Strong and consistent effects of waterbird composition on HPAI H5 occurrences across Europe.

Since 2014, highly pathogenic avian influenza (HPAI) H5 viruses of clade 2.3.4.4 have been dominating the outbreaks across Europe, causing massive deaths among poultry and wild birds. However, the factors shaping these broad-scale outbreak patterns, especially those related to waterbird community composition, remain unclear. In particular, we do not know whether these risk factors differ from those of other H5 clades. Addressing this knowledge gap is important for predicting and preventing future HPAI outbreaks. Using extensive waterbird survey datasets from about 6883 sites, we here explored the effect of waterbird community composition on HPAI H5Nx (clade 2.3.4.4) spatial patterns in the 2016/2017 and 2020/2021 epidemics in Europe, and compared it with the 2005/2006 HPAI H5N1 (clade 2.2) epidemic. We showed that HPAI H5 occurrences in wild birds in the three epidemics were strongly associated with very similar waterbird community attributes, which suggested that, in nature, similar interspecific transmission processes operate between the HPAI H5 subtypes or clades. Importantly, community phylogenetic diversity consistently showed a negative association with H5 occurrence in all three epidemics, suggesting a dilution effect of phylogenetic diversity. In contrast, waterbird community variables showed much weaker associations with HPAI H5Nx occurrence in poultry. Our results demonstrate that models based on previous epidemics can predict future HPAI H5 patterns in wild birds, implying that it is important to include waterbird community factors in future HPAI studies to predict outbreaks and improve surveillance activities.

Host functional traits as the nexus for multilevel infection patterns.

Understanding pathogen transmission and infection patterns at multiple biological scales is a central issue in disease ecology and evolution. Here, we suggest that functional traits of host species readily affect infection patterns of species, communities, and landscapes, and thus serve as a linkage for multilevel studies of infectious disease.

Functional traits explain waterbirds' host status, subtype richness, and community-level infection risk for avian influenza.

Species functional traits can influence pathogen transmission processes, and consequently affect species' host status, pathogen diversity, and community-level infection risk. We here investigated, for 143 European waterbird species, effects of functional traits on host status and pathogen diversity (subtype richness) for avian influenza virus at species level. We then explored the association between functional diversity and HPAI H5Nx occurrence at the community level for 2016/17 and 2021/22 epidemics in Europe. We found that both host status and subtype richness were shaped by several traits, such as diet guild and dispersal ability, and that the community-weighted means of these traits were also correlated with community-level risk of H5Nx occurrence. Moreover, functional divergence was negatively associated with H5Nx occurrence, indicating that functional diversity can reduce infection risk. Our findings highlight the value of integrating trait-based ecology into the framework of diversity-disease relationship, and provide new insights for HPAI prediction and prevention.

Risk factors for Lyme disease: A scale-dependent effect of host species diversity and a consistent negative effect of host phylogenetic diversity.

Biodiversity can influence disease risk. One example of a diversity-disease relationship is the dilution effect, which suggests higher host species diversity (often indexed by species richness) reduces disease risk. While numerous studies support the dilution effect, its generality remains controversial. Most studies of diversity-disease relationships have overlooked the potential importance of phylogenetic diversity. Furthermore, most studies have tested diversity-disease relationships at one spatial scale, even though such relationships are likely scale dependent. Using Lyme disease as a model system, we investigated the effects of host species richness and phylogenetic relatedness on the number of reported Lyme disease cases in humans in the U.S.A. at two spatial scales (the county level and the state level) using piecewise structural equation modelling. We also accounted for relevant climatic and habitat-related factors and tested their correlations with the number of Lyme disease cases. We found that species assemblages with more related species (i.e., host species in the order Rodentia) were associated with more Lyme disease cases in humans. Host species richness correlated negatively with the number of Lyme disease cases at the state level (i.e., a dilution effect), a pattern that might be explained by the higher number of reservoir-incompetent species at high levels of species richness at this larger spatial scale. In contrast, a positive correlation was found between species richness and the number of Lyme disease cases at the county level, where a higher proportion of rodent species was associated with higher levels of species richness, potentially amplifying the disease risk. Our results highlight that analyse at a single spatial scale can miss some impacts of biodiversity on human health. Thus, multi-scale analyses with consideration of host phylogenetic diversity are critical for improving our understanding of diversity-disease relationships.

