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Robust epidemiological knowledge and predictive modelling tools are needed to address challenging objectives, such as: understanding epidemic drivers; forecasting epidemics; and prioritising control measures. Often, multiple modelling approaches can be used during an epidemic to support effective decision making in a timely manner. Modelling challenges contribute to understanding the pros and cons of different approaches and to fostering technical dialogue between modellers. In this paper, we present the results of the first modelling challenge in animal health - the ASF Challenge - which focused on a synthetic epidemic of African swine fever (ASF) on an island. The modelling approaches proposed by five independent international teams were compared. We assessed their ability to predict temporal and spatial epidemic expansion at the interface between domestic pigs and wild boar, and to prioritise a limited number of alternative interventions. We also compared their qualitative and quantitative spatio-temporal predictions over the first two one-month projection phases of the challenge. Top-performing models in predicting the ASF epidemic differed according to the challenge phase, host species, and in predicting spatial or temporal dynamics. Ensemble models built using all team-predictions outperformed any individual model in at least one phase. The ASF Challenge demonstrated that accounting for the interface between livestock and wildlife is key to increasing our effectiveness in controlling emerging animal diseases, and contributed to improving the readiness of the scientific community to face future ASF epidemics. Finally, we discuss the lessons learnt from model comparison to guide decision making., Competing Interests: Declaration of interest The authors have no conflict of interest., (Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.)

Over the last decade African swine fever virus, one of the most virulent pathogens known to affect pigs, has devastated pork industries and wild pig populations throughout the world. Despite a growing literature on specific aspects of African swine fever transmission dynamics, it remains unclear which methods and approaches are most effective for controlling the disease during a crisis. As a consequence, an international modelling challenge was organized in which teams analyzed and responded to a stream of data from an in silico outbreak in the fictive country of Merry Island. In response to this outbreak, we developed a modelling approach that aimed to predict the evolution of the epidemic and evaluate the impact of potential control measures. Two independent models were developed: a stochastic mechanistic space-time compartmental model for characterizing the dissemination of the virus among wild boar; and a deterministic probabilistic risk model for quantifying infection probabilities in domestic pig herds. The combined results of these two models provided valuable information for anticipating the main risks of dissemination and maintenance of the virus (speed and direction of African swine fever spread among wild boar populations, pig herds at greatest risk of infection, the size of the epidemic in the short and long terms), for evaluating the impact of different control measures and for providing specific recommendations concerning control interventions., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 The Author(s). Published by Elsevier B.V. All rights reserved.)

Sex chromosomes are generally derived from a pair of autosomes that have acquired a locus controlling sex. Sex chromosomes may evolve reduced recombination around this locus and undergo a long process of molecular divergence. At that point, the original loci controlling sex may be difficult to pinpoint. This difficulty has affected many model species from mammals to birds to flies, which present highly diverged sex chromosomes. Identifying sex-controlling loci is easier in species with molecularly similar sex chromosomes. Here we aimed at pinpointing the sex-determining region (SDR) of Armadillidium vulgare, a terrestrial isopod with female heterogamety (ZW females and ZZ males) and whose sex chromosomes appear to show low genetic divergence. To locate the SDR, we assessed single-nucleotide polymorphism (SNP) allele frequencies in F1 daughters and sons sequenced in pools (pool-seq) in several families. We developed a Bayesian method that uses the SNP genotypes of individually sequenced parents and pool-seq data from F1 siblings to estimate the genetic distance between a given genomic region (contig) and the SDR. This allowed us to assign more than 43 Mb of contigs to sex chromosomes, and to demonstrate extensive recombination and very low divergence between these chromosomes. By taking advantage of multiple F1 families, we delineated a very short genomic region (∼65 kb) that presented no evidence of recombination with the SDR. In this short genomic region, the comparison of sequencing depths between sexes highlighted female-specific genes that have undergone recent duplication, and which may be involved in sex determination in A. vulgare., (© The Author(s) 2021. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.)

