ABSTRACT
The COVID-19 pandemic has turned out to be one of the worst disasters that mankind has ever faced. This pandemic has disturbed the homeostasis of the entire globe. Various degrees of lockdowns are being implemented worldwide to prepare the healthcare infrastructure of the country as well as to sensitize people. The new mutations in the genome of the virus are possessing a greater threat in triggering the future waves of the pandemic. Adhering to strict usage of masks, highest standards of hand hygiene, practicing social distancing and vaccination are the only weapons to battle the pandemic. Governments are rolling the vaccination plans worldwide. There are various strategies to improve the vaccination status of a country. There is a dire need for a robust, efficient delivery system for the effective transportation of the COVID-19 vaccines. This chapter proposes distribution methods for CoVacciDrone, a smart-drone-based delivery system of COVID-19 vaccines. This would enable transport of the COVID-19 vaccine to even the remotest locations of the country. Deployment of such smart systems would improve the vaccination status of the nation. This would propel the vaccination drive, which would be imperative in avoiding future waves of the COVID-19 pandemic. © 2023 selection and editorial matter, Saravanan Krishnan and M. Murugappan;individual chapters, the contributors.
ABSTRACT
The COVID-19 pandemic has turned out to be one of the dreadful disaster mankind has ever faced. With the subsequent waves of the pandemic setting in several countries, the number of cases being reported is quite alarming. People need to stay extremely vigilant and ensure strict adherence to social distancing, hand hygiene, and usage of personal protectives like masks, hand gloves and face shields. Remdesivir, an anti-viral drug used against the COVID-19, believed to have some therapeutic effects is on a surplus demand. There have been reports of illegal hoarding of these drugs. We need to be vigilant and keep a check on the circulation of fake Remdesivir drugs in the market amidst the pandemic. The study proposed development of a novel Drug Validator Application to detect fake Remdesivir drugs. This is done by scanning the carton or the vial of the Remdesivir drug through the dedicated Android application. This is further sent to the cloud server for processing. The AI model which runs in the cloud server evaluates the genuineness of the drug image. The report comprising the recommendation as Genuine or Fake is sent to the user through his/her registered mobile number and e-mail address. This application could curb the circulation of fake drugs in the market amidst the pandemic and could help in undertaking a real-time surveillance. © 2022 IEEE.
ABSTRACT
Background: Unexpectedly, COVID-19 is less prevalent in Chronic Respiratory Disease(CRD) than in the general population.[1-4] The vaccine and infection-related immune status of CRD patients are unknown. We performed a cross-sectional COVID-19 seroprevalence study among our CRD patients. Methods: Patients with Asthma, COPD, ILD, PTBsequelae and restrictive lung diseases attending the pulmonology OPD were recruited. Relevant clinical and laboratory information were captured. The Roche Elecsys SARS-CoV-2 assay was used to detect anti-N and anti-S antibodies. Results: We recruited 364 patients (Asthma & COPD -100 each, Bronchiectasis, ILD & PTB-sequelae - 50 each and restrictive diseases-14 ). The overall seroprevalence in CRD (Anti-S) was 85.16%, significantly higher than the 4th national serosurvey data of 67.60% (p = 0.001).[5] Asthma had a higher seroprevalence than COPD [93% vs 78%, p=0.027] and bronchiectasis [93% vs 80%, p=0.018]. Prevalence of antibody through natural infection as assessed by Anti-N was nearly 5 folds higher (67.62%) than those with PCR confirmed COVID-19 (13.74%). PTB-sequelae patients had higher natural infections than COPD. [48 (75%) vs 57 (59.37%), p=0.065]. Seroprevalence dropped with age: <40 years: 93%, 41-60 years: 87% and 61+ years: 77% (p=0.004). Those on inhaled-steroids had higher seroprevalence than those without (89% vs 80%, p = 0.026). Patients on inhaled-anticholinergics had lower seroprevalence (79%vs 89%;p=0.013) and lower confirmed COVID (6% vs 19%, p<0.001) than no-anticholinergics. Conclusion: The COVID-19 overall seroprevalence is higher in CRD than in the general population.