Habitat loss exacerbates pathogen spread: An Agent-based model of avian influenza infection in migratory waterfowl.

Habitat availability determines the distribution of migratory waterfowl along their flyway, which further influences the transmission and spatial spread of avian influenza viruses (AIVs). The extensive habitat loss in the East Asian-Australasian Flyway (EAAF) may have potentially altered the virus spread and transmission, but those consequences are rarely studied. We constructed 6 fall migration networks that differed in their level of habitat loss, wherein an increase in habitat loss resulted in smaller networks with fewer sites and links. We integrated an agent-based model and a susceptible-infected-recovered model to simulate waterfowl migration and AIV transmission. We found that extensive habitat loss in the EAAF can 1) relocate the outbreaks northwards, responding to the distribution changes of wintering waterfowl geese, 2) increase the outbreak risk in remaining sites due to larger goose congregations, and 3) facilitate AIV transmission in the migratory population. In addition, our modeling output was in line with the predictions from the concept of "migratory escape", i.e., the migration allows the geese to "escape" from the location where infection risk is high, affecting the pattern of infection prevalence in the waterfowl population. Our modeling shed light on the potential consequences of habitat loss in spreading and transmitting AIV at the flyway scale and suggested the driving mechanisms behind these effects, indicating the importance of conservation in changing spatial and temporal patterns of AIV outbreaks.

Mammal assemblage composition predicts global patterns in emerging infectious disease risk.

As a source of emerging infectious diseases, wildlife assemblages (and related spatial patterns) must be quantitatively assessed to help identify high-risk locations. Previous assessments have largely focussed on the distributions of individual species; however, transmission dynamics are expected to depend on assemblage composition. Moreover, disease-diversity relationships have mainly been studied in the context of species loss, but assemblage composition and disease risk (e.g. infection prevalence in wildlife assemblages) can change without extinction. Based on the predicted distributions and abundances of 4466 mammal species, we estimated global patterns of disease risk through the calculation of the community-level basic reproductive ratio R0, an index of invasion potential, persistence, and maximum prevalence of a pathogen in a wildlife assemblage. For density-dependent diseases, we found that, in addition to tropical areas which are commonly viewed as infectious disease hotspots, northern temperate latitudes included high-risk areas. We also forecasted the effects of climate change and habitat loss from 2015 to 2035. Over this period, many local assemblages showed no net loss of species richness, but the assemblage composition (i.e. the mix of species and their abundances) changed considerably. Simultaneously, most areas experienced a decreased risk of density-dependent diseases but an increased risk of frequency-dependent diseases. We further explored the factors driving these changes in disease risk. Our results suggest that biodiversity and changes therein jointly influence disease risk. Understanding these changes and their drivers and ultimately identifying emerging infectious disease hotspots can help health officials prioritize resource distribution.

Effects of migration network configuration and migration synchrony on infection prevalence in geese.

Migration can influence dynamics of pathogen-host interactions. However, it is not clearly known how migration pattern, in terms of the configuration of the migration network and the synchrony of migration, affects infection prevalence. We therefore applied a discrete-time SIR model, integrating environmental transmission and migration, to various migration networks, including networks with serial, parallel, or both serial and parallel stopover sites, and with various levels of migration synchrony. We applied the model to the infection of avian influenza virus in a migratory geese population. In a network with only serial stopover sites, increasing the number of stopover sites reduced infection prevalence, because with every new stopover site, the amount of virus in the environment was lower than that in the previous stopover site, thereby reducing the exposure of the migratory population. In a network with parallel stopover sites, both increasing the number and earlier appearance of the stopover sites led to an earlier peak of infection prevalence in the migratory population, because the migratory population is exposed to larger total amount of virus in the environment, speeding-up the infection accumulation. Furthermore, higher migration synchrony reduced the average number of cumulative infection, because the majority of the population can fly to a new stopover site where the amount of virus is still relatively low and has not been increased due to virus shedding of infected birds. Our simulations indicate that a migration pattern with multiple serial stopover sites and with highly synchronized migration reduces the infection prevalence.

