Pregnancy with anxiety and depression during COVID-19 pandemic: a single centre study

Background: Corona-virus pandemic has become a major health problem worldwide. It evokes mental health disorders affecting the population globally, especially pregnant women and is associated with adverse maternal and fetal outcomes. The aim of the study was to assess anxiety and depression in pregnant women during the Covid-19 pandemic. Material & Methods: This was a cross-sectional study conducted at Islami Bank Central Hospital Kakrail, Dhaka, Bangladesh. Pregnant women visiting the gynae& obs outpatient department, and women who had recently delivered in the gynae ward (in the past 15 days) were included in the study and asked to fill out a questionnaire. Results: A total of 152 patients were enrolled and analyzed in this study. Out of the total, 108 (71.05%) of the patients were less than 30 years, 38 (25.00%) were between 31 and 35 years old, and only 6 (3.95%) were older than 35 years. We found that 103(67.76%) of pregnant women had developed mental health disorders during this pandemic and there is a need to reform policies for the care and counseling of pregnant women as they are particularly susceptible. Conclusions: This study examined the mental health of pregnant women during the COVID-19 pandemic. The majority of the women thought COVID-19 could affect their pregnancy. Proper screening and diagnosis would bring early treatment to the needy thus preventing complications to both the mother and the newborn.

Trade-off between future travel avoidance and self-protectiveness post-COVID-19: the roles of adventurousness and safety-seeking tendency

Purpose: Underpinned by sensation-seeking theory (SST) and regulatory focus theory (RFT), this paper highlights the crucial role of adventurousness in self-protective behavior and future travel avoidance. Furthermore, this paper investigates safety-seeking tendency as a moderator and travel anxiety post-COVID-19 as a mediator. Design/methodology/approach: Data were gathered from 574 potential visitors to St. Catherine post-COVID-19 and analyzed using Smart-PLS approach. Findings: Adventurousness negatively and significantly affected travel anxiety, while the latter negatively influenced self-protective behavior and positively influenced future travel avoidance. Besides, the findings proved that travel anxiety partially mediated the adventurousness linkage with self-protective behavior and future travel avoidance. Moreover, safety-seeking tendencies dampened travel anxiety's connection with self-protective behavior and future travel avoidance. Practical implications: This paper provides valuable insights into travel research in theory and practice to revive tourist attractions post-COVID-19 in developing countries via an adventure tourism pattern. The study helps figure out how to deal with the pandemic and restore the monument of heavenly religions, St. Catherine—sacred mountain peaks, mosques, churches and many monasteries—in addition to its charming and picturesque nature. Originality/value: The current paper examines a traveler's adventurous nature and post-COVID-19 behavior when visiting St. Catherine and their behaviors related to future avoidance and self-protection. This paper adds the first investigation of travel anxiety and safety-seeking through the lens of SST and RFT theories in the Egyptian tourism context. © 2023, Emerald Publishing Limited.

Asymptomatic RT-PCR positive COVID-19 patients in orthopaedic pre-operative evaluation during the peak of the second wave.

Introduction: Asymptomatic COVID-19 patients are the most challenging and feared obstacles in resuming these surgical procedures. The purpose of this study was to evaluate the proportion of asymptomatic carriers detected by RT-PCR in pre-operative orthopaedic evaluation during the peak of the second wave. Methods: 514 asymptomtomatic COVID-19 patients, negative for TOCC (Travel, Profession, Cluster, Contact) risk factors were observed retrospectively. A nasopharyFngeal RT-PCR test was obtained 48 to 72 h before the surgery in all cases. Possible risk factors for a positive test was identified. Results: The detected asymptomatic COVID-19 infection rate during the peak of the second wave among the pre-operative orthopaedic patients was 12.3%. Younger age, female gender, longer duration of admission to RT-PCR test interval were found to be significant (p= < 0.05) risk factors for asymptomatic RT-PCR to be positive. The hazard ratio (HR) for being asymptomatic RT-PCR positive was 4.3 (p = 0. 025), while the RT-PCR was performed at 14 days, but the HR increased to 9.2 (p = 0.049) when the test was performed after 45 days. Conclusion: According to our findings, pre-operative testing to rule out COVID-19 should be regarded as a critical step in preventing the disease clusters in hospitals.

