Social Disruption Research Articles

Enhancing ethical awareness through generative AI literacy: A study on user engagement and competence

Generative artificial intelligence (AI) enables users to quickly and easily create desired outputs. However, it poses potential risks of social disruption due to biases in the data used to generate such outputs. This study examines whether providing literacy-based guidance on the risks and cautionary aspects of generative AI at the point of user acceptance of its outputs can enhance the user's ethical competence. For the study, participants were divided into an experimental group and a control group. The experimental group received warnings about the risks and considerations of accepting AI-generated outputs before using the AI, while the control group received no such guidance. The results revealed that the experimental group, which was informed of the risks and cautionary aspects, showed significant improvements in ethical awareness across various dimensions, including values, self-efficacy, self-regulation and engagement, and ethics and security. Based on these findings, the study suggests that systematic education on the risks and cautionary aspects of generative AI, alongside the technology’s dissemination, can play a crucial role in addressing social and ethical challenges.

Communication, Contact, and Intergenerational Dynamics: Aging in Not-So-Normal Times.

This Epilogue extends themes from the Special Issue, with a particular focus on how communication operates during times of social disruption. Three forms of disruption are discussed: societal-global disruption (manifested in the Covid-19 pandemic), individual-relational disruption (manifested in a dementia diagnosis), and societal progress (manifested in technological change). The Epilogue discusses how these disruptions affect the quality and quantity of intergenerational contact, and feed into hostile and benevolent forms of ageism. The conclusions discuss connections between disruptions and the Communication Ecology Model of Successful Aging, as well as links to societal segregation, thus suggesting the multiplicity of ways that communication serves as a platform for healthier approaches to aging in society.

Global digital overload: how Snapchat communication cycles influence workplace efficiency

Purpose This paper aims to explore the growing integration of social media, specifically Snapchat, into workplace environments and its impact on communication behaviors, especially among Generation Z and Millennials. The focus is on analyzing how Snapchat’s communication cycles, such as notifications, Snap streaks and best friend rankings, affect workplace efficiency. This study also investigates how cultural variations around connectivity and work-life balance amplify or mitigate these effects in global settings. Design/methodology/approach This research uses social comparison theory and self-determination theory to examine the psychological and social impacts of Snapchat’s features on workplace productivity. Drawing on qualitative and quantitative literature, the paper explores how different cultural contexts influence employees’ interaction with Snapchat during work hours. Theoretical frameworks are applied to understand the cognitive and social disruptions caused by social media, while practical strategies for human resource management are explored. Findings Snapchat’s design fosters continuous user engagement, often leading to fragmented attention and reduced productivity, particularly in work environments. Cultural norms surrounding social media usage and work-life boundaries either intensify or alleviate the disruptive effects of Snapchat. For example, the pressure to maintain social ties amplifies workplace distractions in collectivist cultures. In contrast, individualistic cultures may emphasize productivity over social connection, allowing for more effectively managing these distractions. Originality/value This paper contributes to the growing body of literature on social media’s impact on workplace dynamics by offering a culturally nuanced approach to understanding digital distractions. By focusing on Snapchat, a platform with unique features that encourage habitual interaction, the study provides novel insights into how global human resource strategies can be tailored to different cultural settings. The findings suggest practical solutions for managing digital overload and optimizing employee performance in increasingly interconnected work environments.

Electron Tomography as a Tool to Study SARS-CoV-2 Morphology.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a novel betacoronavirus, is the causative agent of COVID-19, which has caused economic and social disruption worldwide. To date, many drugs and vaccines have been developed for the treatment and prevention of COVID-19 and have effectively controlled the global epidemic of SARS-CoV-2. However, SARS-CoV-2 is highly mutable, leading to the emergence of new variants that may counteract current therapeutic measures. Electron microscopy (EM) is a valuable technique for obtaining ultrastructural information about the intracellular process of virus replication. In particular, EM allows us to visualize the morphological and subcellular changes during virion formation, which would provide a promising avenue for the development of antiviral agents effective against new SARS-CoV-2 variants. In this review, we present our recent findings using transmission electron microscopy (TEM) combined with electron tomography (ET) to reveal the morphologically distinct types of SARS-CoV-2 particles, demonstrating that TEM and ET are valuable tools for visually understanding the maturation status of SARS-CoV-2 in infected cells. This review also discusses the application of EM analysis to the evaluation of genetically engineered RNA viruses.

