Monitoramento das Produções

by Eline Mennis, Michelle Hobus, Maria van den Muijsenbergh, Tessa van Loenen
Introduction People who are homeless might be more at risk for getting infected by the SARS-COV-2 virus or for experiencing severe course of the infection due to their often more fragile health, unmet health needs, and poorer living conditions. This study aims to gain insight into the morbidity and mortality of the SARS-COV-2 virus among the homeless population in the Netherlands. Methods In this observational retrospective study, anonymized data about patients experiencing homelessness who contacted a street doctor were gathered in nine cities in the Netherlands from March 2020 until March 2021. Data included patient characteristics, COVID-19 -related symptoms, diagnosis, and disease course of a SARS-COV-2 infection. Results Of the total 1419 patients in whom 1544 COVID-19 related consults were registered, 16% tested positive for a SARS-COV-2 infection, and an additional 12% were clinically suspected of having a SARS-COV-2 infection but were seen before there were any COVID-19 tests available in General Practice or for some other reason not tested. Significantly more (p =

by Leonie Richardson, Emily Long, Claire Goodfellow, Jelena Milicev, Maria Gardani

Students who began their undergraduate university studies in the midst of the COVID-19 pandemic (the ‘COVID cohort’), may have been particularly at risk for experiencing increased loneliness. This study employed an exploratory egocentric network and mixed-methods approach to investigate the links between social networks and loneliness in the COVID cohort. Of sixty-one respondents meeting inclusion criteria for the study, fifty-eight first-year undergraduate students from the September 2020 intake at a large Scottish University provided egocentric network data via an online survey, as well as responses to three open-ended questions which were aimed at generating qualitative data about participants’ experiences of starting university in the context of the COVID-19 pandemic. Bivariate analyses suggest that having a larger social network, and higher satisfaction with that network, was associated with reduced loneliness. We additionally explored these associations in subsamples of students living on-campus and living off-campus. Our qualitative data adds valuable insight into the impact that pandemic-related social-distancing restrictions had on limiting students’ opportunities for meeting their peers and forging meaningful social connections at university. Limitations of this study include a small sample size and an exploratory approach requiring further investigation and replication. However, in the context of universities continuing to use hybrid teaching models, this study provides useful initial insights, highlighting potential avenues for institutions to support students in developing social connections in the transition to higher education.

by Fu Feifei

Drawing on Critical Metaphor Analysis, this study investigates major metaphors of the COVID-19 pandemic used by the Chinese government in the specific genre of news picture. It examines patterns of metaphor use in the first year of the pandemic in China and explains how and why the government employs the identified metaphors in the Chinese political context. Results reveal that pandemic metaphors (45%) are not as widely used in news pictures as presumed, the vast majority (95%) are rendered in verbal mode, and the most salient metaphors used in news pictures are the UP/DOWN (spatial), WAR, FAMILY, and COMPETITION metaphors. This study then addresses how COVID-19 metaphors are used in the Chinese political context and claims that the Chinese government uses specific metaphors with persuasive and ideological functions. The WAR metaphor aids comprehension of abstract concepts of the pandemic treatment, the FAMILY metaphor fosters empathy among Chinese individuals to counter blame and discrimination in society, UP/DOWN (spatial) and COMPETITION metaphors stimulate action to overcome the common “enemy.” WAR and FAMILY metaphors also contribute to the construction of a greater sense of collectivism and play a crucial role in fostering a positive national identity. Implications, limitations and some directions for future research are suggested.

by Manuel Ribeiro, Leonardo Azevedo, André Peralta Santos, Pedro Pinto Leite, Maria João Pereira

During the SARS-CoV-2 pandemic, governments and public health authorities collected massive amounts of data on daily confirmed positive cases and incidence rates. These data sets provide relevant information to develop a scientific understanding of the pandemic’s spatiotemporal dynamics. At the same time, there is a lack of comprehensive approaches to describe and classify patterns underlying the dynamics of COVID-19 incidence across regions over time. This seriously constrains the potential benefits for public health authorities to understand spatiotemporal patterns of disease incidence that would allow for better risk communication strategies and improved assessment of mitigation policies efficacy. Within this context, we propose an exploratory statistical tool that combines functional data analysis with unsupervised learning algorithms to extract meaningful information about the main spatiotemporal patterns underlying COVID-19 incidence on mainland Portugal. We focus on the timeframe spanning from August 2020 to March 2022, considering data at the municipality level. First, we describe the temporal evolution of confirmed daily COVID-19 cases by municipality as a function of time, and outline the main temporal patterns of variability using a functional principal component analysis. Then, municipalities are classified according to their spatiotemporal similarities through hierarchical clustering adapted to spatially correlated functional data. Our findings reveal disparities in disease dynamics between northern and coastal municipalities versus those in the southern and hinterland. We also distinguish effects occurring during the 2020–2021 period from those in the 2021–2022 autumn-winter seasons. The results provide proof-of-concept that the proposed approach can be used to detect the main spatiotemporal patterns of disease incidence. The novel approach expands and enhances existing exploratory tools for spatiotemporal analysis of public health data.

