An Improved Data Driven Dynamic SIRD Model for Predictive Monitoring of COVID-19

Abstract

COVID-19 pandemic spreaded across the world in early 2020. It forced many countries to impose lockdown to prevent surge in the number of infected cases. There has been a huge impact on social and economic activities worldwide. In this work, we carry out the functional modeling of COVID-19 infection trends using two models: the Gaussian mixture model (GMM) and the composite logistic growth model (CLGM). Unlike the traditional SIRD models that use numerical data fitting, we utilize the best data-fitted curves employing GMM and/or CLGM to construct the Susceptible-Infected-Recovered-Dead (SIRD) pandemic model. Further, we derive the explicit expressions of time-varying parameters of the SIRD model unlike most works that consider static parameters without any closed form solution. The proposed parameterized dynamic SIRD model is generically applicable to any pandemic, can capture the day-to-day dynamics of the pandemic and can assist the governing bodies in devising efficient action plans to deal with the prevailing pandemic.

Enhancing Supply Chain Traceability through Blockchain and IoT Integration: A Comprehensive Review

“…To improve DSCM, pharmaceutical companies leverage technologies such as blockchain, IoT, and AI to enhance traceability, increase inventory management, and improve communication and collaboration between stakeholders. These serve as motivation for [87] to work on the design of a Blockchain Assisted Archimedes Optimization with ML Driven Drug Supply Management (BAOML-DSM) technique for the Pharmaceutical Sector. The presented BAOML-DSM technique focuses on the recommendation of drugs in the pharmaceutical sector.…”

“…It addresses the need for transparent and secure traceability systems in the fish industry and agriculture, advocating for the adoption of digital technologies to ensure food safety, consumer confidence, and sustainability [85,86]. The pharmaceutical sector leverages these technologies to enhance drug supply chain management, emphasizing traceability, inventory management, and stakeholder communication [87]. Resilience and efficiency in supply chains, particularly in the context of global challenges, are underlined, with IoT and blockchain technology enabling real-time traceability and efficiency improvements [88].…”

On the evolution of the COVID-19 epidemiological parameters using only the series of deceased. A study of the Spanish outbreak using Genetic Algorithms

“…Alternatively, compartmental models can also be formulated by means of stochastic processes described by a renewal integral equation [16] , Markov Chain models [25] , time series prediction models such as ARIMA [29] , and by integrating with the Gaussian mixture model and the composite logistic growth model [30] ; finally, there have also been agent type models simulating individual activities for a population [12] . See Hethcote [19] for a broad perspective on SIR-type models.…”

ECG-iCOVIDNet: Interpretable AI model to identify changes in the ECG signals of post-COVID subjects

“…Based on the global statistics, until August 12, 2021, more than 205 million people suffered from this infection, and 4.3 million people lost their battle to COVID-19 ( https://www.worldometers.info/coronavirus ). Researchers have been trying to develop time-series models to predict the statistics in order to support the agencies with appropriate policy decisions [ 2 , 3 ].…”