Various mosquito control methods use factory raised males to suppress vector densities. But the efficiency of these methods is currently insufficient to prevent epidemics of arbovirus diseases such as dengue, chikungunya or Zika. Suggestions that the sterile insect technique (SIT) could be "boosted" by applying biopesticides to sterile males remain unquantified. Here, we assess mathematically the gains to SIT for Aedes control of either: boosting with the pupicide pyriproxifen (BSIT); or, contaminating mosquitoes at auto-dissemination stations. Thresholds in sterile male release rate and competitiveness are identified, above which mosquitoes are eliminated asymptotically. Boosting reduces these thresholds and aids population destabilisation, even at sub-threshold release rates. No equivalent bifurcation exists in the auto-dissemination sub-model. Analysis suggests that BSIT can reduce by over 95% the total release required to circumvent dengue epidemics compared to SIT. We conclude, BSIT provides a powerful new tool for the integrated management of mosquito borne diseases., Competing Interests: Competing interestsThe authors declare no competing interests.

Determining how reproductive barriers modulate gene flow between populations represents a major step toward understanding the factors shaping the course of speciation. Although many indices quantifying reproductive isolation (RI) have been proposed, they do not permit the quantification of cross-direction-specific RI under varying species frequencies and over arbitrary sequences of barriers. Furthermore, techniques quantifying associated uncertainties are lacking, and statistical methods unrelated to biological process are still preferred for obtaining confidence intervals and P-values. To address these shortcomings, we provide new RI indices that model changes in gene flow for both directions of hybridization, and we implement them in a Bayesian model. We use this model to quantify RI between two species of the psyllid Cacopsylla pruni based on field genotypic data for mating individuals, inseminated spermatophores and progeny. The results showed that preinsemination isolation was strong, mildly asymmetric, and indistinguishably different between study sites despite large differences in species frequencies; that postinsemination isolation strongly affected the more common hybrid type; and that cumulative isolation was close to complete. In the light of these results, we discuss how these developments can strengthen comparative RI studies., (© 2018 The Author(s). Evolution © 2018 The Society for the Study of Evolution.)

Characterising the spatio-temporal dynamics of pathogens in natura is key to ensuring their efficient prevention and control. However, it is notoriously difficult to estimate dispersal parameters at scales that are relevant to real epidemics. Epidemiological surveys can provide informative data, but parameter estimation can be hampered when the timing of the epidemiological events is uncertain, and in the presence of interactions between disease spread, surveillance, and control. Further complications arise from imperfect detection of disease and from the huge number of data on individual hosts arising from landscape-level surveys. Here, we present a Bayesian framework that overcomes these barriers by integrating over associated uncertainties in a model explicitly combining the processes of disease dispersal, surveillance and control. Using a novel computationally efficient approach to account for patch geometry, we demonstrate that disease dispersal distances can be estimated accurately in a patchy (i.e. fragmented) landscape when disease control is ongoing. Applying this model to data for an aphid-borne virus (Plum pox virus) surveyed for 15 years in 605 orchards, we obtain the first estimate of the distribution of flight distances of infectious aphids at the landscape scale. About 50% of aphid flights terminate beyond 90 m, which implies that most infectious aphids leaving a tree land outside the bounds of a 1-ha orchard. Moreover, long-distance flights are not rare-10% of flights exceed 1 km. By their impact on our quantitative understanding of winged aphid dispersal, these results can inform the design of management strategies for plant viruses, which are mainly aphid-borne.

Identifying the key factors underlying the spread of a disease is an essential but challenging prerequisite to design management strategies. To tackle this issue, we propose an approach based on sensitivity analyses of a spatiotemporal stochastic model simulating the spread of a plant epidemic. This work is motivated by the spread of sharka, caused by plum pox virus , in a real landscape. We first carried out a broad-range sensitivity analysis, ignoring any prior information on six epidemiological parameters, to assess their intrinsic influence on model behaviour. A second analysis benefited from the available knowledge on sharka epidemiology and was thus restricted to more realistic values. The broad-range analysis revealed that the mean duration of the latent period is the most influential parameter of the model, whereas the sharka-specific analysis uncovered the strong impact of the connectivity of the first infected orchard. In addition to demonstrating the interest of sensitivity analyses for a stochastic model, this study highlights the impact of variation ranges of target parameters on the outcome of a sensitivity analysis. With regard to sharka management, our results suggest that sharka surveillance may benefit from paying closer attention to highly connected patches whose infection could trigger serious epidemics., Competing Interests: All authors declare they have no competing interests.