by Maryam N. Chaudhary, Voon-Ching Lim, Erwin Martinez Faller, Pramod Regmi, Nirmal Aryal, Siti Nursheena Mohd Zain, Adzzie Shazleen Azman, Norhidayu Sahimin
Background Globally, 390 million dengue virus infections occur per year. In Malaysia, migrant workers are particularly vulnerable to dengue fever (DF) due to mosquito breeding sites exposure and poor health literacy. Therefore, this study aimed to (i) assess the current DF knowledge, attitudes and practices (KAP), and (ii) identify strategies to promote DF awareness, among migrant workers in Klang Valley. Method A survey was conducted with 403 Nepali, Filipino and Indonesian migrant workers through phone interviews and online self-administered questionnaires. Piecewise structural equation modelling was applied to identify predictor variables for DF KAP. Results Most respondents were male, working in the services industry, had completed high school, aged between 30–39 years and with less than ten years work experience in Malaysia. Overall, respondents’ knowledge was positively correlated with attitude but negatively with practices. Older respondents, who had completed higher education, obtained higher knowledge scores. Similarly, those with working experience of >20 years in Malaysia obtained higher attitude scores. Respondents with a previous history of DF strongly considered the removal of mosquito breeding sites as their own responsibility, hence tended to frequently practise DF preventive measures. Respondents’ knowledge was also positively correlated to their understanding of DF information sourced from social media platforms. Conclusion These findings highlighted: (i) the need for targeted DF educational intervention among younger and newly arrived workers with lower levels of education and (ii) maximising the usage of social media platforms to improve DF public awareness.

by Hong Duo, Mengying Jin, Yanwei Yang, Rewaan Baheti, Yujia Feng, Zirui Fu, Yuyue Jiang, Lanzhuoying Zheng, Jing Wan, Huaqin Pan
Background Coronavirus disease 2019 (COVID-19) may predispose patients to thrombotic disease in the venous and arterial circulations. Methods Based on the current debate on antiplatelet therapy in COVID-19 patients, we performed a systematic review and meta-analysis to investigate the effect of antiplatelet treatments. We searched PubMed, EMBASE, Cochrane Central Register of Controlled Trials, and Web of Science on February 1, 2023, and only included Randomized clinical trials. The study followed PRISMA guidelines and used Random-effects models to estimate the pooled percentage and its 95% CI. Results Five unique eligible studies were included, covering 17,950 patients with COVID-19. The result showed no statistically significant difference in the relative risk of all-cause death in antiplatelet therapy versus non-antiplatelet therapy (RR 0.94, 95% CI, 0.83–1.05, P = 0.26, I2 = 32%). Compared to no antiplatelet therapy, patients who received antiplatelet therapy had a significantly increased relative risk of major bleeding (RR 1.81, 95%CI 1.09–3.00, P = 0.02, I2 = 16%). The sequential analysis suggests that more RCTs are needed to draw more accurate conclusions. This systematic review and meta-analysis revealed that the use of antiplatelet agents exhibited no significant benefit on all-cause death, and the upper bound of the confidence interval on all-cause death (RR 95% CI, 0.83–1.05) suggested that it was unlikely to be a substantiated harm risk associated with this treatment. However, evidence from all RCTs suggested a high risk of major bleeding in antiplatelet agent treatments. Conclusion According to the results of our sequential analysis, there is not enough evidence available to support or negate the use of antiplatelet agents in COVID-19 cases. The results of ongoing and future well-designed, large, randomized clinical trials are needed.

by Qiang Wang, Hailing Gu, Jianjun Ren, Yu Zhao, Zhaoli Meng

The purpose of this study was to explore the characteristics of and risk factors for otological symptoms after contracting COVID-19. We invited 468 participants who had been infected with COVID-19 to participate in a survey. 310 (66.2%) were women and 158 (33.8%) were men. The mean age is 38.73 (12.21) years. The questionnaire included their basic information, symptoms and symptom duration after SARS-CoV-2 infection, number of vaccine doses received, and details regarding otological symptoms. In total, 106/468 (22.6%) participants experienced tinnitus, 66/468 (14.1%) hearing loss, 103/468 (22.0%) aural fullness, and 71/468 (15.2%) dizziness. Women were more prone to experience tinnitus (P = 0.022) and dizziness (P = 0.001) than men. The group with hearing loss were older (P = 0.025), and their initial COVID-19 symptoms lasted longer (P = 0.028) than those of patients without. Patients with aural fullness were more likely to experience fatigue than patients without (P = 0.002). Patients experiencing dizziness were more likely to experience pharyngalgia (P = 0.040) and fatigue (P = 0.005) than those without. The number of vaccine doses was positively associated with the resolution of otological symptoms (P = 0.035). Multiple logistic regression analysis revealed that sex was an independent risk factor for tinnitus (odds ratio [OR], 1.802; 95% confidence interval [CI], 1.099–2.953; P = 0.020), the duration of initial COVID-19 symptoms for hearing loss (OR, 1.055; 95% CI, 1.008–1.105; P = 0.023), and sex for dizziness (OR, 2.870; 95% CI, 1.489–5.535; P = 0.002). Sex, age, COVID-19-related fatigue, and the duration of initial COVID-19 symptoms may affect the occurrence of otological symptoms, and vaccines may aid their resolution.

by Yu-Yu Chang, An-Chi Wei

The effects of coronavirus disease 2019 (COVID-19) primarily concern the respiratory tract and lungs; however, studies have shown that all organs are susceptible to infection by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). COVID-19 may involve multiorgan damage from direct viral invasion through angiotensin-converting enzyme 2 (ACE2), through inflammatory cytokine storms, or through other secondary pathways. This study involved the analysis of publicly accessible transcriptome data from the Gene Expression Omnibus (GEO) database for identifying significant differentially expressed genes related to COVID-19 and an investigation relating to the pathways associated with mitochondrial, cardiac, hepatic, and renal toxicity in COVID-19. Significant differentially expressed genes were identified and ranked by statistical approaches, and the genes derived by biological meaning were ranked by feature importance; both were utilized as machine learning features for verification. Sample set selection for machine learning was based on the performance, sample size, imbalanced data state, and overfitting assessment. Machine learning served as a verification tool by facilitating the testing of biological hypotheses by incorporating gene list adjustment. A subsequent in-depth study for gene and pathway network analysis was conducted to explore whether COVID-19 is associated with cardiac, hepatic, and renal impairments via mitochondrial infection. The analysis showed that potential cardiac, hepatic, and renal impairments in COVID-19 are associated with ACE2, inflammatory cytokine storms, and mitochondrial pathways, suggesting potential medical interventions for COVID-19-induced multiorgan damage.

