Challenges in modelling the dynamics of infectious diseases at the wildlife–human interface

The Covid-19 pandemic is of zoonotic origin, and many other emerging infections of humans have their origin in an animal host population. We review the challenges involved in modelling the dynamics of wildlife-human interfaces governing infectious disease emergence and spread. We argue that we need a better understanding of the dynamic nature of such interfaces, the underpinning diversity of pathogens and host-pathogen association networks, and the scales and frequencies at which environmental conditions enable spillover and host shifting from animals to humans to occur. The major drivers of the emergence of zoonoses are anthropogenic, including the global change in climate and land use. These, and other ecological processes pose challenges that must be overcome to counterbalance pandemic risk. The development of more detailed and nuanced models will provide better tools for analysing and understanding infectious disease emergence and spread

Optimizing noninvasive sampling of a zoonotic bat virus

Outbreaks of infectious viruses resulting from spillover events from bats have brought much attention to bat-borne zoonoses, which has motivated increased ecological and epidemiological studies on bat populations. Field sampling methods often collect pooled samples of bat excreta from plastic sheets placed under-roosts. However, positive bias is introduced because multiple individuals may contribute to pooled samples, making studies of viral dynamics difficult. Here, we explore the general issue of bias in spatial sample pooling using Hendra virus in Australian bats as a case study. We assessed the accuracy of different under-roost sampling designs using generalized additive models and field data from individually captured bats and pooled urine samples. We then used theoretical simulation models of bat density and under-roost sampling to understand the mechanistic drivers of bias. The most commonly used sampling design estimated viral prevalence 3.2 times higher than individual-level data, with positive bias 5–7 times higher than other designs due to spatial autocorrelation among sampling sheets and clustering of bats in roosts. Simulation results indicate using a stratified random design to collect 30–40 pooled urine samples from 80 to 100 sheets, each with an area of 0.75–1 m2, and would allow estimation of true prevalence with minimum sampling bias and false negatives. These results show that widely used under-roost sampling techniques are highly sensitive to viral presence, but lack specificity, providing limited information regarding viral dynamics. Improved estimation of true prevalence can be attained with minor changes to existing designs such as reducing sheet size, increasing sheet number, and spreading sheets out within the roost area. Our findings provide insight into how spatial sample pooling is vulnerable to bias for a wide range of systems in disease ecology, where optimal sampling design is influenced by pathogen prevalence, host population density, and patterns of aggregation

A cyst-forming coccidian with large geographical range infecting forest and commensal rodents: Sarcocystis muricoelognathis sp. nov.

The geographic distribution and host-parasite interaction networks of Sarcocystis spp. in small mammals in eastern Asia remain incompletely known.Experimental infections, morphological and molecular characterizations were used for discrimination of a new Sarcocystis species isolated from colubrid snakes and small mammals collected in Thailand, Borneo and China.We identified a new species, Sarcocystis muricoelognathis sp. nov., that features a relatively wide geographic distribution and infects both commensal and forest-inhabiting intermediate hosts. Sarcocystis sporocysts collected from rat snakes (Coelognathus radiatus, C. flavolineatus) in Thailand induced development of sarcocysts in experimental SD rats showing a type 10a cyst wall ultrastructure that was identical with those found in Rattus norvegicus from China and the forest rat Maxomys whiteheadi in Borneo. Its cystozoites had equal sizes in all intermediate hosts and locations, while sporocysts and cystozoites were distinct from other Sarcocystis species. Partial 28S rRNA sequences of S. muricoelognathis from M. whiteheadi were largely identical to those from R. norvegicus in China but distinct from newly sequenced Sarcocystis zuoi. The phylogeny of the nuclear 18S rRNA gene placed S. muricoelognathis within the so-called S. zuoi complex, including Sarcocystis attenuati, S. kani, S. scandentiborneensis and S. zuoi, while the latter clustered with the new species. However, the phylogeny of the ITS1-region confirmed the distinction between S. muricoelognathis and S. zuoi. Moreover, all three gene trees suggested that an isolate previously addressed as S. zuoi from Thailand (KU341120) is conspecific with S. muricoelognathis. Partial mitochondrial cox1 sequences of S. muricoelognathis were almost identical with those from other members of the group suggesting a shared, recent ancestry. Additionally, we isolated two partial 28S rRNA Sarcocystis sequences from Low’s squirrel Sundasciurus lowii that clustered with those of S. scandentiborneensis from treeshews.Our results provide strong evidence of broad geographic distributions of rodent-associated Sarcocystis and host shifts between commensal and forest small mammal species, even if the known host associations remain likely only snapshots of the true associations