Understanding distribution patterns of hosts implicated in the transmission of zoonotic disease remains a key goal of parasitology. Here, random forests are employed to model spatial patterns of the presence of the plateau pika ( Ochotona spp .) small mammal intermediate host for the parasitic tapeworm Echinococcus multilocularis which is responsible for a significant burden of human zoonoses in western China. Landsat ETM+ satellite imagery and digital elevation model data were utilized to generate quantified measures of environmental characteristics across a study area in Sichuan Province, China. Land cover maps were generated identifying the distribution of specific land cover types, with landscape metrics employed to describe the spatial organisation of land cover patches. Random forests were used to model spatial patterns of Ochotona spp . presence, enabling the relative importance of the environmental characteristics in relation to Ochotona spp . presence to be ranked. An index of habitat aggregation was identified as the most important variable in influencing Ochotona spp . presence, with area of degraded grassland the most important land cover class variable. 71% of the variance in Ochotona spp . presence was explained, with a 90.98% accuracy rate as determined by 'out-of-bag' error assessment. Identification of the environmental characteristics influencing Ochotona spp . presence enables us to better understand distribution patterns of hosts implicated in the transmission of Em. The predictive mapping of this Em host enables the identification of human populations at increased risk of infection, enabling preventative strategies to be adopted.

Vaccination is one of the most efficient ways to control the spread of infectious diseases. Simulations are now widely used to assess how vaccination can limit disease spread as well as mitigate morbidity or mortality in susceptible populations. However, field studies investigating how much vaccines decrease the velocity of epizootic wave-fronts during outbreaks are rare. This study aimed at investigating the effect of vaccination on the propagation of bluetongue, a vector-borne disease of ruminants. We used data from the 2008 bluetongue virus serotype 1 (BTV-1) epizootic of southwest France. As the virus was newly introduced in this area, natural immunity of livestock was absent. This allowed determination of the role of vaccination in changing the velocity of bluetongue spread while accounting for environmental factors that possibly influenced it. The average estimated velocity across the country despite restriction on animal movements was 5.4 km/day, which is very similar to the velocity of spread of the bluetongue virus serotype 8 epizootic in France also estimated in a context of restrictions on animal movements. Vaccination significantly reduced the propagation velocity of BTV-1. In comparison to municipalities with no vaccine coverage, the velocity of BTV-1 spread decreased by 1.7 km/day in municipalities with immunized animals. For the first time, the effect of vaccination has been quantified using data from a real epizootic whilst accounting for environmental factors known to modify the velocity of bluetongue spread. Our findings emphasize the importance of vaccination in limiting disease spread across natural landscape. Finally, environmental factors, specifically those related to vector abundance and activity, were found to be good predictors of the velocity of BTV-1 spread, indicating that these variables need to be adequately accounted for when evaluating the role of vaccination on bluetongue spread.

Background: Human alveolar echinococcocosis (AE) is a highly pathogenic zoonotic disease caused by the larval stage of the cestode E. multilocularis. Its life-cycle includes more than 40 species of small mammal intermediate hosts. Therefore, host biodiversity losses could be expected to alter transmission. Climate may also have possible impacts on E. multilocularis egg survival. We examined the distribution of human AE across two spatial scales, (i) for continental China and (ii) over the eastern edge of the Tibetan plateau. We tested the hypotheses that human disease distribution can be explained by either the biodiversity of small mammal intermediate host species, or by environmental factors such as climate or landscape characteristics., Methodology/findings: The distributions of 274 small mammal species were mapped to 967 point locations on a grid covering continental China. Land cover, elevation, monthly rainfall and temperature were mapped using remotely sensed imagery and compared to the distribution of human AE disease at continental scale and over the eastern Tibetan plateau. Infection status of 17,589 people screened by abdominal ultrasound in 2002-2008 in 94 villages of Tibetan areas of western Sichuan and Qinghai provinces was analyzed using generalized additive mixed models and related to epidemiological and environmental covariates. We found that human AE was not directly correlated with small mammal reservoir host species richness, but rather was spatially correlated with landscape features and climate which could confirm and predict human disease hotspots over a 200,000 km(2) region., Conclusions/significance: E. multilocularis transmission and resultant human disease risk was better predicted from landscape features that could support increases of small mammal host species prone to population outbreaks, rather than host species richness. We anticipate that our study may be a starting point for further research wherein landscape management could be used to predict human disease risk and for controlling this zoonotic helminthic.