Vaccine efficacy and SARS CoV 2 control in California and USA during the session 2020 2026: A modeling study (preprint)

Besides maintaining health precautions, vaccination has been the only prevention from SARS-CoV-2, though no clinically proved 100% effective vaccine has been developed till date. At this stage, to withhold the debris of this pandemic, experts need to know the impact of the vaccine efficacy rate's threshold and how long this pandemic may extent with vaccines that have different efficacy rates. In this article, a mathematical model study has been done on the importance of vaccination and vaccine efficiency rate during an ongoing pandemic. We simulated a five compartment mathematical model to analyze the pandemic scenario in both California, and whole U.S. We considered four vaccines, Pfizer, Moderna, AstraZeneca, and Johnson and Johnson, which are being used rigorously to control the COVID-19 pandemic, in addition with two special cases: a vaccine with 100% efficacy rate and no vaccine under use. Both the infection and death rates are very high in California. Our model suggests that the pandemic situation in California will be under control in the last quartile of the year 2023 if frequent vaccination is continued with the Pfizer vaccine. During this time, six waves will happen from the beginning of the immunization where the case fatality and recovery rates will be 1.697% and 98.30%, respectively. However, according to the considered model, this period might be extended to the mid of 2024 when vaccines with lower efficacy rates are used. The more effective a vaccine, the less people suffer from this malign infection. Although specific groups of people get prioritized initially, mass vaccination is needed to control the spread of the disease.

Diversity and genomic determinants of the microbiomes associated with COVID-19 and non-COVID respiratory diseases (preprint)

The novel coronavirus disease 2019 (COVID-19) is a rapidly emerging and highly transmissible disease caused by the Severe Acute Respiratory Syndrome CoronaVirus-2 (SARS-CoV-2). Understanding the microbiomes associated with the upper respiratory tract infection (URTI), chronic obstructive pulmonary disease (COPD) and COVID-19 diseases has clinical interest. We hypothesized that the diversity of microbiome compositions and their genomic features are associated with different pathological conditions of these human respiratory tract diseases (COVID-19 and non-COVID; URTI and COPD). To test this hypothesis, we analyzed 21 whole metagenome sequences (WMS) including eleven COVID-19 (BD = 6 and China = 5), six COPD (UK = 6) and four URTI (USA = 4) samples to unravel the diversity of microbiomes, their genomic features and relevant metabolic functions. The WMS data mapped to 534 bacterial, 60 archaeal and 61 viral genomes with distinct variation in the microbiome composition across the samples (COVID-19>COPD>URTI). Notably, 94.57%, 80.0% and 24.59% bacterial, archaeal and viral genera shared between the COVID-19 and non-COVID samples, respectively, however, the COVID-19 related samples had sole association with 16 viral genera other than SARS-CoV-2. Strain-level virome profiling revealed 660 and 729 strains in COVID-19 and non-COVID sequence data, respectively and of them 34.50% strains shared between the conditions. Functional annotation of metagenomics sequences of thevCOVID-19 and non-COVID groups identified the association of several biochemical pathways related to basic metabolism (amino acid and energy), ABC transporters, membrane transport, replication and repair, clustering-based subsystems, virulence, disease and defense, adhesion, regulation of virulence, programmed cell death, and primary immunodeficiency. We also detected 30 functional gene groups/classes associated with resistance to antibiotics and toxic compounds (RATC) in both COVID-19 and non-COVID microbiomes. Furthermore, a predominant higher abundance of cobalt-zinc-cadmium resistance (CZCR) and multidrug resistance to efflux pumps (MREP) genes were detected in COVID-19 metagenome. The profiles of microbiome diversity and associated microbial genomic features found in both COVID-19 and non-COVID (COPD and URTI) samples might be helpful for developing the microbiome-based diagnostics and therapeutics for COVID-19 and non-COVID respiratory diseases. However, future studies might be carried out to explore the microbiome dynamics and the cross-talk between host and microbiomes employing larger volume of samples from different ethnic groups and geoclimatic conditions.

An engineered decoy receptor for SARS-CoV-2 broadly binds protein S sequence variants (preprint)

The spike S of SARS-CoV-2 recognizes ACE2 on the host cell membrane to initiate entry. Soluble decoy receptors, in which the ACE2 ectodomain is engineered to block S with high affinity, potently neutralize infection and, due to close similarity with the natural receptor, hold out the promise of being broadly active against virus variants without opportunity for escape. Here, we directly test this hypothesis. We find an engineered decoy receptor, sACE22.v2.4, tightly binds S of SARS-associated viruses from humans and bats, despite the ACE2-binding surface being a region of high diversity. Saturation mutagenesis of the receptor-binding domain followed by in vitro selection, with wild type ACE2 and the engineered decoy competing for binding sites, failed to find S mutants that discriminate in favor of the wild type receptor. We conclude that resistance to engineered decoys will be rare and that decoys may be active against future outbreaks of SARS-associated betacoronaviruses.