by Wang Xiang, Zezhi Wang, Xin Pan, Xiaobing Liu, Xuedong Yan, Li Chen

Selecting an appropriate intensity of epidemic prevention and control measures is of vital significance to promoting the two-way dynamic coordination of epidemic prevention and control and economic development. In order to balance epidemic control and economic development and suggest scientific and reasonable traffic control measures, this paper proposes a SEIQR model considering population migration and the propagation characteristics of the exposed and the asymptomatic, based on the data of COVID-19 cases, Baidu Migration, and the tourist economy. Further, the factor traffic control intensity is included in the model. After determining the functional relationship between the control intensity and the number of tourists and the cumulative number of confirmed cases, the NSGA-II algorithm is employed to perform multi-objective optimization with consideration of the requirements for epidemic prevention and control and for economic development to get an appropriate traffic control intensity and suggest scientific traffic control measures. With Xi’an City as an example. The results show that the Pearson correlation coefficient between the predicted data of this improved model and the actual data is 0.996, the R-square in the regression analysis is 0.993, with a significance level of below 0.001, suggesting that the predicted data of the model are more accurate. With the continuous rise of traffic control intensity in different simulation scenarios, the cumulative number of cases decreases by a significant amplitude. While balancing the requirements for epidemic prevention and control and for tourist economy development, the model works out the control intensity to be 0.68, under which some traffic control measures are suggested. The model presented in this paper can be used to analyze the impacts of different traffic control intensities on epidemic transmission. The research results in this paper reveal the traffic control measures balancing the requirements for epidemic prevention and control and for economic development.

by Stephan Gehring, Frank Kowalzik, Omar Okasha, Tobias Engelmann, Daniel Schreiner, Christian Jensen, Aline Mähringer-Kunz, Wendy Hartig-Merkel, Thao Mai Phuong Tran, Cornelia Oostvogels, Thomas Verstraeten

We assessed the seroepidemiology of SARS-CoV-2 infection and the incidence of coronavirus disease 2019 (COVID-19) before and during the rollout of COVID-19 vaccines, in a prospective observational cohort study on healthcare workers (HCWs) in a large tertiary hospital in Mainz, Germany. Antibody status was assessed during six visits between September 2020 and February 2022. Self-reported symptoms were collected using a smartphone application; symptomatic HCWs were tested using real-time polymerase chain reaction (RT-PCR) assays for SARS-CoV-2. Rates of virologically confirmed and severe COVID-19 were estimated using the U.S. Food and Drug Administration (FDA) and Coalition for Epidemic Preparedness Innovations (CEPI) case definitions, respectively, and were contrasted to background community transmission and circulating SARS-CoV-2 variants. A total of 3665 HCWs were enrolled (mean follow-up time: 18 months); 97 met the FDA definition of virologically confirmed COVID-19 (incidence rate (IR) 2.3/1000 person-months (PMs), one severe case). Most cases reported ≥2 symptoms, commonly, cough and anosmia or ageusia. Overall, 263 individuals seroconverted (IR 6.6/1000 PMs—2.9 times the estimated IR of COVID-19), indicating many cases were missed, either due to asymptomatic infections or to an atypical presentation of symptoms. A triphasic trend in anti-SARS-CoV-2 seroprevalence and seroconversion was observed, with an initial increase following the rollout of COVID-19 vaccines, a two-fold decline six months later, and finally a six-fold increase by the end of the study when Omicron was the dominant circulating variant. Despite the increase in infection rates at the end of the study due to the circulation of the Omicron variant, the infection and disease rates observed were lower than the published estimates in HCWs and rates in the general local population. Preferential vaccination of HCWs and the strict monitoring program for SARS-CoV-2 infection are the most likely reasons for the successful control of COVID-19 in this high-risk population.

by J. Sunil Rao, Tianhao Liu, Daniel Andrés Díaz-Pachón

We argue that information from countries who had earlier COVID-19 surges can be used to inform another country’s current model, then generating what we call back-to-the-future (BTF) projections. We show that these projections can be used to accurately predict future COVID-19 surges prior to an inflection point of the daily infection curve. We show, across 12 different countries from all populated continents around the world, that our method can often predict future surges in scenarios where the traditional approaches would always predict no future surges. However, as expected, BTF projections cannot accurately predict a surge due to the emergence of a new variant. To generate BTF projections, we make use of a matching scheme for asynchronous time series combined with a response coaching SIR model.

by Anthony K. Nkyi, Bridgette Baaba

The aim of this study is to investigate coping strategies, health anxiety and stress among healthcare professionals in selected hospitals in the Cape Coast Metropolis during the Covid 19 pandemic. This study adopted the Descriptive survey design. The Multistage sampling technique was used to select 322 health professionals. The health professionals included Medical Officers, Physician Assistants and Nurses. Data were gathered using the Health Anxiety Inventory (HAI-SF), Perceived Stress Scale (PSS), and the Brief-COPE Inventory. Analyses were conducted using mean and standard deviation, ANOVA as well as Independent Samples t-test. Results indicate that Health professionals adopted diverse coping strategies ranging from positive to negative coping style to overcome the negative impact of the COVID-19 pandemic. Results also indicate that coping strategies significantly influenced health anxiety levels of health professionals, and that Active Coping is a significant determinant of stress among health professionals. Male health professionals had significantly more health anxiety than females. However, gender was not a significant factor in the experiences of stress. Lastly, age of health professionals does not determine the type of coping strategy they adopted during the pandemic.