Got milk? Got cybersecurity risks! Unraveling ransomware threats in the German dairy industry

PurposeThis study aims to explore the vulnerabilities of the dairy industry to ransomware threats, focusing particularly on the upstream supply chain and applying routine activity theory (RAT) to understand the evolving dynamics of cybercrime in critical infrastructure sectors.Design/methodology/approachUtilizing expert interviews and network analysis, this research investigates the exploitation of complex supply chain vulnerabilities by motivated offenders. It delves into the intricate interplay between digital threats and physical supply continuity.FindingsThe study uncovers that ransomware threats transcend digital boundaries, manifesting in disruptions to physical operations and presenting significant risks to food security. It underscores the threat posed by the convergence of information technology (IT) and operational technology (OT), emphasizing the urgent need for heightened awareness and robust defenses against this substantial menace.Practical implicationsAddressing cyber vulnerabilities in critical sectors like dairy ensures not only the security of operations but also safeguards broader societal interests such as food security. Collaboration and proactive measures are essential to mitigate potential social and economic disruptions caused by cyber incidents.Originality/valueThis research fills a knowledge gap by shedding light on the nexus between cyber threats and supply chain resilience. It emphasizes the need for industries to adapt traditional defense mechanisms in the face of sophisticated digital adversaries.

A Survey on Advanced Persistent Threat Detection: A Unified Framework, Challenges, and Countermeasures

In recent years, frequent Advanced Persistent Threat (APT) attacks have caused disastrous damage to critical facilities, leading to severe information leakages, economic losses, and even social disruptions. Via sophisticated, long-term, and stealthy network intrusions, APT attacks are often beyond the capabilities of traditional intrusion detection methods. Existing methods employ various techniques to enhance APT detection at different stages, but this makes it difficult to fairly and objectively evaluate the capability, value, and orthogonality of available techniques. Overly focusing on hardening specific APT detection stages cannot address some essential challenges from a global perspective, which would result in severe consequences. To holistically tackle this problem and explore effective solutions, we abstract a unified framework that covers the complete process of APT attack detection, with standardized summaries of state-of-the-art solutions and analysis of feasible techniques. Further, we provide an in-depth discussion of the challenges and countermeasures faced by each component of the detection framework. In addition, we comparatively analyze public datasets and outline the capability criteria to provide a reference for standardized evaluations. Finally, we discuss insights into potential areas for future research.

Birth Outcomes and Prenatal Care Use in the U.S. During the COVID-19 Pandemic in 2020 and 2021.

The COVID-19 pandemic has posed substantial social and economic disruptions that may have had adverse effects on maternal and infant health. This study examines the changes in birth outcomes and prenatal care use during the COVID-19 pandemic in 2020 and 2021 compared to pre-pandemic years. Data come from birth certificates from the U.S. Vital Statistics Natality Files. The analytical sample includes 18,678,327 births in the 50 states and Washington, DC between 2017 and 2021. An event study is employed to examine changes in multiple birth outcomes and prenatal care use over years adjusting for demographic/socioeconomic characteristics and state of residence. There were very small changes in birth outcomes during pandemic years in 2020 and 2021. Specifically, low birth weight odds were lower in 2020 (OR = 0.99; 95 CI: 0.98-0.99) but higher in 2021 (OR = 1.03; 95% CI: 1.03-1.04) compared to 2019. C-section odds were higher in 2021 (OR = 1.01, 95% CI: 1.002-1.008) than in 2019. The mean number of prenatal visits in both 2020 and 2021 relative to 2019 was lower by about 0.3 visits (95% CI: -0.31 to -0.30 in 2021). Overall, there is no evidence of broad pandemic effects on low birth weight and preterm birth in 2020-2021.

