We investigate the evolution of virulence of pathogens that reduce their hosts' fitness primarily by affecting host fecundity. We show that, under many conditions, such sterilizing pathogens evolve high rather than intermediate levels of virulence, and this pushes the pathogen population and sometimes the host population toward extinction. We also show that spatial population structure can reverse this evolutionary result and allow the persistence of intermediate-virulence pathogens. Thus, spatial population structure may be vital to the persistence of sterilizing pathogens in nature.

The outbreak of SARS-CoV-2 in Wuhan, China in late December 2019 became the harbinger of the COVID-19 pandemic. During the pandemic, geospatial techniques, such as modeling and mapping, have helped in disease pattern detection. Here we provide a synthesis of the techniques and associated findings in relation to COVID-19 and its geographic, environmental, and socio-demographic characteristics, following the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) methodology for scoping reviews. We searched PubMed for relevant articles and discussed the results separately for three categories: disease mapping, exposure mapping, and spatial epidemiological modeling. The majority of studies were ecological in nature and primarily carried out in China, Brazil, and the USA. The most common spatial methods used were clustering, hotspot analysis, space-time scan statistic, and regression modeling. Researchers used a wide range of spatial and statistical software to apply spatial analysis for the purpose of disease mapping, exposure mapping, and epidemiological modeling. Factors limiting the use of these spatial techniques were the unavailability and bias of COVID-19 data—along with scarcity of fine-scaled demographic, environmental, and socio-economic data—which restrained most of the researchers from exploring causal relationships of potential influencing factors of COVID-19. Our review identified geospatial analysis in COVID-19 research and highlighted current trends and research gaps. Since most of the studies found centered on Asia and the Americas, there is a need for more comparable spatial studies using geographically fine-scaled data in other areas of the world.

Bacteriophages are the most numerous entities in the biosphere. Despite this numerical dominance, the genetic structure of bacteriophage populations is poorly understood. Here, we present a biogeography study involving 25 previously undescribed bacteriophages from the Cystoviridae clade, a group characterized by a dsRNA genome divided into three segments. Previous laboratory manipulation has shown that, when multiple Cystoviruses infect a single host cell, they undergo (i) rare intrasegment recombination events and (ii) frequent genetic reassortment between segments. Analyzing linkage disequilibrium (LD) within segments, we find no significant evidence of intrasegment recombination in wild populations, consistent with (i). An extensive analysis of LD between segments supports frequent reassortment, on a time scale similar to the genomic mutation rate. The absence of LD within this group of phages is consistent with expectations for a completely sexual population, despite the fact that some segments have >50% nucleotide divergence at 4-fold degenerate sites. This extraordinary rate of genetic exchange between highly unrelated individuals is unprecedented in any taxa. We discuss our results in light of the biological species concept applied to viruses.sex ͉ virus ͉ linkage disequilibrium ͉ Cystoviridae ͉ biogeography

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