Future Pandemics Research Articles

Fear of COVID-19 predicts increases in anxiety, depressive symptoms, health anxiety, psychosocial distress, and loneliness: Findings from a prospective two-year follow-up study

The role of fear of COVID-19 in prospectively predicting changes in psychopathological symptoms during the COVID-19 pandemic remains unclear. The present data were obtained from a longitudinal non-probability sample in Germany, initially assessed at the beginning of the COVID-19 pandemic in Germany (April–May 2020) and reassessed after two years (n = 846; 83% female; mean age: 44.59 years, SD = 12.32; response rate: 19.5%). Multiple linear regressions were used to examine associations of fear of COVID-19 at baseline with depressive symptoms, anxiety, health anxiety, psychosocial distress, and loneliness controlling for (a) the respective symptom measure, and (b) all psychopathological symptoms at baseline. The data were weighted to minimize attrition and representativeness biases. Overall, loneliness decreased from the beginning of the COVID-19 pandemic until the two-year follow-up, whereas all other symptoms did not change. Fear of COVID-19 at the beginning of the pandemic predicted an increase in anxiety symptoms, health anxiety, psychosocial distress, and loneliness two years later. In addition, fear of COVID-19 predicted higher health anxiety, depressive symptoms, psychosocial distress, and loneliness, but not anxiety symptoms when controlling for all baseline symptom measures at once. Fear of COVID-19 seems to play a central role in predicting negative mental health outcomes, emphasizing the necessity of indicated prevention and intervention to decrease worry and manage anxiety, thereby reducing the negative impact on mental health caused by fear during future pandemics.

School modality, race and ethnicity, and mental health of U.S. adolescents during the COVID-19 pandemic

BackgroundWhile minoritized ethnoracial groups were most likely to be in online learning during the COVID-19 pandemic, the impact of these ethnoracial disparities on adolescent mental health is unclear. Since past studies do not directly examine whether the association between school modality and self-reported mental health outcomes varied by race and ethnicity among U.S. adolescents during the COVID-19 pandemic, this study addresses the gap.MethodsAdolescents aged 13 to 17 years old (n = 510) were surveyed for self-reports of anxiety and depression symptoms using the 4-item Patient Health Questionnaire during Spring 2021. Seemingly unrelated regressions were used to estimate the differential association between school modality and mental health by respondents’ race and ethnicity.ResultsEstimates without interaction between school modality and race and ethnicity suggested that Latino respondents reported a significantly higher frequency of depressive symptoms than their White counterparts (b = 0.459; p < 0.05). Similarly, the estimates without the interaction suggested respondents reporting hybrid learning had a higher frequency of depressive symptoms than in-person learning (b = 0.504; p < 0.05). Estimates with interaction between school modality and race and ethnicity suggested fully online learning was associated with poorer mental health only among White respondents and better mental health among Black respondents. Among adolescents attending school fully online, Black adolescents reported fewer mental health symptoms than their White counterparts (anxiety, b =– 1.364; p < 0.05, and depression, b =– 1.647; p < 0.05).ConclusionsFully online learning may have benefitted the mental health of Black adolescents during the COVID-19 pandemic, perhaps because it buffered racial discrimination and social anxiety in schools. Additional interventions should be explored to promote in-person school environments that better support the mental health of Black adolescents. Moreover, prioritizing equitable access to broadband internet will provide better access to online learning and ensure positive mental health, particularly for adolescents from minoritized ethnoracial groups during instances of future pandemics. Future research should continue to consider the race and ethnicity of adolescents to promote mental well-being in schools across learning modalities.

