Primate malarias: Diversity, distribution and insights for zoonotic Plasmodium

Protozoans within the genus Plasmodium are well-known as the causative agents of malaria in humans. Numerous Plasmodium species parasites also infect a wide range of non-human primate hosts in tropical and sub-tropical regions worldwide. Studying this diversity can provide critical insight into our understanding of human malarias, as several human malaria species are a result of host switches from non-human primates. Current spillover of a monkey malaria, Plasmodium knowlesi, in Southeast Asia highlights the permeability of species barriers in Plasmodium. Also recently, surveys of apes in Africa uncovered a previously undescribed diversity of Plasmodium in chimpanzees and gorillas. Therefore, we carried out a meta-analysis to quantify the global distribution, host range, and diversity of known non-human primate malaria species. We used published records of Plasmodium parasites found in non-human primates to estimate the total diversity of non-human primate malarias globally. We estimate that at least three undescribed primate malaria species exist in sampled primates, and many more likely exist in unstudied species. The diversity of malaria parasites is especially uncertain in regions of low sampling such as Madagascar, and taxonomic groups such as African Old World Monkeys and gibbons. Presence–absence data of malaria across primates enables us to highlight the close association of forested regions and non-human primate malarias. This distribution potentially reflects a long coevolution of primates, forest-adapted mosquitoes, and malaria parasites. The diversity and distribution of primate malaria are an essential prerequisite to understanding the mechanisms and circumstances that allow Plasmodium to jump species barriers, both in the evolution of malaria parasites and current cases of spillover into humans

Disease Ecology, Biodiversity, and the Latitudinal Gradient in Income

While most of the world is thought to be on long-term economic growth paths, more than one-sixth of the world is roughly as poor today as their ancestors were hundreds of years ago. The majority of the extremely poor live in the tropics. The latitudinal gradient in income is highly suggestive of underlying biophysical drivers, of which disease conditions are an especially salient example. However, conclusions have been confounded by the simultaneous causality between income and disease, in addition to potentially spurious relationships. We use a simultaneous equations model to estimate the relative effects of vector-borne and parasitic diseases (VBPDs) and income on each other, controlling for other factors. Our statistical model indicates that VBPDs have systematically affected economic development, evident in contemporary levels of per capita income. The burden of VBDPs is, in turn, determined by underlying ecological conditions. In particular, the model predicts it to rise as biodiversity falls. Through these positive effects on human health, the model thus identifies measurable economic benefits of biodiversity

Assessing rotation-invariant feature classification for automated wildebeest population counts

Accurate and on-demand animal population counts are the holy grail for wildlife conservation organizations throughout the world because they enable fast and responsive adaptive management policies. While the collection of image data from camera traps, satellites, and manned or unmanned aircraft has advanced significantly, the detection and identification of animals within images remains a major bottleneck since counting is primarily conducted by dedicated enumerators or citizen scientists. Recent developments in the field of computer vision suggest a potential resolution to this issue through the use of rotation-invariant object descriptors combined with machine learning algorithms. Here we implement an algorithm to detect and count wildebeest from aerial images collected in the Serengeti National Park in 2009 as part of the biennial wildebeest count. We find that the per image error rates are greater than, but comparable to, two separate human counts. For the total count, the algorithm is more accurate than both manual counts, suggesting that human counters have a tendency to systematically over or under count images. While the accuracy of the algorithm is not yet at an acceptable level for fully automatic counts, our results show this method is a promising avenue for further research and we highlight specific areas where future research should focus in order to develop fast and accurate enumeration of aerial count data. If combined with a bespoke image collection protocol, this approach may yield a fully automated wildebeest count in the near future

