ABSTRACT
We present a case study on modeling and predicting the course of Covid-19 in the Indian city of Pune. The results presented in this paper are concerned primarily with the wave of infections triggered by the Delta variant during the period between February and June 2021. Our work demonstrates the necessity for bringing together compartmental stock-and-flow and agent-based models and the limitations of each approach when used individually. Some of the work presented here was carried out in the process of advising the local city administration and reflects the challenges associated with employing these models in a real-world environment with its uncertainties and time pressures. Our experience, described in the paper, also highlights the risks associated with forecasting the course of an epidemic with evolving variants. © 2022 IEEE.
ABSTRACT
Predicting the evolution of Covid19 pandemic has been a challenge as it is significantly influenced by the characteristics of people, places and localities, dominant virus strains, extent of vaccination, and adherence to pandemic control interventions. Traditional SEIR based analyses help to arrive at a coarse-grained 'lumped up' understanding of pandemic evolution which is found wanting to determine locality-specific measures of controlling the pandemic. We comprehend the problem space from system theory perspective to develop a fine-grained simulatable city digital-twin for 'in-silico' experimentations to systematically explore - Which indicators influence infection spread to what extent? Which intervention to introduce, and when, to control the pandemic with some a-priori assurance? How best to return to a new normal without compromising individual health safety? This paper presents a digital twin centric simulation-based approach, illustrates it in a real-world context of an Indian City, and summarizes the learning and insights based on this experience. © 2022 IEEE.
ABSTRACT
Predicting the evolution of the Covid-19 pandemic during its early phases was relatively easy as its dynamics were governed by few influencing factors that included a single dominant virus variant and the demographic characteristics of a given area. Several models based on a wide variety of techniques were developed for this purpose. Their prediction accuracy started deteriorating as the number of influencing factors and their interrelationships grew over time. With the pandemic evolving in a highly heterogeneous way across individual countries, states, and even individual cities, there emerged a need for a contextual and fine-grained understanding of the pandemic to come up with effective means of pandemic control. This paper presents a fine-grained model for predicting and controlling Covid-19 in a large city. Our approach borrows ideas from complex adaptive system-of-systems paradigm and adopts a concept of agent as the core modeling ion. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
ABSTRACT
Open economy, globalization and effect of Covid19 pandemic are transforming the consumer behavior rapidly. The business is nudging consumers towards hyper consumption through online shopping, e-commerce and other conveniences with affordable cost. The companies from courier, express and parcel (CEP) industry are trying to capitalize on this opportunity by tying up with business to consumers (B2C) companies with a promise of delivering parcels to the doorstep in an ever-shrinking time window. In this endeavor, the conventional optimization-based planning approach to manage the fixed parcel payload is turning out to be inadequate. The CEP companies need to quickly adapt to the situation more frequently so as to be efficient and resilient in this growing demand situation. We propose an agent-based digital twin of the sorting terminal, a key processing element of parcel delivery operation, as an experimentation aid to: (i) explore and arrive at the right configuration of the existing sorting terminal infrastructure, (ii) be prepared for possible outlier conditions, and (iii) identify plausible solutions for mitigating the outlier conditions in an evidence-backed manner. This paper presents digital twin of the sorting terminal and demonstrates its use as “in silico” experimentation aid for domain experts to support evidence-backed decision-making. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
ABSTRACT
Objective: Mesenchymal stem cells can serve as a therapeutic option for COVID-19. Their immunomodula-tory and anti-inflammatory properties can regulate the exaggerated inflammatory response and promote recovery of lung damage. Method: Phase-1, single-centre open-label, prospective clinical trial was conducted to evaluate the safety and efficacy of intravenous administration of mesenchymal stem cells derived from umbilical cord and placenta in moderate COVID-19. The study was done in 2 stages with total 20 patients. Herein, the results of stage 1 including first 10 patients receiving 100 million cells on day 1 and 4 with a follow up of 6 months have been discussed. Results: No adverse events were recorded immediately after the administration of MSCs or on follow up. There was no deterioration observed in clinical, laboratory and radiological parameters. All symptoms of the study group resolved within 10 days. Levels of inflammatory biomarkers such as NLR, CRP, IL6, ferritin and D-dimer improved in all patients after intervention along with improved oxygenation demonstrated by improvement in the SpO2/FiO2 ratio and PaO2/FiO2 ratio. None of the patients progressed to severe stage. 9 out of 10 patients were discharged within 9 days of their admission. Improvements were noted in chest x-ray and chest CT scan scores at day 7 in most patients. No post-covid fibrosis was observed on chest CT 28 days after intervention and Chest X ray after 6 months of the intervention. Conclusion: Administration of 100 million mesenchymal stem cells in combina-tion with standard treatment was found to be safe and resulted in prevention of the cytokine storm, halting of the disease progression and acceleration of recovery in moderate COVID-19. This clinical trial has been registered with the Clinical Trial Registry-India (CTRI) as CTRI/2020/08/027043. http://www.ctri.nic.in/Clinicaltrials/pmaindet2. php?trialid=43175.
ABSTRACT
OBJECTIVE: In the current pandemic, Health Care Workers (HCWs) are at a high risk of developing COVID-19. Preventive methods like the use of personal protective equipment, isolation, social distancing, and chemoprophylaxis show limited benefit. Despite standard prophylaxis, many of the HCWs develop COVID-19. Medical ozone therapy has immunomodulatory, antioxidant and antiviral effect, and, therefore, it can be explored as prophylaxis for COVID-19. PATIENTS AND METHODS: We conducted a retrospective controlled cohort study. IV ozonized saline was administered once a day for a total of 4 days in one month in addition to standard prophylaxis for COVID-19 to HCWs in a dedicated COVID hospital. Fresh ozonized saline was prepared for every administration and was given over 1 hour. RESULTS: There were 235 HCWs, 64 received the ozone prophylaxis and 171 did not. The incidence of COVID-19 was significantly (p=0.04) lesser in HCWs that received ozone prophylaxis (4.6%) as compared to those who did not (14.03%). The benefit was seen irrespective of the risk of exposure. In the red zone, 8.69% of the HCWs who received ozone prophylaxis tested positive as opposed to 15.3% of those who did not. In the orange zone, 4.34% of the HCWs who received ozone prophylaxis tested positive, remarkably lesser than those who did not (20%). In the green zone, none of the HCWs who received ozone prophylaxis tested positive; however, 3.4% of the HCWs who did not receive ozone prophylaxis tested positive. No major adverse events were noted. CONCLUSIONS: IV ozonized saline can be used in addition to the standard prophylactic regimen for the prevention of COVID-19 in HCWs. Prospective larger studies are required to establish the potency of IV ozonized saline as prophylaxis.