A recent US study showed that in order to prevent or largely extinguish the coronavirus disease 2019 (COVID-19) outbreak without social distancing or any other measures, any vaccine would have to have an efficacy of at least 70%. The research paper is currently available on the medRxiv* preprint server.
An unremitting COVID-19 pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), continues to disrupt the way we live. Due to a serious lack of alternatives, the race to develop a vaccine is a burning public health issue if we are to eliminate the need for social distancing.
Novel Coronavirus SARS-CoV-2 Colorized scanning electron micrograph of an apoptotic cell (green) heavily infected with SARS-COV-2 virus particles (purple), isolated from a patient sample. Image captured at the NIAID Integrated Research Facility (IRF) in Fort Detrick, Maryland. Credit: NIAID
Towards the ideal vaccine candidate
As different vaccine development endeavors progress, it is still not completely clear what vaccine efficacies are needed to ensure adequate protection and halt the viral spread. From an epidemiological viewpoint, it is pivotal to determine efficacy thresholds to aim for early on.
This is especially valid in the early stages of development when modifications can still be implemented more efficiently. At the moment, there are sixteen vaccine candidates under clinical phase I or II evaluation; however, over 100 preclinical vaccine candidates are in the immunization pipeline.
In order to set up ideal levels of vaccine efficacies that are needed to prevent and put out COVID-19 epidemic, researchers from the City University of New York, Baylor College of Medicine in Houston (Texas), as well as from Lundquist Institute and Torrance Memorial Medical Center in California, developed a computer simulation model representing the US population, SARS-CoV-2 spread, and vaccine impact under various conditions.
Developing a stringent model
The model advances in discrete, one-day steps for 2.5 days. Each individual in the model is in one of five mutually exclusive SARS-CoV-2 states: susceptible, exposed, infectious/asymptomatic, infectious/symptomatic, or recovered/immune. This was basically the base for transmission modeling.
Then the model introduces vaccination, which occurs on different days during the epidemic and protects in two primary ways: by preventing infection and by preventing symptomatic disease (the latter reduces viral shedding). The assumption was that vaccination protection is immediate and without impact on already infected or exposed patients.
All clinical probabilities, durations, and costs were age-specific (when available) and extracted either from representative data sources or from scientific literature. Age-specific COVID-19 data was specific to the US context as of March 16, 2020.
Finally, the researchers appraised the impact of introducing a vaccine with different efficacies in the absence of other measures from the third-party payer and societal perspectives. Experiments consisted of a thousand trial Monte Carlo simulations (i.e., computational algorithms often used in risk analysis and decision making), with varying parameters throughout their range.
Vaccine efficacy thresholds
"Our study found that to either prevent or largely extinguish an epidemic without any other measures (e.g., social distancing), the vaccine has to have an efficacy (i.e., probability of preventing infection) of at least 70% when vaccination within 90 days of the epidemic start and covers at least 60% of the population", explains study authors.
Such coverage is not entirely unreasonable, as recent polls show that approximately 75% of respondents would get the COVID-19 vaccine if it was deemed safe. Naturally, the coverage threshold rises the later the vaccination is implemented until it reaches 100% at the peak of the epidemic.
Furthermore, this estimation is based on the SARS-CoV-2 reproductive number (R0) of 2.5, which represents the number of newly infected individuals stemming from a single case. If R0 were to jump from 2.5 to 3.5, then this coverage threshold would actually increase to 100%.
Informing future research endeavors
"Our study focused on identifying the efficacy thresholds required to eliminate the need for other measures (e.g., social distancing) in order for life to 'return to normal' because that is a primary concern of the general public," study authors highlight the importance of their study.
"A vaccine with an efficacy between 40% and 70% could still obviate the need for other measures under certain circumstances such as much higher, and in some cases, potentially unachievable, vaccination coverages", they add.
Naturally, all models (including this) are by definition simplifications of real-life situations – hence, they cannot account for every possible outcome. This model drew inputs for diverse sources, but new data on SARS-CoV-2 continues to emerge on a daily rate.
Nonetheless, the study provides valuable insights on what kind of vaccine do we need to extinguish this pandemic successfully. And while the research is occurring at breakneck speed, this type of forecasting may enable the researchers to make informed decisions in this era of uncertainty.
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.