Outbreak Of COVID-19 Pandemic Research Articles

A comparative study of the growth indicators of infants born before and during the Covid-19 pandemic

IntroductionGrowth disorders pose significant mental and physical health challenges with long-term complications for children. As monitoring children's growth is of paramount importance, in the present study attempts are made to compare growth indicators of infants from birth to 12 months before and during the outbreak of COVID-19 pandemic. Material and methodThe present descriptive-analytical study was conducted using cluster sampling method in 10 comprehensive healthcare centers and on 200 infants in southwest of Iran during 2023. The infants’ health records and growth chart before and during the outbreak of COVID-19 pandemic served as data collection instruments. The collected data were analyzed using SPSS 21 software and descriptive and analytical statistics. ResultEconomic hardship, job loss, maternal disease and neonatal acquired disease were found to be significantly higher during the pandemic outbreak compared to the pre-pandemic time. the average weight and BMI of the infants in both groups showed no significant difference from birth to two months old, but the difference was found to be significantly higher from 4 months to 1-year-old among infants born during the pandemic (P-value<0.05). Result this study showed that during the pandemic trend of The age of word articulation by infants was increasing (P-value=0.022) and at this time 6 cases of missed vaccination were observed. ConclusionThe results indicate that the COVID-19 pandemic can affect the growth and development of infants, and may, in some cases, disrupt the growth and routine vaccination schedule during infancy and breastfeeding, which should be prevented by proper parental training.

Global Emerging Infections Surveillance Program Contributions to Pandemic Preparedness and Response.

Since its establishment in 1997, the US Department of Defense (DoD) Global Emerging Infections Surveillance (GEIS) program has provided support for infectious disease pandemic preparedness and response. The GEIS program has shown the value of having a central hub responsible for coordinating a global network of DoD laboratories that conduct surveillance for militarily relevant infectious disease threats. The program has supported the establishment and maintenance of capabilities for collecting, characterizing, and reporting on major infectious disease events, including the COVID-19 pandemic and mpox outbreak. The GEIS program enables the US government to mitigate infectious disease threats to DoD mission readiness and to effectively respond to pathogens worldwide. Continued investment in maintaining the GEIS program and its network is critical for timely detection and response to future emerging infectious disease threats in various populations within locations where gaps in US government or host-nation surveillance might exist.

Uncertainties of Economic Policy and Government Management Stability Played Important Roles in Increasing Suicides in Japan from 2009 to 2023.

Standardized suicide mortality rates per 100,000 (SMRs) in Japan consistently decreased from 2009 to 2019 but increased from 2020. The causes of these temporal SMR fluctuations remain to be clarified. Therefore, this study was conducted to identify the causalities underlying the recently transformed fluctuations of suicide mortality in Japan. Monthly suicide numbers disaggregated by sex and social standing, and political uncertainty indices, such as economic policy uncertainty (EPU) and government management instability (AENROP), were obtained from Japanese government databases. Interrupted time-series analysis was performed to analyze temporal fluctuations of SMRs disaggregated by sex/social standing associated with the three General Principles of Suicide Prevention Policy (GPSPP) periods and the COVID-19 pandemic. Panel data and vector autoregressive analyses were conducted to investigate causalities from political uncertainties to SMRs. During the first and second GPSPPs (2009-2017), all SMRs disaggregated by sex and social standing decreased, whereas those of unemployed females did not change. During the third GPSPP (2017-2022), decreasing trends in all SMRs were attenuated compared to previous periods. All female SMRs, except unemployed females, showed sharp increases synchronized with the pandemic outbreak. No male SMRs showed sharply increasing at the pandemic outbreak. SMRs of unemployed males/females drastically increased in the later periods of the pandemic, while SMRs of employed and multiple-person/single-person household males did not increase during the pandemic. SMR of unemployed males was positively related to AENROP but not EPU. Other male SMRs were positively related to EPU/AENROP. On the contrary, not all female SMRs were related to EPU/AENROP. Increasing AENROP generally contributed to increasing male SMRs throughout the observation period; however, susceptibility to AENROP and/or political information might have unexpectedly contributed to suppressing the sharply increasing male SMRs induced by large-scale social shocks (the COVID-19 pandemic outbreak) in Japan.

