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Fulltext Simulation via instant messaging - Birmingham advance (SIMBA): an innovative simulation-based learning model that helped to keep medical education continue during the COVID-19 pandemic

Morgan G, Ooi E, Hanania T, Davitadze M, Zhou D, Blaggan P, et al.

Clin Med (Lond), 2021 Mar;21(Suppl 2):34-35.
PMID: 34078689 DOI: 10.7861/clinmed.21-2-s34
Matched MeSH terms: Pandemics/prevention & control
Fulltext A cross-sectional survey of self-medication with Traditional Chinese Medicine for treatment and prevention of COVID-19

Lin Y, Cai CZ, Alias H, Wong LP, Hu Z

Complement Ther Med, 2022 Dec;71:102898.
PMID: 36372316 DOI: 10.1016/j.ctim.2022.102898

OBJECTIVE: To investigate user behavioural profiles and the prevalence of self-medication with traditional Chinese medicine (TCM) for COVID-19 among the general public in China.
DESIGN: Cross-sectional study.
SETTING: Self-administered online survey was carried out between January and June 2021 in China.
RESULTS: A total of 1132 complete responses were received from a nationwide sample. A considerable proportion viewed TCM to be more effective than Western medicine for treating COVID-19 (67.1 %) and stated that it is safer to use TCM (63.5 %) and easier to access TCM for treating COVID-19 (63.5 %). A total of 16.4 % (95 %CI 14.3-18.7) reported ever self-medicating with TCM to resolve COVID-19 symptoms and 12.2 % (95 % CI 10.3-14.2) ever using TCM to prevent SARS-CoV-2 infection. Lianhua Qingwen capsule/granule (53.2 %), Ganmao granule (50.5 %) and Banlangen granule (44.6 %) were most commonly used to resolve COVID-19 symptoms whereas Banlangen granule (60.1 %) was commonly used for the prevention of SARS-CoV-2 infection. Older age participants, from rural areas, with chronic diseases, higher socioeconomic status, and a positive attitude towards TCM were more likely to self-medicate using TCM to resolve COVID-19 symptoms.
CONCLUSION: Self-medication with TCM during the COVID-19 pandemic for symptom control or prevention is prevalent. The findings of the user behavioural profile and types of TMCs commonly used in this study provide beneficial information for the development of strategies to improve public health-seeking behaviour and the performance of the country's healthcare system in the era of the COVID-19 pandemic.

Matched MeSH terms: Pandemics
Fulltext The Use of System Dynamics Methodology in Building a COVID-19 Confirmed Case Model

Mohd Yusoff MI

Comput Math Methods Med, 2020;2020:9328414.
PMID: 33224268 DOI: 10.1155/2020/9328414

Researchers used a hybrid model (a combination of health resource demand model and disease transmission model), Bayesian model, and susceptible-exposed-infectious-removed (SEIR) model to predict health service utilization and deaths and mixed-effect nonlinear regression. Further, they used the mixture model to predict the number of confirmed cases and deaths or to predict when the curve would flatten. In this article, we show, through scenarios developed using system dynamics methodology, besides close to real-world results, the detrimental effects of ignoring social distancing guidelines (in terms of the number of people infected, which decreased as the percentage of noncompliance decreased).

Matched MeSH terms: Pandemics/prevention & control; Pandemics/statistics & numerical data*
Fulltext Side chain similarity comparisons for integrated drug repositioning and potential toxicity assessments in epidemic response scenarios: The case for COVID-19

Ab Ghani NS, Emrizal R, Makmur H, Firdaus-Raih M

Comput Struct Biotechnol J, 2020;18:2931-2944.
PMID: 33101604 DOI: 10.1016/j.csbj.2020.10.013