Distance Education through the Perspective of Students of Anesthetic Technician, Emergency Medical Technician, and Medical Imaging Technician Programs

Aim: The study aimed to evaluate the distance education process through the perspective of associate degree programs and to identify crucial issues for potential future pandemics. Methods: The study group (n=166) consisted of associate degree students of the Anesthetic Technician, Emergency Medical Technician, and Medical Imaging Technician Programs. Data were collected through an electronic questionnaire regarding main headings: 'Theoretical Courses, Practical Courses, and Professional Development', 'Course Participation and Motivation', 'Measurement and Evaluation', and 'Student Suggestions for Distance Education'. Questions and statements were scored by 5-point Likert. Results: When the effects of distance education ‘on the level of internalization of the profession’ and ‘on the effect on professional competencies’ were assessed, the scores of Medical Imaging Technician Program students were lower than the scores of Anesthetic Technician Program students and Emergency Medical Technician Program students (p

The Veterinarian’s Role in Biocontainment Research Animal Facilities and Prevention of Spread of Pathogens: A Case of Nigeria and South Africa

Infections acquired in research laboratories and unintentional pathogen escapes from breaches in biocontainment pose risks to humans and the environment, necessitating the need for effective biosafety and biosecurity management frameworks in biocontainment research animal facilities (BRAFs). We examine key biosafety issues associated with BRAFs, including inadequate decontamination procedures for wastewater and experimental samples, handling high biosafety level pathogens in lower-level laboratories, risks of animal bites and sharps injuries, contamination of bedding and enrichment materials, and improper management and transportation of biohazard samples. Additionally, we discuss the role of veterinarians in research animal facilities and the challenges they encounter in maintaining biocontainment standards. We emphasise the importance of routine monitoring of effluent water to detect possible disease outbreaks. We recommend a thorough investigation of disease outbreaks to identify potential sources of pathogen release from BRAFs, which could serve as hotspots for future disease outbreaks. Findings from such investigations will inform the development of policies aimed at safeguarding human populations from future pandemics and preventing BRAFs from becoming sources of infectious disease outbreaks.

Hematological Markers as Predictors of ICU Admission in COVID-19 Patients: A Case-Control Study From a Tertiary Hospital.

COVID-19 illness severity ranges from mild- to life-threatening cases necessitating critical care. Rapid prediction of disease severity and the need for critical care support in COVID-19 patients remain essential, not only for current management but also for preparedness in future pandemics. This study aimed to assess hematological parameters as predictors of intensive care unit (ICU) admission and survival in COVID-19 patients, providing insights applicable to a broad range of infectious diseases. A case-control study was conducted at Hospital Raja Perempuan Zainab II, a tertiary referral hospital in Kelantan, Malaysia, from March 2020 to August 2021. Demographics, clinical, and laboratory data were retrieved from patients' medical records. Statistical analyses, including the Chi-square (χ2) test, independent t-tests, and simple and multiple logistic regressions, were used to analyze the data. A receiver operating characteristic (ROC) curve analysis was conducted to assess the accuracy of the predictors. The median age was 51 years, with females comprising 56.7% (n=148) and males 43.3% (n=113). A total of 88.5% of patients were admitted to non-ICU wards, with a mortality rate of 5.7%. Significant differences were observed in the distribution of hematological parameters between ICU-admitted and non-admitted patients. Neutrophil (OR: 23.96, 95% CI: 7.296-78.675) and white blood cell (WBC) count (OR: 36.677, 95% CI: 2.086-644.889) were the most significant predictors for ICU admission and survival, respectively. WBC and neutrophil counts exhibited high predictive value for ICU admission, while WBC, neutrophil, lymphocyte, and immature granulocyte (IG) counts were significant predictors of survival status among COVID-19 patients. These findings underscore the continued relevance of hematological markers in managing severe respiratory infections and improving critical care triage, with implications for current and future healthcare challenges.

A small molecule compound targeting hemagglutinin inhibits influenza A virus and exhibits broad-spectrum antiviral activity.

