Understanding the intent behind sharing misinformation on social media

Several studies have been conducted in annotating and collecting the misinformation spread on various social media sites. The misinformation spread during COVID-19 pandemic increased many folds. Understanding the reasons and intent of the misinformation during COVID-19 is a crucial task. Existing approaches have not focused on understanding the intent behind sharing misinformation in the first place. To understand the intent, we introduce a new dataset MisMemoir that apart from annotating misinformation, also collects the social context and site history of the user sharing misinformation. Utilising the established benefits of game theory in social media behaviour analysis, we deploy two-person cooperative games to understand how prominent positive feedback cues like likes and retweets are in motivating an individual to share misinformation on the platform Twitter. Experimental results demonstrate that the spread of misinformation's primary intent is the intentional/unintentional manoeuvre to increased reach and possibly a false sense of accomplishment. Empirically, we show that in a competitive environment like social media, feedback cues like retweets and comments assume the role of 'attention' payoff that significantly affects the strategy of a user on Twitter to share misinformation intentionally. [ FROM AUTHOR] Copyright of Journal of Experimental & Theoretical Artificial Intelligence is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Effect of total population, population density and weighted population density on the spread of Covid-19 in Malaysia.

Since November 2019, most countries across the globe have suffered from the disastrous consequences of the Covid-19 pandemic which redefined every aspect of human life. Given the inevitable spread and transmission of the virus, it is critical to acknowledge the factors that catalyse transmission of the disease. This research investigates the relation of the external demographic parameters such as total population, population density and weighted population density on the spread of Covid-19 in Malaysia. Pearson correlation and simple linear regression were utilized to identify the relation between the population-related variables and the spread of Covid-19 in Malaysia using data from 15th March 2020 to 31st March 2021. As a result, a strong positive significant correlation between the total population and Covid-19 cases was found. However, a weak positive relationship was found between the density variable (population density and weighted population density) and the spread of Covid-19. Our findings suggest that the transmission of Covid-19 during lockdown (Movement Control Order, MCO) in Malaysia was more readily explained by the demographic variable population size, than population density or weighted population density. Thus, this study could be helpful in intervention planning and managing future virus outbreaks in Malaysia.

Burden of COVID-19 on health and wellbeing, education, and economy of Bangladesh.

The long-term impact of this pandemic will continue in almost all sectors of a country such as health, economic situations, education, mental health, and violence. Therefore, the authors intended to discuss the prolonged effect of COVID-19 on the health along with wellbeing, education, and economy of Bangladesh through a mixed approach. To assess the possible scenario in health sector of Bangladesh, we conducted a short survey through online with a structured questionnaire. The impact of the pandemic is highlighted by graphical presentations and discussed the issues in light of the existing literature. It is realized that health care services and resources are always essential for predominant health conditions and fatal diseases patients. Mental health has also been impacted a lot during this pandemic. Moreover, students of only those schools located in urban areas are attended some online classes but due to the internet interruption and scarcity of devices students from rural areas cannot attend the classes and it will widen the gap between pupils from urban areas and those who live in remote rural areas. Additionally, many students terminate school. The country's youth unemployment is projected to intensify as a result of the economic effects, which would promote antisocial behavior and cause social discontent among young people. Also, the flow of remittances greatly declined in the last couple of months and a many people were jobless abroad, and the majority of them were sent back home. The demographic dividend's intended results are expected to be negatively impacted by COVID-19's overall effect as well as sustainable development goals (SDGs) in Bangladesh. Therefore, many social services systems need strategic backup resources at community, national, and global levels if any basic system may collapse due to COVID-19 and socio-economic as well as geopolitical negligence in handling post-pandemic challenges.

Challenges and difficulties faced in low- and middle-income countries during COVID-19.

