  This paper uses new and existing methods to study collective trends across
countries throughout the pandemic, with a focus on the multivariate time series
of reproduction numbers and vaccine proliferation. We begin with a time-varying
analysis of the collective nature of infectivity, where we evaluate the
eigenspectrum and collective magnitude of reproduction number time series on a
country-by-country basis. Next, we study the topology of this eigenspectrum,
measuring the deviation between all points in time, and introduce a
graph-theoretic methodology to reveal a clear partition in global infectivity
dynamics. Then, we compare countries' vaccine rollouts with economic indicators
such as their GDP and HDI in a collective fashion. We investigate time-varying
consistency and determine points in time where there is the greatest
discrepancy between these indicators as a whole. Our two primary findings are a
considerable increase in collective infectivity in the latter half of the
period, and a concave-up (``down then up'') pattern in the collective
consistency between vaccine coverage and economic/development indicators across
countries.