Mpox in East Africa: Learning from COVID-19 and Ebola to Strengthen Public Health Responses.

The Africa Centers for Disease Control and Prevention declared mpox a Public Health Emergency of Continental Security (PHECS) in Africa. African public health systems have moved to mobilize a response against a backdrop of inherent significant challenges. With this commentary, we discuss how lessons from past public health emergencies, particularly COVID-19 and Ebola outbreaks, have prepared the region for improved disease surveillance, rapid response strategies, and effective public health communication and how these lessons can be applied to the mpox response, emphasizing the importance of strong healthcare infrastructure, effective data sharing, community engagement, targeted interventions, and robust contact tracing. Additionally, addressing misinformation and building public trust are crucial for controlling the spread of any disease. By leveraging these strategies, African countries can enhance their response to mpox. This includes improving diagnostic capabilities, strengthening cross-border collaborations, and prioritizing vaccination campaigns where needed. Ultimately, by applying the hard-earned lessons from the COVID-19 pandemic and Ebola outbreak, the East Africa region can better address the challenges posed by mpox and safeguard public health.

Erythema Multiforme and Epidermal Necrolysis Following COVID-19 Vaccines: A Systematic Review.

The outbreak of COVID-19 pandemic has raised urgent vaccine development to prevent viral transmission. Cutaneous adverse events such as erythema multiforme (EM), Stevens-Johnson syndrome (SJS), and toxic epidermal necrolysis (TEN) have been observed following COVID-19 vaccination. In this systematic review, we aimed to investigate the clinical features and outcomes of EM/SJS/TEN following COVID-19 vaccination. A comprehensive literature search was conducted in PubMed, Embase, Web of Science, and Cochrane databases up to July 3, 2022. We included studies reporting patients who developed EM, SJS, or TEN following COVID-19 vaccination. A total of 47 studies involving 90 patients with EM and 16 patients with SJS/TEN were reviewed and outlined. EM predominantly occurred after the messenger ribonucleic acid vaccines (70.4%), mostly after the first (47.5%) and second doses (42.4%), with delayed onsets ranging from 1 day to 30 days. SJS/TEN were observed following either the first (55.6%)- or second-dose (33.3%) vaccination, with onset times ranging from 6 hours to 14 weeks. Three EM cases and 1 SJS case showed recurrence upon reexposure to the same vaccines. No mortality was reported. Most patients exhibited improvement or resolution after treatment, with resolution times ranging from 6 days to 8 weeks. In conclusion, EM and epidermal necrolysis, including SJS and TEN, have emerged as potential cutaneous adverse events following COVID-19 vaccine administration. Further research is warranted to elucidate the pathogenesis and casual relationship between COVID-19 vaccines and EM/SJS/TEN.

Evaluating Airline Passengers’ Satisfaction during the COVID-19 Pandemic: A Case Study of AirAsia Services through Sentiment Analysis and Topic Modelling

AirAsia has emerged as a dominant force among prominent low-cost airlines in recent years. However, the COVID-19 pandemic outbreak has severely impacted airline services, including AirAsia. There is a strong need for airline services to monitor customer experience and satisfaction from online customer reviews on the website to keep pace with changing customer perceptions toward their service quality. A growing number of travelers choose to express their experiences and emotions on online customer review platforms, resulting in substantial online airline service evaluations. The research analyzes 796 online customer reviews from Skytrax, a well-known online airline review website. The information hidden in customer-generated reviews is analyzed with the text mining technique, including topic modeling and sentiment analysis. The research uses the Latent Dirichlet Allocation (LDA) model for topic analysis and the Valence Aware Dictionary for Sentiment Reasoning (VADER) model for sentiment analysis. The sentiment ratio for AirAsia’s online reviews is approximately 59% positive and 41% negative. Only four reviews are neutral. The findings indicate that the online review of AirAsia has a greater proportion of positive sentiments than negative sentiments. In addition, the topic modeling shows hidden topics with the top high-probability keywords concerned with interior and seat, baggage, online service, staff service, flight schedule, and refund. The research demonstrates using sentiment analysis and topic modeling on customer review data as a more thorough alternative to survey-based models for researching airline service. The research contributes to the methodological advancements in text mining analysis and expands the current knowledge of customer review data.