Objectives: The ongoing COVID-19 pandemic, caused by a novel coronavirus SARS-CoV-2, has created a severe threat to global human health. We are extremely lucky because within the first year of the COVID-19 pandemic, scientists developed a number of vaccines against COVID-19. In this paper, the authors discuss the difficulties and challenges faced in different low-and middle-income countries due to the ongoing pandemic. Study design and methods: This research is primarily based on secondary data and existing literature reviews. The authors use maps and graphical representations to show information about vaccination coverage. Results: The lacking vaccination coverage and insufficient supply of oxygen tanks in hospitals of low- and middle-income countries (LMICs) raise the likelihood of death of the critical COVID-19 patients. Developed countries vaccinate their citizens more quickly than LMICs. In comparison to wealthy countries, LMICs usually lack the resources and capacity to obtain the required vaccination doses. Conclusion: It is frequently observed that hospitals in low- and middle-income nations with a dearth of oxygen tanks result in increased suffering and mortality. To avoid a worldwide disaster, LMICs urgently require COVID-19 vaccinations since viruses have no borders, and no one is safe until every one is protected in our interconnected world. Therefore, more national and international collaborative supports are urgently necessary for LMICs in this regard.

Understanding the intent behind sharing misinformation on social media

Several studies have been conducted in annotating and collecting the misinformation spread on various social media sites. The misinformation spread during COVID-19 pandemic increased many folds. Understanding the reasons and intent of the misinformation during COVID-19 is a crucial task. Existing approaches have not focused on understanding the intent behind sharing misinformation in the first place. To understand the intent, we introduce a new dataset MisMemoir that apart from annotating misinformation, also collects the social context and site history of the user sharing misinformation. Utilising the established benefits of game theory in social media behaviour analysis, we deploy two-person cooperative games to understand how prominent positive feedback cues like likes and retweets are in motivating an individual to share misinformation on the platform Twitter. Experimental results demonstrate that the spread of misinformation’s primary intent is the intentional/unintentional manoeuvre to increased reach and possibly a false sense of accomplishment. Empirically, we show that in a competitive environment like social media, feedback cues like retweets and comments assume the role of ‘attention’ payoff that significantly affects the strategy of a user on Twitter to share misinformation intentionally.

Likelihood of infectious diseases due to lack of exclusive breastfeeding among infants in Bangladesh.

BACKGROUND: Bangladesh is a South Asian developing country trying to achieve the Sustainable Development Goals (SDG)-3 and the objective of the Rural Electrification Board (REB) regarding child mortality. Infectious diseases are leading causes of child mortality, and lack of exclusive breastfeeding (EBF) among infants aged 0-6 months increases child morbidity and mortality from various infectious diseases in developing countries. However, as per existing literature, no study has been conducted yet to determine the lack of EBF practice effect on child mortality in Bangladesh. With this backdrop, the authors intend to measure the likelihood of infectious diseases due to the lack of EBF of infants aged 0-6 months in Bangladesh. MATERIALS AND METHODS: This study used Bangladesh Demographic and Health Survey (BDHS) data over 1996-97 to 2017-18. The mothers of infants aged 0-6 months who were willingly participated in the BDHSs were considered to include in our analysis. Initially, there were 9,133 cases in the combined dataset. After filtering, there were 5,724 cases in the final dataset. We have considered diarrhea (D), acute respiratory infection (ARI) separately as well as the presence of either D or ARI or both and named as CoDARI as outcome variables. This study used both graphical and statistical techniques (Chi-square test, Wald test, and logistic regression) to analyze the data. The odds ratio (OR) and 95% confidence interval (CI) were used to quantify the likelihood of infectious diseases due to lack of EBF practice and its elasticity, respectively. RESULTS: The EBF practice got a conspicuous increasing trend, but the prevalence of infectious diseases was declined from 0 to 3 months of age of infants, whereas an inverse scenario is observed between 4-6 months. The significance of that inverse relationship was confirmed by p-value corresponding to the chi-square test and the Wald test of the adjusted regression coefficients after adjusting the associated factor's effect on infectious diseases. The adjusted ORs also concluded that the lack of EBF practice up to six months of age could enhance the risk of D, ARI, and CoDARI by 2.11 [95% CI: 1.56-2.85], 1.43 [95% CI: 1.28-1.60], and 1.48 [95% CI: 1.32-1.66] times higher, respectively. CONCLUSION: Findings of this study emphasize the importance of EBF up to six months of age of infants against diarrhea and ARI specific morbidity and mortality. Our results also agreed to the recommendation of the World Health Organization (WHO), United Nations International Children's Emergency Fund (UNICEF), American Academy of Pediatrics (AAP), American Academy of Family Physicians (AAFP), and National Nutrition Programme of Ethiopia (NNPE) that the EBF practice for the first six months of age could be a best, cost-effective, long-lasting natural preventive way to reduce the child morbidity and mortality due to infectious diseases in developing countries. Therefore, findings would help policymakers ensuring the achievement target of REB and SDG-3 associated with the health sector in Bangladesh.

