Related Experiment Video
Updated: Aug 27, 2025
08:53
Integrating Computerized Linguistic and Social Network Analyses to Capture Addiction Recovery Capital in an Online Community
Published on: May 31, 2019
5.2K
Community implications for gun violence prevention during co-occurring pandemics; a qualitative and computational
Desmond U Patton1, Nathan Aguilar2, Aviv Y Landau3
1School of Social Policy & Practice, Annenberg School for Communication, Department of Child and Adolescent Psychiatry and Behavioral Sciences, University of Pennsylvania, Philadelphia, USA.
Preventive Medicine
|September 26, 2022
Summary
New York City residents perceive increased violence due to COVID-19 and anti-Black racism. Community-based data science and qualitative interviews offer insights for effective gun violence prevention strategies.
Area of Science:
- Public Health
- Sociology
- Data Science
Background:
- The COVID-19 pandemic and social movements like Black Lives Matter have impacted community safety.
- Low-income residents of color in New York City Housing Authority (NYCHA) buildings face unique challenges.
- Understanding resident perceptions is crucial for effective violence prevention.
Purpose of the Study:
- To explore New York City residents' perceptions of violence during the COVID-19 pandemic.
- To examine the impact of co-occurring health and social pandemics on community safety.
- To identify community-driven recommendations for violence prevention.
Main Methods:
- Conducted 69 in-depth qualitative interviews with residents and stakeholders.
- Facilitated two focus groups with 38 participants.
- Utilized community data science with natural language processing and computer vision on 12 million tweets.
Main Results:
- Qualitative interviews and focus groups revealed resident concerns about safety.
- Social media analysis confirmed and expanded upon themes from interviews.
- Community members provided direct and indirect recommendations for safety improvements.
Conclusions:
- Co-occurring pandemics significantly impact residents' experiences of gun violence.
- Integrated qualitative and computational methods provide holistic community insights.
- Findings have implications for digital-era gun violence prevention strategies.
Related Concept Videos
01:18Steps in Outbreak Investigation
171
In the ever-evolving field of public health, statistical analysis serves as a cornerstone for understanding and managing disease outbreaks. By leveraging various statistical tools, health professionals can predict potential outbreaks, analyze ongoing situations, and devise effective responses to mitigate impact. For that to happen, there are a few possible stages of the analysis:
171
01:21Causality in Epidemiology
699
Causality or causation is a fundamental concept in epidemiology, vital for understanding the relationships between various factors and health outcomes. Despite its importance, there's no single, universally accepted definition of causality within the discipline. Drawing from a systematic review, causality in epidemiology encompasses several definitions, including production, necessary and sufficient, sufficient-component, counterfactual, and probabilistic models. Each has its strengths and...
699
01:25Statistical Methods for Analyzing Epidemiological Data
493
Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
493
01:08Prevalence and Incidence
737
In statistical epidemiology and health sciences, two essential metrics—prevalence and incidence—are fundamental for understanding disease dynamics within a population. These measures enable public health officials, epidemiologists, and researchers to assess the burden of diseases, allocate resources effectively, and design impactful public health policies and interventions.
Prevalence indicates the proportion of individuals in a population who have a specific disease or health...
Prevalence indicates the proportion of individuals in a population who have a specific disease or health...
737
01:26Principles of Disease Surveillance
172
Disease surveillance is the systematic collection, analysis, and interpretation of health data essential to the planning, implementation, and evaluation of public health practice. This process integrates data dissemination to entities responsible for preventing and controlling disease, injury, and disability. Surveillance systems provide crucial information for action, helping public health authorities make informed decisions to manage and prevent outbreaks, ensure public safety, optimize...
172
01:29Bias in Epidemiological Studies
534
Biases can arise at various stages of research, from study design and data collection to analysis and interpretation. Recognizing and addressing these biases is essential to ensure the validity and reliability of epidemiological findings.Broadly speaking, biases in epidemiology fall into three main categories: selection bias, information bias, and confounding. A more detailed description of possible biases is:
534