scholarly journals The Potential of Social Media and Internet-Based Data in Preventing and Fighting Infectious Diseases: From Internet to Twitter

2016 ◽  
pp. 131-139 ◽  
Author(s):  
Khaled Al-Surimi ◽  
Mohammed Khalifa ◽  
Salwa Bahkali ◽  
Ashraf EL-Metwally ◽  
Mowafa Househ
Keyword(s):  
Social Media ◽  
Infectious Diseases

Preparedness 3.0: Addressing the Future

2015 ◽  
Vol 9 (6) ◽  
pp. 728-729 ◽  
Author(s):  
Georges C. Benjamin
Keyword(s):  
Public Health ◽  
Climate Change ◽  
Social Media ◽  
Infectious Diseases ◽  
Extreme Weather ◽  
Common Occurrence ◽  
Public Health Preparedness ◽  
Public Health Emergencies ◽  
State Sponsorship ◽  
The Future

ABSTRACTThe last 14 years has taught us that that we are facing a new reality; a reality in which public health emergencies are a common occurrence. Today, we live in a world with dangerous people without state sponsorship who are an enormous threat to our safety; one where emerging and reemerging infectious diseases are waiting to break out; a world where the benefits of globalization in trade, transportation, and social media brings threats to our communities faster and with a greater risk than ever before. Even climate change has entered into the preparedness equation, bringing with it the forces of nature in the form of extreme weather and its complications. (Disaster Med Public Health Preparedness. 2015;9:728–729)

scholarly journals 289. Impact of Clinician Specialty on the Use of Oral Antibiotic Therapy for Definitive Treatment of Uncomplicated Bloodstream Infections

2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S144-S145
Author(s):  
Jasmine R Marcelin ◽  
Mackenzie R Keintz ◽  
Jihyun Ma ◽  
Erica J Stohs ◽  
Bryan Alexander ◽  
...  
Keyword(s):  
Social Media ◽  
Soft Tissue ◽  
Infectious Diseases ◽  
Antibiotic Therapy ◽  
Bloodstream Infections ◽  
Definitive Treatment ◽  
Oral Antibiotic ◽  
Soft Tissue Infections ◽  
Gram Positive ◽  
Oral Antibiotic Therapy

Abstract Background No established guidelines exist regarding the role of oral antibiotic therapy (OAT) to treat uncomplicated bloodstream infections (uBSIs) and practices may vary depending on clinician specialty and experience. Methods An IRB-exempt web-based survey was emailed to Nebraska Medicine clinicians caring for hospitalized patients, and widely disseminated using social media. The survey was open access and once disseminated on social media, it was impossible to ascertain the total number of individuals who received the survey. Chi-squared analysis for categorical data was conducted to evaluate the association between responses and demographic groups. Results Of 275 survey responses, 51% were via social media, and 94% originated in the United States. Two-thirds of respondents were physicians, 16% pharmacists, and infectious diseases clinicians (IDC) represented 71% of respondents. The syndromes where most were comfortable using OAT routinely for uBSI were urinary tract infection (92%), pneumonia (82%), pyelonephritis (82%), and skin/soft tissue infections (69%). IDC were more comfortable routinely using OAT to treat uBSIs associated with vertebral osteomyelitis and prosthetic joint infections than non-infectious diseases clinicians (NIDC), but NIDC were more likely to report comfort with routine use of OAT to treat uBSIs associated with meningitis and skin/soft tissue infections. IDC were more likely to report comfort with routine use of OAT for uBSIs due to Enterobacteriaceae and gram-positive anaerobes, while NIDC were more likely to be comfortable with routinely using OAT to treat uBSIs associated with S. aureus, coagulase-negative staphylococci and gram-positive bacilli. In one clinical vignette of S. aureus uBSI due to debrided abscess, 11% of IDC would be comfortable using OAT vs 28% of NIDC; IDC were more likely to report routinely repeating blood cultures (99% vs 83%, p< 0.05). Figure 1: Clinician comfort using oral antibiotic therapy to treat uncomplicated bacteremia due to specific syndromes Figure 2: Clinician comfort using oral antibiotic therapy to treat uncomplicated bacteremia due to specific organisms Conclusion Considerable variation in comfort using OAT for uBSIs among IDC vs NIDC exists, highlighting opportunities for IDC to continue to demonstrate their value in clinical practice. Understanding the reasons for variability may be helpful in creating best practice guidelines to standardize decision making. Disclosures All Authors: No reported disclosures

scholarly journals Health Perceptions and Misconceptions Regarding COVID-19 in China: Online Survey Study (Preprint)