A comparison of rural Australian First Nations and Non-First Nations survey responses to COVID-19 risks and impacts: implications for health communications.

INTRODUCTION: This study investigated differences between rural Australian First Nations and non-First Nations survey respondents' perceptions of COVID-19-related risks and analysed other variables that could predict an exacerbation of anxiety related to COVID-19 harms. METHODS: A cross-sectional online and paper survey of rural residents from the western regions of NSW, Australia, was conducted. Descriptive and multivariate statistical analyses were used to assess links between First Nations status and demographic measures including postcode, age, gender, education, rural or town/village location, proximity to medical services and living situation. The analysis included five items related to perceptions about COVID-19: perceived likelihood of contracting COVID-19 in the next 12 months, perceived harmfulness of the virus, how often people felt afraid, perception about respondents' ability to do something about the virus and perceived economic impacts of the pandemic. RESULTS: There were significant differences between First Nations (n=60) and non-First Nations (n= 639) respondents across all sociodemographic categories. The results reflect a significantly higher level of anxiety among the First Nations Australians in the sample: they felt afraid more often, felt it was highly likely they would catch the virus and if they did catch the virus perceived that it would be very harmful. Living with children under eighteen years of age and in small rural towns were key factors linked to feeling afraid of COVID-19 and First Nations status. CONCLUSION: Health risk communication in pandemic response should include an equitable focus on rural areas, recognising that First Nations Australians are a significant proportion of the rural population with different risk factors and concerns than those of non-First Nations Australians. This principle of First Nations-led design is critical to all health policy and planning. The Australian Government should include rural areas in planning pandemic responses, recognising that First Nations populations are a significant proportion of the rural population creating syndemic conditions.

Determining an effective short term COVID-19 prediction model in ASEAN countries.

The challenge of accurately short-term forecasting demand is due to model selection and the nature of data trends. In this study, the prediction model was determined based on data patterns (trend data without seasonality) and the accuracy of prediction measurement. The cumulative number of COVID-19 affected people in some ASEAN countries had been collected from the Worldometers database. Three models [Holt's method, Wright's modified Holt's method, and unreplicated linear functional relationship model (ULFR)] had been utilized to identify an efficient model for short-time prediction. Moreover, different smoothing parameters had been tested to find the best combination of the smoothing parameter. Nevertheless, using the day-to-day reported cumulative case data and 3-days and 7-days in advance forecasts of cumulative data. As there was no missing data, Holt's method and Wright's modified Holt's method showed the same result. The text-only result corresponds to the consequences of the models discussed here, where the smoothing parameters (SP) were roughly estimated as a function of forecasting the number of affected people due to COVID-19. Additionally, the different combinations of SP showed diverse, accurate prediction results depending on data volume. Only 1-day forecasting illustrated the most efficient prediction days (1 day, 3 days, 7 days), which was validated by the Nash-Sutcliffe efficiency (NSE) model. The study also validated that ULFR was an efficient forecasting model for the efficient model identifying. Moreover, as a substitute for the traditional R-squared, the study applied NSE and R-squared (ULFR) for model selection. Finally, the result depicted that the prediction ability of ULFR was superior to Holt's when it is compared to the actual data.