A new approach to species distribution modelling based on unsupervised classification via a finite mixture of GAMs incorporating habitat suitability curves is proposed. A tailored EM algorithm is outlined for computing maximum likelihood estimates. Several submodels incorporating various parameter constraints are explored. Simulation studies confirm, that under certain constraints, the habitat suitability curves are recovered with good precision. The method is also applied to a set of real data concerning presence/absence of observable small mammal indices collected on the Tibetan plateau. The resulting classification was found to correspond to species-level differences in habitat preference described in previous ecological work.

Background: Alveolar echinococcosis is a major zoonosis of public health significance in western China. Overgrazing was recently assumed as a potential risk factor for transmission of alveolar echinococcosis. The research was designed to further test the overgrazing hypothesis by investigating how overgrazing influenced the burrow density of intermediate host small mammals and how the burrow density of small mammals was associated with dog Echinococcus multilocularis infection., Methods: The study sites were chosen by previous studies which found areas where the alveolar echinococcosis was prevalent. The data, including grass height, burrow density of intermediate host small mammals, dog and fox fecal samples as well as Global Positioning System (GPS) position, were collected from field investigations in Shiqu County, Sichuan Province, China. The fecal samples were analyzed using copro-PCR. The worms, teeth, bones and hairs in the fecal samples were visually examined. Single factor and multifactor analyses tools including chi square and generalized linear models were applied to these data., Results: By using grass height as a proxy of grazing pressure in the homogenous pasture, this study found that taller grass in the pasture led to lower small mammals' burrow density (chi(2) = 4.670, P = 0.031, coefficient = -1.570). The Echinococcus multilocularis worm burden in dogs was statistically significantly related to the maximum density of the intermediate host Ochotona spp. (chi(2) = 5.250, P = 0.022, coefficient = 0.028). The prevalence in owned dogs was positively correlated to the number of stray dogs seen within a 200 meter radius (Wald chi(2) = 8.375, P = 0.004, odds ratio = 1.198)., Conclusions: Our findings support the hypothesis that overgrazing promotes transmission of alveolar echinococcosis and confirm the role of stray dogs in the transmission of alveolar echinococcosis.

We investigate the relationship between landscape heterogeneity and the spatial distribution of small mammals in two areas of Western Sichuan, China. Given a large diversity of species trapped within a large number of habitats, we first classified small mammal assemblages and then modelled the habitat of each in the space of quantitative environmental descriptors. Our original two step "classify then model" procedure is appropriate for the frequently encountered study scenario: trapping data collected in remote areas with sampling guided by expert field knowledge.In the classification step, we defined assemblages by grouping sites of similar species composition and relative densities using an expert-class-merging procedure which reduced redundancy in the habitat factor used within a multinomial logistic regression predicting species trapping probabilities. Assemblages were thus defined as mixtures of small mammal frequency distributions in discrete groups of sampled sites.In the modelling step, assemblages' habitats and environments of the two sampled areas were discriminated in the space of remotely sensed environmental descriptors. First, we compared the discrimination of assemblage/study areas by linear and non-linear forms of Discriminant Analysis (Linear Discriminant Analysis versus Mixture Discriminant Analysis) and of Multiple Regression (Generalized Linear Models versus Multiple Adaptive Regression Splines). The "best" predictive modelling technique was then used to quantify the contribution of each environmental variable in discriminations of assemblages and areas.Mixtures of Gaussians provided a more efficient model of assemblage coverage in environmental space than a single Gaussian cluster model. However, non-linearity in assemblage response to environmental gradients was consistently predicted with lower deviance and misclassification error by Multiple Adaptive Regression Splines. The two study areas were mainly discriminated along vegetation indices. However, although the Normalized Difference Vegetation Index (NDVI) could discriminate forested from non-forested habitats, its power to discriminate assemblages in Maerkang, where a greater diversity of forest habitat was observed, was seen to be limited, and in this case NDVI was outperformed by the Enhanced Vegetation Index (EVI). Our analyses highlight previously unobserved differences between the environments and small mammal communities of two fringe areas of the Tibetan plateau and suggests that a biogeograph-ical approach is required to elucidate ecological processes in small mammal communities and to reduce extrapolation uncertainty in distribution mapping.

