DaXi-high-resolution, large imaging volume and multi-view single-objective light-sheet microscopy.

The promise of single-objective light-sheet microscopy is to combine the convenience of standard single-objective microscopes with the speed, coverage, resolution and gentleness of light-sheet microscopes. We present DaXi, a single-objective light-sheet microscope design based on oblique plane illumination that achieves: (1) a wider field of view and high-resolution imaging via a custom remote focusing objective; (2) fast volumetric imaging over larger volumes without compromising image quality or necessitating tiled acquisition; (3) fuller image coverage for large samples via multi-view imaging and (4) higher throughput multi-well imaging via remote coverslip placement. Our instrument achieves a resolution of 450 nm laterally and 2 µm axially over an imaging volume of 3,000 × 800 × 300 µm. We demonstrate the speed, field of view, resolution and versatility of our instrument by imaging various systems, including Drosophila egg chamber development, zebrafish whole-brain activity and zebrafish embryonic development - up to nine embryos at a time.

A minimal model for household-based testing and tracing in epidemics.

In a previous work (Huberet al.2020Phys. Biol.17065010), we discussed virus transmission dynamics modified by a uniform clustering of contacts in the population: close contacts within households and more distant contacts between households. In this paper, we discuss testing and tracing in such a stratified population. We propose a minimal tracing strategy consisting of random testing of the entire population plus full testing of the households of those persons found positive. We provide estimates of testing frequency for this strategy to work.

A minimal model for household effects in epidemics.

Shelter-in-place and other confinement strategies implemented in the current COVID-19 pandemic have created stratified patterns of contacts between people: close contacts within households and more distant contacts between the households. The epidemic transmission dynamics is significantly modified as a consequence. We introduce a minimal model that incorporates these household effects in the framework of mean-field theory and numerical simulations. We show that the reproduction number R 0 depends on the household size in a surprising way: linearly for relatively small households, and as a square root of size for larger households. We discuss the implications of the findings for the lockdown, test, tracing, and isolation policies.

A high-resolution flux-matrix model describes the spread of diseases in a spatial network and the effect of mitigation strategies.

Propagation of an epidemic across a spatial network of communities is described by a variant of the SIR model accompanied by an intercommunity infectivity matrix. This matrix is estimated from fluxes between communities, obtained from cell-phone tracking data recorded in the USA between March 2020 and February 2021. We apply this model to the SARS-CoV-2 pandemic by fitting just one global parameter representing the frequency of interaction between individuals. We find that the predicted infections agree reasonably well with the reported cases. We clearly see the effect of "shelter-in-place" policies introduced at the onset of the pandemic. Interestingly, a model with uniform transmission rates produces similar results, suggesting that the epidemic transmission was deeply influenced by air travel. We then study the effect of alternative mitigation policies, in particular restricting long-range travel. We find that this policy is successful in decreasing the epidemic size and slowing down the spread, but less effective than the shelter-in-place policy. This policy can result in a pulled wave of infections. We express its velocity and characterize the shape of the traveling front as a function of the epidemiological parameters. Finally, we discuss a policy of selectively constraining travel based on an edge-betweenness criterion.

Anthroponumbers.org: A quantitative database of human impacts on Planet Earth.

The Human Impacts Database (www.anthroponumbers.org) is a curated, searchable resource housing quantitative data relating to the diverse anthropogenic impacts on our planet, with topics ranging from sea-level rise to livestock populations, greenhouse gas emissions, fertilizer use, and beyond. Each entry in the database reports a quantitative value (or a time series of values) along with clear referencing of the primary source, the method of measurement or estimation, an assessment of uncertainty, and links to the underlying data, as well as a permanent identifier called a Human Impacts ID (HuID). While there are other databases that house some of these values, they are typically focused on a single topic area, like energy usage or greenhouse gas emissions. The Human Impacts Database facilitates access to carefully curated data, acting as a quantitative resource pertaining to the myriad ways in which humans have an impact on the Earth, for practicing scientists, the general public, and those involved in education for sustainable development alike. We outline the structure of the database, describe our curation procedures, and use this database to generate a graphical summary of the current state of human impacts on the Earth, illustrating both their numerical values and their intimate interconnections.