Logistics Hub Location Optimization: A K-Means and P-Median Model Hybrid Approach Using Road Network Distances (preprint)

Logistic hubs play a pivotal role in the last-mile delivery distance; even a slight increment in distance negatively impacts the business of the e-commerce industry while also increasing its carbon footprint. The growth of this industry, particularly after Covid-19, has further intensified the need for optimized allocation of resources in an urban environment. In this study, we use a hybrid approach to optimize the placement of logistic hubs. The approach sequentially employs different techniques. Initially, delivery points are clustered using K-Means in relation to their spatial locations. The clustering method utilizes road network distances as opposed to Euclidean distances. Non-road network-based approaches have been avoided since they lead to erroneous and misleading results. Finally, hubs are located using the P-Median method. The P-Median method also incorporates the number of deliveries and population as weights. Real-world delivery data from Muller and Phipps (M&P) is used to demonstrate the effectiveness of the approach. Serving deliveries from the optimal hub locations results in the saving of 815 (10%) meters per delivery.

Clinical Spectrum of COVID-19 Patients after Vaccination

Objective: To examine the clinical severity and magnitude of COVID-19 patients after the second dose of the COVID-19 vaccine. Study Design: Cross-sectional study. Place and Duration of Study: Tertiary Care Hospital, Islamabad Pakistan, from Feb to Jun 2021. Methodology: The individuals who had two doses of the vaccine (dead inactivated-Vero Cell) and got COVID-19 at least two weeks after vaccination were included in the study. These patients were divided into Mild, Moderate and Severe categories based on their symptoms and Investigations. Results: Out of 5000 individuals vaccinated, 225(4.5%) got infected with COVID-19 later. Among these 225, 172(76.4%) had mild symptoms and recovered, with only 1(0.4%) death was reported. Conclusion: COVID-19 vaccination does not infer 100% immunity, but if someone gets infected with COVID after vaccination, there are remarkable chances of recovery.

Evaluation of Core Coordination Strategies and Concept of Operations implemented during activation of Public Health Emergency Operations Center for COVID-19 Response in Pakistan (preprint)

Background: Public health emergency management systems encountered difficulties in developing countries, especially in Pakistan. The COVID-19 pandemic was extremely challenging for different agencies, departments, and institutions in Pakistan. Public health emergency management depends on a well-established public health emergency operations center that could generate a coordinated response to escalated incidents. We conducted an assessment of public health emergency response and coordination implemented during the COVID-19 pandemic management at a strategic level in Pakistan. Methods: This was mix-method study including qualitative and quantitative data collection processes implemented in 2022-23. Primary data was collected by using a structured questionnaire, and secondary data was collected by desk review. The agencies engaged in pandemic response at the national level in Pakistan were included in the assessment. Results: The overall score of the emergency response coordination system during COVID-19 was 49% for all agencies. We found that agencies faced challenges in leadership, legislation, and financing issues during the pandemic response (44%). None of the agencies had a fully developed framework for joint planning and response system for health emergencies. Roles and responsibilities attached to designated agencies in response were relatively clear (55%) for most of the agencies. Conclusion: An effective public health emergency response is based on multi-departmental coordination, resource mobilization, and correct information. Pakistan must proactively address these and other relevant challenges for future pandemic response.

Elevated plasma CAF22 are incompletely restored six months after COVID-19 infection in older men.

