Ecology drives the worldwide distribution of human diseases

Abstract

Identifying the factors underlying the origin and maintenance of the latitudinal diversity gradient is a central problem in ecology, but no consensus has emerged on which processes might generate this broad pattern. Interestingly, the vast majority of studies exploring the gradient have focused on free-living organisms, ignoring parasitic and infectious disease (PID) species. Here, we address the influence of environmental factors on the biological diversity of human pathogens and their global spatial organization. Using generalized linear multivariate models and Monte Carlo simulations, we conducted a series of comparative analyses to test the hypothesis that human PIDs exhibit the same global patterns of distribution as other taxonomic groups. We found a significant negative relationship between latitude and PID species richness, and a nested spatial organization, i.e., the accumulation of PID species with latitude, over large spatial scales. Additionally, our results show that climatic factors are of primary importance in explaining the link between latitude and the spatial pattern of human pathogens. Based on our findings, we propose that the global latitudinal species diversity gradient might be generated in large part by biotic interactions, providing strong support for the idea that current estimates of species diversity are substantially underestimated. When parasites and pathogens are included, estimates of total species diversity may increase by more than an order of magnitude.

Figure 1. The Spatial Organization of Species

Letters represent different PID species. Numbered rectangles represent different countries or areas. (A) Nested organization of species. Applying Diamond's theory, we here distinguish (1) “high-S” species, like species E, which are exclusively confined to the most species-rich communities; and (2) “tramps,” like species A, which occur mostly in richer communities but also in species-poor communities (e.g., measles, which is found in virtually every country). Thus, this nested pattern implies that some pathogens are restricted to the tropics, while others, more ubiquitous species, are widely and regularly distributed all over the world. (B) Random distribution of species, where no spatial organization occurs (see also Materials and Methods).

Figure 2. The Latitudinal Gradients of PID Species

(A) Relationship between PID species richness and latitude across the two hemispheres. Linear relationships between PID species richness and latitude (dotted lines) are highly significant (F = 12.29, df = 29, p = 0.0015 and F = 18.01, df = 130, p < 0.0001 for Southern and Northern hemispheres, respectively). No difference in disease species richness with latitude across the two hemispheres was observed (interaction: F = 2.68, df = 159, p = 0.1036). Residuals of PID species richness on the y axis were extracted from minimal models controlling for the effects of confounding factors on PID species diversity estimates (see Materials and Methods). Locally weighted regression (tension 0.5) did not change the general linear shape. Latitude is expressed in minute degrees. (B) Presence/absence matrix for the 229 distinct PID species across the hemispheres. The figure was generated by the Nestedness Temperature Calculator (see Atmar and Patterson 1995). The distribution is nonsymetrical because of the 224 studied countries, 172 countries are found in the Northern hemisphere versus only 52 in the Southern one. (B) indicates that PID species diversity decreases as one moves northwards or southwards from the equator. The black exponential curves are the occurrence boundary lines (see Materials and Methods). The color scale indicates the nonuniform probability of state occupancy among all of the cells of the matrix, i.e., the probability of encountering a species as function of its position in the matrix. Black cells are highly predictable presences, whereas red cells are unexpected presences. (C) Monte Carlo–derived histogram after 1,000 permutations. The histogram represents the 1,000 values obtained after Monte Carlo permutations. The average theoretical value under the null hypothesis is compared to our real value, to assess the likelihood that the parent matrix was nonrandomly generated. The probability is highly significant (p < 0.0001), confirming that the spatial organization of PID species richness on the largest scale matches the nested species subset hierarchy illustrated in Figure 1A. The symmetrical Gaussian distribution indicates that 1,000 permutations are enough to obtain reliable variance estimates for probability calculations.