David Simons

@davidsimons.bsky.social

88 Followers 105 Following

Former Dr. (👨‍⚕️), current Dr. (👨‍💻). Fascinated by ecological drivers of zoonosis, particularly rodent-borne 🐀🦠. Work @Penn State, Live in Stockholm, Sweden, Brexited. www.dsimons.org

A global bivariate choropleth map illustrating the intersection of small mammal species richness and mean intrinsic zoonotic hazard (community competence). A three-by-three colour matrix serves as the legend. Teal regions, such as the Amazon basin and Southeast Asia, indicate high species richness but low mean hazard. Pink regions, including northern latitudes and arid zones like Australia, indicate low species richness but high mean hazard. Dark purple regions, such as West and East Africa, Central America, and parts of South America, represent overlapping hotspots of both high biodiversity and high intrinsic hazard. Areas with fewer than two modelled species, including Antarctica and Greenland, are masked in dark grey.

Four panels detailing host phylogenetic diversity (PD) discovery over time. Panel A is a scatter plot of annual change in host PD (ΔPD_t) for arenaviruses. Each point represents a host-year discovery event, coloured by calendar year, with outlined circles indicating the yearly maximum. Panel B shows the equivalent annual change plot for hantaviruses. Spearman trend statistics for yearly maxima and all points are provided in both panels. Panel C displays a line graph of cumulative host PD for arenaviruses based on empirical discovery order. A coloured line tracks the observed trajectory against a red logarithmic least-squares fit and a hatched band representing the 95% null envelope from 10,000 random permutations. Panel D mirrors Panel C for hantaviruses. Light grey vertical bands in Panels C and D mark successive discovery-year intervals.

Three panels illustrating Bayesian phylogenetic model outputs for reservoir status. Panel A shows posterior distributions for pace of life and sampling effort coefficients. A slow pace of life is negatively associated with reservoir status, whereas increased sampling effort is strongly positively associated. Panel B is a line graph showing the marginal effect of surveillance bias, demonstrating a substantially elevated probability of reservoir detection as the number of sampled individuals increases. Panel C is a line graph showing that the probability of reservoir status strictly decreases as the pace of life transitions from fast to slow.

Three bar charts detailing sampling biases in small mammals. Panel A shows taxonomic sampling coverage for rodents, shrews, and hedgehogs; no single genus has more than 50% of its constituent species sampled. Panel B displays sampling bias by synanthropy state: non-synanthropic (NS), occasionally synanthropic (OS), and totally synanthropic (TS). The majority of species are categorised as unknown, but among known states, sampling effort increases progressively from NS to TS. Panel C shows the number of unique viruses tested per species. The distribution is heavily right-skewed; most are tested for 0 to 1 virus, decaying towards 10, with a small secondary peak at 10 and a long tail indicating a few highly investigated species tested for over 30 viruses.

A global bivariate map illustrating the intersection of small mammal species richness and mean intrinsic zoonotic hazard (community competence). A 3x3 colour matrix serves as the legend. Teal regions, such as the Amazon basin and Southeast Asia, indicate high species richness but low mean hazard. Pink regions, including northern latitudes and arid zones like Australia, indicate low species richness but high mean hazard. Dark purple regions, such as West and East Africa, Central America and parts of South America, represent overlapping hotspots of both high biodiversity and high intrinsic hazard. Areas with fewer than two modelled species, such as Antarctica and Greenland, are masked in dark grey.

a) Annual change in host phylogenetic diversity (ΔPD_t) for arenaviruses. Each point is a host-year discovery event, coloured by calendar year; outlined circles indicate the yearly maximum ΔPD_t event. b) Annual ΔPD_t for hantaviruses, with the same point encoding and yearly maximum outlines. Spearman trend statistics for yearly maxima (r_max) and all points (r_all) are shown in a) and b) (one-tailed p-values). c) Cumulative host PD for arenaviruses as hosts are added in empirical discovery order. The hatched band is the 95% null envelope from 10,000 random permutations of host discovery order; the observed trajectory is shown as the coloured line and points, and the red curve is the logarithmic least-squares fit. d) Cumulative host PD for hantaviruses, shown as in c). Light grey vertical bands in c) and d) mark successive discovery-year intervals.

Figure a) shows the posterior distributions of the PGLMM for pace of life and sampling effort. A slow pace of life is negatively associated with being a reservoir, while increased sampling effort is associated with a substantially elevated probability of being a reservoir. b) shows the marginal effect of surveillance bias alone with an increasing probability of detection with increasing number of individuals sampled. c) shows that as pace of life moves from "fast" to "slow" the probability of reservoir status decreases.

Bar chart A) shows taxonomic sampling coverage for rodent, shrew and hedgehogs. No single genera exceeds 50% of species within it sampled. Bar chart B) shows sampling biases by synanthropy states of speecies. NS refers to non-synanthropic species, OS are occasionally synanthropic species and TS are totally synanthropic. The majority of species fall in the unknown category. There is an increasing trend as you move from non-synanthropic through to totally synanthropic. Bar chart C) shows the number of unique viruses tested for by species. Most species are tested for 0-1 species, with a decay towards 10 viruses per species. There is a small secondary peak around 10 unique viruses suggesting some species are heavily investigated with the few species being tested for over 30 virus species.

Machine translation from original russian text.