Present and historical landscape structure shapes current species richness in Central European grasslands

Current diversity and species composition of ecological communities can often not exclusively be explained by present land use and landscape structure. Historical land use may have considerably influenced ecosystems and their properties for decades and centuries.We analysed the effects of present and historical landscape structure on plant and arthropod species richness in temperate grasslands, using data from comprehensive plant and arthropod assessments across three regions in Germany and maps of current and historical land cover from three time periods between 1820 and 2016.We calculated local, grassland class and landscape scale metrics for 150 grassland plots. Class and landscape scale metrics were calculated in buffer zones of 100 to 2000 m around the plots. We considered effects on total species richness as well as on the richness of species subsets determined by taxonomy and functional traits related to habitat use, dispersal and feeding.Overall, models containing a combination of present and historical landscape metrics showed the best fit for several functional groups. Comparing three historical time periods, data from the 1820/50s was among the most frequent significant time periods in our models (29.7% of all significant variables).Our results suggest that the historical landscape structure is an important predictor of current species richness across different taxa and functional groups. This needs to be considered to better identify priority sites for conservation and to design biodiversity-friendly land use practices that will affect landscape structure in the future

Modelling nonlinear responses of a desert rodent species to environmental change with hierarchical dynamic generalized additive models

Modelling abundance fluctuations of species is a crucial first step for understanding and forecasting system dynamics under future conditions. But, especially in multivariate response data, this can be hampered by characteristics of the study system such as unknown complexity, differently formed spatial and temporal dependency, non-linear relationships, and observation characteristics such as zero-inflation. This study aimed to explore how such challenges can be addressed by using hierarchical Dynamic Generalized Additive Models (DGAM) for multivariate count responses in a Bayesian framework while modelling multi-site monthly captures for the Desert Pocket Mouse (Chaetodipus penicillatus) over 23 years from a long-term study in Arizona, USA. By fitting models of increasing complexity and developing bespoke checking functions that captured targeted ecological aspects such as spatio-temporal dependence, we show how nonlinear dynamic models can be built to improve forecasts for multivariate count-valued time series.We found strong evidence that accounting for non-linear and time-lagged effects of as much as 12 months improved model fit and forecasting performance. Evaluation of models for other species in geographically different habits is essential for generalizing model strategies and insights into long-term abundance-environment relationships, while systematic comparisons will only be possible if multivariate modelling workflows account for the complexity of non-linear and lagged effects and potentially also other aspects such as biotic interactions

Host Specificity in Variable Environments

Host specificity encompasses the range and diversity of host species that a parasite is capable of infecting and is considered a crucial measure of a parasite's potential to shift hosts and trigger disease emergence. Yet empirical studies rarely consider that regional observations only reflect a parasite's 'realized' host range under particular conditions: the true 'fundamental' range of host specificity is typically not approached. We provide an overview of challenges and directions in modelling host specificity under variable environmental conditions. Combining tractable modelling frameworks with multiple data sources that account for the strong interplay between a parasite's evolutionary history, transmission mode, and environmental filters that shape host-parasite interactions will improve efforts to quantify emerging disease risk in times of global change

Challenges in modelling the dynamics of infectious diseases at the wildlife-human interface.

Funder: Alborada TrustThe Covid-19 pandemic is of zoonotic origin, and many other emerging infections of humans have their origin in an animal host population. We review the challenges involved in modelling the dynamics of wildlife-human interfaces governing infectious disease emergence and spread. We argue that we need a better understanding of the dynamic nature of such interfaces, the underpinning diversity of pathogens and host-pathogen association networks, and the scales and frequencies at which environmental conditions enable spillover and host shifting from animals to humans to occur. The major drivers of the emergence of zoonoses are anthropogenic, including the global change in climate and land use. These, and other ecological processes pose challenges that must be overcome to counterbalance pandemic risk. The development of more detailed and nuanced models will provide better tools for analysing and understanding infectious disease emergence and spread

Joint effects of species traits and environmental preferences on range edge shifts of British birds

