Precision Prevention and Public Health

A new trend, “Precision Prevention,” is emerging in public health. This term is borrowed from “Precision Medicine,” a concept in medicine that allows for individualized treatments for patients. Precision prevention utilizes “biologic, behavioral, socioeconomic, and epidemiologic data to devise and implement strategies” tailored to specific individuals or populations. The goal of precision prevention is to target the “right intervention to the right population at the right time.” Much of precision prevention accounts for one’s social determinants of health, tailoring interventions based on a set of individual factors related to where we live, learn, work, and play that impact our health. Precision prevention works to move away from universal approaches to illness and injury prevention. Flaura Koplin Winston, MD, MPH, Chair of the Science and Medical Advisory Committee for Entrepreneurship and Innovation at The Children’s Hospital of Philadelphia (CHOP), applies a precision prevention framework, using a “tiered risk model” (see figure 1) for the Violence Prevention Initiative at CHOP. In the tiered risk model, there are three types of interventions focused around the needs of universal, selected, and indicated populations. At each level, interventions range from meeting the universal needs of the general population, to the select needs of populations at increased or different risk, and finally to interventions tailored for populations with adverse or indicated needs. For example, within the Violence Prevention Initiative, selected interventions that integrate appropriate community support services are tailored to children at greater risk for violence, and indicated interventions tailor the most intensive, direct support to child victims of violence.https://repository.upenn.edu/publichealth_databriefs/1001/thumbnail.jp

Advances in Digital Health Research

Social media and emerging mobile technologies have sparked radical shifts in human behavior, with people worldwide spending an average of 2 hours and 15 minutes daily on social networks. Facebook, Instagram, and Twitter have more than 2 billion users globally. Social networking site use has risen dramatically by all age groups, with the highest use among 18-29 year olds (see Figure below). Every second, Twitter users send 6,000 tweets, amounting to 500 million tweets per day. Instagram users post approximately 95 million photos, generating 4.2 billion likes, each day. A newer platform, Snapchat, has 178 million daily users, 60% of whom are under 25 years of age. They share an average of 3 billion snaps, or rapidly vanishing photos, every day. Researchers at Penn are turning these Tweets, posts, and snaps into innovative data sources that hold vital clues about behaviors, emotions, preferences, opinions, and social networks—all with potential implications for population health. Through the analysis of keywords, images, phrases, emoticons, likes, and hashtags, Penn teams are turning troves of digital information into human-centered health interventions and educational initiatives.https://repository.upenn.edu/publichealth_databriefs/1004/thumbnail.jp

De la “simple” collecte de données à des collaborations avec les habitant.e.s qui interrogent l’engagement des chercheurs : retour sur l’expérience terrain du projet UrbASanté à la Porte de la Chapelle (Paris)

International audienc

De la “simple” collecte de données à des collaborations avec les habitant.e.s qui interrogent l’engagement des chercheurs : retour sur l’expérience terrain du projet UrbASanté à la Porte de la Chapelle (Paris)

International audienc

De la “simple” collecte de données à des collaborations avec les habitant.e.s qui interrogent l’engagement des chercheurs : retour sur l’expérience terrain du projet UrbASanté à la Porte de la Chapelle (Paris)

International audienc