Background: Alveolar echinococcosis (AE) presents a serious public health challenge within China. Mass screening ultrasound surveys can detect pre-symptomatic AE, but targeting areas identified from hospital records is inefficient regarding AE. Prediction of undetected or emerging hotspots would increase detection rates. Voles and lemmings of the subfamily Arvicolinae are important intermediate hosts in sylvatic transmission systems. Their populations reach high densities in productive grasslands where food and cover are abundant. Habitat availability is thought to affect arvicoline population dynamic patterns and definitive host-intermediate host interactions. Arvicoline habitat correlates with AE prevalence in Western Europe and southern Gansu Province, China., Methods and Findings: Xiji County, Ningxia Hui Autonomous Region, borders southern Gansu. The aims of this study were to map AE prevalence across Xiji and test arvicoline habitat as a predictor. Land cover was mapped using remotely sensed (Landsat) imagery. Infection status of 3,205 individuals screened in 2002-2003 was related, using generalised additive mixed models, to covariates: gender; farming; ethnicity; dog ownership; water source; and areal cover of mountain pasture and lowland pasture. A Markov random field modelled additional spatial variation and uncertainty. Mountain pasture and lowland pasture were associated with below and above average AE prevalence, respectively., Conclusions: Low values of the normalised difference vegetation index indicated sub-optimality of lowland pasture for grassland arvicolines. Unlike other known endemic areas, grassland arvicolines probably did not provide the principal reservoir for Echinococcus multilocularis in Xiji. This result is consistent with recent small mammal surveys reporting low arvicoline densities and high densities of hamsters, pikas and jerboas, all suitable intermediate hosts for E. multilocularis, in reforested lowland pasture. The risk of re-emergence is discussed. We recommend extending monitoring to: southern Haiyuan County, where predicted prevalence was high; southern Xiji County, where prediction uncertainty was high; and monitoring small mammal community dynamics and the infection status of dogs.

Objective: To determine the true community prevalence of human cystic (CE) and alveolar (AE) echinococcosis (hydatid disease) in a highly endemic region in Ningxia Hui, China, by detecting asymptomatic cases., Methods: Using hospital records and "AE-risk" landscape patterns we selected study communities predicted to be at risk of human echinococcosis in Guyuan, Longde and Xiji counties. We conducted community surveys of 4773 individuals from 26 villages in 2002 and 2003 using questionnaire analysis, ultrasound examination and serology., Findings: Ultrasound and serology showed a range of prevalences for AE (0-8.1%; mean 2%) and CE (0-7.4%; mean 1.6%), with the highest prevalence in Xiji (2% for CE, 2.5% for AE). There were significant differences in the prevalence of CE, AE and total echinococcosis between the three counties and villages (with multiple degrees of freedom). While hospital records showed 96% of echinococcosis cases attributable to CE, our survey showed a higher prevalence of human AE (56%) compared to CE (44%). Questionnaire analysis revealed that key risk factors for infection were age and dog ownership for both CE and AE, and Hui ethnicity and being female for AE. Drinking well-water decreased the risk for both AE and CE., Conclusion: Echinococcosis continues to be a severe public health problem in this part of China because of unhygienic practices/habits and poor knowledge among the communities regarding this disease.

A striking feature of the transmission ecology of Echinococcus multilocularis in China is the diversity of hosts that contribute to the parasite cycle. Considering the population dynamics of key reservoir intermediate hosts and the ratio of their preferred habitat in a landscape (ROMPA) is essential to understanding transmission, but the numerous communities in which the parasite cycles and the extent of those communities is currently far from being fully documented. On the Tibetan plateau grassland management influences intermediate host species populations and the sheer size of the area could be a major contributing factor to sustaining transmission in the region. In Southern Gansu and Southern Ningxia the processes of deforestation have temporarily provided optimal habitat for key reservoir intermediate hosts of E. multilocularis, resulting in high transmission and human disease, however currently the parasite may be extinct locally. Faced with this pattern of potentially transient transmission in a diversity of communities the question of the dispersal potential of the parasite arises. The reforestation program currently active across much of Western China has the potential to give rise to a massive increase in habitat favourable to suitable intermediate hosts and emergence or re-emergence of the zoonosis alveolar echinococcosis in many areas. This potential epidemic could be mitigated by both natural and human induced parasite dispersal mechanisms including fox migration and the sale of infected dogs originating from stable endemic foci on the Tibetan plateau. However, currently the degree of genetic exchange between discrete transmission foci is unknown and it is expected that genetic techniques could provide crucial information regarding this important question.