Structures of protein-drug-complexes provide an atomic level profile of drug-target interactions. In this work, the three-dimensional arrangements of amino acid side chains in known drug binding sites (substructures) were used to search for similarly arranged sites in SARS-CoV-2 protein structures in the Protein Data Bank for the potential repositioning of approved compounds. We were able to identify 22 target sites for the repositioning of 16 approved drug compounds as potential therapeutics for COVID-19. Using the same approach, we were also able to investigate the potentially promiscuous binding of the 16 compounds to off-target sites that could be implicated in toxicity and side effects that had not been provided by any previous studies. The investigations of binding properties in disease-related proteins derived from the comparison of amino acid substructure arrangements allows for effective mechanism driven decision making to rank and select only the compounds with the highest potential for success and safety to be prioritized for clinical trials or treatments. The intention of this work is not to explicitly identify candidate compounds but to present how an integrated drug repositioning and potential toxicity pipeline using side chain similarity searching algorithms are of great utility in epidemic scenarios involving novel pathogens. In the case of the COVID-19 pandemic caused by the SARS-CoV-2 virus, we demonstrate that the pipeline can identify candidate compounds quickly and sustainably in combination with associated risk factors derived from the analysis of potential off-target site binding by the compounds to be repurposed.

Matched MeSH terms: Pandemics
Fulltext Exploiting reverse vaccinology approach for the design of a multiepitope subunit vaccine against the major SARS-CoV-2 variants

Campos DMO, Silva MKD, Barbosa ED, Leow CY, Fulco UL, Oliveira JIN

Comput Biol Chem, 2022 Dec;101:107754.
PMID: 36037724 DOI: 10.1016/j.compbiolchem.2022.107754

The current COVID-19 pandemic, an infectious disease caused by the novel coronavirus (SARS-CoV-2), poses a threat to global health because of its high rate of spread and death. Currently, vaccination is the most effective method to prevent the spread of this disease. In the present study, we developed a novel multiepitope vaccine against SARS-CoV-2 containing Alpha (B.1.1.7), Beta (B.1.351), Gamma (P.1), Delta (B.1.617.2), and Omicron (BA.1) variants. To this end, we performed a robust immunoinformatics approach based on multiple epitopes of the four structural proteins of SARS-CoV-2 (S, M, N, and E) from 475 SARS-CoV-2 genomes sequenced from the regions with the highest number of registered cases, namely the United States, India, Brazil, France, Germany, and the United Kingdom. To investigate the best immunogenic epitopes for linear B cells, cytotoxic T lymphocytes (CTL), and helper T lymphocytes (HTL), we evaluated antigenicity, allergenicity, conservation, immunogenicity, toxicity, human population coverage, IFN-inducing, post-translational modifications, and physicochemical properties. The tertiary structure of a vaccine prototype was predicted, refined, and validated. Through docking experiments, we evaluated its molecular coupling to the key immune receptor Toll-Like Receptor 3 (TLR3). To improve the quality of docking calculations, quantum mechanics/molecular mechanics calculations (QM/MM) were used, with the QM part of the simulations performed using the density functional theory formalism (DFT). Cloning and codon optimization were performed for the successful expression of the vaccine in E. coli. Finally, we investigated the immunogenic properties and immune response of our SARS-CoV-2 multiepitope vaccine. The results of the simulations show that administering our prototype three times significantly increases the antibody response and decreases the amount of antigens. The proposed vaccine candidate should therefore be tested in clinical trials for its efficacy in neutralizing SARS-CoV-2.

Matched MeSH terms: Pandemics/prevention & control
Fulltext Helping doctors hasten COVID-19 treatment: Towards a rescue framework for the transfusion of best convalescent plasma to the most critical patients based on biological requirements via ml and novel MCDM methods

Albahri OS, Al-Obaidi JR, Zaidan AA, Albahri AS, Zaidan BB, Salih MM, et al.

Comput Methods Programs Biomed, 2020 Nov;196:105617.
PMID: 32593060 DOI: 10.1016/j.cmpb.2020.105617