Repurposed Drugs during the Outbreak of Pandemic COVID-19: A Mini-Review on Their Molecular Structures and Hit-and-Trial Results.

One of the most significant threats to global public health in the 21st century is the novel coronavirus disease (COVID-19) caused by SARS-CoV-2. It rapidly turned into a global pandemic after it was identified in late 2019, and the World Health Organization announced the end of the pandemic on May 5, 2023. Current strategies for managing this disease include vaccination and repurposing antimalarial and antibiotic medications to alleviate symptoms like fever and throat pain, which are associated with acute respiratory distress syndrome (ARDS). Antiviral drugs such as chloroquine, hydroxychloroquine, azithromycin, remdesivir, and favipiravir have been repurposed for the treatment of COVID-19. They were previously recommended for treating SARS-CoV and MERS-CoV. However, the inefficacy and adverse side effects of these repurposed drugs led to a decrease in their widespread use in treating COVID-19 patients. The lack of approved drugs for combating this coronavirus and its unpredictable variants remains a significant challenge.

Nationwide Trends in Hospitalizations for Atrial Fibrillation and Flutter in the United States before and during the Outbreak of the COVID-19 Pandemic.

Background/Objectives: Atrial fibrillation (AF) and flutter (AFL) are the most common cardiac arrhythmias worldwide. Cardiovascular complications are a common manifestation of acute and post-acute COVID-19 infection. We aimed to analyze the nationwide trends in clinical characteristics and outcomes of patients hospitalized for AF/AFL before and during the COVID-19 outbreak in the U.S. Methods: This study is a retrospective analysis of patients, aged 18 and older, hospitalized for AF/AFL in the U.S. between 2016 and 2020. We drew data from the National Inpatient Sample (NIS) database. Baseline sociodemographic and clinical data, as well as outcomes including stroke, acute coronary syndrome (ACS), and mortality, were analyzed. Multivariable analysis was performed to identify independent associations between the different clinical and demographic characteristics and the composite endpoint of Mortality/ACS/Stroke. Results: An estimated total of 2,163,699 hospitalizations for AF/AFL were identified. The hospitalization volume between 2016 and 2019 was stable, averaging 465,176 a year, followed by a significant drop to 302,995 in 2020. Patients' median age was 72 years (IQR 62-80), 50.9% were male, and 81.5% were white. The composite endpoint steadily increased from 6.5% in 2016 to 11.8% in 2020 (Ptrend < 0.001). In a multivariable regression analysis, age > 75 (OR: 1.35; 95% CI 1.304-1.399, p < 0.001), ischemic heart disease (OR: 1.466; 95% CI: 1.451-1.481; p < 0.001), and chronic kidney disease (OR: 1.635; 95% CI: 1.616-1.653; p < 0.001) were associated with the composite endpoint. COVID-19 was associated with the composite endpoint outcome in the year 2020 (OR: 1.147; 95% CI: 1.037-1.265; p = 0.007). Conclusions: Hospitalization for AF/AFL dropped significantly during the first year of the COVID-19 pandemic outbreak, possibly due to patients' avoidance of hospital visits. The composite endpoint of Mortality/ACS/Stroke uptrended significantly during the study period. COVID-19 was shown to be independently associated with the adverse composite outcome Mortality/ACS/Stroke.

