Network meta‐analysis (NMA) is an extension of pairwise meta‐analysis (PMA) which combines evidence from trials on multiple treatments in connected networks. NMA delivers internally consistent estimates of relative treatment efficacy, needed for rational decision making. Over its first 20 years NMA's use has grown exponentially, with applications in both health technology assessment (HTA), primarily re‐imbursement decisions and clinical guideline development, and clinical research publications. This has been a period of transition in meta‐analysis, first from its roots in educational and social psychology, where large heterogeneous datasets could be explored to find effect modifiers, to smaller pairwise meta‐analyses in clinical medicine on average with less than six studies. This has been followed by narrowly‐focused estimation of the effects of specific treatments at specific doses in specific populations in sparse networks, where direct comparisons are unavailable or informed by only one or two studies. NMA is a powerful and well‐established technique but, in spite of the exponential increase in applications, doubts about the reliability and validity of NMA persist. Here we outline the continuing controversies, and review some recent developments. We suggest that heterogeneity should be minimized, as it poses a threat to the reliability of NMA which has not been fully appreciated, perhaps because it has not been seen as a problem in PMA. More research is needed on the extent of heterogeneity and inconsistency in datasets used for decision making, on formal methods for making recommendations based on NMA, and on the further development of multi‐level network meta‐regression.

Immune correlates of protection from COVID-19 are incompletely understood. 2,826 keyworkers had T-SPOT ^® Discovery SARS-CoV-2 tests (measuring interferon-γ secreting, SARS-CoV-2 responsive T cells, Oxford Immunotec Ltd), and anti-Spike S1 domain IgG antibody levels (EuroImmun AG) performed on recruitment into a cohort study. 285/2,826 (10.1%) of participants had positive SARS-CoV-2 RT-PCR tests, predominantly associated with symptomatic illness, during 200 days followup. T cell responses to Spike, Nucleoprotein and Matrix proteins (SNM responses) were detected in some participants at recruitment, as were anti-Spike S1 IgG antibodies; higher levels of both were associated with protection from subsequent SARS-CoV-2 test positivity. In volunteers with moderate antibody responses, who represented 39% (252/654) of those with detectable anti-Spike IgG, protection was partial, and higher with higher circulating T cell SNM responses. SARS-CoV-2 responsive T cell numbers predict protection in individuals with low anti-Spike IgG responses; serology alone underestimates the proportion of the population protected after infection.