A Short Overview: Marine Resources as Potential Interventions for the Omicron SARS-CoV-2 Variant

In November of 2021, a recently evolved variant of SARS-CoV-2, omicron, was discovered. In just one month, omicron has spread to more than 89 countries resulting in a rapid rise in cases and a new wave of infections. With over 46 mutations, omicron brings concern to the public health and may be able to infect at a greater capacity than previous strains. Although able to infect double vaccinated and previously infected individuals, the booster vaccine may prove promising. However, more research is needed to fully elucidate the key function of each mutation and to better develop effective drugs. Marine resources may be a promising drug discovery avenue to investigate. For example, compounds such as natural bromotyrosines and inorganic polyphosphate have been shown to have multiple mechanisms of action against viruses, like SARS-CoV-2. Through viral entry blockade and preventing viral replication and protein synthesis, metabolites produced from marine organisms may be promising against the evolving SARS-CoV-2. The present review highlights key features of the omicron SARS-CoV-2 variant, summarizes key studies and reports on omicron viral infection and examines the potential for intervention using renewable marine resources.

A Review of COVID-19 Modelling Strategies in Three Countries to Develop a Research Framework for Regional Areas.

At the end of December 2019, an outbreak of COVID-19 occurred in Wuhan city, China. Modelling plays a crucial role in developing a strategy to prevent a disease outbreak from spreading around the globe. Models have contributed to the perspicacity of epidemiological variations between and within nations and the planning of desired control strategies. In this paper, a literature review was conducted to summarise knowledge about COVID-19 disease modelling in three countries-China, the UK and Australia-to develop a robust research framework for the regional areas that are urban and rural health districts of New South Wales, Australia. In different aspects of modelling, summarising disease and intervention strategies can help policymakers control the outbreak of COVID-19 and may motivate modelling disease-related research at a finer level of regional geospatial scales in the future.

Regional and temporal patterns of influenza: Application of functional data analysis.

BACKGROUND: The accurate estimation of temporal patterns of influenza may help in utilizing hospital resources and guiding influenza surveillance. This paper proposes functional data analysis (FDA) to improve the prediction of temporal patterns of influenza. METHODS: We illustrate FDA methods using the weekly Influenza-like Illness (ILI) activity level data from the U.S. We propose to use the Fourier basis function for transforming discrete weekly data to the smoothed functional ILI activities. Functional analysis of variance (FANOVA) is used to examine the regional differences in temporal patterns and the impact of state's political orientation. RESULTS: The ILI activity has a very distinct peak at the beginning and end of the year. There are significant differences in average level of ILI activities among geographic regions. However, the temporal patterns in terms of the peak and flat time are quite consistent across regions. The geographic and temporal patterns of ILI activities also depend on the political make-up of states. The states affiliated with Republicans had higher ILI activities than those affiliated with Democrats across the whole year. The influence of political party affiliation on temporal pattern is quite different among geographic regions. CONCLUSIONS: Functional data analysis can help us to reveal the temporal variability in average ILI levels, rate of change in ILI levels, and the effect of geographical regions. Consideration should be given to wider application of FDA to generate more accurate estimates in public health and biomedical research.

Trends and determinants of vaccination among children aged 06-59 months in Bangladesh: country representative survey from 1993 to 2014.

BACKGROUND: Vaccination has important consequences for childhood development, mortality, and inequalities in health and well-being. This research explores the trend of vaccinations coverage from 1993 to 2014 and determines the significant factors for vaccinations coverage in Bangladesh, considering geospatial, socioeconomic, and demographic characteristics. METHODS: This study uses a secondary dataset extracted from the Bangladesh Demographic and Health Survey (BDHS) from 1992 to 93 to 2014. The association between selected independent variables and vaccination coverage of children was examined through the Chi-square test. In addition, unadjusted and adjusted logistic regression approaches were applied to determine the effects of covariates on vaccination status by using the BDHS-2014 dataset. RESULTS: The results reveal that the trend of the vaccination coverage rate has gradually been increased over the study period. The coverage rate of BCG is observed maximum while the lowest for Measles vaccination among all types of vaccinations. The findings revealed that the significantly lower coverage of all vaccination had been observed in the Sylhet region. Children of higher educated mothers (OR 10.21; CI: 4.10-25.37) and father (OR 8.71; CI: 4.03-18.80), born at health facilities (OR 4.53; CI: 2.4-8.55) and whose mother has media exposure (OR 3.20; CI: 2.22-4.60) have more chance of receiving BCG vaccine. For DPT vaccination coverage, there is a significant difference from children whose mothers have primary (OR 1.7; CI: 1.35-2.15), secondary (OR 3.5; CI: 2.75-4.45), and higher (OR 9.6; CI: 5.28-17.42) educational qualification compared to children of illiterate mothers. Findings demonstrated that children born in wealthier households have a higher likelihood of being immunized against DPT, Polio, and Measles vaccination than children born in the poorest households. CONCLUSIONS: The findings reveal that to enhance and make sustainable the overall country's vaccination coverage, we should pay more attention to the mother's education, socioeconomic condition, children's age, birth order number, having media exposure, place of residence, and religion. The authors think that this finding would be helpful to accelerate the achievement target of Sustainable Development Goals (SDGs) for children's health in Bangladesh.

