A group of pandemic modeling experts from the University of Sydney’s
Faculty of Engineering have published new research that simulated viral
influenza outbreaks to examine the efficacy of pandemic interventions in
the absence of a tailored vaccine.
The general use of low-efficacy vaccines, coupled with a targeted
application of antiviral medications, may be effective at countering the
spread of influenza pandemics, new research from the University of
Sydney has found.
Published by the
Journal of The Royal Society Interface, the modeling sought to examine the effectiveness of pandemic interventions in the absence of a strain-specific
vaccine.
“Pandemics typically occur with the emergence of new viral strains
for which no tailored vaccine exists,” said Dr. Cameron Zachreson from
the University’s Centre for Complex Systems, who in 2018 published
research that found urbanization and air travel were leading to a
growing risk of pandemic in Australian cities.
“Without a readily available vaccine, governments must mitigate
outbreaks in other ways, making do with mechanisms at hand, such as
antiviral medications, social distancing and low-efficacy vaccines
developed for different viral strains. These are known as pre-pandemic
vaccines.”
Dr. Zachreson’s team found pre-pandemic vaccines are most effective
at containing a pandemic when combined with fast, contact-targeted,
antiviral medication, which helps reduce transmission.
“These targeted interventions need to be implemented quickly compared
to the transmission rate of the disease,” said Dr. Zachreson.
“The more effective a targeted strategy is at mitigating the
epidemic, the longer it will have to be in place,” he added. “Mitigation
will slow down disease spread but is unlikely to eradicate the pathogen
completely.”
Even if a pre-pandemic vaccine is unable to bring about herd
immunity, it can slow the spread of the virus and open a longer time
window in which other measures can be effectively implemented, the
researchers found.
Lessons for the COVID-19 pandemic
“Our study focuses on
influenza,
for which many vaccines have previously been developed. There are no
coronavirus vaccines available so pre-pandemic vaccination is not
currently possible for COVID-19,” said Dr. Zachreson.
“If, hypothetically, a low-efficacy coronavirus vaccine was
developed, our study would support its distribution in combination with
other measures, as this would likely make them more effective.
“Another takeaway is that timing is everything in preventing a
pandemic
with targeted interventions. Cases must be identified, contacts traced,
and measures implemented before the disease has time to spread within
the community.”
Targeting neighborhoods less effective than contact targeting
The study showed that giving antiviral medication to people living in
the same neighborhoods as index cases (the first documented patients
within a population) was inefficient and did not significantly impact
the disease’s rate of spread.
“On the other hand, giving antiviral medication to the social
contacts of index cases did slow down disease spread if the response was
fast compared to disease transmission speed,” Dr. Zachreson said.
“While there are no known antivirals that are effective for COVID-19,
our study does reinforce the importance of contact tracing for the
targeting of mitigation measures, as opposed to targeting by residential
location.”
How the modeling worked
The AceMod simulator, a peer-reviewed method created by the Centre
for Complex Systems, comprises over twenty-four million software agents,
each with attributes of an anonymous individual, such as age,
occupation, susceptibility and immunity to diseases. Contact rates
within different social contexts, such as households, household
clusters, local neighborhoods, schools, classrooms and workplaces are
also built into the program.
The set of generated agents captures average characteristics of the
real population and is calibrated to 2016 Australian Census data with
respect to key demographic statistics.
More information: Cameron Zachreson et al. Interfering with influenza: nonlinear coupling of reactive and static mitigation strategies,
Journal of The Royal Society Interface (2020).
DOI: 10.1098/rsif.2019.0728