Dynamical analysis of the infection status in diverse communities due to COVID-19 using a modified SIR model DOI Creative Commons
Ian A. Cooper, Argha Mondal, Chris G. Antonopoulos

et al.

Nonlinear Dynamics, Journal Year: 2022, Volume and Issue: 109(1), P. 19 - 32

Published: March 19, 2022

In this article, we model and study the spread of COVID-19 in Germany, Japan, India highly impacted states India, i.e., Delhi, Maharashtra, West Bengal, Kerala Karnataka. We consider recorded data published Worldometers websites from April 2020 to July 2021, including periods interest where these countries were hit severely by pandemic. Our methodology is based on classic susceptible-infected-removed (SIR) can track evolution infections communities, countries, or groups individuals, (a) allow for susceptible infected populations be reset at times surges, outbreaks secondary waves appear sets, (b) parameters SIR that represent effective transmission recovery rates functions time (c) estimate number deaths combining solutions with sets approximate them between consecutive waves, providing a more accurate estimate. report status current states, Japan. adapt used explain importantly, forecast infected, recovered, removed dead as well it infection time, assuming an outbreak occurs given time. The latter information future basic reproduction together our approach further suggest implementation intervention strategies mitigation policies keep bay individuals. This, conjunction vaccination programs worldwide, help reduce significantly impact around world improve wellbeing people.

Language: Английский

Optimal levels of vaccination to reduce COVID-19 infected individuals and deaths: A global analysis DOI Open Access
Mario Coccia

Environmental Research, Journal Year: 2021, Volume and Issue: 204, P. 112314 - 112314

Published: Nov. 2, 2021

Language: Английский

Citations

180
Deterministic optimal control compartmental model for COVID-19 infection DOI

Barbara Fosua Afful,

Godfred Agyemang Safo,

D. Marri

et al.

Modeling Earth Systems and Environment, Journal Year: 2025, Volume and Issue: 11(2)

Published: Jan. 20, 2025

Language: Английский

Citations

2
Using digital traces to build prospective and real-time county-level early warning systems to anticipate COVID-19 outbreaks in the United States DOI Creative Commons
Lucas M. Stolerman,

Leonardo Clemente,

Canelle Poirier

et al.

Science Advances, Journal Year: 2023, Volume and Issue: 9(3)

Published: Jan. 18, 2023

Coronavirus disease 2019 (COVID-19) continues to affect the world, and design of strategies curb outbreaks requires close monitoring their trajectories. We present machine learning methods that leverage internet-based digital traces anticipate sharp increases in COVID-19 activity U.S. counties. In a complementary direction efforts led by Centers for Disease Control Prevention (CDC), our models are designed detect time when an uptrend will occur. Motivated need finer spatial resolution epidemiological insights, we build upon previous conceived at state level. Our methods-tested out-of-sample manner, as events were unfolding, 97 counties representative multiple population sizes across United States-frequently anticipated 1 6 weeks before local outbreaks, defined effective reproduction number

Language: Английский

Citations

28
Efficient social distancing during the COVID-19 pandemic: Integrating economic and public health considerations DOI Open Access
Kexin Chen, Chi Seng Pun, Hoi Ying Wong

et al.

European Journal of Operational Research, Journal Year: 2021, Volume and Issue: 304(1), P. 84 - 98

Published: Nov. 11, 2021

Language: Английский

Citations

47
Investigation of Statistical Machine Learning Models for COVID-19 Epidemic Process Simulation: Random Forest, K-Nearest Neighbors, Gradient Boosting DOI Creative Commons
Dmytro Chumachenko, Ievgen Meniailov, Kseniia Bazilevych

et al.

Computation, Journal Year: 2022, Volume and Issue: 10(6), P. 86 - 86

Published: May 30, 2022

COVID-19 has become the largest pandemic in recent history to sweep world. This study is devoted developing and investigating three models of epidemic process based on statistical machine learning evaluation results their forecasting. The developed are Random Forest, K-Nearest Neighbors, Gradient Boosting methods. were studied for adequacy accuracy predictive incidence 3, 7, 10, 14, 21, 30 days. used data new cases Germany, Japan, South Korea, Ukraine. These countries selected because they have different dynamics process, governments applied various control measures contain pandemic. simulation showed sufficient practical use Neighbors models. Public health agencies can predictions address containment challenges. Such challenges investigated depending duration constructed forecast.

Language: Английский

Citations

36
Disease spreading modeling and analysis: a survey DOI
Pietro Hiram Guzzi, Francesco Petrizzelli, Tommaso Mazza

et al.

Briefings in Bioinformatics, Journal Year: 2022, Volume and Issue: 23(4)

Published: June 12, 2022

Abstract Motivation The control of the diffusion diseases is a critical subject broad research area, which involves both clinical and political aspects. It makes wide use computational tools, such as ordinary differential equations, stochastic simulation frameworks graph theory, interaction data, from molecular to social granularity levels, model ways arise spread. coronavirus disease 2019 (COVID-19) perfect testbench example show how these models may help avoid severe lockdown by suggesting, for instance, best strategies vaccine prioritization. Results Here, we focus on discuss some graph-based epidemiological their significantly improve spreading control. We offer examples related recent COVID-19 pandemic generalize them other diseases.