INTRODUCTION: The long-term complications of COVID-19 appear as significant health problems. However, the long-term muscle decline in these patients is poorly characterized. METHODS: We investigated the age-related muscle decline, termed sarcopenia, before and following the COVID-19 infection in older male patients (n = 87). We evaluated handgrip strength (HGS) and functional capacity (short physical performance battery; SPPB) in COVID-19 patients 7-42 days before and one week and 6-month after COVID-19 infection. We used ELISA tests to measure plasma c-terminal agrin fragment-22 (CAF22), c-reactive protein (CRP), and 8-isoprostanes as markers of degraded neuromuscular junctions, inflammation, and oxidative stress, respectively. RESULTS: Before the COVID-19 infection, 54 patients were non-sarcopenic, and 25 patients were sarcopenic, while eight patients subsequently developed sarcopenia. All patients exhibited reduced HGS and SPPB, while elevated CAF22, CRP, and 8-isoprostane levels one week post-COVID-19 infection (all p < 0.05). At six months post-COVID-19 infection, the HGS, SPPB, CAF22, CRP, and 8-isoprostanes were partly restored to baseline levels (all p < 0.05). Correlation analysis revealed that the plasma CAF22 had a significant correlation with HGS, SPPB, and COVID-19 disease severity. CAF22 also demonstrated significant areas under the curves in diagnosing sarcopenia at all three time-points. CONCLUSION: Altogether, the muscle detriment due to COVID-19 persists six months post-infection, and plasma CAF22 may be helpful to detect muscle and functional decline in these patients. Timely evaluation and intervention of sarcopenia may be critical in COVID-19 treatment.

Do the green bonds overreact to the COVID-19 pandemic?

This paper explores the impacts of the COVID-19 pandemic on the global green bond and conventional assets, including commodity, treasury, stock and clean energy markets, using Diebold and Yilmaz (2012) and Baruník and Krehlík, 2018b spillover framework. The results show that spillover transmitted from COVID-19 is relatively strong over a medium- and long-term horizon, and the spillover effects sharply increased when the pandemic became severe. Furthermore, green bonds are most affected by the COVID-19 pandemic, followed by the treasury, while the other conventional assets are only slightly affected. Additionally, our findings also contain a low-risk portfolio during COVID-19 pandemic.

Emerging mutations in envelope protein of SARS-CoV-2 and their effect on thermodynamic properties.

Structural proteins of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are potential drug targets due to their role in the virus life cycle. The envelope (E) protein is one of the structural proteins; plays a critical role in virulency. However, the emergence of mutations oftenly leads to drug resistance and may also play a vital role in virus stabilization and evolution. In this study, we aimed to identify mutations in E proteins that affect the protein stability. About 0.3 million complete whole genome sequences were analyzed to screen mutations in E protein. All these mutations were subjected to stability prediction using the DynaMut server. The most common mutations that were detected at the C-terminal domain, Ser68Phe, Pro71Ser, and Leu73Phe, were examined through molecular dynamics (MD) simulations for a 100ns period. The sequence analysis shows the existence of 259 mutations in E protein. Interestingly, 16 of them were detected in the DFLV amino acid (aa) motif (aa72-aa75) that binds the host PALS1 protein. The results of root mean square deviation, fluctuations, radius of gyration, and free energy landscape show that Ser68Phe, Pro71Ser, and Leu73Phe are exhibiting a more stabilizing effect. However, a more comprehensive experimental study may be required to see the effect on virus pathogenicity. Potential antiviral drugs, and vaccines may be developed used after screening the genomic variations for better management of SARS-CoV-2 infections.

Classification and Detection of COVID-19 and Other Chest-Related Diseases Using Transfer Learning.

COVID-19 has infected millions of people worldwide over the past few years. The main technique used for COVID-19 detection is reverse transcription, which is expensive, sensitive, and requires medical expertise. X-ray imaging is an alternative and more accessible technique. This study aimed to improve detection accuracy to create a computer-aided diagnostic tool. Combining other artificial intelligence applications techniques with radiological imaging can help detect different diseases. This study proposes a technique for the automatic detection of COVID-19 and other chest-related diseases using digital chest X-ray images of suspected patients by applying transfer learning (TL) algorithms. For this purpose, two balanced datasets, Dataset-1 and Dataset-2, were created by combining four public databases and collecting images from recently published articles. Dataset-1 consisted of 6000 chest X-ray images with 1500 for each class. Dataset-2 consisted of 7200 images with 1200 for each class. To train and test the model, TL with nine pretrained convolutional neural networks (CNNs) was used with augmentation as a preprocessing method. The network was trained to classify using five classifiers: two-class classifier (normal and COVID-19); three-class classifier (normal, COVID-19, and viral pneumonia), four-class classifier (normal, viral pneumonia, COVID-19, and tuberculosis (Tb)), five-class classifier (normal, bacterial pneumonia, COVID-19, Tb, and pneumothorax), and six-class classifier (normal, bacterial pneumonia, COVID-19, viral pneumonia, Tb, and pneumothorax). For two, three, four, five, and six classes, our model achieved a maximum accuracy of 99.83, 98.11, 97.00, 94.66, and 87.29%, respectively.