by Mohak Gupta, Giridara G. Parameswaran, Manraj S. Sra, Rishika Mohanta, Devarsh Patel, Amulya Gupta, Bhavik Bansal, Vardhmaan Jain, Archisman Mazumder, Mehak Arora, Nishant Aggarwal, Tarun Bhatnagar, Jawaid Akhtar, Pankaj Pandey, Vasanthapuram Ravi, Giridhara R Babu

by Tristan A. Moxley, Jennifer Johnson-Leung, Erich Seamon, Christopher Williams, Benjamin J. Ridenhour
Objectives COVID-19 has been at the forefront of global concern since its emergence in December of 2019. Determining the social factors that drive case incidence is paramount to mitigating disease spread. We gathered data from the Social Vulnerability Index (SVI) along with Democratic voting percentage to attempt to understand which county-level sociodemographic metrics had a significant correlation with case rate for COVID-19. Methods We used elastic net regression due to issues with variable collinearity and model overfitting. Our modelling framework included using the ten Health and Human Services regions as submodels for the two time periods 22 March 2020 to 15 June 2021 (prior to the Delta time period) and 15 June 2021 to 1 November 2021 (the Delta time period). Results Statistically, elastic net improved prediction when compared to multiple regression, as almost every HHS model consistently had a lower root mean square error (RMSE) and satisfactory R2 coefficients. These analyses show that the percentage of minorities, disabled individuals, individuals living in group quarters, and individuals who voted Democratic correlated significantly with COVID-19 attack rate as determined by Variable Importance Plots (VIPs). Conclusions The percentage of minorities per county correlated positively with cases in the earlier time period and negatively in the later time period, which complements previous research. In contrast, higher percentages of disabled individuals per county correlated negatively in the earlier time period. Counties with an above average percentage of group quarters experienced a high attack rate early which then diminished in significance after the primary vaccine rollout. Higher Democratic voting consistently correlated negatively with cases, coinciding with previous findings regarding a partisan divide in COVID-19 cases at the county level. Our findings can assist regional policymakers in distributing resources to more vulnerable counties in future pandemics based on SVI.

by Haruka Shida, Maki Komamine, Kazuhiro Kajiyama, Takashi Waki, Hotaka Maruyama, Yoshiaki Uyama
Objective Prescription trends and patterns of anti-COVID-19 drugs in hospitalized patients were examined based on real world data to understand the use of anti-COVID-19 drugs in clinical practice in Japan. Design The longitudinal and cross-sectional study was conducted utilizing data from January 1, 2019 to December 31, 2021 of the MID-NET® medical information database, which stored the electronic medical records, administrative claim data, and diagnosis procedure combination data of patients in Japan. Participants Hospitalized patients with a COVID-19-related diagnosis who received at least one anti-COVID-19 drug between April 1, 2020 and December 31, 2021. Exposures The following 14 drugs were included in this study: remdesivir, baricitinib, combination product of casirivimab and imdevimab, favipiravir, dexamethasone, ivermectin, azithromycin, nafamostat mesylate, camostat mesylate, ciclesonide, tocilizumab, sarilumab, combination product of lopinavir and ritonavir, and hydroxychloroquine. Results We identified 5,717 patients hospitalized with COVID-19 and prescribed at least one anti-COVID-19 drug. The entire cohort generally included patients over 41–50 years and more males. The most common prescription pattern was dexamethasone monotherapy (22.9%), followed by the concomitant use of remdesivir and dexamethasone (15.0%), azithromycin monotherapy (15.0%), remdesivir monotherapy (10.2%), and nafamostat mesylate monotherapy (8.5%). However, an often prescribed anti-COVID-19 drug differed depending on the period. Conclusions and relevance This study revealed the real-world situation of anti-COVID-19 drug prescriptions in hospitalized COVID-19 patients in Japan. A prescribed drug would depend on the latest scientific evidence, such as efficacy, safety, and approval status, at the time of prescription. Understanding the prescription of anti-COVID-19 drugs will be important for providing the most up-to-date treatments to patients and evaluating the benefit and/or risk of anti-COVID-19 drugs based on the utilization of an electronic medical record database.

by Vytenis Kalibatas, Lina Kalibatienė, Dulat Imashpayev

The coronavirus disease (COVID-19) pandemic has significantly affected blood donors worldwide. It is important for the blood service to return to its pre-pandemic level as soon as possible and to perform its functions fully. This study compared the donation and demographic profiles of blood and its component donors one year before and during three pandemic years in Lithuania. All blood and blood component donations (n = 413,358) and demographic characteristics of all donors from April 1, 2019, to March 31, 2023, were analyzed. All data were obtained from annual publications, and statistics were obtained from the Blood Donor Register. Data were analyzed using descriptive statistics. Following a 9.41 percent decrease in the first year of the pandemic, the quantity of blood and blood component donations increased by 3.49 percent in the third year compared to the pre-pandemic year. Throughout the three years of the pandemic, a statistically significant decrease in the proportion of first-time blood and blood component donations was observed. Both the number and proportion of donations by donors under 25 years old decreased during the pandemic. The proportion of pre-donation deferrals for all attempts to donate significantly decreased during the pandemic. There was a statistically significant lower prevalence of all positive transfusion-transmitted infectious (TTI) markers among all donations compared to the pre-pandemic year for all three pandemic years. The odds for hepatitis B virus, hepatitis C virus, and all TTI markers during the second and third pandemic years were significantly lower than those in the pre-pandemic year. In conclusion, most dimensions of blood and its component donations and donor characteristics have returned to pre-pandemic levels or show positive trends. However, the major concern is the remaining decrease in donations from first-time and donors under 25 years old.

by Iván Ochoa-Moreno, Ravita Taheem, Kathryn Woods-Townsend, Debbie Chase, Keith M. Godfrey, Neena Modi, Mark Hanson
Background The prevalence of overweight and obesity in young children rose sharply during the COVID-19 pandemic. Here we estimate the potential future health and economic effects of these trends in England. Methods Using publicly available annual Body Mass Index (BMI) data from 2006–2022, we calculated the increase in overweight/obesity prevalence (BMI ≥85th reference percentile) during the COVID-19 pandemic among children aged 4–5 and 10–11, and variation by deprivation and ethnicity. We projected the impact of child BMI trends on adult health measures to estimate added lifelong medical and social costs. Results During 2020–2021 there were steep increases in overweight and obesity prevalence in children. By 2022, overweight and obesity prevalence in children aged 4–5 returned to expected levels based on pre-pandemic trends. However, overweight and obesity prevalence in children aged 10–11 persisted and was 4 percentage points (p

by Sarah Keep, Phoebe Stevenson-Leggett, Isobel Webb, Albert Fones, James Kirk, Paul Britton, Erica Bickerton

