The reproduction number R has been a central metric of
the COVID-19 pandemic response, published weekly by
the UK government and regularly reported in the media.
Here, we provide a formal definition and discuss the
advantages and most common misconceptions around
this quantity. We consider the intuition behind different formulations of R, the complexities in its estimation
(including the unavoidable lags involved), and its value
compared to other indicators (e.g. the growth rate) that
can be directly observed from aggregate surveillance
data and react more promptly to changes in epidemic
trend. As models become more sophisticated, with age
and/or spatial structure, formulating R becomes increasingly complicated and inevitably model-dependent. We
present some models currently used in the UK pandemic
response as examples. Ultimately, limitations in the
available data streams, data quality and time constraints force pragmatic choices to be made on a quantity that
is an average across time, space, social structure and
settings. Effectively communicating these challenges is
important but often difficult in an emergency.