Infectious disease and corporate activities

We investigate the effect of equity market volatility due to infectious disease on U.S. firms’ corporate activities from 1985 to 2020. Consistent with the theoretical framework, firms decrease their debt levels, debt maturity, corporate investments and dividend payout, and increase their cash holdings, research and development expenditure.

Renessans Helps in Early Clearance of SARS-CoV-2: In-Vivo Activity of the Iodine Complex in Rhesus macaque.

Iodine complexes have known antimicrobial properties along with reported in-vitro antiviral activity for several viruses. Renessans is one such product with iodine complexes and ascorbic acid. The present study was designed to determine its efficacy for SARS-CoV-2 in Rhesus macaque. Rhesus macaque were assigned to: A) prophylactic group (n = 3), (B) treatment group (n = 3), (C) infection control group (n = 4), and (D) negative control group (n = 4). Groups A, B, and C were challenged with 2 × 106 TCID of SARS-CoV-2. The prophylactic group (A) was administered Renessans from 5 days before infection till 8 days postinfection (DPI). The treatment group (B) was administered Renessans from 3 till 8 DPI. Group C was administered water-insoluble fractions only. Nasal swabs from all monkeys of groups A, B, and C remained positive for SARS-CoV-2 till 2 and 7 DPI, while the swabs became negative for groups A and B at 14 DPI. Likewise, fecal matter of monkeys in group A returned negative results during the experiment, while that of group B had significantly decreased viral load (101.5 genome copies/mL) compared to group C (103 genome copies/mL). Hence, it is concluded that Renessans has in-vivo SARS-CoV-2 activity and may result in early clearance of SARS-CoV-2.

Bio-Inspired Modelling of Disease Through Delayed Strategies

In 2020, the reported cases were 0.12 million in the six regions to the official report of the World Health Organization (WHO). For most children infected with leprosy, 0.008629 million cases were detected under fifteen. The total infected ratio of the children population is approximately 4.4 million. Due to the COVID-19 pandemic, the awareness programs implementation has been disturbed. Leprosy disease still has a threat and puts people in danger. Nonlinear delayed modeling is critical in various allied sciences, including computational biology, computational chemistry, computational physics, and computational economics, to name a few. The time delay effect in treating leprosy delayed epidemic model is investigated. The whole population is divided into four groups: those who are susceptible, those who have been exposed, those who have been infected, and those who have been vaccinated. The local and global stability of well-known conclusions like the Routh Hurwitz criterion and the Lyapunov function has been proven. The parameters’ sensitivity is also examined. The analytical analysis is supported by computer results that are presented in a variety of ways. The proposed approach in this paper preserves equilibrium points and their stabilities, the existence and uniqueness of solutions, and the computational ease of implementation.

Trudeau Vs Trump During COVID-19 Pandemic- A CDA Study

The examination tried to research how the language utilized in Donald Trump's and Justin Trudeau's Speeches given on the pinnacle of the expansion of COVID-19. The explicit focus was on how language is utilized to connote, produce and challenge inconsistent force relations. Likewise, the investigation not just tried to unload how the language utilized serves belief system and force, yet in addition how it empowers a superior comprehension of the political reason for the talks. The examination utilized a subjective exploration plan. Fairclough's (1989, 2010) three-level model of depiction, understanding, and clarification was utilized by zeroing in on both miniature and full-scale talk investigation. Then again, a linguistic portrayal of belief system, force, and predominance was uncovered: the talk shows the relationship of America with different nations and the activities taken by both the leader of a superpower and a non-super power. The investigation uncovered that Donald Trump set himself in the principal position and sees himself as generally able than some other government, the situation of most noteworthy accentuation, which is my hypothesis depicts him as egotistical and troublesome. Then again Prime Minister Justin Trudeau depicts himself as a profoundly sympathetic leader. He is taken the circumstance of the pandemic genuinely and taken intense measures.