Contrasting effects of host species and phylogenetic diversity on the occurrence of HPAI H5N1 in European wild birds.

Studies on the highly pathogenic avian influenza (HPAI) H5N1 suggest that wild bird migration may facilitate its long-distance spread, yet the role of wild bird community composition in its transmission risk remains poorly understood. Furthermore, most studies on the diversity-disease relationship focused on host species diversity without considering hosts' phylogenetic relationships, which may lead to rejecting a species diversity effect when the community has host species that are only distantly related. Here, we explored the influence of waterbird community composition for determining HPAI H5N1 occurrence in wild birds in a continental-scale study across Europe. In particular, we tested the diversity-disease relationship using both host species diversity and host phylogenetic diversity. Our results provide the first demonstration that host community composition-compared with previously identified environmental risk factors-can also effectively explain the spatial pattern of H5N1 occurrence in wild birds. We further show that communities with more higher risk host species and more closely related species have a higher risk of H5N1 outbreaks. Thus, both host species diversity and community phylogenetic structure, in addition to environmental factors, jointly influence H5N1 occurrence. Our work not only extends the current theory on the diversity-disease relationship, but also has important implications for future monitoring of H5N1 and other HPAI subtypes.

Hierarchical structure in the world's largest high-speed rail network.

Presently, China has the largest high-speed rail (HSR) system in the world. However, our understanding of the network structure of the world's largest HSR system remains largely incomplete due to the limited data available. In this study, a publicly available data source, namely, information from a ticketing website, was used to collect an exhaustive dataset on the stations and routes within the Chinese HSR system. The dataset included all 704 HSR stations that had been built as of June, 2016. A classical set of frequently used metrics based on complex network theory were analyzed, including degree centrality, betweenness centrality, and closeness centrality. The frequency distributions of all three metrics demonstrated highly consistent bimodal-like patterns, suggesting that the Chinese HSR network consists of two distinct regimes. The results indicate that the Chinese HSR system has a hierarchical structure, rather than a scale-free structure as has been commonly observed. To the best of our knowledge, such a network structure has not been found in other railway systems, or in transportation systems in general. Follow-up studies are needed to reveal the formation mechanisms of this hierarchical network structure.

Spatial heterogeneity of hemorrhagic fever with renal syndrome is driven by environmental factors and rodent community composition.

Hemorrhagic fever with renal syndrome (HFRS) is a rodent-borne disease caused mainly by two hantaviruses in China: Hantaan virus and Seoul virus. Environmental factors can significantly affect the risk of contracting hantavirus infections, primarily through their effects on rodent population dynamics and human-rodent contact. We aimed to clarify the environmental risk factors favoring rodent-to-human transmission to provide scientific evidence for developing effective HFRS prevention and control strategies. The 10-year (2006-2015) field surveillance data from the rodent hosts for hantavirus, the epidemiological and environmental data extracted from satellite images and meteorological stations, rodent-to-human transmission rates and impacts of the environment on rodent community composition were used to quantify the relationships among environmental factors, rodent species and HFRS occurrence. The study included 709 cases of HFRS. Rodent species in Chenzhou, a hantavirus hotspot, comprise mainly Rattus norvegicus, Mus musculus, R. flavipectus and some other species (R. losea and Microtus fortis calamorum). The rodent species played different roles across the various land types we examined, but all of them were associated with transmission risks. Some species were associated with HFRS occurrence risk in forest and water bodies. R. norvegicus and R. flavipectus were associated with risk of HFRS incidence in grassland, whereas M. musculus and R. flavipectus were associated with this risk in built-on land. The rodent community composition was also associated with environmental variability. The predictive risk models based on these significant factors were validated by a good-fit model, where: cultivated land was predicted to represent the highest risk for HFRS incidence, which accords with the statistics for HFRS cases in 2014-2015. The spatial heterogeneity of HFRS disease may be influenced by rodent community composition, which is associated with local environmental conditions. Therefore, future work should focus on preventing HFRS is moist, warm environments.