Transmission Dynamics and Contact Tracing Assessment of COVID-19 in Chattogram, Bangladesh and Potential Risk of Close Contacts at Different Exposure Settings (preprint)

Background: Given the limited understanding of the behaviors of the virus it is crucial to decipher the transmission dynamics for the development of strategic plans and evaluation of effective control measures. We aimed to estimate the key components of disease transmission and secondary attack rate from different exposure settings and highlight the measures of control of the virus.Methods: In this study, we used COVID-19 symptomatic surveillance cases and their close contacts from April 3 to June 2, 2020. From this pool of cases, we compared the time from symptom onset and serial intervals. We also estimated disease transmission in different exposure settings and factors leading to transmission risk.Findings: The mean age was 41.5 years, including 159 (87.85%) of males and 22 (12.15%) females. At the initial case assessment, 53 (29.28%) were mild, 114 (62.30%) were moderate and 14 (7.7%) were severe cases. The median time to recovery was 21.09 days (95% CI 19.44-22.9). The crude case fatality rate amongst all cases was 6.08% (95% CI 4.62-7.54), relatively higher in age over 60 (17.78, 95% CI 14.85-20.70). Patients who were admitted to hospitals were treated with intravenous fluids and antibiotics and severe cases were given supplemental oxygen therapy. Median time from symptom onset to death was 15.7 days (95% CI 13.83-17.91). Among 319 close contacts, there were 13 secondary cases having an overall secondary attack rate of 4.08 (95% CI 1.95-6.20). The secondary attack rate among household contacts was at the highest risk of attack (13.04%, 95% CI 9.67-16.41) followed by funeral ceremonies (8.33%, 95% CI 3.99-12.66) and family contacts (6.52%, 95% CI 4.02-9.02). The attack rate was higher in age groups 50-59 (10.89%, 95% CI 7.05-14.66) and 60-69 (9.09%, 95% CI 5.08-13.09).Interpretation: Considering the demographic interactions, our data on index cases as well as their close contacts suggest critical insights into the epidemiological characteristics of COVID-19. Our analyses suggest that prompt isolation, physical distancing and contact tracing of symptomatic cases significantly reduce the spread of virus and thereby reduce the overall secondary infection in the community.Funding Statement: This study was supported by Bangladesh Medical Research Council (BMDC).Declaration of Interests: The authors declare no competing interests.Ethics Approval Statement: This work was conducted as part of the ongoing public health response, therefore institutional or regional review board approval and individual cases consent approval was waived. This study was approved by ethics committee of the Bangladesh Medical Research Council (BMDC).

Host range projection of SARS-CoV-2: South Asia perspective (preprint)

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), the causing agent of Coronavirus Disease-2019 (COVID-19), is likely to be originated from bat and transmitted through intermediate hosts. However, the immediate source species of SARS-CoV-2 has not yet been confirmed. Here, we used diversity analysis of the angiotensin I converting enzyme 2 (ACE2) that serves as cellular receptor for SARS-CoV-2 and transmembrane protease serine 2 (TMPRSS2), which has been proved to be utilized by SARS-CoV-2 for spike protein priming. We also simulated the structure of receptor binding domain of SARS-CoV-2 spike protein (SARS-CoV-2 S RBD) with the ACE2s to investigate their binding affinity to determine the potential intermediate animal hosts that could spread the SARS-CoV-2 virus to humans in South Asia. We identified cow, buffalo, goat and sheep, which are predominant species in the household farming system in South Asia that can potentially be infected by SARS-CoV-2. All the bird species studied along with rat and mouse were considered less potential to interact with SARS-CoV-2. The interaction interfaces of SARS-CoV-2 S RBD and ACE2 protein complex suggests pangolin as a potential intermediate host in SARS-CoV-2. Our results provide a valuable resource for the identification of potential hosts for SARS-CoV-2 in South Asia and henceforth reduce the opportunity for a future outbreak of COVID-19.

Host transcriptional responses and SARS-CoV-2 isolates from the nasopharyngeal samples of Bangladeshi COVID-19 patients (preprint)

As the COVID-19 pandemic progresses, fatality and cases of new infections are also increasing at an alarming rate. SARS-CoV-2 follows a highly variable course and it is becoming more evident that individuals immune system has a decisive influence on the progression of the disease. However, the detailed underlying molecular mechanisms of the SARS-CoV-2 mediate disease pathogenesis are largely unknown. Only a few host transcriptional responses in COVID-19 have been reported so far from the Western world, but no such data has been generated from the South-Asian region yet to correlate the conjectured lower fatality around this part of the globe. In this context, we aimed to perform the transcriptomic profiling of the COVID-19 patients from Bangladesh along with the reporting of the SARS-CoV-2 isolates from these patients. Moreover, we performed a comparative analysis to demonstrate how differently the various SARS-CoV-2 infection systems are responding to the viral pathogen. We detected a unique missense mutation at 10329 position of ORF1ab gene, annotated to 3C like proteinase, which is found in 75% of our analyzed isolates; but is very rare globally. Upon the functional enrichment analyses of differentially modulated genes, we detected a similar host induced response reported earlier; this response was mainly mediated by the innate immune system, interferon stimulation, and upregulated cytokine expression etc. in the Bangladeshi patients. Surprisingly, we did not perceive the induction of apoptotic signaling, phagosome formation, antigen presentation and production, hypoxia response within these nasopharyngeal samples. Furthermore, while comparing with the other SARS-CoV-2 infection systems, we spotted that lung cells trigger the more versatile immune and cytokine signaling which was several folds higher compared to our reported nasopharyngeal samples. We also observed that lung cells did not express ACE2 in a very high amount as suspected, however, the nasopharyngeal cells are found overexpressing ACE2. But the amount of DPP4 expression within the nasal samples was significantly lower compared to the other cell types. Surprisingly, we observed that lung cells express a very high amount of integrins compared to the nasopharyngeal samples, which might suggest the putative reasons for an increased amount of viral infections in the lungs. From the network analysis, we got clues on the probable viral modulation for the overexpression of these integrins. Our data will provide valuable insights in developing potential studies to elucidate the roles of ethnicity effect on the viral pathogenesis, and incorporation of further data will enrich the search of an effective therapeutics.