Evaluation of COVID-19 Mitigation Policies in Australia Using Generalised Space-Time Autoregressive Intervention Models.

In handling the COVID-19 pandemic, various mitigation policies aiming at slowing the spread and protecting all individuals, especially the vulnerable ones, were implemented. A careful evaluation of the effectiveness of these policies is necessary so that policy-makers can implement informed decisions if another wave of COVID-19 or another pandemic happens in the future. This paper reports an assessment of some policies introduced by the Australian governments using a generalised space-time autoregressive model which incorporates multiple exogenous variables and delay effects. Our results show that the number of daily new cases from the states and territories are influenced by both temporal and spatial aspects. Business and border restrictions are found helpful in reducing the number of new cases a few days after implementation while gathering restrictions may not be effective.

Analysis of COVID-19 using a modified SLIR model with nonlinear incidence.

Infectious diseases kill millions of people each year, and they are the major public health problem in the world. This paper presents a modified Susceptible-Latent-Infected-Removed (SLIR) compartmental model of disease transmission with nonlinear incidence. We have obtained a threshold value of basic reproduction number ( R 0 ) and shown that only a disease-free equilibrium exists when R 0 < 1 and endemic equilibrium when R 0 > 1 . With the help of the Lyapunov-LaSalle Invariance Principle, we have shown that disease-free equilibrium and endemic equilibrium are both globally asymptotically stable. The study has also provided the model calibration to estimate parameters with month wise coronavirus (COVID-19) data, i.e. reported cases by worldometer from March 2020 to May 2021 and provides prediction until December 2021 in China. The Partial Rank Correlation Coefficient (PRCC) method was used to investigate how the model parameters' variation impact the model outcomes. We observed that the most important parameter is transmission rate which had the most significant impact on COVID-19 cases. We also discuss the epidemiology of COVID-19 cases and several control policies and make recommendations for controlling this disease in China.

Modelling the Transmission Dynamics of COVID-19 in Six High-Burden Countries.

The new Coronavirus Disease 19, officially known as COVID-19, originated in China in 2019 and has since spread worldwide. We presented an age-structured Susceptible-Latent-Mild-Critical-Removed (SLMCR) compartmental model of COVID-19 disease transmission with nonlinear incidence during the pandemic period. We provided the model calibration to estimate parameters with day-wise COVID-19 data, i.e., reported cases by worldometer from 15th February to 30th March 2020 in six high-burden countries, including Australia, Italy, Spain, the USA, the UK, and Canada. We estimate transmission rates for each country and found that the country with the highest transmission rate is Spain, which may increase the new cases and deaths than the other countries. We found that saturation infection negatively impacted the dynamics of COVID-19 cases in all the six high-burden countries. The study used a sensitivity analysis to identify the most critical parameters through the partial rank correlation coefficient method. We found that the transmission rate of COVID-19 had the most significant influence on prevalence. The prediction of new cases in COVID-19 until 30th April 2020 using the developed model was also provided with recommendations to control strategies of COVID-19. We also found that adults are more susceptible to infection than both children and older people in all six countries. However, in Italy, Spain, the UK, and Canada, older people show more susceptibility to infection than children, opposite to the case in Australia and the USA. The information generated from this study would be helpful to the decision-makers of various organisations across the world, including the Ministry of Health in Australia, Italy, Spain, the USA, the UK, and Canada, to control COVID-19.

A Non-Linear Biostatistical Graphical Modeling of Preventive Actions and Healthcare Factors in Controlling COVID-19 Pandemic.