Development of Protective Cotton Textiles Against Biohazards and Harmful UV Radiation Using Eco-Friendly Novel Fiber-Reactive Bioactive Agent

Due to the increase in biological hazards to global security particularly after COVID-19 crises, the need to develop effective and adaptable technologies to protect humans from biological warfare agents (viruses, bacteria, fungi) has increased. Current protective textiles against biohazards are fabricated through finishing of textiles with bioactive agents. However, bioactive agents are leached from the treated textiles due to the poor durability following their accumulation in environment. The objective of this research was to design a sustainable approach for developing ecologically sound antimicrobial textiles in which the antimicrobial agent is covalently bonded to fabric and does not leach into the effluent when laundered. For this, a novel bifunctional reactive finish was synthesized in which chloroxylenol (antimicrobial agent) was covalently integrated into two reactive systems (triazine and vinyl sulfone). For structural validation, 13C-NMR, 1H-NMR, and, FTIR characterization were employed. The as-synthesized reactive finish was applied on the cotton fabric through pad-dry-cure method. The antimicrobial action of treated fabric (before and after 20 laundry cycles) towards viruses, bacteria, and fungi as well as ultraviolet protection factor (UPF) were evaluated according to standard. The treated fabric showed significant fungicidal (>85%) bactericidal (>95%), and viricidal (>85%) action, that remained effective even after 20 washes, revealing that antimicrobial agent has not leached during washing of treated textiles which established non-leaching behavior of the treated textiles. The treated fabric also exhibited outstanding UPF values (>135). The current study has proposed a novel approach for the fabrication of ecologically sustainable antimicrobial textiles and the proposed method is easily scalable at industrial level.

Loss of Interleukin–18 Negative–Feedback Associated with Severity and Mortality in Prospective Cohort Study of 206 Hospitalised COVID–19 Patients (preprint)

Background: Divergence between deterioration to life–threatening COVID–19 or clinical improvement occurs for most within the first 14 days of symptoms. Life–threatening COVID–19 shares clinical similarities with Macrophage Activation Syndrome, which can be driven by elevated Free Interleukin–18 (IL–18) due to failure of negative-feedback release of IL–18 binding protein (IL–18bp). We therefore designed a prospective, longitudinal cohort study to examine IL–18 negative–feedback control in relation to COVID–19 severity and mortality from symptom day 15 onwards. Methods: 662 blood samples, matched to time from symptom onset, from 206 COVID–19 patients were analysed by enzyme–linked immunosorbent assay for IL–18 and IL–18bp, enabling calculation of free IL–18 (fIL–18) using the updated dissociation constant (Kd) of 0.05 nanomoles. Adjusted multivariate regression analysis was used to assess the relationship between highest fIL–18 and outcome measures of COVID-19 severity and mortality. Results: Up to symptom day 14, mean fIL–18 levels increase in all patients. Levels in survivors declined thereafter, but remained elevated in non–survivors, due to IL–18 production without commensurate IL–18bp release. Adjusted regression analysis from symptom day 15 onwards showed a 100 mmHg decrease in Pa02/Fi02 (primary outcome) for each 37.7 pg/ml increase in highest fIL–18 (p < 0.03). Per 50 pg/ml increase in highest fIL–18, adjusted logistic regression gave an odds–ratio (OR) for crude 60–day mortality of 1.41 (1.1 – 2.0) (p < 0.03), and an OR for death with hypoxaemic respiratory failure of 1.90 [1.3 – 3.1] (p < 0.01). Highest fIL–18 was associated also with organ failure, with an increase of 63.67 pg/ml for every additional organ supported (p < 0.01) in patients with hypoxaemic respiratory failure. In this same sub-group, highest fIL–18 showed a direct correlation with Neutrophil/Lymphocyte ratio, with an increase in fIL–18 by 3.54 pg/ml (p < 0.03) for each unit increase. Conclusions: Loss of IL–18 negative–feedback control, from symptom day 15 onwards is associated with COVID–19 severity and mortality. ISRCTN: #13450549; registration date: 30/12/2020. 