Linking Influenza Virus Tissue Tropism to Population-Level Reproductive Fitness

Influenza virus tissue tropism defines the host cells and tissues that support viral replication and contributes to determining which regions of the respiratory tract are infected in humans. The location of influenza virus infection along the respiratory tract is a key determinant of virus pathogenicity and transmissibility, which are at the basis of influenza burdens in the human population. As the pathogenicity and transmissibility of influenza virus ultimately determine its reproductive fitness at the population level, strong selective pressures will shape influenza virus tissue tropisms that maximize fitness. At present, the relationships between influenza virus tissue tropism within hosts and reproductive fitness at the population level are poorly understood. The selective pressures and constraints that shape tissue tropism and thereby influence the location of influenza virus infection along the respiratory tract are not well characterized. We use mathematical models that link within-host infection dynamics in a spatially-structured human respiratory tract to between-host transmission dynamics, with the aim of characterizing the possible selective pressures on influenza virus tissue tropism. The results indicate that spatial heterogeneities in virus clearance, virus pathogenicity or both, resulting from the unique structure of the respiratory tract, may drive optimal receptor binding affinity-that maximizes influenza virus reproductive fitness at the population level-towards sialic acids with α2,6 linkage to galactose. The expanding cell pool deeper down the respiratory tract, in association with lower clearance rates, may result in optimal infectivity rates-that likewise maximize influenza virus reproductive fitness at the population level-to exhibit a decreasing trend towards deeper regions of the respiratory tract. Lastly, pre-existing immunity may drive influenza virus tissue tropism towards upper regions of the respiratory tract. The propo

Epidemic Enhancement in Partially Immune Populations

We observe that a pathogen introduce/pmcdata/journal/plosone/2-2007/1/ingest/pmcmod/sgml/pone.0000165.xmld into a population containing individuals with acquired immunity can result in an epidemic longer in duration and/or larger in size than if the pathogen were introduced into a naive population. We call this phenomenon “epidemic enhancement,” and use simple dynamical models to show that it is a realistic scenario within the parameter ranges of many common infectious diseases. This finding implies that repeated pathogen introduction or intermediate levels of vaccine coverage can lead to pathogen persistence in populations where extinction would otherwise be expected

Investigating the Dynamics of Elk Population Size and Body Mass in a Seasonal Environment Using a Mechanistic Integral Projection Model

Environmentally mediated changes in body size often underlie population responses to environmental change, yet this is not a universal phenomenon. Understanding when phenotypic change underlies population responses to environmental change is important for obtaining insights and robust predictions of population dynamics in a changing world. We develop a dynamic integral projection model that mechanistically links environmental conditions to demographic rates and phenotypic traits (body size) via changes in resource availability and individual energetics. We apply the model to the northern Yellowstone elk population and explore population responses to changing patterns of seasonality, incorporating the interdependence of growth, demography, and density-dependent processes operating through population feedback on available resources. We found that small changes in body size distributions can have large impacts on population dynamics but need not cause population responses to environmental change. Environmental changes that altered demographic rates directly, via increasing or decreasing resource availability, led to large population impacts in the absence of substantial changes to body size distributions. In contrast, environmentally driven shifts in body size distributions could occur with little consequence for population dynamics when the effect of environmental change on resource availability was small and seasonally restricted and when strong density-dependent processes counteracted expected population responses. These findings highlight that a robust understanding of how associations between body size and demography influence population responses to environmental change will require knowledge of the shape of the relationship between phenotypic distributions and vital rates, the population status with regard to its carrying capacity, and importantly the nature of the environmentally driven change in body size and carrying capacity

Assessing direct contributions of morphological awareness and prosodic sensitivity to children’s word reading and reading comprehension

We examined the independent contributions of prosodic sensitivity and morphological awareness to word reading, text reading accuracy, and reading comprehension. We did so in a longitudinal study of English-speaking children (N = 70). At 5 to 7 years of age, children completed the metalinguistic measures along with control measures of phonological awareness and vocabulary. Children completed the reading measures two years later. Morphological awareness, but not prosodic sensitivity made a significant independent contribution to word reading, text reading accuracy and reading comprehension. The effects of morphological awareness on reading comprehension remained after controls for word reading. These results suggest that morphological awareness needs to be considered seriously in models of reading development and that prosodic sensitivity might have primarily indirect relations to reading outcomes. Keywords: Morphological Awareness; Prosody; Word Reading; Reading Comprehension