Distributed impact of severe mental health conditions in rural Ethiopia, a qualitative study

AimTo explore the distributed impact of severe mental health conditions (SMHCs) among people with lived experience of SMHCs, their family members, and community members.MethodsWe conducted in-depth interviews with family key informants of people with SMHCs (n = 32), people with SMHCs (schizophrenia, bipolar disorder, and major depression) (n = 10), and community members (n = 6) in rural Ethiopia. The study was nested within a long-standing population-based cohort of people with SMHCs. Interviews were conducted in Amharic and were audiotaped. We conducted a thematic analysis.ResultsWe identified four themes: stress and physical tolls, lost expectations, social disruption, and economic threat. Family members reported stress and hopelessness; some also tried to harm themselves. Family members reported that their relationships with each other and with the wider community were disrupted significantly. Spouses and children did not get the support they needed, leading to unmet expectations: being left alone to care for children, unable to go to school or dropping out early. The study participants with SMHCs also spoke about the impacts of their illness on other family members and the community which appeared to be a source of shame and self-isolation. Both the family and the community respondents reported the economic effect of the illness which sometimes led to selling assets, debt, unemployment, forced migration, and food insecurity. Community members emphasised the economic burden and danger related to the aggressive behavior of the person with SMHCs, while the person with the illness and their family members blamed the community for the stigma and discrimination they experienced.ConclusionSMHCs have profound consequences for the person with the illness, their family members, and the community. Future interventions for SMHCs should consider household-level interventions to address economic and care needs and mitigate the intergenerational impact. The community should be considered as a resource as well as a target for intervention.

Caregivers on point: a randomized treatment–control prevention trial for foster and kinship caregivers to reduce behavior challenges among children in foster care

BackgroundChildren in foster care who are newly placed with licensed or kinship caregivers are often vulnerable to increased behavior problems associated with trauma and social disruptions. When those issues are not addressed, children are susceptible to placement disruptions that exacerbate behavior problems. Few preventive interventions are available for foster and kinship caregivers, and none are designed to be delivered at the time of a child’s placement into the home. This study aims to examine the impact of the Chicago Parent Program adapted and customized for foster and kinship caregivers (CPP-FC), locally branded as Caregivers on Point, on caregiver stress, parenting confidence and strategies, children’s behaviors, and placement stability.MethodsCaregivers (N = 300) are being recruited from a specialized foster care clinic that sees children and caregivers within five business days of a new placement. Upon completing baseline surveys and behavioral observation, caregiver-child dyads are randomized to receive CPP-FC (n = 150) or usual care (n = 150). Those in the treatment condition will complete 11 weekly sessions addressing child behavior management and caregiving approaches. A booster session will occur one month after the weekly sessions conclude. A mid-point assessment and behavioral observation will be collected four months after the baseline assessment for all participants, coinciding with the completion of the CPP-FC programming. At 6 months post-baseline, an end-of-study assessment will be collected. Administrative data will be extracted from the child welfare record to determine placement stability for the 12 months following enrolment. The primary outcome of interest is child behavior, indicated by changes in caregiver reports and objective ratings of behavior from observations, where raters are blinded to the treatment arm and timing of data collection. Secondary outcomes include placement stability and changes in caregiver stress and confidence in managing children’s behavior.DiscussionIf found to be effective, CPP-FC would be helpful for families involved with child welfare. It could be delivered by child welfare agencies, licensing and kinship navigator agencies, and foster care clinics and may be eligible for government reimbursement as a preventive intervention for children in foster care.Trial registrationThis study was prospectively registered with ClinicalTrials.gov, NCT06170047.

The association of personal, parental, school and community factors with depressive symptoms among a sample of Colombian students of ages 9 to 12 years.

Few studies have examined how the personal characteristics of students, together with factors from their local social environments and communities, affect students living in generally high levels of social disruption. We examined the influence that personal characteristics as well as factors from the local social environments and communities may have on Colombian students' levels of depressive symptoms shortly after the end of the of armed conflict. Data were collected from 710 students attending the fifth grade in a random sample of elementary schools in the province of Sucre in Colombia. Information was gathered on the students' ages and gender as well as characteristics of their parents, school factors, and community factors. A five-level hierarchical regression model was used to determine the extent to which all these variables predicted depression scores, as measured by the Adolescent Depression Rating Scale. While personal, parental, school and community factors were all found to predict depression scores, the category, parental factors had the most impact. That was followed by school factors, community factors and finally personal characteristics. Multiple social and environmental factors were associated with the level of depression experienced by Colombian students.