FORECASTING NUMBER OF INTERNATIONAL TOURIST ARRIVALS USING MULTI INPUT INTERVENTION ARIMA MODEL

In 2020, the Covid-19 pandemic caused a very significant impact resulting in the drastic decline in the number of international tourist visits. As the Covid-19 pandemic ends, the government reopen international flight to Indonesia in early 2022 to remark the revival of the tourism industry. To determine how big the impact of the Covid-19 pandemic as well as the recovery process on international tourist visits through Soekarno-Hatta, Ngurah-Rai, and Kualanamu airports in the coming period, forecasting is needed. The forecasting method utilized in this study is multi-input intervention analysis. The first input is caused by the outbreak of Covid-19 pandemic, while the second input is due to the international flight reopening. The type of intervention variable chosen is a step function because both inputs give permanent effect to the international tourist arrivals. The data used in this study are monthly international tourist arrivals based on the entrances to Soekarno-Hatta, Ngurah-Rai, and Kualanamu International Airports from January 2008 to September 2023, taken from the Central Bureau of Statistics website. Based on the results, it was found that the number of international tourist arrivals entering Soekarno-Hatta airport can be modelled using SARIMA (0,1,1)(0,1,0)12 with (b=2, s=1, r=0) and (b=2, s=[3], r=0) for first and second input of intervention variable, respectively. Furthermore, the number of international tourist visits through Ngurah-Rai airport was more appropriate to be modelled using SARIMA (1,1,1)(0,1,1)12 with intervention inputs (b=1, s=[2], r=0) and (b=4, s=0, r=1). In Kualanamu airport, the first intervention order is equal to that in Ngurah-Rai airport, with (b=3, s=[3], r=0) for second intervention input and SARIMA (0,1,1)(1,1,1)12 for pre-intervention data. The forecast results show that the number of international tourist arrivals entering Soekarno-Hatta, Ngurah-Rai, and Kualanamu international airports are already recovered to pre-pandemic conditions at a quick pace

The nexus between board audit committee attributes and financial performance of firms in Africa

This research aims to study the connection between the features of board audit committee of a firm and its financial performance in Africa, by looking at the board audit committees’ characteristics of publicly traded companies in the four (4) biggest African financial markets. This research conducted an empirical analysis of the committee features in the years following the global financial crisis and before the COVID-19 pandemic outbreak. The data covered the period between 2013 and 2019. We analyzed the data using correlation analysis, GLS (Fixed and Random Effect Models), and GMM. We used features of the committee as explanatory variables. These include an independent outside director as the chairperson of the committee, whether the committee guards the integrity of the financial reporting of a firm, whether the committee regularly meets and hears the recommendations and complaints of the firm’s external auditor, and whether the committee effectively monitors the management of the firm. Furthermore, for the dependent variable; ROE and ROA were utilized as the metrics of the financial performance of a firm. The results exhibit positive and significant relations between the board audit committee features such as; effective monitoring of management, guarding the integrity of financial reporting, an independent director as chairperson of the committee, regularly meeting and hearing the recommendations and complaints of the external auditor, and the firm’s financial performance measures. The findings are useful to corporate governance regulators who are seeking to improve corporate governance guidelines and minimize the corporate insolvency of firms in Africa.

Volatility spillover and dynamic correlation between Islamic, conventional, cryptocurrency and precious metal markets during the immediate outbreak of COVID-19 pandemic

PurposeThis paper aims to investigate the immediate effect of the outbreak of the COVID-19 pandemic by investigating volatility transmission and dynamic correlation between stock (conventional and Islamic) markets, bitcoin and major commodities such as gold, oil and silver at different investment horizons before and after 161 trading days of the outbreak of the COVID-19 pandemic.Design/methodology/approachThe MGARCH-DCC and maximum overlap discrete wavelet transform -based cross-correlation were used in the estimation of the volatility spillover and continuous wavelet transform in the estimation of the time-varying volatility and correlation between the assets at different investment horizons.FindingsThe authors observed a sudden correlation breakdown following the COVID-19 shock. Oil (Bitcoin) was a major volatility transmitter before (during) COVID-19. Digital gold (Bitcoin), gold and silver became highly correlated during COVID-19. The highest co-movement between the assets was observed at medium and long-term investment horizons.Practical implicationsThe study findings have a financial implication for day traders, investors and policymakers in the understanding of volatility transmission and intercorrelation in a bid to actively manage stylized and well-diversified asset portfolios.Originality/valueThis study is unique for its employment in estimating the time-varying conditional volatility of the investable assets and cross-correlations between them at different investment horizons, particularly before and after COVID-19 outbreak.