Influenza A virus (IAV) is a widespread pathogen that poses a significant threat to human health, causing pandemics with high mortality and pathogenicity. Given the emergence of increasingly drug-resistant strains of IAV, currently available antiviral drugs have been reported to be inadequate to meet clinical demands. Therefore, continuous exploration of safe, effective and broad-spectrum antiviral medications is urgently required. Here, we found that the small molecule compound J1 exhibited low toxicity both in vitro and in vivo. Moreover, J1 exhibits broad-spectrum antiviral activity against enveloped viruses, including IAV, respiratory syncytial virus (RSV), severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), human coronavirus OC43 (HCoV-OC43), herpes simplex virus type 1 (HSV-1) and HSV-2. In this study, we explored the inhibitory effects and mechanism of action of J1 on IAV in vivo and in vitro. The results showed that J1 inhibited infection by IAV strains, including H1N1, H7N9, H5N1 and H3N2, as well as by oseltamivir-resistant strains. Mechanistic studies have shown that J1 blocks IAV infection mainly through specific interactions with the influenza virus hemagglutinin HA2 subunit, thereby blocking membrane fusion. BALB/c mice were used to establish a model of acute lung injury (ALI) induced by IAV. Treatment with J1 increased survival rates and reduced viral titers, lung index and lung inflammatory damage in virus-infected mice. In conclusion, J1 possesses significant anti-IAV effects in vitro and in vivo, providing insights into the development of broad-spectrum antivirals against future pandemics.

DNA tweezer-assembled, regenerated nanosensor for one-step and sustainable detection of viral RNA and Hg2+

Transcription-polymerase chain reaction (RT-qPCR) is the golden standard to detect viral RNA. However, it suffers from several inherent defects such as high false-negative rates, time-consuming and expensive. To exploit better analytical methods for future global pandemics, it is vital to develop rapid, sustainable, and environmentally-friendly sensing methods. Here, a one-step, regenerated nanosensor assembled by DNA tweezers is developed for rapid and sustainable detection of viral RNA. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA is selected as model analyte. The DNA tweezer is designed with a central strand and two arm strands containing overhangs complementary to SARS-CoV-2 RNA. The SARS-CoV-2 RNA hybridizes with the two arm overhangs and strains the DNA tweezer to closed conformation, resulting in the close proximity of the donor and acceptor fluorophores. With the addition of an anti-strand complementary to the SARS-CoV-2 RNA, the closed DNA tweezer is relaxed to open conformation through a strand displacement process, leading to the separation of the dual fluorophores. Thus, the DNA tweezer is revived for fresh SARS-CoV-2 RNA. The proposed nanosensor can be regenerated for three cycles with the same performance. Moreover, the viral RNA can be detected within 30 min with a detection limit of 0.04 nM. By altering the sequences of the DNA tweezer, rapid, sensitive, and sustainable detection of Hg2+ is achieved. The proposed nanosensor provides a novel approach for rapid, flexible, and sustainable detection of viral RNA and Hg2+, exhibiting great potential for routine preliminary coronavirus disease tests, epidemic control, and environmental monitoring.

Canada's approach to SARS-CoV-2 sero-surveillance: Lessons learned for routine surveillance and future pandemics.

In Canada's federated healthcare system, 13 provincial and territorial jurisdictions have independent responsibility to collect data to inform health policies. During the COVID-19 pandemic (2020-2023), national and regional sero-surveys mostly drew upon existing infrastructure to quickly test specimens and collect data but required cross-jurisdiction coordination and communication. There were 4 national and 7 regional general population SARS-CoV-2 sero-surveys. Survey methodologies varied by participant selection approaches, assay choices, and reporting structures. We analyzed Canadian pandemic sero-surveillance initiatives to identify key learnings to inform future pandemic planning. Over a million samples were tested for SARS-CoV-2 antibodies from 2020 to 2023 but siloed in 11 distinct datasets. Most national sero-surveys had insufficient sample size to estimate regional prevalence; differences in methodology hampered cross-regional comparisons of regional sero-surveys. Only four sero-surveys included questionnaires. Sero-surveys were not directly comparable due to different assays, sampling methodologies, and time-frames. Linkage to health records occurred in three provinces only. Dried blood spots permitted sample collection in remote populations and during stay-at-home orders. To provide timely, high-quality information for public health decision-making, routine sero-surveillance systems must be adaptable, flexible, and scalable. National capability planning should include consortiums for assay design and validation, defined mechanisms to improve test capacity, base documents for data linkage and material transfer across jurisdictions, and mechanisms for real-time communication of data. Lessons learned will inform incorporation of a robust sero-survey program into routine surveillance with strategic sampling and capacity to adapt and scale rapidly as a part of a comprehensive national pandemic response plan.