CONTEXT: People who have recently recovered from the threat of deteriorating coronavirus disease-2019 (COVID-19) have antibodies to the coronavirus circulating in their blood. Thus, the transfusion of these antibodies to deteriorating patients could theoretically help boost their immune system. Biologically, two challenges need to be surmounted to allow convalescent plasma (CP) transfusion to rescue the most severe COVID-19 patients. First, convalescent subjects must meet donor selection plasma criteria and comply with national health requirements and known standard routine procedures. Second, multi-criteria decision-making (MCDM) problems should be considered in the selection of the most suitable CP and the prioritisation of patients with COVID-19.
OBJECTIVE: This paper presents a rescue framework for the transfusion of the best CP to the most critical patients with COVID-19 on the basis of biological requirements by using machine learning and novel MCDM methods.
METHOD: The proposed framework is illustrated on the basis of two distinct and consecutive phases (i.e. testing and development). In testing, ABO compatibility is assessed after classifying donors into the four blood types, namely, A, B, AB and O, to indicate the suitability and safety of plasma for administration in order to refine the CP tested list repository. The development phase includes patient and donor sides. In the patient side, prioritisation is performed using a contracted patient decision matrix constructed between 'serological/protein biomarkers and the ratio of the partial pressure of oxygen in arterial blood to fractional inspired oxygen criteria' and 'patient list based on novel MCDM method known as subjective and objective decision by opinion score method'. Then, the patients with the most urgent need are classified into the four blood types and matched with a tested CP list from the test phase in the donor side. Thereafter, the prioritisation of CP tested list is performed using the contracted CP decision matrix.
RESULT: An intelligence-integrated concept is proposed to identify the most appropriate CP for corresponding prioritised patients with COVID-19 to help doctors hasten treatments.
DISCUSSION: The proposed framework implies the benefits of providing effective care and prevention of the extremely rapidly spreading COVID-19 from affecting patients and the medical sector.

Matched MeSH terms: Pandemics
Fulltext Scenario analysis of COVID-19 transmission dynamics in Malaysia with the possibility of reinfection and limited medical resources scenarios

Salman AM, Ahmed I, Mohd MH, Jamiluddin MS, Dheyab MA

Comput Biol Med, 2021 06;133:104372.
PMID: 33864970 DOI: 10.1016/j.compbiomed.2021.104372

COVID-19 is a major health threat across the globe, which causes severe acute respiratory syndrome (SARS), and it is highly contagious with significant mortality. In this study, we conduct a scenario analysis for COVID-19 in Malaysia using a simple universality class of the SIR system and extensions thereof (i.e., the inclusion of temporary immunity through the reinfection problems and limited medical resources scenarios leads to the SIRS-type model). This system has been employed in order to provide further insights on the long-term outcomes of COVID-19 pandemic. As a case study, the COVID-19 transmission dynamics are investigated using daily confirmed cases in Malaysia, where some of the epidemiological parameters of this system are estimated based on the fitting of the model to real COVID-19 data released by the Ministry of Health Malaysia (MOH). We observe that this model is able to mimic the trend of infection trajectories of COVID-19 pandemic in Malaysia and it is possible for transmission dynamics to be influenced by the reinfection force and limited medical resources problems. A rebound effect in transmission could occur after several years and this situation depends on the intensity of reinfection force. Our analysis also depicts the existence of a critical value in reinfection threshold beyond which the infection dynamics persist and the COVID-19 outbreaks are rather hard to eradicate. Therefore, understanding the interplay between distinct epidemiological factors using mathematical modelling approaches could help to support authorities in making informed decisions so as to control the spread of this pandemic effectively.

Matched MeSH terms: Pandemics*
Fulltext Application of deep learning technique to manage COVID-19 in routine clinical practice using CT images: Results of 10 convolutional neural networks

Ardakani AA, Kanafi AR, Acharya UR, Khadem N, Mohammadi A

Comput Biol Med, 2020 06;121:103795.
PMID: 32568676 DOI: 10.1016/j.compbiomed.2020.103795