The avian Gammacoronavirus infectious bronchitis virus (IBV) causes major economic losses in the poultry industry as the aetiological agent of infectious bronchitis, a highly contagious respiratory disease in chickens. IBV causes major economic losses to poultry industries across the globe and is a concern for global food security. IBV vaccines are currently produced by serial passage, typically 80 to 100 times in chicken embryonated eggs (CEE) to achieve attenuation by unknown molecular mechanisms. Vaccines produced in this manner present a risk of reversion as often few consensus level changes are acquired. The process of serial passage is cumbersome, time consuming, solely dependent on the supply of CEE and does not allow for rapid vaccine development in response to newly emerging IBV strains. Both alternative rational attenuation and cell culture-based propagation methods would therefore be highly beneficial. The majority of IBV strains are however unable to be propagated in cell culture proving a significant barrier to the development of cell-based vaccines. In this study we demonstrate the incorporation of a heterologous Spike (S) gene derived from the apathogenic Beaudette strain of IBV into a pathogenic M41 genomic backbone generated a recombinant IBV denoted M41K-Beau(S) that exhibits Beaudette’s unique ability to replicate in Vero cells, a cell line licenced for vaccine production. The rIBV M41K-Beau(S) additionally exhibited an attenuated in vivo phenotype which was not the consequence of the presence of a large heterologous gene demonstrating that the Beaudette S not only offers a method for virus propagation in cell culture but also a mechanism for rational attenuation. Although historical research suggested that Beaudette, and by extension the Beaudette S protein was poorly immunogenic, vaccination of chickens with M41K-Beau(S) induced a complete cross protective immune response in terms of clinical disease and tracheal ciliary activity against challenge with a virulent IBV, M41-CK, belonging to the same serogroup as Beaudette. This implies that the amino acid sequence differences between the Beaudette and M41 S proteins have not distorted important protective epitopes. The Beaudette S protein therefore offers a significant avenue for vaccine development, with the advantage of a propagation platform less reliant on CEE.

by Romanus A. Osabohien, Amar Hisham Jaaffar, Joshua Ibrahim, Ojonugwa Usman, Amechi E. Igharo, Adeleke Abdulrahman Oyekanmi

Africa has been known to experience series of problems among which are poverty, food insecurity, lack of access to energy, lack of infrastructure among others. These problems were exacerbated by the COVID-19 pandemic, which has had a severe impact on the socioeconomic status of households in Africa. This paper examines the relationship between socioeconomic shocks, social protection, and household food security during the pandemic in Nigeria, the Africa’s largest economy. Using the World Bank’s COVID-19 national longitudinal baseline phone survey (2020) for the analysis and applied the multinomial logit regression, the study finds that socioeconomic shocks resulting from the pandemic have led to an increased level of food insecurity. Social protection programmes have played a crucial role in mitigating the impact of these shocks on households. However, the study also highlights the need for more targeted and effective social protection policies to ensure that vulnerable households are adequately protected from the adverse effects of the pandemic. The findings of this study have important implications for policymakers and stakeholders in Africa’s largest economy, as they seek to address the challenges posed by the pandemic and promote household food security for the actualisation the United Nations (UN) Sustainable Development Goal (SDG) of food and nutrition security (SDG2). The study, therefore, recommends that efforts be made to preserve food supply chains by mitigating the pandemic’s effect on food systems, increasing food production, and looking forward beyond the pandemic by building resilient food systems with the use of social protection interventions.

by Thanin Methiyothin, Insung Ahn

The coronavirus disease (COVID-19) pandemic has considerably impacted public health, including the transmission patterns of other respiratory pathogens, such as the 2009 pandemic influenza (H1N1). COVID-19 and influenza are both respiratory infections that started with a lack of vaccination-based immunity in the population. However, vaccinations have been administered over time, resulting in a transition of the status of both diseases from a pandemic to an endemic. In this study, unsupervised clustering techniques were used to identify clusters of disease trends in Thailand. The analysis incorporated three distinct surveillance datasets: the pandemic influenza outbreak, influenza in the endemic stage, and the early stages of COVID-19. The analysis demonstrated a significant difference in the distribution of provinces between Cluster -1, representing those with unique transmission patterns, and the other clusters, indicating provinces with similar transmission patterns among their members. Specifically, for Pandemic Influenza, the ratio was 61:16, while for Pandemic COVID-19, it was 65:12. In contrast, Endemic Influenza exhibited a ratio of 46:31, with a notable emergence of more clustered provinces in the southern, western, and central regions. Furthermore, a pair of provinces with highly similar spreading patterns were identified during the pandemic stages of both influenza and COVID-19. Although the similarity decreased slightly for endemic influenza, they still belonged to the same cluster. Our objective was to identify the transmission patterns of influenza and COVID-19, with the aim of providing quantitative and spatial information to aid public health management in preparing for future pandemics or transitioning into an endemic phase.