BACKGROUND: With the insurgence of the COVID-19 pandemic, many people died in the past several months, and the situation is ongoing with increasing health, social, and economic panic and vulnerability. As most of the countries relying on different preventive actions to control the outcomes of COVID-19, it is necessary to boost the knowledge about the effectiveness of such actions so that the policymakers take their country-based appropriate actions. This study generates evidence of taking the most impactful actions to combat COVID-19. OBJECTIVE: In order to generate community-based scientific evidence, this study analyzed the outcome of COVID-19 in response to different control measures, healthcare facilities, life expectancy, and prevalent diseases. METHODS: It used more than a hundred countries' data collected from different databases. We performed a comparative graphical analysis with non-linear correlation estimation using R. RESULTS: The reduction of COVID-19 cases is strongly correlated with the earliness of preventive initiation. The apathy of taking nationwide immediate precaution measures has been identified as one of the critical reasons to make the circumstances worse. There is significant non-linear relationship between COVID-19 case fatality and number of physicians (NCC = 0.22; p-value ≤ 0.001), nurses and midwives (NCC = 0.17; p-value ≤ 0.001), hospital beds (NCC = 0.20; p-value ≤ 0.001), life expectancy of both sexes (NCC = 0.22; p-value ≤ 0.001), life expectancy of female (NCC = 0.27; p-value ≤ 0.001), and life expectancy of male (NCC = 0.19; p-value ≤ 0.001). COVID-19 deaths were found to be reduced with increased medical personnel and hospital beds. Interestingly, no association between the comorbidities and severity of COVID-19 was found excluding asthma, cancer, Alzheimer's, and smoking. CONCLUSIONS: Enhancing healthcare facilities and early imposing the control measures could be valuable to prevent the COVID-19 pandemic. No association between COVID-19 and other comorbidities warranted further investigation at the pathobiological level.

Therapeutic Endoscopy during COVID-19 Pandemic: An Observational Study from Bangladesh.

How to cite this article: Al Mahtab M, Huq AKMF, Rahman MF, et al. Therapeutic Endoscopy during COVID-19 Pandemic: An Observational Study from Bangladesh. Euroasian J Hepato-Gastroenterol 2020;10(1): 47-49.

Real-life Management Strategy of COVID-19 Patients in Bangladesh with No Death: An Observational and Cohort Study.

BACKGROUND: Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has been declared as pandemic by World Health Organization (WHO) with increasing morbidity (more than 4.6 million patients) and mortality (300,000 deaths). The world-wide target of management COVID-19 is to reduce complications with available management options; this become highly variable from country to country and even within different regions of the same country. AIM AND OBJECTIVE: This observational prospective study represents a single center study in which all patients in this cohort received almost similar medicines and care. MATERIALS AND METHODS: All patients in this cohort (N: 32) were positive for SARS-CoV-2 by polymerase chain reaction (PCR) with variable presenting symptoms. The management strategy included Standard of Care (SoC) and administration of hydroxychloroquine and doxycycline. Out of 32 patients, 9 patients also received favipiravir. All patients were followed until they were discharged after negativity of SARS-CoV-2 confirmed by PCR on two consecutive occasions taken within 2 days. RESULTS: No death has been recorded in this cohort of 32 patients within the study period. The average hospital staying duration was 13.9 days with a range of 8-21 days. All patients were discharged with improvement of subjective symptoms and SARS-CoV-2 negativity. The vital signs (pulse, blood pressure) as well as and levels of electrolyte and blood counts were within normal and acceptable ranges at the time of discharge. CONCLUSION: The study presented here provide and evidence of a real-life situation of management of limited numbers of COVID-19 patients at a tertiary center of Bangladesh. This study inspires optimism that proper diagnosis, establishment of effective inclusion and exclusion criteria, ensuring application of proper SoC with drugs available in Bangladesh may be a practical option for management of COVID-19 in the country. HOW TO CITE THIS ARTICLE: Huq AKMF, Rahman MF, Islam MA, et al. Real-life Management Strategy of COVID-19 Patients in Bangladesh with No Death: An Observational and Cohort Study. Euroasian J Hepato-Gastroenterol 2020;10(1):31-35.