  COVID-19 is having a dramatic impact on research and researchers. The
pandemic has underlined the severity of known challenges in research and
surfaced new ones, but also accelerated the adoption of innovations and
manifested new opportunities. This review considers early trends emerging from
meta-research on COVID-19. In particular, it focuses on the following topics:
i) mapping COVID-19 research; ii) data and machine learning; iii) research
practices including open access and open data, reviewing, publishing and
funding; iv) communicating research to the public; v) the impact of COVID-19 on
researchers, in particular with respect to gender and career trajectories. This
overview finds that most early meta-research on COVID-19 has been reactive and
focused on short-term questions, while more recently a shift to consider the
long-term consequences of COVID-19 is taking place. Based on these findings,
the author speculates that some aspects of doing research during COVID-19 are
more likely to persist than others. These include: the shift to virtual for
academic events such as conferences; the use of openly accessible pre-prints;
the `datafication' of scholarly literature and consequent broader adoption of
machine learning in science communication; the public visibility of research
and researchers on social and online media.
