Estimation of the dispersal distances of an aphid-borne virus in a patchy landscape

Diverse RNA viruses discovered in multiple seagrass species

Seagrasses are marine angiosperms that form highly productive and diverse ecosystems. These ecosystems, however, are declining worldwide. Plant-associated microbes affect critical functions like nutrient uptake and pathogen resistance, which has led to an interest in the seagrass microbiome. However, despite their significant role in plant ecology, viruses have only recently garnered attention in seagrass species. In this study, we produced original data and mined publicly available transcriptomes to advance our understanding of RNA viral diversity in Zostera marina, Zostera muelleri, Zostera japonica, and Cymodocea nodosa. In Z. marina, we present evidence for additional Zostera marina amalgavirus 1 and 2 genotypes, and a complete genome for an alphaendornavirus previously evidenced by an RNA-dependent RNA polymerase gene fragment. In Z. muelleri, we present evidence for a second complete alphaendornavirus and near complete furovirus. Both are novel, and, to the best of our knowledge, this marks the first report of a furovirus infection naturally occurring outside of cereal grasses. In Z. japonica, we discovered genome fragments that belong to a novel strain of cucumber mosaic virus, a prolific pathogen that depends largely on aphid vectoring for host-to-host transmission. Lastly, in C. nodosa, we discovered two contigs that belong to a novel virus in the family Betaflexiviridae. These findings expand our knowledge of viral diversity in seagrasses and provide insight into seagrass viral ecology.

Discovery of Pyrido[1,2-α] Pyrimidinone Mesoionic Compounds as Potential Control Agents Against Potato Virus Y

Potato virus Y (PVY) relies on aphids and tubers to spread in the field and causes serious economic losses in the potato industry. Here, we found that pyrido[1,2-α] pyrimidinone mesoionic compounds with insecticidal activity against aphids possessed a good inhibitory effect on PVY. Among them, compound 35 had the best inhibitory activity against PVY (EC50 = 104 μg/mL), even superior to that of ningnanmycin (125 μg/mL). The fluorescence and qPCR results confirmed that compound 35 could inhibit the proliferation of PVY in Nicotiana benthamiana. Preliminary experiments on the mechanism of action indicated that compound 35 had good binding affinity with the coat protein (CP), which plays an essential role in aphid-PVY interactions. Molecular docking revealed that compound 35 could bind to the pocket of CP formed by Ser52, Glu204, and Arg208. Compound 35 had substantially lower binding affinity (Kd) values with CPS52A (219 μM), CPE204A (231 μM), and CPR208A (189 μM) than those with CPWT (5.80 μM). A luciferase assay confirmed that mutating Ser52, Glu204, and Arg208 significantly affected the expression level of CP and further reduced virus proliferation. Therefore, the broad-spectrum activity of compound 35 provides a unique strategy for the prevention and treatment of PVY.

Why do viruses make aphids winged?

Aphids are hosts to diverse viruses and are important vectors of plant pathogens. The spread of viruses is heavily influenced by aphid movement and behaviour. Consequently, wing plasticity (where individuals can be winged or wingless depending on environmental conditions) is an important factor in the spread of aphid-associated viruses. We review several fascinating systems where aphid-vectored plant viruses interact with aphid wing plasticity, both indirectly by manipulating plant physiology and directly through molecular interactions with plasticity pathways. We also cover recent examples where aphid-specific viruses and endogenous viral elements within aphid genomes influence wing formation. We discuss why unrelated viruses with different transmission modes have convergently evolved to manipulate wing formation in aphids and whether this is advantageous for both host and virus. We argue that interactions with viruses are likely shaping the evolution of wing plasticity within and across aphid species, and we discuss the potential importance of these findings for aphid biocontrol.

Bayesian inference for spatio-temporal stochastic transmission of plant disease in the presence of roguing: A case study to characterise the dispersal of Flavescence dorée

Estimating the distance at which pathogens disperse from one season to the next is crucial for designing efficient control strategies for invasive plant pathogens and a major milestone in the reduction of pesticide use in agriculture. However, we still lack such estimates for many diseases, especially for insect-vectored pathogens, such as Flavescence dorée (FD). FD is a quarantine disease threatening European vineyards. Its management is based on mandatory insecticide treatments and the removal of infected plants identified during annual surveys. This paper introduces a general statistical framework to model the epidemiological dynamics of FD in a mechanistic manner that can take into account missing hosts in surveyed fields (resulting from infected plant removals). We parameterized the model using Markov chain Monte Carlo (MCMC) and data augmentation from surveillance data gathered in Bordeaux vineyards. The data mainly consist of two snapshot maps of the infectious status of all the plants in three adjacent fields during two consecutive years. We demonstrate that heavy-tailed dispersal kernels best fit the spread of FD and that on average, 50% (resp. 80%) of new infection occurs within 10.5 m (resp. 22.2 m) of the source plant. These values are in agreement with estimates of the flying capacity of Scaphoideus titanus, the leafhopper vector of FD, reported in the literature using mark-capture techniques. Simulations of simple removal scenarios using the fitted model suggest that cryptic infection hampered FD management. Future efforts should explore whether strategies relying on reactive host removal can improve FD management.

