Each week we will bring you a summary of what happened this week on our site, on Twitter, and in the wider world of civic data. Suggest stories on Twitter with #ThisWeekInData.
Here on Data-Smart, Sean Thornton discussed the city of Chicago’s efforts to use predictive analytics to target mosquito-spraying efforts to combat West Nile Virus (WNV). The city’s Department of Innovation and Technology (DoIT) partnered with the Department of Public Health (CDPH) to develop a model that can determine one week in advance whether or not a particular area will have WNV-carrying mosquitoes. In a test, the model was able to correctly predict consecutive results for WNV virus about 80 percent of the time.
Also on Data-Smart, Sibella Matthews examined a policy known as Birth Match, in which jurisdictions cross check the birth records of newborns to information held by child protective services on prior instances of abuse from the parents. This cross-check occurs in real time, sending any matches to child protective services to trigger an assessment of whether intervention is required. An intervention may involve the offer of preventative services, or in egregious cases, removing the newborn to a safe environment.
CityLab profiled a program in Los Angeles that uses artificial intelligence (AI) to improve education around HIV and sexually transmitted infections. The program uses an algorithm to identify influencers among LA’s homeless youth that are likely to share information via peer-to-peer education. In a pilot, 70 percent of the homeless youths who were identified through the algorithm received HIV information, compared to 25 percent in a control group. Thirty-seven percent changed their behavior and got tested for HIV and other STIs, whereas no change was seen in the control group.
Also on the topic of artificial intelligence, the City of Atlanta is using an AI chatbot to improve resident interactions with its 311 service. The chatbbot will be integrated into an upcoming 311 app and the city’s existing 311 website and will allow users to ask the bot for information, rather speaking with phone operators or searching for info manually on the 311 site. The bot works by mining the city's 311 website for information people might request, and is designed to learn and improve by asking users for feedback on how useful its answers are. Read more at StateScoop.
The Conversation published an article that argues that existing laws do not adequately protect health data. It is fairly easy for interested parties—like financial institutions or employers—to gain access to health data via social media, wellness programs, or data brokers that collect, compile and sell personal information. The article calls for an expansion of the Americans With Disabilities Act (ADA) to address these technological advances, extending protections to “individuals who are perceived as likely to develop physical or mental impairments in the future.”
For Map Monday, Jess Weaver analyzed Multi-Family Housing in Single Family Zones: Housing, an interactive map from The Sightline Institute that examines the relationship between zoning regulations and school quality across Seattle. Specifically, the map compares the ranking of public schools on the Great Schools index and a neighborhood’s availability of single vs. multi-family units. The visualization shows that higher ranked schools are concentrated in Northern Seattle—an area where there are very few multi-family homes and therefore few affordable housing options—making many high quality schools inaccessible to low-income families.
According to StateScoop, he State of Ohio launched the Ohio Opioid Technology Challenge, a competition intended to garner innovative ideas for tackling the opioid crisis that invites solutions in prevention, education, treatment and recovery, and law enforcement. The state will select five ideas to compete for a top prize of $10,000, along with 40 $500 runners-up prizes to be awarded early 2018. Ohio will then integrate the most promising idea into its broader opioid addiction measures.
Route Fifty highlighted the critical value of federal data to city governments and documented growing concern with the accuracy and accessibility of federal data under the current administration. The federal government collects information that cities often cannot efficiently gather themselves to allocate resources, prioritize projects and compare their performance against other municipalities. However, many city officials are concerned with the administration’s data-related efforts, including its failure to appoint a U.S. Census Bureau head, chief technology officer, or chief of data science and its gutting of the White House Office of Science and Technology Policy.