Accuracy and Timeliness of Knowledge Dissemination on COVID-19 Among People in Rural and Remote Regions of China at the Early Stage of Outbreak

Coronavirus disease 2019 (COVID-19) spread throughout China in January 2020. To contain the virus outbreak, the Chinese government took extraordinary measures in terms of public policy, wherein accurate and timely dissemination of information plays a crucial role. Despite all of the efforts toward studying this health emergency, little is known about the effectiveness of public policies that support health communication during such a crisis to disseminate knowledge for self-protection. Particularly, we focus on the accuracy and timeliness of knowledge dissemination on COVID-19 among people in remote regions—a topic largely omitted in existing research. In February 2020, at the early-stages of the COVID-19 outbreak, a questionnaire survey was carried out. In total, 8,520 participants from seven less economically developed provinces situated in the borderlands of China with large ethnic minority groups responded. We analyzed the data through poisson regression and logistic regression analyses. We found that (1) people in remote regions of China obtained accurate information on COVID-19. Further, they were able to take appropriate measures to protect themselves. (2) Result from both descriptive analysis and multivariable regression analysis revealed that there is no large difference in the accuracy of information among groups. (3) Older, less educated, and rural respondents received information with a significant delay, whereas highly educated, younger, urban residents and those who obtained information through online media were more likely to have received the news of the outbreak sooner and to be up to date on the information. This research provides evidence that disadvantage people in remote regions obtained accurate and essential information required to act in an appropriate manner in responses to the COVID-19 outbreak. However, they obtained knowledge on COVID-19 at a slower pace than other people; thus, further improvement in the timely dissemination of information among disadvantage people in remote regions is warranted.

Twitter-Based Disaster Response Using Recurrent Nets

Twitter has become the major source of data for the research community working on the social computing domain. The microblogging site receives millions of tweets every day on its platform. Earlier studies have shown that during any disaster, the frequency of tweets specific to an event grows exponentially, and these tweets, if monitored, processed, and analyzed, can contain actionable information relating to the event. However, during disasters, the number of tweets can be in the hundreds of thousands thereby necessitating the design of a semi-automated artificial intelligence-based system that can extract actionable information based on which steps can be taken for effective disaster response. This paper proposes a Twitter-based disaster response system that uses recurrent nets for training a classifier on a disaster specific tweets dataset. The proposed system would enable timely dissemination of information to various stakeholders so that timely response and proactive measures can be taken in order to reduce the severe consequences of disasters. Experimental results show that the recurrent nets outperform the traditional machine learning algorithms with regard to accuracy in classifying disaster-specific tweets.

The Journal of Respiration (JoR): A New Open Access Journal Dedicated to the Timely Dissemination of Information Related to Thoracic Structures

Over the last decade, the amount of information pertaining to thoracic structures has been unprecedented [...]

Psychosocial challenges and concerns of COVID-19: A qualitative study in Iran

As the world struggles to cope with the COVID-19 pandemic, it is critical that the psychosocial aspects related to health are attended to in addition to biological aspects. To this end, the present study aimed to explore the challenges and concerns facing people affected by COVID-19. This qualitative study was conducted using the content analysis method. A total of 25 people affected by COVID-19 were selected purposefully and administered semi-structured interviews. The sampling continued until data saturation. Coding and analysis of data were performed simultaneously using the Granheim method. After reviewing codes, checking the consistency and comparing categories, 5 categories, and 15 subcategories were explored. The most important psychosocial challenges of COVID-19 included the lack of accurate and timely dissemination of information, the intensification of economic problems, psychological instability, weakness in social prevention, and the suspension of social rituals. Identifying the psychosocial challenges and problems of people who faced by pandemic diseases such as COVID-19, and developing appropriate and timely planning for managing them can lead to designing effective strategies for prevention, treatment, and recovery of affected communities.

