COVID-19 vaccination status based infection likelihood in New Zealand
Several strategies have been formulated to combat the ongoing coronavirus disease 2019 (COVID-19) pandemic caused by a novel coronavirus, namely, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). After the rapid outbreak of the SARS-CoV-2 Delta strain, the strategy of the government of New Zealand to manage the outbreak heavily depended on the rate of vaccination, i.e., double-dose vaccination rates increased from approximately 19% of the total population to 70% as on 21 November 2021.
Scientists observed that among the fully vaccinated group, only 5% of COVID-19 infected individuals required hospitalization. An individual was considered to be fully vaccinated after two weeks post the second dose of the vaccine.
Recently, the country began the transition to the COVID-19 Protection Framework, which is based on vaccine certificates. The government has relaxed the Auckland border to those who are either fully vaccinated or possess COVID-19 negative test reports performed within 72 hours of traveling. Therefore, it is imperative to understand the probability of COVID-19 transmission through vaccinated and unvaccinated individuals.
Contact tracers are associated with preventing onward COVID-19 transmission, but they do not identify the source of infection. The risk associated with an individual getting infected or infecting others as a function of vaccination status is not available.
Using real-world cases, a new study has addressed this research gap and determined the possible number of infections caused by an unvaccinated versus vaccinated individual. The author used a previously developed stochastic model for this simulation. The study has been published on the medRxiv* preprint server.
A new study
The main importance of this study is that it could help formulate effective reopening decisions and restrictions on travel. The author estimated the possibility of getting infected or infecting others based on COVID-19 vaccination status. Mathematical tools could play a promising role in predicting these possibilities, which is important because, recently, the number of SARS-CoV-2 cases across communities has increased substantially.
In this study, a stochastic branching process model was used for simulation, seeded with either one vaccinated or one unvaccinated individual at a given time/day, and studied for 31 days. To obtain effective outcomes from the stochastic model, the simulation was run 100,000 times for each scenario. The study assumed that a COVID-19 infected person could travel and seed a new outbreak.
Despite formulating preventive measures before relaxing the Auckland border, there has been an increase in the number of COVID-19 cases in several locations of the country, such as Waikato and Northland.
In the given scenario, the author performed simulations in the stochastic mathematical model considering the latest vaccination rate of the country, i.e., 78.7% of the total population. According to the District Health Boards reports, approximately 90% of the eligible population, including individuals above 12 years, have been vaccinated.
This study projected the possibility of infections by vaccinated individuals or unvaccinated individuals within 31 days with the cumulative probabilities. It revealed the existence of a small risk of large outbreaks developing within the first 31 days of an infection being seeded by either vaccinated or unvaccinated individuals.
There is a higher possibility that the COVID-19 infection would not be transmitted beyond the initial case with vaccinated seed infection than unvaccinated seed infection. This study reported a 54% chance that unvaccinated travelers could cause 151 infections after 31 days. This finding emphasized the importance of COVID-19 vaccination in containing the pandemic.
The current study estimated that a vaccinated traveler is nine times less likely to seed an outbreak in a community than unvaccinated travelers. Therefore, this study highlighted the importance of the travelers to be vaccinated or tested negative before traveling, or both, as an essential approach to prevent further outbreaks.
The mathematical model can track the number of vaccinated and unvaccinated cases along with the vaccination status of the individuals that cause the infections. This facilitated the author to estimate the probability of infection based on the vaccination status of the infecting and infected individual. The results were obtained by calculating the mean across 100,000 realizations.
The author stated that although the vaccine provides significant protection from getting infected, vaccinated individuals may become infected from unvaccinated individuals than by another vaccinated and infected individual. This study strongly stated that most of the infections are caused by unvaccinated individuals, i.e., around 65% of infections. In contrast, vaccinated individuals are only responsible for 35% of infections.
The findings highlight the importance of COVID-19 vaccination in preventing an individual from contracting an infection and passing it to others. According to the author, unvaccinated individuals are the main cause of the continual spread of COVID-19. Thereby, restricting unvaccinated individuals from high-risk locations will help to reduce COVID-19 transmission.
medRxiv publishes preliminary scientific reports that are not peer-reviewed and, therefore, should not be regarded as conclusive, guide clinical practice/health-related behavior, or treated as established information.
- Watson, M.L. (2021) Likelihood of infecting or getting infected with COVID-19 as a function of vaccination status, as investigated with a stochastic model for New Zealand (Aotearoa). medRxiv. doi: https://doi.org/10.1101/2021.11.28.21266967 https://www.medrxiv.org/content/10.1101/2021.11.28.21266967v1