by Yuvaraahnee Suresh, Aishah Hani Azil, Syamsa Rizal Abdullah

In some laboratories, mosquitoes’ direct blood-feeding on live animals has been replaced with various membrane blood-feeding systems. The selection of blood meal sources used in membrane feeding is crucial in vector mass rearing as it influences the mosquitoes’ development and reproductive fitness. Therefore, this scoping review aimed to evaluate the existing literature on the use of different blood sources and components in artificial membrane feeding systems and their effects on blood-feeding and the fecundity rate of Ae. aegypti. A literature review search was conducted by using PubMed, Scopus, and Web of Science databases according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA-ScR). The EndNote version 20 software was used to import all searched articles. Relevant information was retrieved for analysis into a Microsoft Excel Spreadsheet. A total of 104 full-text articles were assessed for eligibility criteria, whereby the articles should include the comparison between different types of blood source by using the membrane feeding systems. Only 16 articles were finally included in the analysis. Several studies had reported that human blood was superior in blood-feeding Ae. aegypti as compared to sheep blood which resulted in lower fecundity due to accumulation of free fatty acids (FFA) in the cuticles. In contrast, cattle whole blood and pig whole blood showed no significant differences in the blood-feeding and fecundity rate as compared to human blood. This review also indicated that bovine whole blood and pig whole blood enhanced Ae. aegypti’s vitellogenesis and egg production as compared to plasma and blood cells. In addition, human blood of up to 10 days after the expiration date could still be used to establish Ae. aegypti colonies with good blood-feeding rates and number of eggs produced. Thus, future studies must consider the importance of selecting suitable blood sources and components for membrane blood feeding especially in mosquito colonisation and control measure studies.

by Yang Wang, Muhui Ye, Fengwei Zhang, Zachary Thomas Freeman, Hong Yu, Xianwei Ye, Yongqun He

To fully understand COVID-19, it is critical to study all possible hosts of SARS-CoV-2 (the pathogen of COVID-19). In this work, we collected, annotated, and performed ontology-based taxonomical analysis of all the reported and verified hosts for all human coronaviruses including SARS-CoV, MERS-CoV, SARS-CoV-2, HCoV-229E, HCoV-NL63, HCoV-OC43, and HCoV-HKU1. A total of 37 natural hosts and 19 laboratory animal hosts of human coronaviruses were identified based on experimental evidence. Our analysis found that all the verified susceptible natural and laboratory animals belong to therian mammals. Specifically, these 37 natural therian hosts include one wildlife marsupial mammal (i.e., Virginia opossum) and 36 Eutheria mammals (a.k.a. placental mammals). The 19 laboratory animal hosts are also classified as therian mammals. The mouse models with genetically modified human ACE2 or DPP4 were more susceptible to virulent human coronaviruses with clear symptoms, suggesting the critical role of ACE2 and DPP4 to coronavirus virulence. Coronaviruses became more virulent and adaptive in the mouse hosts after a series of viral passages in the mice, providing clue to the possible coronavirus origination. The Huanan Seafood Wholesale Market animals identified early in the COVID-19 outbreak were also systematically analyzed as possible COVID-19 hosts. To support knowledge standardization and query, the annotated host knowledge was modeled and represented in the Coronavirus Infectious Disease Ontology (CIDO). Based on our and others’ findings, we further propose a MOVIE model (i.e., Multiple-Organism viral Variations and Immune Evasion) to address how viral variations in therian animal hosts and the host immune evasion might have led to dynamic COVID-19 pandemic outcomes.

by Manuel Leitner, Gloria Pötz, Martin Berger, Maria Fellner, Stephan Spat, Marisa Koini
Background COVID-19 infection and its associated consequence, known as long-COVID, lead to a significant burden on the global healthcare system and limitations in people’s personal and work lives. This study aims to provide further insight into the impact of acute and ongoing COVID-19 symptoms and investigates the role of patients’ gender and vaccination status. Methods 416 individuals (73.9% female) between the ages of 16 and 80 years (M = 44.18, SD = 12.90) with self-reported symptoms of long-COVID participated in an online survey conducted between March and May 2022. Results 6.0%, 74.3%, and 19.7% of all respondents reported having had an asymptomatic, mild, or severe acute illness, respectively. Out of all participants, 7.8% required hospitalization. The most prevalent symptoms during the acute infection (Mdn = 23.50 symptoms, IQR = 13–39) included fatigue, exhaustion, cough, brain fog, and memory problems. The median long-COVID disease duration was 12.10 months (IQR = 2.8–17.4). Among 64 inquired long-COVID symptoms (Mdn = 17.00 symptoms, IQR = 9–27), participants reported fatigue, exhaustion, memory problems, brain fog, and dyspnea as the most common ongoing symptoms, which were generally experienced as fluctuating and deteriorating after physical or cognitive activity. Common consequences of long-COVID included financial losses (40.5%), changes in the participants’ profession (41.0%), stress resistance (87.5%), sexual life (38.1%), and mood (72.1%), as well as breathing difficulties (41.3%), or an increased drug intake (e.g., medicine, alcohol; 44.6%). In addition, vaccinated individuals exhibited a shorter acute illness duration and an earlier onset of long-COVID symptoms. In general, women reported more long-COVID symptoms than men. Conclusion Long-COVID represents a heterogeneous disease and impacts multiple life aspects of those affected. Tailored rehabilitation programs targeting the plurality of physical and mental symptoms are needed.