A Methodological Approach to Improving Extreme Precipitation Reanalysis Data Using the Clausius-Clapeyron Relationship: A Case Study in a Mediterranean City

Climate change is a crucial issue of the 21st century, leading to more frequent and severe extreme precipitation events globally. These events result in significant social and economic disruptions, including flooding, loss of life, and damage to infrastructure. Projections suggest that extreme rainfall will intensify in the latter half of the century, underscoring the need for accurate and timely forecasting. Despite advancements in meteorological and climate models that offer high accuracy for various weather parameters, these models still struggle to detect extreme values, particularly for precipitation. This research examines the sensitivity of extreme precipitation events to temperature, based on the Clausius-Clapeyron relationship, focusing on Thessaloniki, Greece. It also evaluates the effectiveness of reanalysis data in identifying extreme precipitation and explores how rainfall-temperature relationships can enhance prediction accuracy. The findings are vital for improving the estimation of extreme rainfall events and informing the design of flood-resilient infrastructure.

U.S. Adolescents’ daily social media use and well-being: Exploring the role of addiction-like social media use

ABSTRACT Associations between adolescent social media use and well-being are inconclusive, and studies using rigorous methodologies and objective measures are needed. Additionally, attention on what individual differences may moderate linkages between social media and well-being is necessary. We tested 1) how daily social media use (assessed via objective-reports and self-reports during an ecological momentary assessment period) relates to daily subjective well-being, 2) the prevalence and concordance between scholar-defined addiction-like social media use (ASMU) and participant perceptions of social media addiction, 3) how these constructs relate to subjective well-being, and 4) if these constructs moderate daily links between social media use and subjective well-being. In a sample of 103 adolescents (M age = 16.48, 47% female), ASMU and perceived addiction were highly correlated but some adolescents’ classification differed when cross-referencing. Both were similarly associated with demographics and depressive symptoms. Self-reported, but not objectively-recorded, social media use was related to greater ASMU and perceived addiction. Links between social media use and well-being were inconsistent, with no moderation by ASMU or perceived addiction. Most adolescents endorsed some degree of ASMU, and future research should examine how social media-triggered disruptions to daily functioning relates to well-being.

Volunteering behavioral declines amid personal and organizational upheaval: Recruitment, retention, and barriers in Australia

ABSTRACT Volunteers have faced recent social disruptions which have brought about a new wave of barriers to wash over survivors of an already declining number of formal volunteers in Australia. How the “environmental jolt” of recent social disruption has played out for volunteering is important to understand because less is known about how organizational responses have interacted with changing individual volunteer motives and meanings in the volunteering context. Understanding the impact of this environmental jolt of recent social disruption on volunteering is crucial, especially considering the implications for well-being in communities of volunteers.

Rootism, Modernity, and the Jew: Antisemitism and the Reactionary Imaginary, 1789–1945

Abstract The far-right identification of Jews with modernity has been noted by many scholars, yet most analyses have fallen short of offering a properly dialectical account of antisemitism, one that will scrutinise the antinomies at the heart of the antisemitic discourse and trace their relations to the contradictions of modernity itself. In this paper, I will make modernity as movement the focus of the analysis. Modernity, philosophically underpinned by the Enlightenment, and politically ushered in by the French Revolution of 1789, was seen by its reactionary and fascist opponents both as a time of great upheaval, constant change and social disruption, but also as the setting-up of an era of stasis and degeneration. It was paradoxically decried, sometimes simultaneously, as both helplessly nomadic and incurably sedentary. And in both respects ‘the Jew’ and ‘the Jewish spirit’ were often placed, no matter how spuriously, at the very centre of attacks. Qua ‘wandering’ or ‘eternal’, the Jews were seen as embodying the spirit of restlessness and lack of roots, undermining tradition and fixed national and racial identities; their dynamic role as revolutionaries, conspirators and rabble rousers was ritually denounced. Jews were also condemned, however, as a major obstacle to movement and expansion, the arch-enemies of imperialism, seeking to establish a realm of universal brotherhood, peace and egalitarianism. By attacking the Jews, reactionaries and fascists thus attempted to settle their scores with a modernity that they feared and loathed in equal measure.