Clinical trial publication trends within neurology

Timely dissemination of results from clinical studies is crucial for the advancement of knowledge and clinical decision making. A large body of research has shown that up to half of clinical trials do not publish their findings. In this study, we sought to determine whether clinical trial publication rates within neurology have increased over time. Focusing on neurology clinical trials completed between 2008 to 2014, we found that while the overall percentage of published trials has not changed (remaining at approximately 50%), time to publication has significantly decreased. Our findings suggest that clinical trials within neurology are being published in a more timely manner.

Position-based emergency message dissemination for Internet of vehicles

With the advancement in communication technologies, Internet of vehicles presents a new set of opportunities to efficiently manage transportation problems using vehicle-to-vehicle communication. However, high mobility in vehicular networks causes frequent changes in network topology, which leads to network instability. This frequently results in emergency messages failing to reach the target vehicles. To overcome this problem, we propose a data dissemination scheme for such messages in vehicular networks, based on clustering and position-based broadcast techniques. The vehicles are dynamically clustered to handle the broadcast storm problem, and a position-based technique is proposed to reduce communication delays, resulting in timely dissemination of emergency messages. The simulation results show that the transmission delay, information coverage, and packet delivery ratios improved up to 14%, 9.7%, and 5.5%, respectively. These results indicate that the proposed scheme is promising as it outperforms existing techniques.

Risk of publication in worthless journals

Implementing research and publishing results is a crucial for a professional development, scientific communication and collaboration of any academicians, scholars, and researchers in science around the world. The timely dissemination of knowledge and scientific information in the global scientific community helps the development of science and worldwide recognition. The researchers working on scientific community cannot appreciate the value of evidence generated without publishing their work in right and quality journals. Therefore, authors should be careful about predatory or fake journals/publishers for communicating their scientific works. The objective of this study is to raise awareness on predatory or fake publishers/journals and of their dishonest publishing practices. In general, the predatory journal publishes without peer review and true editorial board, often publish mediocre or even worthless papers on charging high publication cost, citing fake and non-existing impact factors and mostly focused on private business motives. On the other hand, publishing in a high impact quality journals undoubtedly enhances the future career prospects, communication ability of authors and deliver concise research messages in the scientific field. Researcher of various disciplines and academic experience should aware with the lists of predatory journals/publishers which are available on Beall’s list in internet before publishing any research articles. Therefore, publishing in predatory/fake journals not only spoil or degrade academic reputations but also waste the time, resources and research message too.

Do Researchers Anchor their Beliefs on the Outcome of an Initial Study? Testing the Time-Reversal Heuristic

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Yield estimation of coconut in Tumkur district of Karnataka

<p>Coconut in India is cultivated mainly in the states of Kerala, Tamil Nadu, Karnataka and Andhra Pradesh which account for more than 90 per cent of area and production of coconut in the country. With about 10 million people dependent on coconut farming and its allied activities, it contributes to more than 83,000 million rupees to the country’s GDP and about 6 per cent to the edible oil pool. However, there are no precise estimates of its production and productivity. The official statistics on area and production of coconut is being published with two years lag by the Department of Economic and Statistics and hence an assessment of surplus/ deficit production and its repercussion in the coconut market economy could not be made many times. Absence of such statistics at the right time for timely dissemination to stakeholders is considered as an impediment for the development and growth of the industry. Coconut Development Board initiated statistical survey for estimation of production of coconut across major coconut growing states in India by undertaking field surveys and yield estimates based on established phenotypic characters of the buttons/ nuts. The estimation was carried out in Tumkur district of Karnataka also which has the highest area under coconut. A total of 406 farms were surveyed in four taluks of the district covering 4060 bearing palms for productivity estimation. The average number of nuts per palm across all age groups for the district as a whole was 98 nuts. The average productivity for Karnataka which was much below to all India average before 2010-11 saw sudden surge post 2011-12. Questions arise as to what are the underlying factors for such sudden spikes. Across many, data capture, estimation and reporting are critical which go on to determine the decision making process on development and growth of the sector. Decisions are formulated on fixation of prices, trade, planning and execution of welfare schemes and policy making. Hence, scientific estimation initiated by Coconut Development Board on production and productivity augurs well for the sector.</p>