2020 ◽  
Author(s):  
Jiawei Zhou ◽  
Bishwajit Ghose ◽  
Ruoxi Wang ◽  
Ruijun Wu ◽  
Zhifei Li ◽  
...  
Keyword(s):  
Public Health ◽  
Social Media ◽  
Infectious Diseases ◽  
Online Survey ◽  
Health Perception ◽  
Western China ◽  
Expert Advice ◽  
Health Perceptions ◽  
Misleading Information ◽  
Chi Square Analysis

BACKGROUND Great efforts have been made to prevent the spread of COVID-19, including national initiatives to promote the change of personal behaviors. The lessons learned from the 2003 SARS outbreak indicate that knowledge and attitudes about infectious diseases are related to panic among the population, which may further complicate efforts to prevent the spread of infectious diseases. Misunderstandings may result in behaviors such as underestimation, panic, and taking ineffective measures to avoid infection; these behaviors are likely to cause the epidemic to spread further. OBJECTIVE The purpose of this study is to assess public health perceptions and misunderstandings about COVID-19 in China, and to propose targeted response measures based on the findings to control the development of the epidemic. METHODS The study was conducted in April 2020 through an online survey, with participants in 8 provinces in Eastern, Central, and Western China. We designed a questionnaire with a health knowledge section consisting of 5 questions (4 conventional questions and 1 misleading question) on clinical features of and preventive measures against COVID-19. Descriptive statistics, chi-square analysis, binary logistic regression, and Mantel-Haenszel hierarchical analysis were used for statistical analysis. RESULTS In total, 4788 participants completed the survey and the mean knowledge score was 4.63 (SD 0.67), gained mainly through experts (76.1%), television (60.0%), newspapers (57.9%), and opinions (46.6%) and videos (42.9%) from social media. Compared to those who obtained information from only 1 or 2 channels, people who obtained information from >3 channels had increased health perception and a better ability to identify misleading information. Suggestions from experts were the most positive information source (χ2=41.61), while information on social media was the most misleading. Those aged >60 years (OR 1.52, 95% CI 1.10-2.11), those with a lower or middle income (OR 1.36, 95% CI 1.00-1.83), those not working and not able to work (OR 1.83, 95% CI 1.04-3.21), those with a household income <100,000 RMB (<US $14,954; OR 1.34, 95% CI 1.08-1.67), and those with >2 suspected symptoms (OR 2.95, 95% CI 1.50-5.80) were more likely to be misled by videos on social media, but the error correction effect of expert advice was limited in these groups. CONCLUSIONS Multiple information channels can improve public health perception and the identification of misleading information during the COVID-19 pandemic. Videos on social media increased the risk of rumor propagation among vulnerable groups. We suggest the government should strengthen social media regulation and increase experts’ influence on the targeted vulnerable populations to reduce the risk of rumors spreading.

scholarly journals Health Perceptions and Misconceptions Regarding COVID-19 in China: Online Survey Study

10.2196/21099 ◽  
2020 ◽  
Vol 22 (11) ◽  
pp. e21099 ◽  
Author(s):  
Jiawei Zhou ◽  
Bishwajit Ghose ◽  
Ruoxi Wang ◽  
Ruijun Wu ◽  
Zhifei Li ◽  
...  
Keyword(s):  
Public Health ◽  
Social Media ◽  
Infectious Diseases ◽  
Online Survey ◽  
Health Perception ◽  
Western China ◽  
Expert Advice ◽  
Health Perceptions ◽  
Misleading Information ◽  
Chi Square Analysis