Mental health among Hispanic college students during the COVID-19 pandemic: Concurrent and predictive effects of negative and positive COVID-19 changes

Objective: We generated items to assess COVID-19 changes among Hispanic college students and examined the concurrent and predictive effects of these changes vis-à-vis mental health. Participants: The sample consisted of 559 Hispanic first-year (69% women; age range 18–22; 88.1% U.S.-born; 84% Mexican/Mexican American) attending a public university in Texas. Methods: Students participated in a three-wave longitudinal online survey assessing stressors, COVID-19 changes, anxious and depressive symptoms, hope, and self-esteem. Results: Students experienced negative changes across six life domains as a result of the pandemic-related lockdowns: education; health; relationships; finances; social issues; death/loss. They also reported positive changes during the lockdowns. Negative changes were positively correlated with higher, and positive changes with lower, acculturative and perceived stress. Negative COVID-19 changes predicted lower mental health. Conclusions: Hispanic students experienced both negative and positive COVID-19 changes, which were related to their mental health. Results can guide research and decision-making during future pandemics.

Cross- and Context-Aware Attention Based Spatial-Temporal Graph Convolutional Networks for Human Mobility Prediction

The COVID-19 pandemic has dramatically transformed human mobility patterns. Therefore, human mobility prediction for the “new normal” is crucial to infrastructure redesign, emergency management, and urban planning post the pandemic. This paper aims to predict people’s number of visits to various locations in New York City using COVID and mobility data in the past two years. To quantitatively model the impact of COVID cases on human mobility patterns and predict mobility patterns across the pandemic period, this paper develops a model CCAAT-GCN ( C ross- and C ontext- A ttention based Spatial-Temporal G raph C onvolutional N etworks). The proposed model is validated using SafeGraph data in New York City from August 2020 to April 2022. A rich set of baselines are performed to demonstrate the performance of our proposed model. Results demonstrate the superior performance of our proposed method. Also, the attention matrix learned by our model exhibits a strong alignment with the COVID-19 situation and the points of interest within the geographic region. This alignment suggests that the model effectively captures the intricate relationships between COVID-19 case rates and human mobility patterns. The developed model and findings can offer insights into the mobility pattern prediction for future disruptive events and pandemics, so as to assist with emergency preparedness for planners, decision-makers and policymakers.

Intolerance of uncertainty and psychological flexibility as predictors of mental health from adolescence to old age

PurposeThe COVID-19 pandemic brought with it significant social, economic and health uncertainties. These were proposed to impact young people more compared to adults, leading adolescents to report more mental health problems during the pandemic. The current study examined whether differences in cognitive risk (tolerance of uncertainty) and protective (psychological flexibility) factors accounted for age-related differences in depression and anxiety.MethodsThese associations were investigated in the COVID-19 Risks Across the Lifespan (CORAL) cohort (N = 2280, 11–89 years).ResultsThe results showed that adolescents experienced greater intolerance of uncertainty and lower psychological flexibility compared to adults and older adults. Tolerance of uncertainty did not account for age-related differences in depression or anxiety. However, psychological flexibility conferred more protective advantage for anxiety in adults compared to adolescents.ConclusionThe observed age-related differences in risk and protective factors advance our understanding of developmental vulnerabilities to depression and anxiety. Implications for mental health interventions in the context of future pandemics are discussed.

Mental Health Hospitalizations in Canadian Children, Adolescents, and Young Adults Over the COVID-19 Pandemic

