A5026155901- Misinformation and Its Impacts
- COVID-19 epidemiological studies
- Data-Driven Disease Surveillance
- COVID-19 and Mental Health
- Health Systems, Economic Evaluations, Quality of Life
- Public Health Policies and Education
- Social Media and Politics
- Hate Speech and Cyberbullying Detection
- Crime, Deviance, and Social Control
- Computational and Text Analysis Methods
- Vaccine Coverage and Hesitancy
- Drilling and Well Engineering
- Literature Analysis and Criticism
- Public Relations and Crisis Communication
- Spam and Phishing Detection
- Reservoir Engineering and Simulation Methods
- Complex Network Analysis Techniques
- Viral Infections and Outbreaks Research
- COVID-19 Digital Contact Tracing
- Seismic Imaging and Inversion Techniques
- Influenza Virus Research Studies
Los Alamos National Laboratory
2019-2023
University of New Mexico
2019-2022
Background: The COVID-19 outbreak has left many people isolated within their homes; these are turning to social media for news and connection, which leaves them vulnerable believing sharing misinformation. Health-related misinformation threatens adherence public health messaging, monitoring its spread on is critical understanding the evolution of ideas that have potentially negative impacts. Results: Analysis using model-labeled data was beneficial increasing proportion matching indicators....
Policymakers must make management decisions despite incomplete knowledge and conflicting model projections. Little guidance exists for the rapid, representative, unbiased collection of policy-relevant scientific input from independent modeling teams. Integrating approaches decision analysis, expert judgment, aggregation, we convened multiple teams to evaluate COVID-19 reopening strategies a mid-sized United States county early in pandemic. Projections seventeen distinct models were...
Abstract Policymakers make decisions about COVID-19 management in the face of considerable uncertainty. We convened multiple modeling teams to evaluate reopening strategies for a mid-sized county United States, novel process designed fully express scientific uncertainty while reducing linguistic and cognitive biases. For scenarios considered, consensus from 17 distinct models was that second outbreak will occur within 6 months reopening, unless schools non-essential workplaces remain closed....
School-age children play a key role in the spread of airborne viruses like influenza due to prolonged and close contacts they have school settings. As result, closures other non-pharmaceutical interventions were recommended as first line defense response novel coronavirus pandemic (COVID-19).
Background Health authorities can minimize the impact of an emergent infectious disease outbreak through effective and timely risk communication, which build trust adherence to subsequent behavioral messaging. Monitoring psychological impacts outbreak, as well public such messaging, is also important for minimizing long-term effects outbreak. Objective We used social media data from Twitter identify human behaviors relevant COVID-19 transmission, perceived on individuals, a first step toward...
Abstract School-age children play a key role in the spread of airborne viruses like influenza due to prolonged and close contacts they have school settings. As result, closures other non-pharmaceutical interventions were recommended as first line defense response novel coronavirus pandemic (COVID-19). Assessing reopening scenarios is priority for states, administrators, parents, order balance educational disparities negative population impacts COVID-19. To address this challenge, we used an...
<sec> <title>BACKGROUND</title> Health authorities can minimize the impact of an emergent infectious disease outbreak through effective and timely risk communication, which build trust adherence to subsequent behavioral messaging. Monitoring psychological impacts outbreak, as well public such messaging, is also important for minimizing long-term effects outbreak. </sec> <title>OBJECTIVE</title> We used social media data from Twitter identify human behaviors relevant COVID-19 transmission,...
Colombia suffered civil conflict for over five decades resulting in thousands of deaths and kidnappings millions displaced citizens. A peace process between the government Revolutionary Armed Forces (FARC) was negotiated 2016. Quantifying public sentiment during may help us understand role social media shaping opinions influencing decision makers. Obtaining these viewpoints using traditional survey approaches is costly logistically challenging. Instead, we used Twitter news data 2010-2018 to...
<sec> <title>BACKGROUND</title> The COVID-19 outbreak has left many people isolated within their homes; these are turning to social media for news and connection, which leaves them vulnerable believing sharing misinformation. Health-related misinformation threatens adherence public health messaging, monitoring its spread on is critical understanding the evolution of ideas that have potentially negative impacts. </sec> <title>OBJECTIVE</title> aim this study use Twitter data explore methods...
Colombia experienced a decades-long civil war between the government and many left-wing guerrilla groups. It was marked by violence, kidnappings, large quantities of human displacement. Monitoring forecasting wars are important to mitigate their potential impact but require access ground truth data. We examine use Internet data streams, namely Google search queries, tweets related politics, traditional news sources retrospectively forecast (i.e., hindcast) state-based armed violence in...