Aim: Despite the strong evidence of species range shifts as a response to environmental change, attempts to identify species traits that modulate those shifts have been equivocal. We investigate the role of species traits and environmental preferences on birds' range shifts in Great Britain, an island where dispersal is limited by the English Channel and the North Sea. Location: Great Britain (England, Scotland and Wales). Taxa: Birds (Aves). Time Period: 1968–2011. Methods: Using 404,949 occurrence records from two time periods, we investigated the potential drivers of leading and rear range edge shifts of breeding birds using phylogenetic linear mixed models. We hypothesized that shifts are influenced by species' trophic and morphological traits, dispersal abilities and environmental preferences, but also by the geographical boundaries of Great Britain. Results: Geographical boundaries—the distance from the northern or southern boundaries of Britain—accounted for most of the variability in range edge shifts. Species traits and environmental preferences emerged as relevant drivers of range shifts only for northern and Passeriform species. Northern habitat specialist, those with more predators and those sensitive to precipitation were more likely to shift their rear edge poleward. For Passeriformes, habitat generalists, species with smaller dispersal capabilities, under higher predatory pressure or associated with forest and grassland were more likely to shift their rear edge poleward. Main Conclusions: While geographical boundaries impose constraints on range shifts in British birds, the subtle effects of species traits and environmental preferences emerge as relevant predictors for Northern and passeriform species' rear edge shifts. This highlights the importance of accounting for geographical boundaries when predicting species responses to global change. Differential range shifts of species across different trophic levels could result in the reorganization of biotic interactions, with consequences for ecosystem structure and stability

Distinct spread of DNA and RNA viruses among mammals amid prominent role of domestic species

AimEmerging infectious diseases arising from pathogen spillover from mammals to humans constitute a substantial health threat. Tracing virus origin and predicting the most likely host species for future spillover events are major objectives in One Health disciplines.We assessed patterns of virus sharing among a large diversity of mammals, including humans and domestic species.LocationGlobal.Time periodCurrent.Major taxa studiedMammals and associated viruses.MethodsWe used network centrality analysis and trait-based Bayesian hierarchical models to explore patterns of virus sharing among mammals. We analysed a global database that compiled the associations between 1,785 virus species and 725 mammalian host species as sourced from automatic screening of meta-data accompanying published nucleotide sequences between 1950 and 2019.ResultsWe show that based on current evidence, domesticated mammals hold the most central positions in networks of known mammal-virus associations. Among entire host-virus networks, Carnivora and Chiroptera hold central positions for mainly sharing RNA viruses, whereas ungulates hold central positions for sharing both RNA and DNA viruses with other host species. We revealed strong evidence that DNA viruses were phylogenetically more host specific than RNA viruses. RNA viruses exhibited low functional host specificity despite an overall tendency to infect phylogenetically related species, signifying high potential to shift across hosts with different ecological niches. The frequencies of sharing viruses among hosts and the proportion of zoonotic viruses in hosts were larger for RNA than for DNA viruses.Main conclusionsAcknowledging the role of domestic species in addition to host and virus traits in patterns of virus sharing is necessary to improve our understanding of virus spread and spillover in times of global change. Understanding multi-host virus-sharing pathways adds focus to curtail disease spread

Diverse MHC IIB allele repertoire increases parasite resistance and body condition in the Long-tailed giant rat (Leopoldamys sabanus)

<p>Abstract</p> <p>Background</p> <p>Genes of the major histocompatibility complex (MHC) code for key functions in the adaptive immune response of vertebrates and most of them show exceptionally high polymorphism. This polymorphism has been associated with the selection by diverse and changing parasite communities. We analysed MHC class IIB diversity, gastrointestinal parasite load and body condition in the wild ranging tropical rat <it>Leopoldamys sabanus </it>(Thomas, 1887) under natural selection conditions in a highly variable rainforest environment in Borneo to explore the mechanisms that maintain these high levels of genetic polymorphism.</p> <p>Results</p> <p>Allelic diversity was determined via SSCP and sequencing, and parasite screening was done through non-invasive faecal egg count. The detected alleles showed expected high levels of polymorphism and balancing selection. Besides a clear advantage for more diverse MHC genotypes in terms of number of alleles, reflected in better body condition and resistance against helminth infection, our data also suggested a positive effect of MHC allele divergence within an individual on these parameters.</p> <p>Conclusion</p> <p>In accordance with the heterozygote advantage hypothesis, this study provides evidence for an advantage of more diverse MHC genotypes. More specifically, the potential negative relation between individual allele divergence and number of parasite species is in line with the '<it>divergent allele advantage</it>' hypothesis.</p