Development of Functional Cotton Fabric by Simultaneous Dyeing and Finishing with Novel Bioactive Reactive dye (preprint)

Bioactive textiles have garnered considerable attention during the current pandemic COVID-19 owing to their antimicrobial properties. However, the fabrication and utilization of bioactive textiles have imposed a toxic impact on the environment due to the leaching of bioactive agents during laundering. In this study, a novel functional reactive dye was synthesized with an antibacterial agent covalently linked to the triazine reactive group for simultaneous dyeing and finishing of cotton fabric. The synthesized dye was characterized by FTIR, 1H-NMR, 13C-NMR, and UV-Vis spectroscopy for structure elucidation and confirmation. The dye was applied to cotton fabric using the exhaust dyeing method. The antibacterial efficacy of the powder dye and dyed fabric against Staphylococcus Aureus and Escherichia Coli was estimated according to standard test protocols. The color strength (K/S), colorimetric data (L*, a*, b*, C*, H*) measurement, ultraviolet protection, and colorfastness properties of dyed fabric were also established and evaluated. The synthesized powder dye revealed outstanding antibacterial activity and killed 99.99% of bacteria (E. coli and S. aureus). The dyed fabric showed excellent antibacterial activity before washing and after 20 industrial laundry cycles, there was no significant reduction in antibacterial activity establishing non-leaching of antibacterial agent into environment. The dyed fabrics before and after washing showed excellent ultraviolet protection values (> 50), better dye fixation, and fastness properties. The current study has established a sustainable process to develop bioactive textiles which do not leach bioactive agent in the environment, and it is easily scalable at industrial scale.

Coronavirus Genomes and Unique Mutations in Structural and Non-Structural Proteins in Pakistani SARS-CoV-2 Delta Variants during the Fourth Wave of the Pandemic.

Genomic epidemiology of SARS-CoV-2 is imperative to explore the transmission, evolution, and also pathogenicity of viruses. The emergence of SARS-CoV-2 variants of concern posed a severe threat to the global public health efforts. To assess the potential consequence of these emerging variants on public health, continuous molecular epidemiology is of vital importance. The current study has been designed to investigate the major SARS-CoV-2 variants and emerging mutations in virus structural and non-structural proteins (NSP) during the fourth wave in September 2021 from the Punjab province of Pakistan. Twenty SARS-CoV-2 positive samples have been collected from major cities were subjected to next-generation sequencing. Among the 20 whole genomes (GenBank Accession SRR16294858-SRR16294877), 2 samples failed to be completely sequenced. These genome sequences harbored 207 non-synonymous mutations, among which 19 were unique to GISAID. The genome sequences were detected: Delta 21I, 21J variants (B.1.617.2). Mutation's spike_F157del, spike_P681R, spike_T478K, spike_T19R, spike_L452R, spike_D614G, spike_G142D, spike_E156G, and spike_R158del have been detected in all samples where K1086Q, E554K, and C1250W were unique in spike protein. These genomic sequences also harbored 129 non-synonymous mutations in NSP. The most common were NSP3_P1469S (N = 17), NSP3_A488S (N = 17), NSP3_P1228L (N = 17), NSP4_V167L (N = 17), NSP4_T492I (N = 17), NSP6_T77A (N = 17), NSP14_A394V (N = 17), NSP12_G671S (N = 18), and NSP13_P77L (N = 18). The mutation, F313Y in NSP12, detected in the current study, was found in a single isolate from Belgium. Numerous other unique mutations have been detected in the virus papain-like protease (NSP3), main protease (NSP5), and RNA-dependent RNA polymerase (NSP12). The most common non-synonymous mutations in the spike protein were subjected to stability analysis, exhibiting a stabilizing effect on structures. The presence of Delta variants may affect therapeutic efforts and vaccine efficacy. Continuous genomic epidemiology of SARS-CoV-2 in Pakistan may be useful for better management of SARS-CoV-2 infections.