Background Great efforts have been made to prevent the spread of COVID-19, including national initiatives to promote the change of personal behaviors. The lessons learned from the 2003 SARS outbreak indicate that knowledge and attitudes about infectious diseases are related to panic among the population, which may further complicate efforts to prevent the spread of infectious diseases. Misunderstandings may result in behaviors such as underestimation, panic, and taking ineffective measures to avoid infection; these behaviors are likely to cause the epidemic to spread further. Objective The purpose of this study is to assess public health perceptions and misunderstandings about COVID-19 in China, and to propose targeted response measures based on the findings to control the development of the epidemic. Methods The study was conducted in April 2020 through an online survey, with participants in 8 provinces in Eastern, Central, and Western China. We designed a questionnaire with a health knowledge section consisting of 5 questions (4 conventional questions and 1 misleading question) on clinical features of and preventive measures against COVID-19. Descriptive statistics, chi-square analysis, binary logistic regression, and Mantel-Haenszel hierarchical analysis were used for statistical analysis. Results In total, 4788 participants completed the survey and the mean knowledge score was 4.63 (SD 0.67), gained mainly through experts (76.1%), television (60.0%), newspapers (57.9%), and opinions (46.6%) and videos (42.9%) from social media. Compared to those who obtained information from only 1 or 2 channels, people who obtained information from >3 channels had increased health perception and a better ability to identify misleading information. Suggestions from experts were the most positive information source (χ2=41.61), while information on social media was the most misleading. Those aged >60 years (OR 1.52, 95% CI 1.10-2.11), those with a lower or middle income (OR 1.36, 95% CI 1.00-1.83), those not working and not able to work (OR 1.83, 95% CI 1.04-3.21), those with a household income <100,000 RMB (<US $14,954; OR 1.34, 95% CI 1.08-1.67), and those with >2 suspected symptoms (OR 2.95, 95% CI 1.50-5.80) were more likely to be misled by videos on social media, but the error correction effect of expert advice was limited in these groups. Conclusions Multiple information channels can improve public health perception and the identification of misleading information during the COVID-19 pandemic. Videos on social media increased the risk of rumor propagation among vulnerable groups. We suggest the government should strengthen social media regulation and increase experts’ influence on the targeted vulnerable populations to reduce the risk of rumors spreading.

Epidemic Spreading

2018 ◽  
Author(s):  
Ginestra Bianconi
Keyword(s):  
Social Media ◽  
Infectious Diseases ◽  
Sir Model ◽  
Temporal Networks ◽  
Epidemic Spreading ◽  
Multilayer Networks ◽  
Multilayer Network ◽  
Sis Model ◽  
Online Social Media ◽  
Different Types

Epidemic processes are relevant to studying the propagation of infectious diseases, but their current use extends also to the study of propagation of ideas in the society or memes and news in online social media. In most of the relevant applications epidemic spreading does not actually take place on a single network but propagates in a multilayer network where different types of interaction play different roles. This chapter provides a comprehensive view of the effect that multilayer network structures have on epidemic processes. The Susceptible–Infected–Susceptible (SIS) Model and the Susceptible–Infected–Removed (SIR) Model are characterized on multilayer networks. Additionally, it is shown that the multilayer networks framework can also allow us to study interacting Awareness and epidemic spreading, competing networks and epidemics in temporal networks.

Will the mRNA Vaccines Interfere with One’s DNA?