ONLINE PERSONA OF VTUBER AYUNDA RISU CH: SOCIOLINGUISTIC STUDY

With the pandemic COVID-19 outbreak throughout the world, the number of social media users multiplied by a massive number. YouTube streaming platforms becomes a place where people spend most of their time online. The trend called Virtual YouTubers becomes popular during the pandemic. One of the prominent factors of VTuber was their persona. VTubers Ayunda Risu becomes the subject of this research to give insight into how VTuber can manifest their persona to attract or retain their audience. By following the guidance of the qualitative method, this article focused on analyzing the live streams done by Ayunda Risu. Combining the method of qualitative study simultaneously with the author's experience in VTuber entertainment, this article creates a conclusion corresponding to how VTubers manifest their persona to attract and retain their audience. The study concludes that persona manifests as a result of the audiences preference. However, VTubers' inner personality also becomes the essential element to manifest their persona and online build personal branding, which as a result can gain or retain an audience.

Perinatal outcomes in newborns of mothers with gestational diabetes – a retrospective analysis

Introduction and objective: Gestational diabetes mellitus (GDM), in case of inadequate glycaemic control, is associated with an increased risk of maternal and neonatal complications. The aim of this study was to evaluate data concerning outcomes of neonates born to mothers with GDM, treated with only diet (GDM G1) compared to diet and insulin therapy (GDM G2). Special consideration was given to data concerning outcomes of neonates born after the COVID-19 pandemic outbreak in 2020. Materials and methods: Medical records were analysed. The data comprised records of newborns born at term or near term in the years 2017–2021. The statistical analysis was performed, with the significance level set at α = 0.05. Results: A total of 646 medical records were analysed. The study groups differed significantly (p &lt; 0.05) in the length of hospitalisation, incidence of cardiological abnormalities, and method of feeding during hospitalisation. There were no differences (p &gt; 0.05) between the groups in the results concerning neonatal anthropometric measurements, general condition after birth, or other perinatal outcomes. In 2020, significantly more (p &lt; 0.05) neonates required support in their adaptation period. These neonates were more often (p &lt; 0.05) diagnosed with birth defects and other complications. Conclusions: The level of maternal glycaemic control, appropriate medical care, and thus effectiveness of maternal treatment are important factors influencing neonatal outcomes and breastfeeding rates.

Collaborative Virtual Environments (CVEs) in the Preparation of Pre-service Mathematics Teachers

In recent times, teacher preparation programmes have faced significant challenges as many universities transitioned to fully online or hybrid instructional models as a result of the COVID-19 pandemic outbreak. These sudden shifts drastically decreased classroom teaching opportunities, which was a cornerstone of teacher preparation programmes to help preservice teachers learn how to teach effectively. Therefore, considering the importance of visualizations in mathematics education for facilitating teaching, motivating students, and satisfying their desire to comprehend abstract mathematical concepts, this study investigates the barriers to utilizing, and the effective ways of integrating Collaborative Virtual Environments (CVEs) in the preparation of pre-service mathematics teachers. Underpinned by an interpretivist paradigm, the study employed a qualitative research approach and a case study design. Data were collected from twenty-five pre-service mathematics teachers, two mathematics teacher educators, and one department head. For this study, data collected were analysed using thematic analysis, and data trustworthiness was ensured through triangulation of the unit of analysis. Research findings revealed that the use of CVEs in teacher education programs is hampered by several factors, which include resistance to change, technological limits, costs and time constraints, assessment difficulties, equality and access issues, and a lack of training and support. Furthermore, the findings highlighted that for CVEs to be effective in teacher preparation programmes, mathematics educators should encourage the simulation of classroom scenarios, facilitate group discussions and cooperative learning and participate in virtual professional development opportunities.

