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Modeling of Vaccination and Contact Tracing as Tools to Control the COVID-19 Outbreak in Spain
Vaccines (Basel) ; 9(4):14, 2021.
Article in English | MEDLINE | ID: covidwho-1209558
ABSTRACT
We developed an agent-based stochastic model, based on P Systems methodology, to decipher the effects of vaccination and contact tracing on the control of COVID-19 outbreak at population level under different control measures (social distancing, mask wearing and hand hygiene) and epidemiological scenarios. Our findings suggest that without the application of protection social measures, 56.1% of the Spanish population would contract the disease with a mortality of 0.4%. Assuming that 20% of the population was protected by vaccination by the end of the summer of 2021, it would be expected that 45% of the population would contract the disease and 0.3% of the population would die. However, both of these percentages are significantly lower when social measures were adopted, being the best results when social measures are in place and 40% of contacts traced. Our model shows that if 40% of the population can be vaccinated, even without social control measures, the percentage of people who die or recover from infection would fall from 0.41% and 56.1% to 0.16% and 33.5%, respectively compared with an unvaccinated population. When social control measures were applied in concert with vaccination the percentage of people who die or recover from infection diminishes until 0.10% and 14.5%, after vaccinating 40% of the population. Vaccination alone can be crucial in controlling this disease, but it is necessary to vaccinate a significant part of the population and to back this up with social control measures.

Full text: Available Collection: Databases of international organizations Database: MEDLINE Topics: Vaccines Language: English Journal: Vaccines (Basel) Year: 2021 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: MEDLINE Topics: Vaccines Language: English Journal: Vaccines (Basel) Year: 2021 Document Type: Article