Fast diagnostic methods can control and prevent the spread of pandemic diseases like coronavirus disease 2019 (COVID-19) and assist physicians to better manage patients in high workload conditions. Although a laboratory test is the current routine diagnostic tool, it is time-consuming, imposing a high cost and requiring a well-equipped laboratory for analysis. Computed tomography (CT) has thus far become a fast method to diagnose patients with COVID-19. However, the performance of radiologists in diagnosis of COVID-19 was moderate. Accordingly, additional investigations are needed to improve the performance in diagnosing COVID-19. In this study is suggested a rapid and valid method for COVID-19 diagnosis using an artificial intelligence technique based. 1020 CT slices from 108 patients with laboratory proven COVID-19 (the COVID-19 group) and 86 patients with other atypical and viral pneumonia diseases (the non-COVID-19 group) were included. Ten well-known convolutional neural networks were used to distinguish infection of COVID-19 from non-COVID-19 groups: AlexNet, VGG-16, VGG-19, SqueezeNet, GoogleNet, MobileNet-V2, ResNet-18, ResNet-50, ResNet-101, and Xception. Among all networks, the best performance was achieved by ResNet-101 and Xception. ResNet-101 could distinguish COVID-19 from non-COVID-19 cases with an AUC of 0.994 (sensitivity, 100%; specificity, 99.02%; accuracy, 99.51%). Xception achieved an AUC of 0.994 (sensitivity, 98.04%; specificity, 100%; accuracy, 99.02%). However, the performance of the radiologist was moderate with an AUC of 0.873 (sensitivity, 89.21%; specificity, 83.33%; accuracy, 86.27%). ResNet-101 can be considered as a high sensitivity model to characterize and diagnose COVID-19 infections, and can be used as an adjuvant tool in radiology departments.

Matched MeSH terms: Pandemics
Fulltext Classification of SARS-CoV-2 and non-SARS-CoV-2 using machine learning algorithms

Singh OP, Vallejo M, El-Badawy IM, Aysha A, Madhanagopal J, Mohd Faudzi AA

Comput Biol Med, 2021 Sep;136:104650.
PMID: 34329865 DOI: 10.1016/j.compbiomed.2021.104650

Due to the continued evolution of the SARS-CoV-2 pandemic, researchers worldwide are working to mitigate, suppress its spread, and better understand it by deploying digital signal processing (DSP) and machine learning approaches. This study presents an alignment-free approach to classify the SARS-CoV-2 using complementary DNA, which is DNA synthesized from the single-stranded RNA virus. Herein, a total of 1582 samples, with different lengths of genome sequences from different regions, were collected from various data sources and divided into a SARS-CoV-2 and a non-SARS-CoV-2 group. We extracted eight biomarkers based on three-base periodicity, using DSP techniques, and ranked those based on a filter-based feature selection. The ranked biomarkers were fed into k-nearest neighbor, support vector machines, decision trees, and random forest classifiers for the classification of SARS-CoV-2 from other coronaviruses. The training dataset was used to test the performance of the classifiers based on accuracy and F-measure via 10-fold cross-validation. Kappa-scores were estimated to check the influence of unbalanced data. Further, 10 × 10 cross-validation paired t-test was utilized to test the best model with unseen data. Random forest was elected as the best model, differentiating the SARS-CoV-2 coronavirus from other coronaviruses and a control a group with an accuracy of 97.4 %, sensitivity of 96.2 %, and specificity of 98.2 %, when tested with unseen samples. Moreover, the proposed algorithm was computationally efficient, taking only 0.31 s to compute the genome biomarkers, outperforming previous studies.

Matched MeSH terms: Pandemics
Fulltext Mathematical modeling of COVID-19 pandemic in India using Caputo-Fabrizio fractional derivative

Pandey P, Gómez-Aguilar JF, Kaabar MKA, Siri Z, Mousa AAA

Comput Biol Med, 2022 Jun;145:105518.
PMID: 35447461 DOI: 10.1016/j.compbiomed.2022.105518

The range of effectiveness of the novel corona virus, known as COVID-19, has been continuously spread worldwide with the severity of associated disease and effective variation in the rate of contact. This paper investigates the COVID-19 virus dynamics among the human population with the prediction of the size of epidemic and spreading time. Corona virus disease was first diagnosed on January 30, 2020 in India. From January 30, 2020 to April 21, 2020, the number of patients was continuously increased. In this scientific work, our main objective is to estimate the effectiveness of various preventive tools adopted for COVID-19. The COVID-19 dynamics is formulated in which the parameters of interactions between people, contact tracing, and average latent time are included. Experimental data are collected from April 15, 2020 to April 21, 2020 in India to investigate this virus dynamics. The Genocchi collocation technique is applied to investigate the proposed fractional mathematical model numerically via Caputo-Fabrizio fractional derivative. The effect of presence of various COVID parameters e.g. quarantine time is also presented in the work. The accuracy and efficiency of the outputs of the present work are demonstrated through the pictorial presentation by comparing it to known statistical data. The real data for COVID-19 in India is compared with the numerical results obtained from the concerned COVID-19 model. From our results, to control the expansion of this virus, various prevention measures must be adapted such as self-quarantine, social distancing, and lockdown procedures.