Modelling uncertainties with TOPSIS and GRA based on q-rung orthopair m-polar fuzzy soft information in COVID-19.

Fuzzy hybrid models are strong mathematical tools to address vague and uncertain information in real-life circumstances. The aim of this article is to introduce a new fuzzy hybrid model named as of q-rung orthopair m-polar fuzzy soft set (q-RO-m-PFSS) as a robust fusion of soft set (SS), m-polar fuzzy set (m-PFS) and q-rung orthopair fuzzy set (q-ROFS). A q-RO-m-PFSS is a new approach towards modelling uncertainties in the multi-criteria decision making (MCDM) problems. Some fundamental operations on q-RO-m-PFSSs, their key properties, and related significant results are introduced. Additionally, the complexity of logistics and supply chain management during COVID-19 is analysed using TOPSIS (technique for ordering preference through the ideal solution) and GRA (grey relational analysis) with the help of q-RO-m-PFS information. The linguistic terms are used to express q-RO-m-PFS information in terms of numeric values. The proposed approaches are worthy efficient in the selection of ventilator's manufacturers for the patients suffering from epidemic disease named as COVID-19. A practical application of proposed MCDM techniques is demonstrated by respective numerical examples. The comparison analysis of the final ranking computed by proposed techniques is also given to justify the feasibility, applicability and reliability of these techniques.

Quantifying the asymmetric spillovers in sustainable investments

Owing to the growing importance of socially responsible investments in the wake of climate change mitigation goals, we estimate the asymmetric time- and frequency-spillovers between global sustainable investments. Additionally, we examine the influence of global risk factors such as US and UK economic policy uncertainties, stock market volatility, US treasury market volatility and infectious diseases related market volatility on the short- and long-run connectedness in these investments. To this end, we use daily returns and volatilities of 14 country-level Dow Jones Sustainability indices from January 2005 to March 2021. By employing the asymmetric versions of Diebold & Yilmaz (2012, 2014) and Barunik & Krehlik (2018) time-frequency connectedness, our study addresses both good and bad contagion among sustainable investments is unexplored in the recent literature. The results reveal significant time-frequency asymmetries in return spillovers across different regions in the short- and long-run. Germany, France, Netherlands, and the UK are the primary transmitters of returns and volatility shocks. We find more intra-regional connectedness among the Asian countries as opposed to inter-regional connectedness. Negative returns propagate more intensely than positive ones, and this contagion is considerably boosted during crises, including the COVID19. The VIX and COVID19 remain influential for financial contagion in the long run. The impact of MOVE is positive in the short-run while negative in the long-run, which shows an overreaction of connectedness to the US treasury market volatility in the short-run. Economic policy uncertainties in the US and the UK increase spillovers more intensely in the short-run. These results are robust to using volatility spillovers, the choice of rolling window and various forecast horizons. Our findings are distinctly important for socially responsible investors as we point out international portfolio diversification opportunities among sustainable investments. Understanding the dynamics of connectedness in sustainable investments can potentially boost financing in this market through portfolio choices and contribute to the climate change mitigation agenda of United Nations.

Emerging Mutations in Nsp1 of SARS-CoV-2 and Their Effect on the Structural Stability.

