Why Data Analytics?
Data analytics has various applications.
It can be useful in analyzing historical data to determine the future direction of a company, analyzing patterns to improve traffic flow on highway roads, or analyzing crime to understand what triggers incidents and how they are resolved.
When trying to measure the number of drug impacts in a city, we can use data analytics by analyzing multiple sets of data such as population size, neighborhood conditions, and crime statistics.
How can we use data analytics to reduce drug-resistant infections and tackle crime in Thunder Bay? We have the data, but how do we analyze it?
Reducing Drug-Resistant Infections
Data analytics can be used to identify high-risk neighborhoods in Thunder Bay by analyzing neighborhood characteristics that are known to contribute to drug-resistant infections and TB (such as poverty levels, population density, unemployment rates, and the number of immigrants).
We can combine this information with TB statistics (incidence level, location of incident) for a selected time period (i.e. past 2 years).
By analyzing these multiple sets of data, we can identify high-risk areas and target our preventive efforts in those neighborhoods.
Tackling Crime
We can use data analytics to understand what is contributing to the increase in crime in Thunder Bay (i.e.firearm related crimes, robbery, assault, homicide). We can combine this information with police data on the location of the incident and the number of incidents for a selected time period (i.e. past 5 years). By analyzing these multiple sets of data, we can identify clusters of crimes that occur at specific locations and develop strategies to tackle them by improving the conditions at those locations.
DV believes using data analytics for crime prevention in Thunder Bay is in its infancy, but Thunder Bay’s data collection efforts provide many opportunities for powerful crime-fighting. Thunder Bay’s data includes a large number of geographic information systems (GIS) layers that record demographics, crime patterns, services, and geographic features.
This data will be combined with crimes already reported by police, creating a detailed picture of where crime is happening and who is committing it..
Conclusion
Data analytics has shown great potential to reduce drug-resistant infections and tackle crime in Thunder Bay.
However, it is important that data analytics is used as a tool for collaboration between various stakeholders and the city. By collaborating with Thunder Bay’s communities and government, we can develop a stronger understanding of how data analytics can be used to unlock greater possibilities for the city.
Potential Recommendations
The city should encourage more people to use the city's open data portal (https://opendata.thunderbay.ca/ ) to analyze data on crime. This data can be used to develop new insights and applications that will improve the quality of life of residents and reduce costs.
The city should partner with more technology companies like Microsoft, Google, and Facebook to create software applications that will help the city collect, analyze and share data online through an online platform such as NextCity (www.nextcity.org)
The city should look at how technology companies like Microsoft, Google, and Facebook create software applications that help cities collect, analyze and share data online.
The city should work with Lakehead University to develop more students who have the specialized skills needed to work in data analytics.
The city should work with senior leaders in the government of Canada (e.g. mayor and senior bureaucrats) to develop a strategic plan for data analytics by sharing their findings on the annual Open Data forum.
The city should work with senior leaders in the government of Canada (e.g. mayor and senior bureaucrats) to create a technology partnership with other Canadian cities through the Canadian Digital Service https://digital.canada.ca/
The city should partner with the provincial government to develop a strategy for data analytics through the provincial government's Open Data Ontario initiative. https://data.ontario.ca/
The city should support the greater use of advanced technologies such as big data analytics, artificial intelligence, and the Internet of Things in transportation (vehicles, roads, and infrastructure) to improve traffic management.
The city should collaborate with other Canadian cities and government agencies to develop a strategic plan for data analytics.
The city should work with leaders of industry (e.g. Microsoft, Google, and Facebook) to develop a strategic plan for data analytics through the Canadian Smart Cities Collaborative by presenting their findings annually at the annual Smart Cities Forum.
The city should support the greater use of novel technologies such as big data analytics, artificial intelligence, and the Internet of Things in cities to reduce crime rates.
The city should encourage faculty and students at the university to conduct research and provide training on how to use data analytics as a tool for civic engagement.
What do you think? Are there other ways that data analytics can be used to reduce drug-resistant infections and tackle crime in Thunder Bay? Are there other ways that they can be combined? Do you think it would be a good idea to use these data analytics to improve the overall health of Thunder Bay’s citizens? Please let us know what you think in the comments below!