Matched MeSH terms: Pandemics/prevention & control
Fulltext Telehealth utilization during the Covid-19 pandemic: A systematic review

Garfan S, Alamoodi AH, Zaidan BB, Al-Zobbi M, Hamid RA, Alwan JK, et al.

Comput Biol Med, 2021 Nov;138:104878.
PMID: 34592585 DOI: 10.1016/j.compbiomed.2021.104878

During the coronavirus disease (COVID-19) pandemic, different technologies, including telehealth, are maximised to mitigate the risks and consequences of the disease. Telehealth has been widely utilised because of its usability and safety in providing healthcare services during the COVID-19 pandemic. However, a systematic literature review which provides extensive evidence on the impact of COVID-19 through telehealth and which covers multiple directions in a large-scale research remains lacking. This study aims to review telehealth literature comprehensively since the pandemic started. It also aims to map the research landscape into a coherent taxonomy and characterise this emerging field in terms of motivations, open challenges and recommendations. Articles related to telehealth during the COVID-19 pandemic were systematically searched in the WOS, IEEE, Science Direct, Springer and Scopus databases. The final set included (n = 86) articles discussing telehealth applications with respect to (i) control (n = 25), (ii) technology (n = 14) and (iii) medical procedure (n = 47). Since the beginning of the pandemic, telehealth has been presented in diverse cases. However, it still warrants further attention. Regardless of category, the articles focused on the challenges which hinder the maximisation of telehealth in such times and how to address them. With the rapid increase in the utilization of telehealth in different specialised hospitals and clinics, a potential framework which reflects the authors' implications of the future application and opportunities of telehealth has been established. This article improves our understanding and reveals the full potential of telehealth during these difficult times and beyond.

Matched MeSH terms: Pandemics/prevention & control
Patients' Technology Readiness and eHealth Literacy: Implications for Adoption and Deployment of eHealth in the COVID-19 Era and Beyond

Lee WL, Lim ZJ, Tang LY, Yahya NA, Varathan KD, Ludin SM

Comput Inform Nurs, 2021 Nov 02;40(4):244-250.
PMID: 34740221 DOI: 10.1097/CIN.0000000000000854

The COVID-19 pandemic has rerouted the healthcare ecosystem by accelerating digital health, and rapid adoption of eHealth is partly influenced by eHealth literacy (eHL). This study aims to examine patients' eHL in relation to their "technology readiness"-an innate attitude that is underexplored in clinical research. A total of 276 adult inpatients with hypertension, diabetes mellitus, and coronary heart disease were surveyed cross-sectionally in 2019 using self-reported questionnaires: eHealth Literacy Scale and Technology Readiness Index (2.0). The study found moderate eHL (mean, 27.38) and moderate technology readiness (mean, 3.03) among patients. The hierarchical regression model shows that lower eHL scores were associated with patients of minor ethnicity (Malaysian Chinese), with an unemployed status, and having >1 cardiovascular risk (β = -0.136 to -0.215, R2 = 0.283, Ps < .005). Technology readiness is a strong determinant of eHL (ΔR2 = 0.295, P < .001) with its subdomains (optimism, innovativeness, and discomfort) significantly influencing eHL (|β| = 0.28-0.40, Ps < .001), except for the insecurity subdomain. Deployment of eHealth interventions that incorporate assessment of patients' eHL and technology readiness will enable targeted strategies, especially in resource-limited settings hit hard by the pandemic crisis.