Language: Английский

Citations

33
Deep learning forecasting using time-varying parameters of the SIRD model for Covid-19 DOI Creative Commons

Arthur Bousquet,

William H. Conrad, Said Omer Sadat

et al.

Scientific Reports, Journal Year: 2022, Volume and Issue: 12(1)

Published: Feb. 22, 2022

Accurate epidemiological models are necessary for governments, organizations, and individuals to respond appropriately the ongoing novel coronavirus pandemic. One informative metric provide is basic reproduction number ([Formula: see text]), which can describe if infected population growing text]) or shrinking text]). We introduce a algorithm that incorporates susceptible-infected-recovered-dead model (SIRD model) with long short-term memory (LSTM) neural network allows real-time forecasting time-dependent parameter estimates, including contact rate, [Formula: text], deceased text]. With an accurate prediction of text] we directly derive find numerical solution compartmental models, such as SIR-type models. Incorporating dynamics SIRD into LSTM network, new improves accuracy. Furthermore, utilize mobility data from cellphones positive test rate in our model, also present vaccination model. Leveraging schedule important capturing behavioral changes by response pandemic well policymakers.

Language: Английский

Citations

28
How does the wealth level of nations affect their COVID-19 vaccination plans? DOI Creative Commons
Bilal Kargı, Mario Coccia, Bekir Cihan Uçkaç

et al.

Economics Management and Sustainability, Journal Year: 2023, Volume and Issue: 8(2), P. 6 - 19

Published: Nov. 29, 2023

This study uses global data to examine how vaccination levels correlate with socioeconomic, institutional and political variables across 150 countries. Results demonstrate that as a country's economic development, measured by GDP per capita, increases, so does the percentage of vaccinated people, reaching peak 70%. Furthermore, countries Monarchy Parliamentary exhibit higher among their populations compared mixed Executives. In this context, manifold are implementing restrictions bureaucratic rules, such green pass/vaccine reports, boost regulating various public private life aspects potentially impact individuals' well-being. The discussion elucidates underlying causes these sociopolitical phenomena within context social insecurity. All results can provide valuable insights for policymakers, aiding them in crafting sustainable policy responses address not only COVID-19 but other similar epidemics, all while adversely affecting nations' economies structures.

Language: Английский

Citations

15
Potential of Microneedle Systems for COVID-19 Vaccination: Current Trends and Challenges DOI Creative Commons
Jasmin Hassan,

Charlotte Haigh,

Tanvir Ahmed

et al.

Pharmaceutics, Journal Year: 2022, Volume and Issue: 14(5), P. 1066 - 1066

Published: May 16, 2022

To prevent the coronavirus disease 2019 (COVID-19) pandemic and aid restoration to prepandemic normality, global mass vaccination is urgently needed. Inducing herd immunity through has proven be a highly effective strategy for preventing spread of many infectious diseases, which protects most vulnerable population groups that are unable develop immunity, such as people with immunodeficiencies or weakened immune systems due underlying medical debilitating conditions. In achieving outreach, maintenance vaccine potency, transportation, needle waste generation become major issues. Moreover, phobia hesitancy act hurdles successful vaccination. The use dissolvable microneedles COVID-19 could paradigm shift in attaining desired goal vaccinate billions shortest time possible. addressing these points, we discuss potential based on current literature.

Language: Английский

Citations

21
Time delay of the appearance of a new strain can affect vaccination behavior and disease dynamics: An evolutionary explanation DOI Creative Commons
Md. Mamun-Ur-Rashid Khan, Md. Rajib Arefin, Jun Tanimoto

et al.

Infectious Disease Modelling, Journal Year: 2023, Volume and Issue: 8(3), P. 656 - 671

Published: June 11, 2023

The emergence of a novel strain during pandemic, like the current COVID-19, is major concern to healthcare system. most effective strategy control this type pandemic vaccination. Many previous studies suggest that existing vaccine may not be fully against new strain. Additionally, strain's late arrival has significant impact on disease dynamics and coverage. Focusing these issues, study presents two-strain epidemic model in which appears with time delay. We considered two vaccination provisions, namely preinfection postinfection vaccinations, are governed by human behavioral dynamics. In such framework, individuals have option commit before being infected first people who forgo become train chance vaccinated (after recovery) an attempt avoid infection from second However, can infect unvaccinated individuals. People additional opportunities protect themselves due Considering cost vaccine, severity strain, vaccine's effectiveness, our results indicated delaying decreases peak size Finally, estimating social efficiency deficit, we discovered dilemma for receiving immunization delay

Language: Английский

Citations

11