The COVID-19 pandemic resulted in multiple socially restrictive public health measures and reported negative mental health impacts in youths. Few studies have evaluated incidence rates by sex, region, and social determinants across an entire population. To estimate the incidence of hospitalizations for mental health conditions, stratified by sex, region, and social determinants, in children and adolescents (hereinafter referred to as youths) and young adults comparing the prepandemic and pandemic-prevalent periods. This Canadian population-based repeated ecological cross-sectional study used health administrative data, extending from April 1, 2016, to March 31, 2023. All youths and young adults from 6 to 20 years of age in each of the Canadian provinces and territories were included. Data were provided by the Canadian Institute for Health Information for all provinces except Quebec; the Institut National d'Excellence en Santé et en Services Sociaux provided aggregate data for Quebec. The COVID-19-prevalent period, defined as April 1, 2020, to March 31, 2023. The main outcome measures were the prepandemic and COVID-19-prevalent incidence rates of hospitalizations for anxiety, mood disorders, eating disorders, schizophrenia or psychosis, personality disorders, substance-related disorders, and self-harm. Secondary measures included hospitalization differences by sex, age group, and deprivation as well as emergency department visits for the same mental health conditions. Among Canadian youths and young adults during the study period, there were 218 101 hospitalizations for mental health conditions (ages 6 to 11 years: 5.8%, 12 to 17 years: 66.9%, and 18 to 20 years: 27.3%; 66.0% female). The rate of mental health hospitalizations decreased from 51.6 to 47.9 per 10 000 person-years between the prepandemic and COVID-19-prevalent years. However, the pandemic was associated with a rise in hospitalizations for anxiety (incidence rate ratio [IRR], 1.11; 95% CI, 1.08-1.14), personality disorders (IRR, 1.21; 95% CI, 1.16-1.25), suicide and self-harm (IRR, 1.10; 95% CI, 1.07-1.13), and eating disorders (IRR, 1.66; 95% CI, 1.60-1.73) in females and for eating disorders (IRR, 1.47; 95% CI, 1.31-1.67) in males. In both sexes, there was a decrease in hospitalizations for mood disorders (IRR, 0.84; 95% CI, 0.83-0.86), substance-related disorders (IRR, 0.83; 95% CI, 0.81-0.86), and other mental health disorders (IRR, 0.78; 95% CI, 0.76-0.79). This cross-sectional study of Canadian youths and young adults found a rise in anxiety, personality disorders, and suicidality in females and a rise in eating disorders in both sexes in the COVID-19-prevalent period. These results suggest that in future pandemics, policymakers should support youths and young adults who are particularly vulnerable to deterioration in mental health conditions during public health restrictions, including eating disorders, anxiety, and suicidality.

Impact of COVID-19 Vaccine Persuasion Strategies on Social Endorsement and Public Response on Chinese Social Media

ABSTRACT Persuading the public to get vaccinated against infectious diseases is critical and carries profound implications for preparing for future pandemics. This study examined whether and how persuasion strategies employed in pro-vaccine messages affect social endorsement and audience stance toward the COVID-19 vaccine expressed in comments on Chinese social media. Through manual coding and pre-trained BERT model, we analyzed 1,500 Weibo posts focused on COVID-19 vaccination persuasion and 238,201 associated comments. Results showed that medical experts succeeded in eliciting heightened social endorsement and receiving more pro-vaccine comments. Posts that employed negative emotional appeal were less likely to be liked or receive pro-vaccine comments. Besides, vaccine persuasion messages presented in a narrative format or emphasizing vaccine efficacy garnered significantly more likes but did not significantly receive more pro-vaccine comments. Discussing domestic issues or employing joy appeal received more pro-vaccine comments. These results offer valuable insights for health practitioners and communicators, highlighting more effective persuasion strategies for engaging citizens in vaccine-related discussions on social media. This study underscores the importance of leveraging persuasion tactics on social media to foster vaccination uptake and better prepare us for handling future pandemics.

Appraisal of policy measures at the beginning of a pandemic: Empirical evidence from the first four months and 12 months of the COVID-19 pandemic

PurposeThe rapid spread of the COVID-19 pandemic upended societies across the world, with billions forced into lockdowns. As countries contemplated instating and rolling back lockdown measures, and considered the impact of pandemic fatigue on policy measures, and furthermore to prepare for the improved management of future pandemics, this study examines the effectiveness of policy measures in limiting the spread of infections and fatalities.Design/methodology/approachThe methodological approach in the study centres on a fixed effects panel regression analysis and employs the COVID-19 Government Response Stringency Index, which comprises eight containment measures and three health campaigns, with progressive degrees of stringency, in order to investigate the efficacy of government policies.FindingsFindings suggest that some government policies were effective at reducing implicit mortality rates, infection cases and fatalities during the first four months of the COVID-19 pandemic. Solid stringency measures to reduce mortality rates include public gathering restrictions on more than 100 attendees, and international travel limits for developed countries and islands. Fatalities can further be reduced through the closing of public transport, whereas infection cases also experience benefits from public information campaigns. Comparable results are observed in a robustness test across 12 months.Originality/valueSome non-pharmaceutical policies are shown to be more effective than others at reducing the spread of infections, fatalities and mortality rates, and support policymakers to manage future pandemics more effectively.