Matched MeSH terms: Pandemics/prevention & control
Fulltext Letter to the Editor in response to "COVID-19: desperate times call for desperate measures"

Chase JG, Chiew YS, Lambermont B, Morimont P, Shaw GM, Desaive T

Crit Care, 2020 07 10;24(1):415.
PMID: 32650807 DOI: 10.1186/s13054-020-03152-6
Matched MeSH terms: Pandemics*
Deploying aptameric sensing technology for rapid pandemic monitoring

Acquah C, Danquah MK, Agyei D, Moy CK, Sidhu A, Ongkudon CM

Crit Rev Biotechnol, 2016 Dec;36(6):1010-1022.
PMID: 26381238

The genome of virulent strains may possess the ability to mutate by means of antigenic shift and/or antigenic drift as well as being resistant to antibiotics with time. The outbreak and spread of these virulent diseases including avian influenza (H1N1), severe acute respiratory syndrome (SARS-Corona virus), cholera (Vibrio cholera), tuberculosis (Mycobacterium tuberculosis), Ebola hemorrhagic fever (Ebola Virus) and AIDS (HIV-1) necessitate urgent attention to develop diagnostic protocols and assays for rapid detection and screening. Rapid and accurate detection of first cases with certainty will contribute significantly in preventing disease transmission and escalation to pandemic levels. As a result, there is a need to develop technologies that can meet the heavy demand of an all-embedded, inexpensive, specific and fast biosensing for the detection and screening of pathogens in active or latent forms to offer quick diagnosis and early treatments in order to avoid disease aggravation and unnecessary late treatment costs. Nucleic acid aptamers are short, single-stranded RNA or DNA sequences that can selectively bind to specific cellular and biomolecular targets. Aptamers, as new-age bioaffinity probes, have the necessary biophysical characteristics for improved pathogen detection. This article seeks to review global pandemic situations in relation to advances in pathogen detection systems. It particularly discusses aptameric biosensing and establishes application opportunities for effective pandemic monitoring. Insights into the application of continuous polymeric supports as the synthetic base for aptamer coupling to provide the needed convective mass transport for rapid screening is also presented.

Matched MeSH terms: Pandemics*
Outcomes of an In Vitro Fertilization Pregnancy With COVID-19 and the Perinatal Outcome in Riyadh, Saudi Arabia

Alhamoud AH, Matary F, Bukhari S, Kelantan M, Bajahzer M

Cureus, 2020 Dec 26;12(12):e12296.
PMID: 33510990 DOI: 10.7759/cureus.12296

Coronavirus disease 2019 (COVID-19) caused by the novel severe respiratory syndrome coronavirus 2 (SARS-CoV-2) is a pandemic and potentially fatal disease. COVID-19 cases are on the rise globally; this also includes risk groups such as pregnant women and neonates. Herein, we report the first COVID-19 cesarean delivery case of an in vitro fertilization (IVF) pregnancy in a Saudi woman. A postdate pregnant healthy woman tested positive with COVID-19 on her 38 weeks + five days. On her 40 weeks + five days, the woman had dilation without contractions; thereby, cesarean delivery was decided. The delivery was successful, with no complications in the mother and neonate. The preferable outcomes of this case could be attributable to some factors: multidisciplinary medical management, the mother's young age, and COVID-19 infection during the late trimester.

Matched MeSH terms: Pandemics
Fulltext Probable Pangolin Origin of SARS-CoV-2 Associated with the COVID-19 Outbreak

Zhang T, Wu Q, Zhang Z

Curr Biol, 2020 04 06;30(7):1346-1351.e2.
PMID: 32197085 DOI: 10.1016/j.cub.2020.03.022

An outbreak of coronavirus disease 2019 (COVID-19) caused by the 2019 novel coronavirus (SARS-CoV-2) began in the city of Wuhan in China and has widely spread worldwide. Currently, it is vital to explore potential intermediate hosts of SARS-CoV-2 to control COVID-19 spread. Therefore, we reinvestigated published data from pangolin lung samples from which SARS-CoV-like CoVs were detected by Liu et al. [1]. We found genomic and evolutionary evidence of the occurrence of a SARS-CoV-2-like CoV (named Pangolin-CoV) in dead Malayan pangolins. Pangolin-CoV is 91.02% and 90.55% identical to SARS-CoV-2 and BatCoV RaTG13, respectively, at the whole-genome level. Aside from RaTG13, Pangolin-CoV is the most closely related CoV to SARS-CoV-2. The S1 protein of Pangolin-CoV is much more closely related to SARS-CoV-2 than to RaTG13. Five key amino acid residues involved in the interaction with human ACE2 are completely consistent between Pangolin-CoV and SARS-CoV-2, but four amino acid mutations are present in RaTG13. Both Pangolin-CoV and RaTG13 lost the putative furin recognition sequence motif at S1/S2 cleavage site that can be observed in the SARS-CoV-2. Conclusively, this study suggests that pangolin species are a natural reservoir of SARS-CoV-2-like CoVs.

