COVID-19 vaccination strategies depend on the underlying network of social interactions

• Published in: Scientific reports Vol. 11; no. 1; p. 24051
• Main Authors: Saunders, Helena A., Schwartz, Jean-Marc
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 15-12-2021; Nature Publishing Group; Nature Portfolio
• Subjects: 631/114; 631/553; Coronaviruses; COVID-19; COVID-19 - prevention & control; COVID-19 - transmission; COVID-19 vaccines; COVID-19 Vaccines - administration & dosage; Disease control; Disease transmission; Epidemic models; Humanities and Social Sciences; Humans; Mass Vaccination - psychology; Mass Vaccination - statistics & numerical data; Models, Theoretical; multidisciplinary; Pandemics; SARS-CoV-2 - genetics; SARS-CoV-2 - pathogenicity; Science; Science (multidisciplinary); Sensitivity analysis; Social behavior; Social Interaction; Social interactions; Social organization; Vaccination; Virulence
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-021-03167-1

Since the onset of the coronavirus disease 2019 (COVID-19) pandemic, different mitigation and management strategies limiting economic and social activities have been implemented across many countries. Despite these strategies, the virus continues to spread and mutate. As a result, vaccinations are now administered to suppress the pandemic. Current COVID-19 epidemic models need to be expanded to account for the change in behaviour of new strains, such as an increased virulence and higher transmission rate. Furthermore, models need to account for an increasingly vaccinated population. We present a network model of COVID-19 transmission accounting for different immunity and vaccination scenarios. We conduct a parameter sensitivity analysis and find the average immunity length after an infection to be one of the most critical parameters that define the spread of the disease. Furthermore, we simulate different vaccination strategies and show that vaccinating highly connected individuals first is the quickest strategy for controlling the disease.