COVID-19 among Hospitalized Patients with Diabetes in Karachi: A Single Centre Study

Aim: To evaluate the clinical characteristics, severity, and outcomes of local COVID-19 patients with diabetes. Study Design: Case series Place and duration of study: Orthopedic Medical Institute Hospital, Karachi from 1st September 2020 to 28th February 2021. Method(s): One hundred and forty seven COVID-19 positive patients with diabetes and pre-diabetes were enrolled. The patients' demographic and clinical information specific to COVID-19 and diabetes was collected and analyzed. Result(s): The mean age of 64.03+/-11.56 years. The ischemic heart disease (39.9%) and hypertension (74.3%) were the two most prevalent comorbid conditions. The overall mortality rate of 20.3%. Between patients with diabetes receiving steroids and those receiving no steroids, the mean fasting (FBG) and random blood glucose (RBG) were relatively elevated. Glycemic control had no discernible impact on the severity, results, or length of the COVID-19 hospital stay (p>0.05). Conclusion(s): No significant effect of diabetes millitus control on COVID severity and outcomes, but the altered blood glucose levels suggest a need to define specific targeted intervention for COVID-19 patients with comorbidities, specifically diabetes mellitus.Copyright © 2023 Lahore Medical And Dental College. All rights reserved.

The SIUQRD and Matern 5/2 GPR Models describing the Covid-19 Pandemic in India

In this study an SIUQRD model for the Corona Virus pandemic in India has been discussed, the Ordinary Differential Equations (ODEs) have been fitted and the parameters have been estimated for the two successive waves that affected the country. The data has been taken from 30/01/2020 to 12/02/2021 for fitting the first wave and 13/02/2021 to 18/06/2021 for fitting the second wave. The value has been calculated for a span of 14 days towards the end of the second wave in absence of original data to analyze the pandemic situation for the next two weeks (19th June to 2nd July). Upon fitting the data for the two waves, the required model parameters are estimated. The study has further been extended to predict the number of cases for the same time period (19th June to 2nd July) using a machine learning model - Matern 5/2 GPR with satisfactory performance metrics. Finally, the original data during the two weeks is compared with the data predicted by the Matern 5/2 GPR model to check the performance of the model. This Matern 5/2 GPR model, to the best of our knowledge is being applied to predict the COVID-19 pandemic for the first time in India. © 2021 IEEE.

A Social Distancing-Based Facility Location Approach for Combating COVID-19

In this paper, we introduce and study the problem of facility location along with the notion of ‘social distancing’. The input to the problem is the road network of a city where the nodes are the residential zones, edges are the road segments connecting the zones along with their respective distance. We also have the information about the population at each zone, different types of facilities to be opened and in which number, and their respective demands in each zone. The goal of the problem is to locate the facilities such that the people can be served and at the same time the total social distancing is maximized. We formally call this problem as the Social Distancing-Based Facility Location Problem. We mathematically quantify social distancing for a given allocation of facilities and proposed an optimization model. As the problem is NP-Hard, we propose a simulation-based and heuristic approach for solving this problem. A detailed analysis of both methods has been done. We perform an extensive set of experiments with synthetic datasets. From the results, we observe that the proposed heuristic approach leads to a better allocation compared to the simulation-based approach. © 2021, Springer Nature Switzerland AG.

Comparison of 16 Serological SARS-CoV-2 Immunoassays in 16 Clinical Laboratories.

Serological assays for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are needed to support clinical diagnosis and epidemiological investigations. Recently, assays for large-scale detection of total antibodies (Ab), immunoglobulin G (IgG), and IgM against SARS-CoV-2 antigens have been developed, but there are limited data on the diagnostic accuracy of these assays. This study was a Danish national collaboration and evaluated 15 commercial and one in-house anti-SARS-CoV-2 assays in 16 laboratories. Sensitivity was evaluated using 150 samples from individuals with asymptomatic, mild, or moderate COVID-19, nonhospitalized or hospitalized, confirmed by nucleic acid amplification tests (NAAT); samples were collected 13 to 73 days either from symptom onset or from positive NAAT (patients without symptoms). Specificity and cross-reactivity were evaluated in samples collected prior to the SARS-CoV-2 epidemic from >586 blood donors and patients with autoimmune diseases, cytomegalovirus or Epstein-Barr virus infections, and acute viral infections. A specificity of ≥99% was achieved by all total-Ab and IgG assays except one, DiaSorin Liaison XL IgG (97.2%). Sensitivities in descending order were Wantai ELISA total Ab (96.7%), CUH-NOVO in-house ELISA total Ab (96.0%), Ortho Vitros total Ab (95.3%), YHLO iFlash IgG (94.0%), Ortho Vitros IgG (93.3%), Siemens Atellica total Ab (93.2%), Roche Elecsys total Ab (92.7%), Abbott Architect IgG (90.0%), Abbott Alinity IgG (median 88.0%), DiaSorin Liaison XL IgG (median 84.6%), Siemens Vista total Ab (81.0%), Euroimmun/ELISA IgG (78.0%), and Snibe Maglumi IgG (median 78.0%). However, confidence intervals overlapped for several assays. The IgM results were variable, with the Wantai IgM ELISA showing the highest sensitivity (82.7%) and specificity (99%). The rate of seropositivity increased with time from symptom onset and symptom severity.