Matched MeSH terms: Pandemics
Fulltext The population genomic legacy of the second plague pandemic

Gopalakrishnan S, Ebenesersdóttir SS, Lundstrøm IKC, Turner-Walker G, Moore KHS, Luisi P, et al.

Curr Biol, 2022 Nov 07;32(21):4743-4751.e6.
PMID: 36182700 DOI: 10.1016/j.cub.2022.09.023

Human populations have been shaped by catastrophes that may have left long-lasting signatures in their genomes. One notable example is the second plague pandemic that entered Europe in ca. 1,347 CE and repeatedly returned for over 300 years, with typical village and town mortality estimated at 10%-40%.1 It is assumed that this high mortality affected the gene pools of these populations. First, local population crashes reduced genetic diversity. Second, a change in frequency is expected for sequence variants that may have affected survival or susceptibility to the etiologic agent (Yersinia pestis).2 Third, mass mortality might alter the local gene pools through its impact on subsequent migration patterns. We explored these factors using the Norwegian city of Trondheim as a model, by sequencing 54 genomes spanning three time periods: (1) prior to the plague striking Trondheim in 1,349 CE, (2) the 17th-19th century, and (3) the present. We find that the pandemic period shaped the gene pool by reducing long distance immigration, in particular from the British Isles, and inducing a bottleneck that reduced genetic diversity. Although we also observe an excess of large FST values at multiple loci in the genome, these are shaped by reference biases introduced by mapping our relatively low genome coverage degraded DNA to the reference genome. This implies that attempts to detect selection using ancient DNA (aDNA) datasets that vary by read length and depth of sequencing coverage may be particularly challenging until methods have been developed to account for the impact of differential reference bias on test statistics.

Matched MeSH terms: Pandemics/history
Knowledge, attitude and practice towards COVID-19 and perceived challenges of working during the movement control order: a quantitative analysis among healthcare workers in a Malaysian northwestern state

Anuar A, Ang WC, Ahmad Musadad NM, Abdol Wahab SN, Abdul Sukur N, Warijo O

Curr Med Res Opin, 2022 02;38(2):327-338.
PMID: 34719309 DOI: 10.1080/03007995.2021.2000738

OBJECTIVE: This study aimed to assess COVID-19 knowledge, attitude and practice (KAP) among healthcare workers (HCWs) in northwest Malaysia and recognize the challenges faced working during the Movement Control Order (MCO). Commonly referred to as "MCO", this order enforcement is a series of national quarantine and cordon sanitaire measures implemented by the federal government of Malaysia in response to the COVID-19 pandemic as of 18th March 2020. It is akin to a national lockdown.
METHODS: A multi-centric cross-sectional web-based study was conducted from 29th May to 27th July 2020 among HCWs in Perlis, Malaysia using a 19-item validated questionnaire [Cronbach's alpha: 0.61 (knowledge domain), 0.74 (attitude domain), and 0.72 (practice domain)]. Challenges when working during MCO were identified from a self-rated five-point Likert scale of 14-item.
RESULTS: There were a total of 373 respondents (response rate more than 40%); 48.0% were nurses, 14.7% were medical doctors, and 12.9% were administrative and technical support staffs. Majority of HCWs (90.1%, n = 336) had good knowledge, optimistic attitude (54.7%, n = 204) and good COVID-19 preventive measure practices (90.9%, n = 339). Multiple logistic regression demonstrated that profession was the single significant factor for good COVID-19 KAP. Though having lesser odds of good knowledge (aOR 0.07, 95% CI:0.01-0.36, p = .009), nurses showed greater odds of good attitude (aOR 3.14, 95% CI: 1.71-5.76, p = .011) and practice (aOR 10.69, 95% CI:2.25-50.86, p = .022) as compared to doctors and dentists. Main challenges identified when working during MCO were increased workload (44.5%, n = 166), difficulty going out shopping (48.3%, n = 180), to exercise (40.2%, n = 150) and meet with family members (64.3%, n = 240).
CONCLUSION: Generally, HCWs in Perlis had good KAP with regards to COVID-19 infection and its preventive measures. Challenges underlined by HCWs while working during the MCO were increased workload, difficulty to shop for daily essentials, exercise and meet with family members. Should good COVID-19 KAP be sustained, they might contribute to success in combating this disease.