Landscape and rodent community composition are associated with risk of hemorrhagic fever with renal syndrome in two cities in China, 2006-2013.

BACKGROUND: Hemorrhagic fever with renal syndrome (HFRS) is a rodent-borne disease caused by hantaviruses. Landscape can influence the risk of hantavirus infection for humans, mainly through its effect on rodent community composition and distribution. It is important to understand how landscapes influence population dynamics for different rodent species and the subsequent effect on HFRS risk. METHODS: To determine how rodent community composition influenced human hantavirus infection, we monitored rodent communities in the prefecture-level cities of Loudi and Shaoyang, China, from 2006 to 2013. Land use data were extracted from satellite images and rodent community diversity was analyzed in 45 trapping sites, in different environments. Potential contact matrices, determining how rodent community composition influence HFRS infection among different land use types, were estimated based on rodent community composition and environment type for geo-located HFRS cases. RESULTS: Apodemus agrarius and Rattus norvegicus were the predominant species in Loudi and Shaoyang, respectively. The major risk of HFRS infection was concentrated in areas with cultivated land and was associated with A. agrarius, R. norvegicus, and Rattus flavipectus. In urban areas in Shaoyang, Mus musculus was related to risk of hantavirus infection. CONCLUSIONS: Landscape features and rodent community dynamics may affect the risk of human hantavirus infection. Results of this study may be useful for the development of HFRS prevention initiatives that are customized for regions with different geographical environments.

Macroecological factors shape local-scale spatial patterns in agriculturalist settlements.

Macro-scale patterns of human systems ranging from population distribution to linguistic diversity have attracted recent attention, giving rise to the suggestion that macroecological rules shape the assembly of human societies. However, in which aspects the geography of our own species is shaped by macroecological factors remains poorly understood. Here, we provide a first demonstration that macroecological factors shape strong local-scale spatial patterns in human settlement systems, through an analysis of spatial patterns in agriculturalist settlements in eastern mainland China based on high-resolution Google Earth images. We used spatial point pattern analysis to show that settlement spatial patterns are characterized by over-dispersion at fine spatial scales (0.05-1.4 km), consistent with territory segregation, and clumping at coarser spatial scales beyond the over-dispersion signals, indicating territorial clustering. Statistical modelling shows that, at macroscales, potential evapotranspiration and topographic heterogeneity have negative effects on territory size, but positive effects on territorial clustering. These relationships are in line with predictions from territory theory for hunter-gatherers as well as for many animal species. Our results help to disentangle the complex interactions between intrinsic spatial processes in agriculturalist societies and external forcing by macroecological factors. While one may speculate that humans can escape ecological constraints because of unique abilities for environmental modification and globalized resource transportation, our work highlights that universal macroecological principles still shape the geography of current human agricultural societies.

Does the dilution effect generally occur in animal diseases?

The dilution effect (DE) has been reported in many diseases, but its generality is still highly disputed. Most current criticisms of DE are related to animal diseases. Particularly, some critical studies argued that DE is less likely to occur in complex environments. Here our meta-analyses demonstrated that the magnitude of DE did not differ between animal vs plant diseases. Moreover, DE generally occurs in all three subgroups of animal diseases, namely direct-transmitted diseases, vector-borne diseases and diseases caused by parasites with free-living stages. Our findings serve as an important contribution to understanding the generality of DE.

Regional level risk factors associated with the occurrence of African swine fever in West and East Africa.