Design and development of fire fighting system using hot redundant PLC in COVID situation

A firefighting system is the most foremost part of any industry and buildings as its aim to protect property, human and industrial equipment. In any pandemic situation like COVID19 it is utmost requirement to increase reliability of all important instruments which are directly involve to human life. In case of fire fighter fight against fire, this required time and skilled man power. Under these pandemic situation chances of infection spreading in firefighters and social distancing will not maintain during this situation. Only one way to resolve this problem is by implementation of fully automated reliable system. In this system we are trying to automate the total system by using hot redundant PLC which is fail safe. It consists of mainly three basic parts – fire storage tank, fire pumps and automated distribution system. Fire storage tank contains the water that used against fire. Fire pumps helps to fill the tank and automated distribution system will be activated during fire and instantly distribute water. There are three pumps one is main electrical pump, second one is diesel backup pump and last one is jockey pump.In redundant configuration there are two PLC acting simultaneously and the entire network component and power supply also has back up so that it will never fail. If one of the PLC fails during operation then second PLC automatically take care of the system within few millisecond. Similarly if power supply failure then UPS supply is also there for uninterrupted power supply. © 2021 Institute of Physics Publishing. All rights reserved.

Design and development of IoT based smart security system in COVID19 situation

In COVID19 pandemic situation social distancing and proper thermal screening is very much essential for restrict the spreading of virus. In security purpose human beings directly contacts with several known and unknown persons that is tremendously thoughtful matter. That problem will be overcome by a prototype device which can detect the temperature of the body and the collected data will be uploaded to the server as well as to the predefined consumer mobile number thorough IoT system. This system very much fruitful for office, factory, school even multi stored building security system. Instantly all related data regarding body temperature, image capturing, coming from area, area details scenario during any pandemic situation will be detect to the consumer mobile or computer. Using this it can keep a record to the number of visitors along with their temperature of the body. And in this current situation using this we can avoid human touch and the chances of getting affected will be less and a huge number of people can save their life. Solar powered IoT based smart security system will be automatically notified to the consumer when visitor come to meet in their premises. It will also give an alert if the visitor coming from containment zone or highly affected area. © 2021 Institute of Physics Publishing. All rights reserved.

Comparison of sixteen serological SARS-CoV-2 immunoassays in sixteen clinical laboratories (preprint)

Serological SARS-CoV-2 assays are needed to support clinical diagnosis and epidemiological investigations. Recently, assays for the large-volume detection of total antibodies (Ab) and immunoglobulin (Ig) G and M against SARS-CoV-2 antigens have been developed, but there are limited data on the diagnostic accuracy of these assays. This study was organized as a Danish national collaboration and included fifteencommercial and one in-house anti-SARS-CoV-2 assays in sixteen laboratories. Sensitivity was evaluated using 150 serum samples from individuals diagnosed with asymptomatic,mild or moderate nonhospitalized (n=129) or hospitalized (n=31) COVID-19, confirmed bynucleic acid amplification tests, collected 13-73 days from symptom onset. Specificity and cross-reactivity were evaluated in samples collected prior to the SARS-CoV-2 epidemic from > 586 blood donors and patients with autoimmune diseases or CMV or EBV infections. Predefined specificity criteria of [≥] 99% were met by all total-Ab and IgG assays except one (Diasorin/LiaisonXL-IgG 97.2%). The sensitivities in descending order were: Wantai/ELISA total-Ab (96.7%), CUH/NOVO in-house ELISA total-Ab (96.0%), Ortho/Vitros total-Ab (95.3%), YHLO/iFlash-IgG (94.0%), Ortho/Vitros-IgG (93.3%), Siemens/Atellica total-Ab (93.2%), Roche-Elecsys total-Ab (92.7%), Abbott-Architect-IgG (90.0%), Abbott/Alinity-IgG (median 88.0%), Diasorin/LiaisonXL-IgG (84.6%),Siemens/Vista total-Ab (81.0%), Euroimmun/ELISA-IgG (78.0%), and Snibe/Maglumi-IgG (median 78.0%). The IgM results were variable, but one assay (Wantai/ELISA-IgM) hadboth high sensitivity (82.7%) and specificity (99%). The rate of seropositivity increased with time from symptom onset and symptom severity. In conclusion, predefined sensitivity and specificity acceptance criteria of 90%/99%, respectively, for diagnostic use were met in five of six total-Ab and three of seven IgG assays.