Matched MeSH terms: Pandemics
SARS-CoV-2 Infection, Inflammation, Immunonutrition, and Pathogenesis of COVID-19

Yu L, Abd Ghani MK, Aghemo A, Barh D, Bassetti M, Catena F, et al.

Curr Med Chem, 2023;30(39):4390-4408.
PMID: 36998130 DOI: 10.2174/0929867330666230330092725

The COVID-19 pandemic, caused by the coronavirus, SARS-CoV-2, has claimed millions of lives worldwide in the past two years. Fatalities among the elderly with underlying cardiovascular disease, lung disease, and diabetes have particularly been high. A bibliometrics analysis on author's keywords was carried out, and searched for possible links between various coronavirus studies over the past 50 years, and integrated them. We found keywords like immune system, immunity, nutrition, malnutrition, micronutrients, exercise, inflammation, and hyperinflammation were highly related to each other. Based on these findings, we hypothesized that the human immune system is a multilevel super complex system, which employs multiple strategies to contain microorganism infections and restore homeostasis. It was also found that the behavior of the immune system is not able to be described by a single immunological theory. However, one main strategy is "self-destroy and rebuild", which consists of a series of inflammatory responses: 1) active self-destruction of damaged/dysfunctional somatic cells; 2) removal of debris and cells; 3) rebuilding tissues. Thus, invading microorganisms' clearance could be only a passive bystander response to this destroy-rebuild process. Microbial infections could be self-limiting and promoted as an indispensable essential nutrition for the vast number of genes existing in the microorganisms. The transient nutrition surge resulting from the degradation of the self-destroyed cell debris coupled with the existing nutrition state in the patient may play an important role in the pathogenesis of COVID-19. Finally, a few possible coping strategies to mitigate COVID-19, including vaccination, are discussed.

Matched MeSH terms: Pandemics
Fulltext Remote extemporaneous compounding lab practical for pharmacy students during the COVID-19 pandemic

Dujaili J, Ong WK, Kc B, Vordenberg SE, Mattingly AN, Lee RFS

Curr Pharm Teach Learn, 2023 Jun;15(6):624-632.
PMID: 37357124 DOI: 10.1016/j.cptl.2023.06.012

BACKGROUND AND PURPOSE: Due to COVID-19 movement restrictions, institutes of higher learning had to deliver pharmacy curricula remotely. One major challenge was teaching practical lab skills, such as extemporaneous compounding, remotely due to the need for hands-on learning and its associated logistical requirements.
EDUCATIONAL ACTIVITY AND SETTING: We present the approach to remote extemporaneous compounding teaching taken by three pharmacy schools: Monash University Malaysia, University of Michigan, and University of Maryland. Prior to delivery, students were either supplied with or asked to procure a set of easily accessible ingredients and equipment to conduct the extemporaneous practicals from home. We conducted lessons remotely using both synchronous and asynchronous delivery, and demonstrated, taught, and assessed practical lab skills using video conferencing modalities.
FINDINGS: We successfully conducted remote teaching of extemporaneous compounding, where similar learning outcomes to the face-to-face implementation were achieved. At Monash University Malaysia, > 90% of students responding to the post-activity surveys found the remote extemporaneous sessions useful for their learning, and qualitative comments supported these views. Mean scores from the remote extemporaneous labs in 2021 were similar to those when conducted physically in 2019, supporting the effectiveness of the approach. The different approaches attempted by the three institutions highlighted the flexibility in implementation that can be considered to achieve similar outcomes.
SUMMARY: Combining technology-based approaches with synchronous and asynchronous teaching and learning methods can successfully deliver extemporaneous compounding skills remotely.

Matched MeSH terms: Pandemics

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