Survival, mortality and epidemic risk status of COVID-19: a population-based Study in Golestan province, Iran

BackgroundAppreciating the various dimensions of the coronavirus disease 2019 (COVID-19) pandemic can improve health systems and prepare them to deal better with future pandemics and public health events. This study was conducted to investigate the association between the survival of hospitalized patients with COVID-19 and the epidemic risk stratification of the disease in Golestan province, Iran.MethodsIn this study, all patients with COVID-19 who were hospitalized in the hospitals of Golestan province of Iran from February 20, 2020, to December 19, 2022, and were registered in the Medical Care Monitoring Center (MCMC) system (85,885 individuals) were examined.The community's epidemic risk status (ERS) was determined based on the daily incidence statistics of COVID-19. The survival distribution and compare Survival in different subgroups was investigated using Kaplan–Meier and log-rank test and association between the survival and ERS by multiple Cox regression modeling.ResultsOut of 68,983 individuals whose data were correctly recorded, the mean age was 49 (SD = 23.98) years, and 52.8% were women. In total, 11.1% eventually died. The length of hospital stay was varying significantly with age, gender, ERS, underlying diseases, and COVID-19 severity (P < 0.001 for all). The adjusted hazard ratio of death for the ERS at medium, high, and very high-risk status compared to the low-risk status increased by 19%, 26%, and 56%, respectively (P < 0.001 for all).ConclusionsEnhancing preparedness, facilitating rapid rises in hospital capacities, and developing backup healthcare capacities can prevent excessive hospital referrals during health crises and further deaths.

Unveiling the detrimental vicious cycle linking skeletal muscle and COVID-19: A systematic review and meta-analysis.

Skeletal muscle catabolism supports multiple organs and systems during severe trauma and infection, but its role in COVID-19 remains unclear. This study investigates the interactions between skeletal muscle and COVID-19. The PubMed, EMbase, and The Cochrane Library databases were systematically searched from January 2020 to August 2023 for cohort studies focusing on the impact of skeletal muscle on COVID-19 prevalence and outcomes, and longitudinal studies examining skeletal muscle changes caused by COVID-19. Skeletal muscle quantity (SMQN) and quality (SMQL) were assessed separately. The random-effect model was predominantly utilized for statistical analysis. Seventy studies with moderate to high quality were included. Low SMQN/SMQL was associated with an increased risk of COVID-19 infection (OR=1.62, p<0.001). Both the low SMQN and SMQL predicted COVID-19-related mortality (OR=1.53, p=0.016; OR=2.18, p=0.001, respectively). Mortality risk decreased with increasing SMQN (OR=0.979, p=0.009) and SMQL (OR=0.972, p=0.034). Low SMQN and SMQL were also linked to the need for intensive care unit/mechanical ventilation, increased COVID-19 severity, and longer hospital stays. Significant skeletal muscle wasting, characterized by reduced volume and strength, was observed during COVID-19 infection and the pandemic. This study reveals a detrimental vicious circle between skeletal muscle and COVID-19. Effective management of skeletal muscle could be beneficial for treating COVID-19 infections and addressing the broader pandemic. These findings have important implications for the management of future virus pandemics. PROSPERO CRD42023395476.

Learning from the COVID-19 Pandemic: Next-generation universal vaccines and immunotherapeutic research

Learning from the COVID-19 Pandemic: Next-generation universal vaccines and immunotherapeutic research With the COVID-19 pandemic behind us, we need to focus on universal vaccines and/or immunotherapeutic strategies and technologies to tackle ongoing endemic infections with SARS-CoV2, influenza, and RSV and prepare for any future pandemics, says Dr Babita Agrawal. In the 21st century, we have witnessed the emergence of respiratory infections with pandemic potential, like corona and influenza viruses, on multiple occasions. Due to the global dissemination of one such coronavirus, SARS-CoV2 (severe acute respiratory syndrome-coronavirus type-2), the World Health Organization (WHO) declared a worldwide pandemic in March 2020. The global public health emergency was declared over in May 2023 by the WHO, but infections with variants of SARS-CoV2 continue to evolve and cause infections worldwide. (1) Besides public health measures, developing, approving, and implementing vaccines against SARS-CoV2 have helped mitigate and end the pandemic. However, the existing vaccines against SARS-CoV2 are not preventive, do not induce mucosal immunity, induce only short-term protection and are ineffective against emerging variants, thereby requiring regular updated boosters.