Impact of pre-existing depression and food insecurity on the trajectory of depressive symptomatology during the COVID-19 pandemic outbreak in South Africa: A panel analysis of nationally representative South African data

We investigated the trajectory of depressive symptoms (“depression”) from the start of the COVID-19 pandemic in South Africa (March 2020) until 2021, between individuals with and without pre-pandemic depression, specifically regarding the role of food security. Our investigation used publicly available panel data (N = 6,930) from the South African National Income Dynamics Study Coronavirus Rapid Mobile Survey (SA-NIDS-CRAM from 2020–2021) on those who had also participated in the pre-pandemic South African National Income Dynamics Study (SA-NIDS, 2017) depression interview. We investigated trends in depressive symptomatology (based on a 2-item Patient Health Questionnaire) at SA-NIDS-CRAM Wave 2 (July 2020), Wave 3 (February 2021) and Wave 5 (May 2021). Generalized estimating equations (GEE) with post-estimation linear combinations of estimators were fitted to investigate the roles of pre-pandemic depression (based on 2017 SA-NIDS data) and food insecurity during the pandemic on depressive symptomatology. During the pandemic, the highest levels of depression were observed consistently among those with pre-pandemic depression and food insecurity; and were lowest among those without pre-pandemic depression and food security. Depressive symptomatology rose in nearly equal magnitude during the early phases of the pandemic in two groups: those without pre-pandemic depression but food insecure during the pandemic; as well as those with pre-pandemic depression but food secure during the pandemic. However, this dynamic changed later in the pandemic, when higher depressive symptomatology was observed in the group with both pre-pandemic depression and food insecurity, widening the gap between them from Wave 3 (adj β = 0.63, p < 0.01) to Wave 5 (adj β = 0.79, p < 0.01). Our results highlight the importance of addressing both population mental health and food insecurity, particularly at the early stages of a crisis/disaster. As we showed that mental health impact is linked to food insecurity during a pandemic, strengthening social protection measures, especially around food and nutrition, would help build resilience to crises in the long term.

COVID-19, Christian Women and Mental Health: An African Interventionist Response

Mental health is posited as a vital constituent of health and well-being. Good mental health is represented by a balance between the mind, body, spirit and context which should all be in tangent. Globally, it has been noted that mental disorders rank among the top ten leading causes of health encumbrance. This dire situation has been compounded by the novel COVID-19 pandemic outbreak which exacerbated the global number of mental disorders, with women carrying a higher risk due to their role as primary caregivers. Using a phenomenological study and drawing from Christian women in Harare, this study sought to explore the common risk factors that expose women to the possibility of developing mental health disorders. Research findings indicated varied stressors including gender-based roles, intimate partner violence, lower socio-economic status and household financial instability due to the COVID-19 induced economic recession during the COVID-19 lockdown period as triggers of mental health disorders. Religio-cultural factors, stigma and discrimination associated with mental health disorders were equally identified as inhibitors to women’s mental healthcare needs. Study participants also cited heightened reverence to God as well as the use of indigenous practices as coping mechanisms. Such a scenario brought to the fore a practice of religious syncretism among the research participants. The study therefore recommends gender-sensitive as well as culturally-sensitive mental health coping mechanisms and practices to mitigate the challenge of mental disorders, especially among women.

Implementation of CNN of Mobile-based COVID-19 Chest X-Ray Images

The COVID-19 pandemic outbreak is the most significant event from 2019 until 2021. A medical examination of radiological images is carried out to check the condition of the patient's lungs. The limitations of this examination need alternative computer-assisted applications for patient CXR. This research aims to implement a back-end and front-end-based Convolutional Neural Network (CNN) model. Its advantage is that it can detect CXR images in real-time and non-real-time using multi-classification, namely normal, pneumonia, and COVID-19. The CNN model carries out the process of convolutional feature extraction and multi-layer perceptron classification at the back-end stage. In contrast, it uses an Android mobile-based application at the front-end stage. The research results show that the non-real-time condition has an accuracy of 98%, while the real-time is 95% lower. This research produces model and application performance that is flexible for user needs. The results can be recommended for developing applications for more comprehensive users.