경찰공무원의 직무몰입이 재난대응역량에 미치는 영향에서 회복탄력성의 매개효과

Modern society faces many forms of disasters, not just emerging viral infectious diseases like COVID-19. These disasters not only cause huge losses in human and material resources, but also cause social disruption. Effective disaster response is an essential part of protecting society and its people, and the role of police officers is pivotal in this process. Police officers are directly involved in maintaining order, saving lives, and recovering from disasters during the initial response phase, so their response capabilities have a direct impact on the effectiveness of disaster management. In this context, it can be argued that police officer engagement plays a key role in enhancing disaster response capacity. To further understand the relationship between job commitment and disaster response capacity, it is also necessary to consider the internal factors of individuals. In this study, we propose resilience as such an internal factor and explore its mediating effect to enhance the effectiveness of the police role in disaster situations. The results of the analysis showed that job commitment (=.66, p<.001) was positively significant as a result of the significance test of the effect of the independent variable on the mediating variable. On the other hand, the results of the significance test of the effects of independent variables and parameters on the dependent variable showed that job commitment (=.29, p<.001) had a significant effect on disaster response capability, and the parameter resilience also had a significant effect on disaster response capability (=.33, p<.001). The results suggest that police officers' job engagement directly enhances their disaster response capabilities and that resilience partially influences this relationship. This suggests that police officers with higher job commitment have the ability to respond more effectively in disaster situations. These findings suggest that programs that promote resilience in police organizations can enhance job commitment, which in turn can improve the disaster response capabilities of police officers. Therefore, police organizations should consider implementing a variety of training and support programs to enhance resilience in addition to strategies to increase job engagement.

Responding to epidemics: the case of the Nguyễn Dynasty, focusing on the period 1802–1883

Abstract In the past, Vietnam was impacted by numerous epidemics, particularly during the Nguyễn Dynasty from 1802 to 1883. Based on data from the Đại Nam Thực Lục (1961) (The Veritable Records of the Great South), this article investigates the frequency and nature of these epidemics, identifies the types of common diseases at that time, and explores the underlying causes of these outbreaks. The study further examines the Nguyễn Dynasty's strategies for managing these health crises. During these outbreaks, the dynasty faced significant challenges, with frequent epidemics leading to high death rates, widespread social disruption, and economic decline. The dynasty's primary preventive measures, heavily reliant on spiritual practices like prayer, highlight the limited medical understanding at the time and the constraints of its socio-political framework. However, there was a progressive shift towards the incorporation of Western medical innovations, particularly in the vaccine approach to treat diseases like smallpox. This transition not only marked a critical evolution in the local healthcare approach but also set the stage for more systematic medical advancements in Vietnam during the colonial period (1884–1945).

Assessing Air Quality Dynamics during Short-Period Social Upheaval Events in Quito, Ecuador, Using a Remote Sensing Framework

This study uses a remote sensing approach to investigate air quality fluctuations during two short-period social upheaval events caused by civil protests in 2019 and the COVID-19 pandemic in 2020 in Quito, Ecuador. We used data from the TROPOMI Sentinel-P5 satellite to evaluate the concentrations of two greenhouse gases, namely O3 and NO2. TROPOMI Sentinel-P5 satellite data are becoming essential in air quality monitoring, particularly for countries that lack ground-based monitoring systems. For a better approximation of satellite data with ground data, we related the remotely sensed data using ground station data and Pearson correlation analysis, which revealed a significant association between the two sources (0.43 ≤ r ≤ 0.78). Using paired t-test comparisons, we evaluated the differences in mean gas concentrations at 30 randomly selected intervals to identify significant changes before and after the events. The results indicate noticeable changes in the two gases over the three analysis periods. O3 significantly decreased between September and November 2019 and between March and May 2020, while NO2 significantly increased. NO2 levels decreased by 18% between February and March 2020 across the study area, as indicated by remote sensing data. The geovisualization of remotely sensed data over these periods supports these patterns, suggesting a potential connection with population density. The results show the complexity of drawing global conclusions about the impact of social disruptions on the atmosphere and emphasize the advantages of using remote sensing as an effective framework to address air quality changes over short periods of time. This study also highlights the advantages of a remote sensing approach to monitor atmospheric conditions in countries with limited air quality monitoring infrastructure and provides a valuable approach for the evaluation of short-term alterations in atmospheric conditions due to social disturbance events.