by Minh-Anh Le-Dang, Hai-Yen Nguyen-Thi, Luyen Pham Dinh, Danh Le Ngoc, Nguyen Dang Tu Le, Hien Pham Thu, Dinh Thanh Le
Background The Coronavirus disease of 2019 (COVID-19) pandemic and the corresponding mitigation measures have had a discernible impact on drug utilization among outpatients. However, limited research exists on the prescription trends in the elderly population during the pandemic period in Viet Nam. Objectives This study aims to analyze the effects of COVID-19 on outpatient drug utilization patterns at a national geriatric hospital in Ho Chi Minh City before and after the early onset of the pandemic. Methods Data was collected from the prescriptions and administration claims, encompassing the period from January 2016 to December 2022. The dataset was divided into two periods: Period 1: January 2016 to December 2020 and Period 2: January 2021 to December 2022. The drug utilization was measured using DDD/1000P (defined daily doses–DDD per 1000 prescriptions) on a monthly basis. The analysis employed interrupted time series using Autoregressive Integrated Moving Average (ARIMA) to detect changes in drug use levels and rates. Results A total of 1,060,507 and 644,944 outpatient prescriptions from Thong Nhat Hospital were included in Period 1 and Period 2, respectively. The median age of the patients were 58 in Period 1 and 67 years old in Period 2. The most common comorbidities were dyslipidemia, hypertension, and diabetes mellitus. In terms of medication utilization, cardiovascular drugs were the most frequently prescribed, followed by drugs active on the digestive and hormonal systems. The study observed significant surges in the number of prescriptions and the average number of drugs per prescription. However, there were no significant changes in the overall consumption of all drugs. Among the drug groups related to the cardiovascular system, three subgroups experienced a sudden and significant increase: cardiac therapy, beta-blocking agents, and antihypertensives, with increasing consumption levels of 1,177.73 [CI 95%: 79.29; 2,276.16], 73.32 [CI 95%: 28.18; 118.46], and 36.70 [CI 95%: 6.74; 66.66] DDD/1000P, respectively. On the other hand, there was a significant monthly decrease of -31.36 [CI 95%: -57.02; -5.70] DDD/1000P in the consumption of anti-inflammatory and antirheumatic products. Interestingly, there was a significant increase of 74.62 [CI 95%: -0.36; 149.60] DDD/1000P in the use of antigout preparations. Conclusion COVID-19 resulted in a sudden, non-significant increase in overall drug consumption levels among outpatients. Notably, our findings highlight significant increases in the utilization of three drug groups related to the cardiovascular system, specifically cardiac therapy, beta-blocking agents, and antihypertensives. Intriguingly, there was a statistically significant increase in the consumption of antigout preparations, despite a decline in the monthly consumption rate of non-steroidal anti-flammatory drugs (NSAIDs). Further studies in the following years are necessary to provide a more comprehensive understanding of the impact of COVID-19 on outpatient drug utilization patterns.

by Christian Hannes, Sarah Schiffer, Rüdiger von Nitzsch

In March 2020, the WHO declared the coronavirus a pandemic. Since then, the German government has tried to control the spread of the virus with various restrictions. These restrictions had a direct impact on the life of German students. In this study, we investigate to what extent the restrictions led to a change of value priorities of German students. From January 2019 to January 2022, we conducted a cross-sectional study with four measurement points and, in total, 1,328 participants. Two measurement points were before the first outbreak of COVID-19 in Germany, one in the second lockdown phase and the third after two years in the pandemic. In this study, the students were asked to indicate their value priorities while solving a real-world decision problem important to them. Results suggest increased value priorities of the values Intellectual Fulfillment and Environment and Nature and a decrease of Family and Partner value priority as a direct effect of the second lockdown phase. We also found small differences regarding value priorities between the male and female subjects. The data show bounce-back effects as the pandemic became more normal to the students. In the long run, value priorities seem to be stable, with the exception of a longer-lasting increase in Freedom and Independence.

by Anita Kovács, Dóra Hantosi, Nikoletta Szabó, Annamária Letoha, Csaba Lengyel, Imre Földesi, Katalin Burián, András Palkó, Dániel Veréb, Zsigmond Tamás Kincses
Objectives Emerging results indicate that, in COVID-19, thromboembolic complications contribute to the high mortality and morbidity. Previous research showed that the prevalence of pulmonary embolism (PE) is between 25–50% in COVID-19 patients, however, most of these reports are based on data from patients with severe pneumonia, treated in intensive care units. Materials and methods We conducted a retrospective, single-center, observational study to estimate the prevalence of PE in COVID-19 patients who underwent CT angiography and to identify the most important predictors.Adult outpatients with COVID-19, who presented at our COVID Outpatient Clinic between 1st and 31st of March in 2021 and underwent CTA examination were included in this study. Multiple linear regression analysis was used to identify predictors of PE in COVID-19 patients. The predictors were: age, gender, disease duration, CT severity index and log-transformed quantitative D-dimer (logQDDIM) value. Results 843 COVID-19 patients were included into the study. 82.56% (693 patients) of the infected patients had a pulmonary CTA examination and D-dimer levels (mean age: 59.82 years ± 15.66). 7.61% (53 patients) of the patients had PE. 2.02% (14 patients) of the patients had main branch or lobar PE.The multiple regression analysis found that only logQDDIM was a significant predictor. A logQDDIM cut-off value of 0.0169 (1.0171 ug/ml serum D-dimer) predicted PE with 99% sensitivity (p

by Magdi E. A. Zaki, Sami A. AL-Hussain, Aamal A. Al-Mutairi, Abdul Samad, Vijay H. Masand, Rahul G. Ingle, Vivek Digamber Rathod, Nikita Maruti Gaikwad, Summya Rashid, Pravin N. Khatale, Pramod V. Burakale, Rahul D. Jawarkar