The genome of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) encodes 16 non-structural (Nsp) and 4 structural proteins. Among the Nsps, Nsp1 inhibits host gene expression and also evades the immune system. This protein has been proposed as a target for vaccine development and also for drug design. Owing to its important role, the current study aimed to identify mutations in Nsp1 and their effect on protein stability and flexibility. This is the first comprehensive study in which 295,000 complete genomes have been screened for mutations after alignment with the Wuhan-Hu-1 reference genome (Accession NC_045512), using the CoVsurver app. The sequences harbored 933 mutations in the entire coding region of Nsp1. The most frequently occurring mutation in the 180-amino-acid Nsp1 protein was R24C (n = 1122), followed by D75E (n = 890), D48G (n = 881), H110Y (n = 860), and D144A (n = 648). Among the 933 non-synonymous mutations, 529 exhibited a destabilizing effect. Similarly, a gain in flexibility was observed in 542 mutations. The majority of the most frequent mutations were detected in the loop regions. These findings imply that Nsp1 mutations might be useful to exploit SARS-CoV-2's pathogenicity. Genomic sequencing of SARS-CoV-2 on a regular basis will further assist in analyzing variations among the drug targets and to test the diagnostic accuracy. This wide range of mutations and their effect on Nsp1's stability may have some consequences for the host's innate immune response to SARS-CoV-2 infection and also for the vaccines' efficacy. Based on this mutational information, geographically strain-specific drugs, vaccines, and antibody combinations could be a useful strategy against SARS-CoV-2 infection.

Combined drug repurposing and virtual screening strategies with molecular dynamics simulation identified potent inhibitors for SARS-CoV-2 main protease (3CLpro).

The current coronavirus (SARS-COV-2) pandemic and phenomenal spread to every nook and cranny of the world has raised major apprehensions about the modern public health care system. So far as a result of this epidemic, 4,434,653 confirmed cases and 302,169 deaths are reported. The growing infection rate and death toll demand the use of all possible approaches to design novel drugs and vaccines to curb this disease. In this study, we combined drugs repurposing and virtual drug screening strategies to target 3CLpro, which has an essential role in viral maturation and replication. A total of 31 FDA approved anti-HIV drugs, and Traditional Chinese medicines (TCM) database were screened to find potential inhibitors. As a result, Saquinavir, and five drugs (TCM5280805, TCM5280445, TCM5280343, TCM5280863, and TCM5458190) from the TCM database were found as promising hits. Furthermore, results from molecular dynamics simulation and total binding free energy revealed that Saquinavir and TCM5280805 target the catalytic dyad (His41 and Cys145) and possess stable dynamics behavior. Thus, we suggest that these compounds should be tested experimentally against the SARS-COV-2 as Saquinavir has been reported to inhibit HIV protease experimentally. Considering the intensity of coronavirus dissemination, the present research is in line with the idea of discovering the latest inhibitors against the coronavirus essential pathways to accelerate the drug development cycle.Communicated by Ramaswamy H. Sarma.

Lower mortality rate in health workers and their families infected with COVID-19 associated pneumonia in Quetta, Baluchistan.

OBJECTIVES: A bunch of pneumonia cases in Wuhan, China, was caused by a novel beta-corona virus, (COVID-19) in December 2019 from where it spread rapidly across the globe. The aim of the study was to find out relevant reasons and offered suggestions to reduce the risk of infection and check clinical outcomes of the infected healthcare workers. METHODS: This study was conducted in COVID-19 Real Time Polymerase Chain Reaction (RT-PCR) laboratory, Bolan Medical Complex Hospital Quetta, Baluchistan from May to June 2020. Eight hundred (n=800) health workers and their families were included in this study. Data were obtained with standardized data collection forms shared by the WHO. Nasopharyngeal samples were collected following the WHO protocols. RNA was extracted and amplified using real time reverse transcriptase polymerase chain reaction (RT-PCR). Serum ferritin level, C-reactive protein, D-dimer and radiological results of the RT-PCR confirmed individuals were also recorded and analyzed. RESULTS: Among (n=800) health workers and their families 457 (57.1%) were COVID-19 PCR negative, 332 (41.5%) positive and 11 (1.4%) individuals were PCR positive but asymptomatic carriers, 234 (29.5%) were male and 103 (12.9%) were female. Mortality rate in our study was very low, only three patients (0.87%) died of this COVID-19 pneumonia. CONCLUSION: Our results showed increased rate of positive cases with fortunately lower mortality rate, although this novel pneumonia was associated with acute respiratory distress syndrome ARDS and intensive care unit (ICU) admission. Timely decisions, risk awareness knowledge and supply of necessary equipments are inevitable for the control of such epidemics.