Analysis of Impacts and Challenges of Online Learning During the Covid-19 Pandemic: A Case Study at SMA Negeri 2 Rantau Selatan

The COVID-19 pandemic outbreak in 2019 significantly impacted various aspects of societal life, particularly in education. The shift to online learning, necessitated by the pandemic, posed numerous challenges for teachers and students at SMA Negeri 2 Rantau Selatan. This study aims to comprehensively understand these difficulties faced by 11th-grade teachers during online instruction. Employing a qualitative descriptive approach, the findings reveal several challenges: difficulties in delivering the curriculum, evaluating students' understanding, and creating engaging online learning environments. Quantitatively, 75% of teachers reported significant challenges in curriculum delivery, 60% found it difficult to assess students' comprehension, and 70% struggled with maintaining student engagement. These findings suggest a need for more active and creative teaching methods, supported by adequate facilities from the government. The implications of these findings highlight the necessity for improved educational practices and policy recommendations to better support online learning.

A Bayesian Survival Analysis on Long COVID and non Long COVID patients: A Cohort Study Using National COVID Cohort Collaborative (N3C) Data.

Since the outbreak of COVID-19 pandemic in 2020, numerous researches and studies have focused on the long-term effects of COVID infection. The Centers for Disease Control (CDC) implemented an additional code into the International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) for reporting 'Post COVID-19 condition, unspecified (U09.9)' effective on October 1st 2021, representing that Long COVID is a real illness with potential chronic conditions. The National COVID Cohort Collaborative (N3C) provides researchers with abundant electronic health records (EHR) data by aggregating and harmonizing EHR data across different clinical organizations in the United States, making it convenient to build up a survival analysis on Long COVID patients and non Long COVID patients among large amounts of COVID positive patients.

The gap between parental knowledge and children practice of myopia control and challenge under COVID-19: a web-based survey in China.

To evaluate parental knowledge of myopia control, investigate its association with children's practice and refractive status, and explore their change under the outbreak of COVID-19 pandemic. In this web-based survey, a self-administered questionnaire was made online available during the COVID-19 outbreak between February 1th, 2022 and August 31th, 2022 in China. Participants were recruited via social media by convenience and snowball sampling. Parents of both sexes whose children aged between 3 and 18 were eligible. The overall questionnaire was composed of four categories: demographic information, parental knowledge of myopia, children's myopia-related behaviors and their change after the COVID-19 pandemic, and children's refractive status. SPSS version 18.0 was applied to perform the statistics analysis and p < 0.05 was considered to be statistically significant. A total of 423 eligible families were included in our online survey. The average age of children was 11.37 ± 2.83y (male 46.1%; female 53.9%), with a myopia incidence of 83.9% (355/423). Both children's age (OR = -0.6; 95%CI = -1.12 to -0.07; p = 0.026) and family income (OR = 2.60; 95%CI = 1.13 to 4.07; p = 0.001) had independently significant impacts on parental knowledge. Unexpectedly, parental knowledge was negatively correlated with children's onset age of myopia (p = 0.002, r = -0.165) and positively correlated with spectacles wearing (p = 0.014, r = 0.131), and no correlation was found between parental knowledge and the occurrence of children myopia, current diopter, annual myopia progression and the diopter of the first glasses (all p > 0.05). We found discordance phenomenon between parents' knowledge and children's behaviors, with parental knowledge being irrelevant to children's sleeping time (p = 0.159, r = 0.069), the frequency of lying reading (p = 0.462, r = -0.036) and keeping nutrition diet (p = 0.142, r = 0.072), and positively correlated with daily homework time (p = 0.012, r = 0.123). After the outbreak of COVID-19, 77.8% (329/423) of parents admitted that their children's daily routine had been changed, with children spending more time on sleeping (p < 0.001) and electronic products (p < 0.001), and taking less time to do outdoor activities (p < 0.001). The ideal interaction mode that establishing positive impact between parental knowledge and children practice has not been reached in China, which might be the result of insufficient parents' cognition and discordance phenomenon between parental knowledge and children's behaviors. The pandemic of COVID-19 has obviously changed children's daily routine. More efforts should be made to narrow the gap between knowledge and behaviors of myopia control, and stay alert to the potential increased risk of myopia during COVID-19.