SICE: an improved missing data imputation technique.

In data analytics, missing data is a factor that degrades performance. Incorrect imputation of missing values could lead to a wrong prediction. In this era of big data, when a massive volume of data is generated in every second, and utilization of these data is a major concern to the stakeholders, efficiently handling missing values becomes more important. In this paper, we have proposed a new technique for missing data imputation, which is a hybrid approach of single and multiple imputation techniques. We have proposed an extension of popular Multivariate Imputation by Chained Equation (MICE) algorithm in two variations to impute categorical and numeric data. We have also implemented twelve existing algorithms to impute binary, ordinal, and numeric missing values. We have collected sixty-five thousand real health records from different hospitals and diagnostic centers of Bangladesh, maintaining the privacy of data. We have also collected three public datasets from the UCI Machine Learning Repository, ETH Zurich, and Kaggle. We have compared the performance of our proposed algorithms with existing algorithms using these datasets. Experimental results show that our proposed algorithm achieves 20% higher F-measure for binary data imputation and 11% less error for numeric data imputations than its competitors with similar execution time.

Effect of Lockdown and Isolation to Suppress the COVID-19 in Bangladesh: An Epidemic Compartments Model (preprint)

In the promptness of the COVID-19 outbreak, it would be very important to observe and estimate the pattern of diseases to reduce the contagious infection. To study this effect, we developed a COVID-19 analytical epidemic framework that combines with isolation and lockdown effect by incorporating five various groups of individuals. Then we analyze the model by evaluating the equilibrium points and analyzing their stability as well as determining the basic reproduction number. The extensive numerical simulations show the dynamics of a different group of the population over time. Thus, our findings based on the sensitivity analysis and the reproduction number highlight the role of outbreak of the virus that can be useful to avoid a massive collapse in Bangladesh and rest of the world. The outcome of this study concludes that outbreak will be in control which ensures the social and economic stability.

Pandemic and the Dynamics of SEIR Model: Case COVID-19 (preprint)

Rapidly spreading disease, COVID-19 is classified as the human-to-human transmission-able disease and currently is a pandemic in the Globe. In this paper, we propose conceptual mathematical models for COVID-19 outbreak and it's control measurement; quarantine, hospitalization and the effect of panic and anxiety. In this situation, mathematical models are a important tool to employ an effective strategy in order to fight against this pandemic. We establish the positivity and boundedness of solutions, local and global stability analysis of equilibria to examine its epidemiological relevance. To validate the model and estimating the important model parameters and prediction about the disease, we consider the real cases of Italy from $15^{th}$ Feb to $13^{th} $ April 2020. In a series of graphical map, we have presented the comparative study to estimate the current scenarios and to predict the control measurement time boundary of the outbreak.

Mathematical Modelling of Social Consciousness to Control the Outbreak of COVID-19 (preprint)

Background: The world, now in an emergency of preventing the drastic spread of COVID-19. After the infection was first reported in December 2019, almost every country did not pay attention to this highly contaminated disease and failed to react swiftly. Now the whole universe is in an vulnerable state, loosing a great loss of lives and facing difficulties in all socio-economic aspects. That is why we have the urge to develop an efficient mathematical model (quarantine) based on social consciousness to control the epidemic. Methods: This is a quarantine mathematical model. The outcome of the system is dependent on social consciousness. We have calculated the awareness level by considering various socio-economic factor of each country. In our model, the parameters are Education Index, GDP per capita, population density, high literacy and stable economy. To maximize the efficiency of the model, it has to be implemented in initial stage. However, strict application of the method in vigorous stage of epidemic will also bring a satisfactory outcome. Results: Higher social consciousness will decrease the number of infected population dramatically while minimal or lower awareness will do a outburst. Conclusion: Outbreak will be in control of health care system, lower the death rate and will ensure social and economic stability.