  The slogan "nobody is safe until everybody is safe" is a dictum to raise
awareness that in an interconnected world, pandemics such as COVID-19, require
a global approach. Motivated by the ongoing COVID-19 pandemic, we model here
the spread of a virus in interconnected communities and explore different
vaccination scenarios, assuming that the efficacy of the vaccination wanes over
time. We start with susceptible populations and consider a
susceptible-vaccinated-infected-recovered model with unvaccinated ("Bronze"),
moderately vaccinated ("Silver") and very well vaccinated ("Gold") communities,
connected through different types of networks via a diffusive linear coupling
for local spreading. We show that when considering interactions in
"Bronze"-"Gold" and "Bronze"-"Silver" communities, the "Bronze" community is
driving an increase in infections in the "Silver" and "Gold" communities. This
shows a detrimental, unidirectional effect of non-vaccinated to vaccinated
communities. Regarding the interactions between "Gold", "Silver" and "Bronze"
communities in a network, we find that two factors play central role: the
coupling strength in the dynamics and network density. When considering the
spread of a virus in Barab\'asi-Albert networks, infections in "Silver" and
"Gold" communities are lower than in "Bronze" communities. We find that the
"Gold" communities are the best in keeping their infection levels low. However,
a small number of "Bronze" communities are enough to give rise to an increase
in infections in moderately and well-vaccinated communities. When studying the
spread of a virus in a dense Erd\H{o}s-R\'enyi, and sparse Watts-Strogatz and
Barab\'asi-Albert networks, the communities reach the disease-free state in the
dense Erd\H{o}s-R\'enyi networks, but not in the sparse Watts-Strogatz and
Barab\'asi-Albert networks. However, we also find that if all these networks...