ABSTRACT
This study concentrates on the analysis of a stochastic SIC epidemic system with an enhanced and general perturbation. Given the intricacy of some impulses caused by external disturbances, we integrate the quadratic Lévy noise into our model. We assort the long-run behavior of a perturbed SIC epidemic model presented in the form of a system of stochastic differential equations driven by second-order jumps. By ameliorating the hypotheses and using some new analytical techniques, we find the exact threshold value between extinction and ergodicity (persistence) of our system. The idea and analysis used in this paper generalize the work of N. T. Dieu et al. (2020), and offer an innovative approach to dealing with other random population models. Comparing our results with those of previous studies reveals that quadratic jump-diffusion has no impact on the threshold value, but it remarkably influences the dynamics of the infection and may worsen the pandemic situation. In order to illustrate this comparison and confirm our analysis, we perform numerical simulations with some real data of COVID-19 in Morocco. Furthermore, we arrive at the following results: (i) the time average of the different classes depends on the intensity of the noise (ii) the quadratic noise has a negative effect on disease duration (iii) the stationary density function of the population abruptly changes its shape at some values of the noise intensity. Mathematics Subject Classification 2020: 34A26; 34A12; 92D30; 37C10; 60H30; 60H10.
ABSTRACT
The COVID-19 pandemic has devastated the public health infrastructure of the globe. The crucial strategy has been to carry out aggressive testing, which could be the only way to get back to normalcy. The COVID-19 testing is carried out through the Reverse Transcriptase Polymerase Chain Reaction (RT-PCR), which is considered to be the gold standard. However, these tests are sometimes known to provide inaccurate results which might be due to improper sample storage and transportation techniques. The swab samples transported in a viral transport medium need to be maintained under optimum environmental conditions. The proposed model involves tagging humidity and thermologger devices with the sample container box. This would record the real-time temperature and humidity, which would be stored in the cloud server. This would predict any breakage in the cold chain using AI-powered pattern analysis techniques. This would intimate the authorities of a possible cold chain breakage, thereby assuring the quality of the samples. This would drastically reduce the possibility of false outcomes. This would help the healthcare workers to trace, isolate and treat the right affected individuals, preventing the further spread of the disease. This model could also be used for distribution of COVID-19 vaccines whenever they are available. This could preserve the potency of the vaccines, thereby significantly reducing the wastage of vaccines. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
ABSTRACT
Coronavirus disease (COVID-19) is a pandemic that has shaken the whole world. The aim of this study is to understand the spatial spread of COVID. In this paper, we have analyzed the dynamics of COVID-19 and epidemiological characteristics by SIRD model fitting and the accuracy is assessed using RMSLE. Also, geospatial mapping of the COVID cases over the districts of Tamil Nadu is made. In our study, Moderate Resolution Imaging Spectroradiometer (MODIS) imagery is used and the normalized difference vegetation index (NDVI) is calculated to estimate the forest canopy. The correlation between the MODIS derived data for forest cover and the COVID cases is analyzed and mapped. Urban density is an important factor in the spread of disease. Transmission occurs at a rapid phase where the population density is high. Regression analysis and the correlation between demography and transmission rate of COVID is analyzed and mapped geospatially. Basic reproduction number helps us estimate the severity of the outbreak of COVID. The basic reproduction number ${\mathbb{R}_0}$ is calculated for all the districts. Demographic factors show stronger correlation with transmission rate of COVID with ρ= 0.58 for India and =0.988 for Tamil Nadu. Forest cover shows weaker correlation with ρ=-0.083 for India and ρ=-0.159 for Tamil Nadu. This paper includes both geospatial analysis and statistical correlation analysis which will help the authorities in better policy making. © 2020 IEEE.