Predictors of COVID-Related stress in a community sample in Turkey: a cross-sectional study

ABSTRACT The distinctive mental health features associated with COVID-19 have gained importance as the psychological effects of the pandemic on the community become more visible. This study aims to assess the COVID-related stress status and associated factors in the community sample of Turkey. The sample of this cross-sectional study is composed of 2.065 people between the ages of 18–90. Data were collected through an online survey prepared by Google.docs between October-December, 2020. Mild to moderate stress was found in the community with the most common symptoms of the fear of contamination and danger. Some variables, such as being female and the severity of COVID-19 illness, were associated with higher COVID-related stress. Vulnerable groups associated with high stress should be monitored during the pandemic. The findings of this study will guide the practices of professionals working in the field of public health, healthcare, or mental health in possible future pandemics.

Temporal dynamics of socioeconomic inequalities in depressive and anxiety symptoms during the COVID-19 pandemic: a scoping review.

The existence of socioeconomic inequalities in the prevalence of symptoms of depression and anxiety is widely acknowledged, and individuals from lower socioeconomic backgrounds tend to exhibit higher rates of symptoms. However, the direction in which the COVID-19 pandemic has influenced these disparities remains uncertain. We therefore aimed to systematically outline the available evidence on the temporal dynamics of socioeconomic inequalities in symptoms related to depression and anxiety during the COVID-19 pandemic across high-income countries. A scoping review was conducted by searching the databases Embase, Scopus and PsycINFO. According to pre-defined eligibility criteria, two reviewers independently screened titles and abstracts as well as full texts of the compiled records. Data from the included studies were extracted using a standardised data-extraction form and analysed numerically and narratively. The scoping review followed the PRISMA-ScR guidelines. A total of 49 studies comprising 149 analyses of socioeconomic indicators in relation to symptoms of depression and anxiety were included. Despite heterogeneous study designs and results, there was a tendency of increasing (40.9%; n = 61) or persistent (38.2%; n = 57) inequality trends to the detriment of those in socially more disadvantaged positions. Increasing inequalities were most pronounced when income was used as a socioeconomic indicator. Groups with lower socioeconomic status appeared most vulnerable in the initial phase of the COVID-19 pandemic. Throughout the pandemic, dynamics were diverse, with persistent trends most frequently reported. Overall, to the detriment of those with lower socioeconomic status, mental-health inequalities persisted or increased in most analyses. Continually monitoring socioeconomic inequalities over time is crucial, since this makes it possible to adapt prevention and intervention strategies to specific pandemic phases. Interventions targeting job security, income security and educational attainment could reduce mental-health inequalities. The results can contribute to preparedness plans for future pandemics and crises.

A review of big data analytics models for assessing non-pharmaceutical interventions for COVID-19 pandemic management

Before vaccine development during the COVID-19 pandemic, Non-Pharmaceutical Interventions (NPIs) were the only solutions to mitigate COVID-19 infections. Governments continued to use them even after starting vaccine administration. In this research, we review different big data analytics models that assess and optimize the effectiveness of NPIs. These models are categorized into three big data analytics groups: descriptive, which measures the infection rate changes caused by NPIs; predictive, which predicts the future of the pandemic by implementing several NPIs; and data-driven prescriptive, which suggests optimal control policies. We further analyze each method's basic assumptions, limitations, and applicability during different pandemic phases and under different scenarios. This review of COVID-19 NPI evaluation methods will be beneficial for decision-makers to know which model to select for policy-making in possible future pandemics, which are more likely recently due to globalization. Finally, we suggest some future research directions.