2021 ◽  
Vol 20 (2) ◽  
pp. 463-464
Author(s):  
Musa Mohd Nordin ◽  
Husna Musa
Keyword(s):  
Social Media ◽  
Clinical Trials ◽  
Adverse Effects ◽  
Infectious Diseases ◽  
Low Cost ◽  
Rapid Development ◽  
Medical Science ◽  
High Potency ◽  
Prophylactic Vaccines

As the number of COVID-19 cases continues to rise with over 65 million recorded cases and more than 1.5 million mortalities as of early December, the race against time to find a vaccine intensifies. In recent years, there has been growing interest in mRNA-based technology for the development of prophylactic vaccines against infectious diseases and even for cancers and allergies. The prospects for mRNA vaccines are very promising because of their high potency, capacity for rapid development and potential for low-cost manufacture and safe administration. However, until now, no vaccines using this technology have made it this far in clinical trials thus there have been concerns on the therapeutic and possible adverse effects and claims especially on social media that the vaccines will alter the DNA. This article discusses the unique attributes of mRNA vaccines and current challenges and expectations within the context of the COVID-19 pandemic. Bangladesh Journal of Medical Science Vol.20(2) 2021 p.463-464

scholarly journals A Framework for Forecasting Outbreak of Infectious Diseases Based on Climate Variability and Social Media Content

2021 ◽  
Vol 9 (5) ◽  
pp. 118-124
Author(s):  
Juliet Johny ◽  
Linda Sara Mathew
Keyword(s):  
Social Media ◽  
Infectious Diseases ◽  
Disease Incidence ◽  
Disease Outbreaks ◽  
Media Content ◽  
Data Generation ◽  
Real Time Analysis ◽  
Weather Observations ◽  
Proposed Model ◽  
Media Data

The amount of data has risen significantly over the last few years, due to the popularity of some of the data generation sources like social media, electronic health records, sensors and online shopping sites. Analyzing, processing and storing this data is very prominent since it helps to uncover hidden patterns and unknown correlations. A big data analysis and prediction System is proposed in this context, which combines weather observations, health data and social media content in order to forecast the outbreaks of infectious diseases in a locality. Finding information about the determinants of disease outbreaks are required to reduce its effects on populations. An In-mapper combiner based MapReduce algorithm is used to calculate the mean of daily measurements of various climate parameters like temperature, atmospheric pressure, relative humidity, solar and wind. The climatic parameter that may leads to the outbreak of a disease is identified by finding the correlation between the parameters and disease incidence count. To evaluate how user’s tweeting patterns and sentiments matched with the outbreak of diseases, all tweets containing keywords related to diseases are collected using twitter streaming APIs and are analyzed and processed using Spark framework. The performance of proposed model is improved due to the presence of tweet processing. This indicates that the real-time analysis of social media data can provide more effective result rather than working on the historical data.

scholarly journals The Ecological Impact of the Covid-19 Pandemic Infodemic Discourse in Social Media: Ecolinguistic Perspectives

2021 ◽  
Vol 1 ◽  
pp. 117-128
Author(s):  
Khusnul Khotimah ◽  
Kisyani Laksono ◽  
Suhartono Suhartono ◽  
Udjang Pairin ◽  
Darni Darni
Keyword(s):  
Mental Health ◽  
Social Media ◽  
Infectious Diseases ◽  
Environmental Ethics ◽  
Ecological Impact ◽  
Confirmation Bias ◽  
Qualitative Approach ◽  
Ecological Impacts ◽  
False Information ◽  
Echo Chambers

Texts on social media often highlight the Covid-19 pandemic. The text influences the mindset and mode of the readers. The purpose of this study is to describe the potential ecological impacts of infodemics, both constructive and destructive for readers. Data sourced from social media (Facebook, Instagram, and Twitter). The method used in this research is a qualitative approach with descriptive methods. The results showed that the ecological impact of infodemic discourse, namely the constructive impact represented by the content, meaning or message can influence the mindset and attitudes of readers to participate in preserving the environment. Positive texts can change negative environmental ethics into positive ones. The destructive impact in the form of excessive use of text, and without clear sources, has an impact on the effects of distraction, mental health, panic buying, confirmation bias and echo chambers, and tends to refuse to protect oneself and heed health protocols, making it difficult to handle the outbreak. In addition, misinformation on health has an impact on exacerbating outbreaks of infectious diseases. Especially damaging advice as false information is crafted with no respect for accuracy and is often integrated with narratives framed by emotion or conspiracy. The text affects attitudes and mindsets so that it damages the environment.

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