Long-term effects of non-pharmaceutical interventions on total disease burden in parsimonious epidemiological models.

The recent global COVID-19 pandemic resulted in governments enacting non-pharmaceutical interventions (NPIs) targeted at reducing transmission of SARS-CoV-2. But the NPIs also affected the transmission of viruses causing non-target seasonal respiratory diseases, including influenza and respiratory syncytial virus (RSV). In many countries, the NPIs were found to reduce cases of such seasonal respiratory diseases, but there is also evidence that subsequent relaxation of NPIs led to outbreaks of these diseases that were larger than pre-pandemic ones, due to the accumulation of susceptible individuals prior to relaxation. Therefore, the net long-term effects of NPIs on the total disease burden of non-target diseases remain unclear. Knowledge of this is important for infectious disease management and maintenance of public health. In this study, we shed light on this issue for the simplified scenario of a set of NPIs that prevent or reduce transmission of a seasonal respiratory disease for about a year and are then removed, using mathematical analyses and numerical simulations of a suite of four epidemiological models with varying complexity and generality. The model parameters were estimated using empirical data pertaining to seasonal respiratory diseases and covered a wide range. Our results showed that NPIs reduced the total disease burden of a non-target seasonal respiratory disease in the long-term. Expressed as a percentage of population size, the reduction was greater for larger values of the basic reproduction number and the immunity loss rate, reflecting larger outbreaks and hence more infections averted by imposition of NPIs. Our study provides a foundation for exploring the effects of NPIs on total disease burden in more-complex scenarios.

A critical assessment of the biodiversity-productivity relationship in forests and implications for conservation.

The question of whether biodiversity conservation and carbon conservation can be synergistic hinges on the form of the biodiversity-productivity relationship (BPR), a fundamental ecological pattern. The stakes are particularly high when it comes to forests, which at a global level comprises a large fraction of both biodiversity and carbon. And yet, in forests, the BPR is relatively poorly understood. In this review, we critically evaluate research on forest BPRs, focussing on the experimental and observational studies of the last 2 decades. We find general support for a positive forest BPR, suggesting that biodiversity and carbon conservation are synergistic to a degree. However, we identify several major caveats: (i) although, on average, productivity may increase with biodiversity, the highest-yielding forests are often monocultures of very productive species; (ii) productivity typically saturates at fewer than ten species; (iii) positive BPRs can be driven by some third variable, in particular stem density, instead of a causal arrow from biodiversity to productivity; (iv) the BPR's sign and magnitude varies across spatial grains and extents, and it may be weak at scales relevant to conservation; and (v) most productivity estimates in forests are associated with large errors. We conclude by explaining the importance of these caveats for both conservation programmes focussed on protection of existing forests and conservation programmes focussed on restoring or replanting forests.