Several studies have revealed that SARS-CoV-2 damages brain function and produces significant neurological disability. The SARS-CoV-2 coronavirus, which causes COVID-19, may infect the heart, kidneys, and brain. Recent research suggests that monoamine oxidase B (MAO-B) may be involved in metabolomics variations in delirium-prone individuals and severe SARS-CoV-2 infection. In light of this situation, we have employed a variety of computational to develop suitable QSAR model using PyDescriptor and genetic algorithm-multilinear regression (GA-MLR) models (R2 = 0.800–793, Q2LOO = 0.734–0.727, and so on) on the data set of 106 molecules whose anti-SARS-CoV-2 activity was empirically determined. QSAR models generated follow OECD standards and are predictive. QSAR model descriptors were also observed in x-ray-resolved structures. After developing a QSAR model, we did a QSAR-based virtual screening on an in-house database of 200 compounds and found a potential hit molecule. The new hit’s docking score (-8.208 kcal/mol) and PIC50 (7.85 M) demonstrated a significant affinity for SARS-CoV-2’s main protease. Based on post-covid neurodegenerative episodes in Alzheimer’s and Parkinson’s-like disorders and MAO-B’s role in neurodegeneration, the initially disclosed hit for the SARS-CoV-2 main protease was repurposed against the MAO-B receptor using receptor-based molecular docking, which yielded a docking score of -12.0 kcal/mol. This shows that the compound that inhibits SARS-CoV-2’s primary protease may bind allosterically to the MAO-B receptor. We then did molecular dynamic simulations and MMGBSA tests to confirm molecular docking analyses and quantify binding free energy. The drug-receptor complex was stable during the 150-ns MD simulation. The first computational effort to show in-silico inhibition of SARS-CoV-2 Mpro and allosteric interaction of novel inhibitors with MAO-B in post-covid neurodegenerative symptoms and other disorders. The current study seeks a novel compound that inhibits SAR’s COV-2 Mpro and perhaps binds MAO-B allosterically. Thus, this study will enable scientists design a new SARS-CoV-2 Mpro that inhibits the MAO-B receptor to treat post-covid neurological illness.

by Suratsawadee Wangnamthip, Nantthasorn Zinboonyahgoon, Pranee Rushatamukayanunt, Patcha Papaisarn, Burapa Pajina, Thanawut Jitsinthunun, Panuwat Promsin, Rujipas Sirijatuphat, César Fernández-de-las-Peñas, Lars Arendt-Nielsen, Daniel Ciampi de Andrade

The COVID-19 pandemic has affected millions of individuals worldwide. Pain has emerged as a significant post-COVID-19 symptom. This study investigated the incidence, characteristics, and risk factors of post-COVID chronic pain (PCCP) in Thailand. A cross-sectional study was conducted in participants who had been infected, including those hospitalized and monitored at home by SARS-CoV-2 from August to September 2021. Data were collected for screening from medical records, and phone interviews were done between 3 to 6 months post-infection. Participants were classified into 1) no-pain, 2) PCCP, 3) chronic pain that has been aggravated by COVID-19, or 4) chronic pain that has not been aggravated by COVID-19. Pain interference and quality of life were evaluated with the Brief Pain Inventory and EuroQol Five Dimensions Five Levels Questionnaire. From 1,019 participants, 90% of the participants had mild infection, assessed by WHO progression scale. The overall incidence of PCCP was 3.2% (95% CI 2.3–4.5), with 2.8% (95% CI 2.0–4.1) in mild infection, 5.2% (95% CI 1.2–14.1) in moderate infection and 8.5% (95% CI 3.4–19.9) in severe infection. Most participants (83.3%) reported pain in the back and lower extremities and were classified as musculoskeletal pain and headache (8.3%). Risk factors associated with PCCP, included female sex (relative risk [RR] 2.2, 95% CI 1.0–4.9) and greater COVID-19 severity (RR 3.5, 95% CI 1.1–11.7). Participants with COVID-19-related exacerbated chronic pain displayed higher pain interferences and lower utility scores than other groups. In conclusion, this study highlights the incidence, features, and risk factors of post-COVID chronic pain (PCCP) in Thailand. It emphasizes the need to monitor and address PCCP, especially in severe cases, among females, and individuals with a history of chronic pain to improve their quality of life in the context of the ongoing COVID-19 pandemic.

by Sharon Teitler Regev, Tchai Tavor

The global health crisis initiated by the COVID-19 pandemic triggered unparalleled economic upheavals. In this comprehensive study of 16 countries categorized by their infection rates, we scrutinize the impact of a range of variables on stock market indices and calculate four critical ratios derived from those variables. Our regression analyses reveal striking differences in how the variables influenced stock indices in countries with low and high infection rates. Notably, in countries with low infection rates, all variables exhibited significant effects on stock returns. An increase in infection numbers and fatalities correlated with greater stock market declines, underscoring the market’s sensitivity to the health and economic risks posed by the pandemic. Recovery and testing rates also displayed positive associations with stock returns, reflecting investor optimism concerning potential recovery scenarios. Conversely, nations grappling with high infection rates experienced notably weaker effects from these variables. Although fatalities had a negative impact on stock indices, other factors, including recoveries, infections, and testing rates, did not result in significant effects. This suggests the likelihood that markets in high-infection countries had likely factored pandemic conditions into their pricing, thereby reducing the immediate impact of these metrics on stock returns. Our findings underscore the intricacies of the COVID-19 pandemic’s impact on stock markets and highlight the importance of tailored strategies and policies for distinct country categories. This study offers valuable insights for policymakers and investors navigating financial markets during global health crises and preparing for future epidemics.

by Maciej Koscielniak, Dorota Marciniak, Dariusz Doliński

Previous laboratory and field studies have demonstrated that the dishonesty of commercial transaction participants may depend on subtle cues. In this field study conducted on a sample of 216 shop assistants in Poland, we planned to demonstrate that coronavirus disease-related factors could result in an increased propensity for dishonesty among shop assistants. This investigation is unique in its application of social psychological theories to illuminate hitherto unexplored side effects of combating the coronavirus disease 2019 pandemic. Our supposition was that the potential detriment encountered by individuals wearing solid surgical masks would involve being viewed as more abstract and remote, thereby heightening the likelihood of being deceived by a vendor. Moreover, we examined the potential relationship between the limited number of customers in retail establishments (related to pandemic restrictions) and the unscrupulous practices of sellers—specifically the act of retaining change. The effect of wearing masks was statistically non-significant, whereas the impact of other customers’ absence was significant. Moreover, unexpected results related to transaction parties’ genders were obtained, showing that shop assistants tended to be more honest when dealing with customers of the same gender. The results are discussed in the context of empathy toward masked customers, self-awareness theory, social norms of honesty, and identification with gender groups.