BACKGROUND: African swine fever (ASF) causes severe socio-economic impacts due to high mortality and trade restrictions. Many risk factors of ASF have been identified at farm level. However, understanding the risk factors, especially wild suid hosts, determining ASF transmission at regional level remains limited. METHODS: Based on ASF outbreak data in domestic pigs during 2006-2014, we here tested, separately for West and East Africa, which risk factors were linked to ASF presence at a regional level, using generalized linear mixed models. RESULTS: Our results show that ASF infections in the preceding year was an important predictor for ASF presence in both West and East Africa. Both pig density and human density were positively associated with ASF presence in West Africa. In East Africa, ASF outbreaks in domestic pigs were also correlated with higher percentages of areas occupied by giant forest hogs and by high-tick-risk areas. CONCLUSIONS: Our results suggest that regional ASF risk in East Africa and in West Africa were associated with different sets of risk factors. Regional ASF risk in West Africa mainly followed the domestic cycle, whereas the sylvatic cycle may influence regional ASF risk in East Africa. With these findings, we contribute to the better understanding of the risk factors of ASF occurrence at regional scales that may aid the implementation of effective control measures.

Dilution versus facilitation: Impact of connectivity on disease risk in metapopulations.

Epidemiological studies have suggested that increasing connectivity in metapopulations usually facilitates pathogen transmission. However, these studies focusing on single-host systems usually neglect that increasing connectivity can increase species diversity which might reduce pathogen transmission via the 'dilution effect', a hypothesis whose generality is still disputed. On the other hand, studies investigating the generality of the dilution effect were usually conducted without considering habitat structure, which is surprising as species loss is often driven by habitat fragmentation. Using a simple general model to link fragmentation to the dilution effect, we determined the effect of connectivity on disease risk and explored when the dilution effect can be detected. We showed that landscape structure can largely modify the diversity-disease relationship. The net impact of connectivity on disease risk can be either positive or negative, depending on the relative importance of the facilitation effect (through increasing contact rates among patches) versus the dilution effect (via increasing species richness). We also demonstrated that different risk indices (i.e. infection prevalence and abundance of infected hosts) react differently to increasing connectivity and species richness. Our study may contribute to the current debate on the dilution effect, and a better understanding of the impacts of fragmentation on disease risks.

Dilution effect in bovine tuberculosis: risk factors for regional disease occurrence in Africa.

Changes in host diversity have been postulated to influence the risk of infectious diseases, including both dilution and amplification effects. The dilution effect refers to a negative relationship between biodiversity and disease risk, whereas the amplification effect occurs when biodiversity increases disease risk. We tested these effects with an influential disease, bovine tuberculosis (BTB), which is widespread in many countries, causing severe economic losses. Based on the BTB outbreak data in cattle from 2005 to 2010, we also tested, using generalized linear mixed models, which other factors were associated with the regional BTB presence in cattle in Africa. The interdependencies of predictors and their correlations with BTB presence were examined using path analysis. Our results suggested a dilution effect, where increased mammal species richness was associated with reduced probability of BTB presence after adjustment for cattle density. In addition, our results also suggested that areas with BTB infection in the preceding year, higher cattle density and larger percentage of area occupied by African buffalo were more likely to report BTB outbreaks. Climatic variables only indirectly influenced the risk of BTB presence through their effects on cattle density and wildlife distribution. Since most studies investigating the role of wildlife species on BTB transmission only involve single-species analysis, more efforts are needed to better understand the effect of the structure of wildlife communities on BTB dynamics.

Species' life-history traits explain interspecific variation in reservoir competence: a possible mechanism underlying the dilution effect.

Hosts species for multi-host pathogens show considerable variation in the species' reservoir competence, which is usually used to measure species' potential to maintain and transmit these pathogens. Although accumulating research has proposed a trade-off between life-history strategies and immune defences, only a few studies extended this to host species' reservoir competence. Using a phylogenetic comparative approach, we studied the relationships between some species' life-history traits and reservoir competence in three emerging infectious vector-borne disease systems, namely Lyme disease, West Nile Encephalitis (WNE) and Eastern Equine Encephalitis (EEE). The results showed that interspecific variation in reservoir competence could be partly explained by the species' life histories. Species with larger body mass (for hosts of Lyme disease and WNE) or smaller clutch size (for hosts of EEE) had a lower reservoir competence [corrected]. Given that both larger body mass and smaller clutch size were linked to higher extinction risk of local populations, our study suggests that with decreasing biodiversity, species with a higher reservoir competence are more likely to remain in the community, and thereby increase the risk of transmitting these pathogens, which might be a possible mechanism underlying the dilution effect.