journal article·2022-12-28Open access

Impact of Quarantine and Vaccination Policies on Viral Load

Dimitrios Koumatzidis, Ioannis Seimenis, Constantinos Loukas, Theodoros Constantinidis, Adam Adamopoulos

Applied Sciences· Volume 13· Issue 1

Abstract

Epidemics and pandemics are a field of scientific research since ancient times. The intensity of the repeated phenomena demonstrates their cyclicality in time. The ongoing COVID-19 pandemic, also known as the coronavirus pandemic, confirmed observations made in previous disease outbreaks. Epidemics are mainly characterized by two factors: (a) the population dynamics and (b) the nature of the disease. This article uses continuous mathematical models, on the basis of a scalable compartmental approach, characterized by systems of ordinary differential equations under the condition that individuals can freely move from one compartment to another. Numerous experiments were carried out to examine the impact of quarantine and vaccination policies, separately or in combination, on cumulative viral load, a measure adopted to reflect the cumulative viral burden of an infected population for a given time period. Current findings demonstrate that quarantine may play a crucial role in controlling an epidemic at its early stages, as well as the importance of early and widespread implementation of a vaccination program. The suggested approach may be utilized to study specific quarantine and vaccination scenarios, by manipulating various parameters such as the duration and extent of social distancing measures or the effectiveness and compliance to vaccination policies, and thus assist in decision making.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: COVID-19 epidemiological studies · Mathematical and Theoretical Epidemiology and Ecology Models · SARS-CoV-2 and COVID-19 Research

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Medical Physics Laboratory, Department of Medicine, Democritus University of Thrace, 68133 Alexandroupolis, Greece

Medical School, National and Kapodistrian University of Athens, 11527 Athens, Greece

References (30)

Show source-provided references
1. Tsiamis, K. (2010). Historical and Epidemiological Approach of Plague during Byzantine Times (330–1453 a. D.). [Ph.D. Thesis, National and Kapodistrian University of Athens].
2. History of the Plague. History of the Plague: An Ancient Pandemic for the Age of COVID-1910.1016/j.amjmed.2020.08.019 ↗
3. Epidemiological trends of leprosy in an endemic state10.15253/2175-6783.2017000600010 ↗
4. Prevention and Treatment of Leprosy
5. A Contribution to the Mathematical Theory of Epidemics. laboratory of the Royal College of Physicians10.1098/rspa.1927.0118 ↗
6. A generalization of the Kermack-Mckendrick deterministic epidemic model10.1016/0025-5564(78)90006-8 ↗
7. The application of simulation models and systems analysis in epidemiology10.1016/0167-5877(93)90105-3 ↗
8. Networks and Epidemic Models10.1098/rsif.2005.0051 ↗
9. Newman, M. (2010). Networks: An Introduction, Oxford University Press.10.1093/acprof:oso/9780199206650.003.0001 ↗
10. Emerging and Reemerging Infectious Diseases: The Perpetual Challenge10.1097/00001888-200512000-00002 ↗
11. Fiore, V.G., DeFelice, N., Glicksberg, B.S., Perl, O., Shuster, A., Kulkarni, K., O'Brien, M., Pisauro, M.A., Chung, D., and Gu, X. (2021). Containment of COVID-19: Simulating the impact of different policies and testing capacities for contact tracing, testing, and isolation. PLoS ONE, 16.10.1371/journal.pone.0247614 ↗
12. Ethics and Childhood Vaccination Policy in the United States10.2105/AJPH.2015.302952 ↗
13. Viral Load in COVID-19 Patients: Implications for Prognosis and Vaccine Efficacy in the Context of Emerging SARS-CoV-2 Variants10.3389/fmed.2021.836826 ↗
14. A viral load-based model for epidemic spread on spatial networks10.3934/mbe.2021285 ↗
15. A Tale of Three Recent Pandemics: Influenza, HIV and SARS-CoV-210.3389/fmicb.2022.889643 ↗
16. Viral Load Difference between Symptomatic and Asymptomatic COVID-19 Patients: Systematic Review and Meta-Analysis10.3390/idr13030061 ↗
17. Puhach, O., Meyer, B., and Eckerle, I. (2022). SARS-CoV-2 viral load and shedding kinetics. Nat. Rev. Microbiol., 2022.10.1038/s41579-022-00822-w ↗
18. The Mathematics of Infectious Diseases
19. Epidemiological models and COVID-19: A comparative view10.1007/s40656-021-00457-9 ↗
20. Complete Coefficient Criteria for Five-Dimensional Hopf Bifurcations, with an Application to Economic Dynamics
21. Global stability of SAIRS epidemic models10.1016/j.nonrwa.2021.103501 ↗
22. Modeling COVID-19 Data using an SIR Model
23. Violato, C., Violato, E.M., and Violato, E.M. (2021). Impact of the stringency of lockdown measures on COVID-19: A theoretical model of a pandemic. PLoS ONE, 16.10.1371/journal.pone.0258205 ↗
24. Quantifying the impact of quarantine duration on COVID-19 transmission10.7554/eLife.63704 ↗
25. The importance of sustained compliance with physical distancing during COVID-19 vaccination rollout10.1038/s43856-022-00207-3 ↗
26. COVID-19 pandemic control using restrictions and vaccination10.3934/mbe.2022062 ↗
27. A geometric analysis of the SIRS epidemiological model on a homogeneous network10.1007/s00285-021-01664-5 ↗
28. Evolution of resistance to COVID-19 vaccination with dynamic social distancing10.1038/s41562-021-01281-8 ↗
29. Global stability of an SIR epidemic model with information dependent vaccination10.1016/j.mbs.2008.07.011 ↗
30. Sequential allocation of vaccine to control an infectious disease10.1016/j.mbs.2022.108879 ↗