An examination of COVID-19’s impact on student learning: a self-determination theory perspective

PurposeWe propose and test a theoretically grounded structural model of our postulation, providing insights into how students’ COVID experiences affect their general learning experiences, specific learning experiences and specific class performance post-COVID.Design/methodology/approachNumerous studies have reported how COVID-19 has impacted student learning in higher education during the pandemic from Spring 2020 to Fall 2021. Students were found to be disengaged, unmotivated, isolated, anxious, having difficulty with emergency remote teaching (ERT) and dealing with financial, physical and/or mental health issues. Against this backdrop, we conduct our own investigation to ascertain what the lasting impacts of COVID-19 are on student learning using a survey instrument. Specifically, we postulate that the academic and social disruptions of COVID-19 affected students’ social connectedness and mental well-being, which in turn, affected their affective and cognitive learning outcomes. We used structural equation modeling to validate a structural model grounded in self-determination theory that capatures the complex relationships between genaral and specfiic COVID-19 impact factors on student learning as seven hypotheses.FindingsAll seven of our hypotheses are supported suggesting that both class-specific factors and broader general factors beyond the classroom affect student's satisfaction with and learning in the class, as postulated in our structural model.Originality/valueWe advance the work of self-determination theory by conceptualizing and modeling the roles that all three self-determination needs play in investigating COVID-19's impact on learning. Overall, our study confirms the value of considering affective factors such as anxiety and satisfaction in learning research.

Occupational Stress in United Kingdom Audiologists.

Occupational stress is known to have detrimental effects on health care professionals worldwide. This study aimed to address a research gap by investigating sources and levels of occupational stress in U.K. audiologists. A mixed-methods cross-sectional design and convenience sampling were utilized. The study used the Audiologist Occupational Stress Questionnaire (AOSQ) and an audiological working practices questionnaire. The study included 100 registered U.K. audiologists. The research revealed that over a third of participants reported experiencing moderate or higher levels of occupational stress. Pediatric audiologists and those with a high daily patient load reported significantly higher stress scores than other specialties and those seeing fewer patients per day. Identified sources of stress for U.K. audiologists included clinical demands and time constraints, staffing issues, leadership in the workplace, and equipment availability. Reported impacts of stress encompassed mental health issues, fatigue, social life disruptions, and physical health concerns. The research validated the use of the AOSQ in a U.K. setting, and the findings provided insights into the sources and levels of occupational stress experienced by U.K. audiologists, supporting existing research on occupational stress in audiologists in other countries. The identification of consistent stress themes across the literature underscores the need for targeted support and interventions to ensure the well-being of audiologists and empower them in maintaining their pivotal role in health care.

A stratified review of COVID-19 infection forecasting and an efficient methodology using multiple domain-based transfer learning

The initial outbreak of COVID-19 was reported in December 2019, China. The pandemic has led to unforeseen challenges, causing unimaginable devastation of the economic and social disruption since its inception. An effective approach for forecasting infections will be beneficial for the health sector and administration in better strategic planning and proficient management of all necessary schemes towards preventive and curative treatments. Most existing studies consider image dataset for COVID-19 prediction, whereas studies involving structural data are very rare. Thus, initially the main focus of this paper is to provide an exhaustive review that discusses about COVID-19 forecasting papers with emphasis on structural data. Then, this paper introduces a pioneering approach to COVID-19 infection forecasting, utilizing structural datasets instead of traditional image datasets. It presents a novel multi-source transfer-learning framework to enhance prediction accuracy, integrating demographic, economic, and COVID-19 data for intra-provincial spread forecasts. The COVID-19 forecasting depends on several parameters such as its current statistics, geographical area, population density and economic status like GDP etc. However, the dataset generated for an individual province of a country is alone inadequate for the precise forecast, as it faces data scarcity. Thus, transfer learning helps in such cases, where the dataset has been collected from multiple provinces. Since, it is a time-series data, thus we also consider lagged features for efficient prediction of COVID cases. Thus, apart from the detailed review, this study also aims to develop robust machine learning models by proposing a novel and efficient multi-source transfer learning technique for accurate forecasting of COVID-19 in a province. The proposed approach has been evaluated over a wide range of datasets involving sixty-two different provinces belonging to a diverse set of countries. We also performed hyperparameter tuning using Bayesian optimisation to optimise the machine learning models used. Later, we performed Friedman and Nemenyi test to compare the results generated from different models. Empirical evidence proved that forecasting using the proposed approach is much more precise with the simpler models such as Decision Trees as compared to complex models. In cases of data scarcity, when target domain data could not be used for training/fine-tuning the models simpler models are far more powerful due to their generalization capabilities than complex models. Hence, the proposed methodology is promising and valuable for governments and organizations to deal with the challenges of any pandemic outbreak for better healthcare planning and management, even when the data is in scarcity.