  The role of direct cell-to-cell spread in viral infections - where virions
spread between host and susceptible cells without needing to be secreted into
the extracellular environment - has come to be understood as essential to the
dynamics of medically significant viruses like hepatitis C and influenza.
Recent work in both the experimental and mathematical modelling literature has
attempted to quantify the prevalence of cell-to-cell infection compared to the
conventional free virus route using a variety of methods and experimental data.
However, estimates are subject to significant uncertainty and moreover rely on
data collected by inhibiting one mode of infection by either chemical or
physical factors, which may influence the other mode of infection to an extent
which is difficult to quantify. In this work, we conduct a
simulation-estimation study to probe the practical identifiability of the
proportion of cell-to-cell infection, using two standard mathematical models
and synthetic data that would likely be realistic to obtain in the laboratory.
We show that this quantity cannot be estimated using non-spatial data alone,
and that the collection of a data which describes the spatial structure of the
infection is necessary to infer the proportion of cell-to-cell infection. Our
results provide guidance for the design of relevant experiments and
mathematical tools for accurately inferring the prevalence of cell-to-cell
infection in $\textit{in vitro}$ and $\textit{in vivo}$ contexts.