Emerging Themes and Approaches in Plant Virus Epidemiology

Plant diseases caused by viruses share many common features with those caused by other pathogen taxa in terms of the host-pathogen interaction, but there are also distinctive features in epidemiology, most apparent where transmission is by vectors. Consequently, the host-virus-vector-environment interaction presents a continuing challenge in attempts to understand and predict the course of plant virus epidemics. Theoretical concepts, based on the underlying biology, can be expressed in mathematical models and tested through quantitative assessments of epidemics in the field; this remains a goal in understanding why plant virus epidemics occur and how they can be controlled. To this end, this review identifies recent emerging themes and approaches to fill in knowledge gaps in plant virus epidemiology. We review quantitative work on the impact of climatic fluctuations and change on plants, viruses, and vectors under different scenarios where impacts on the individual components of the plant-virus-vector interaction may vary disproportionately; there is a continuing, sometimes discordant, debate on host resistance and tolerance as plant defense mechanisms, including aspects of farmer behavior and attitudes toward disease management that may affect deployment in crops; disentangling host-virus-vector-environment interactions, as these contribute to temporal and spatial disease progress in field populations; computational techniques for estimating epidemiological parameters from field observations; and the use of optimal control analysis to assess disease control options. We end by proposing new challenges and questions in plant virus epidemiology.

Asymmetric interactions between barley yellow dwarf virus -PAV and wheat dwarf virus in wheat

The deciphering of the epidemiology of a plant virus has long been focused on the study of interactions between partners of one pathosystem. However, plants are exposed to numerous viruses which lead to frequent co-infection scenarios. This can change characteristics of virus-vector-host interactions and could impact the epidemiology of viral diseases. Barley yellow dwarf virus-PAV (BYDV-PAV; species: Luteovirus pavhordei; genus Luteovirus), wheat dwarf virus (WDV; genus Mastrevirus) and their respective vectors (BYDV-PAV: e.g. Rhopalosiphum padi and WDV: Psammotettix alienus) are commonly found in cereal fields. Wheat plants co-infected with BYDV-PAV and WDV have been reported from field surveys, although epidemiological outcomes of BYDV-PAV - WDV interactions in planta have not yet been studied. Experiments were carried out to evaluate and compare, through different competition scenarios (i.e. single- and co- (simultaneous and sequential) inoculations), the efficiency of BYDV-PAV and WDV to infect, to accumulate in and to be spread between wheat plants. Moreover, the impact of competition scenarios on the biological parameters of these two viruses was evaluated at different stages of the infection and with plants at different ages at inoculation. Results showed i) that these viruses achieve their infection cycle and their plant-to-plant transmission with different efficiencies and ii) BYDV-PAV - WDV interactions lead to different phenotypes ranging from antagonism to synergism. Finally, when these two viruses share a host, the nature and strength of virus-virus interactions varied depending on the order of virus arrival, stages of the infection cycle and plant age at inoculation. Precisely, the introduction (i.e. co- and sequential inoculation) and infection process (i.e. virus accumulation) of BYDV-PAV in a wheat benefit from the presence of WDV. For the latter, the sympatry with BYDV-PAV exerts opposite pressure on parameters involved in virus introduction (i.e. benefit during sequential inoculation) and spread (i.e. lower transmission efficiency and virus accumulation in co-infected plants). In the context of increased potential exposure of crops to insect vectors, this study participates in a better understanding of the impact of BYDV-PAV and WDV co-infections on biological and ecological parameters of the diseases induced by these viruses.

Direct and indirect viral associations predict coexistence in wild plant virus communities

Viruses are a vastly underestimated component of biodiversity that occur as diverse communities across hierarchical scales from the landscape level to individual hosts. The integration of community ecology with disease biology is a powerful, novel approach that can yield unprecedented insights into the abiotic and biotic drivers of pathogen community assembly. Here, we sampled wild plant populations to characterize and analyze the diversity and co-occurrence structure of within-host virus communities and their predictors. Our results show that these virus communities are characterized by diverse, non-random coinfections. Using a novel graphical network modeling framework, we demonstrate how environmental heterogeneity influences the network of virus taxa and how the virus co-occurrence patterns can be attributed to non-random, direct statistical virus-virus associations. Moreover, we show that environmental heterogeneity changed virus association networks, especially through their indirect effects. Our results highlight a previously underestimated mechanism of how environmental variability can influence disease risks by changing associations between viruses that are conditional on their environment.

Insect allies-Assessment of a viral approach to plant genome editing

The Insect Allies program of the Defense Advanced Research Projects Agency has already sparked scientific debate concerning technology assessment-related issues, among which the most prevalent is that of dual use. Apart from the issues concerning peaceful applications, the technology also provides the blueprint for a potential bioweapon. However, the combination of a virus-induced genetic modification of crop plants in the field using genetically modified insect vectors poses a greater risk than the hitherto existing use of genetically modified organisms. The technology's great depth of intervention allows a number of sources for hazard and a tendency towards high exposure, but it is also encumbered with notable deficits in knowledge. These issues call for a thorough technology assessment. This article aims to provide an initial characterization from a technology assessment perspective, focusing on potential sources of risk for this novel invasive environmental biotechnology at an early stage of research and development. Integr Environ Assess Manag 2022;18:1488-1499. © 2022 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Increasing risk of aphids spreading plant viruses in maize fields on both sides of China's Heihe-Tengchong line under climate change

BACKGROUND

In the coming decades, geographical distribution patterns of farmland organisms may undergo drastic changes due to climate change, with significant implications for global food security. In China, Rhopalosiphum maidis and its spread of sugarcane mosaic virus (ScMV) can become an increasingly serious threat to maize (Zea mays) production. We conducted ecological niche modeling for Z. mays, R. maidis, and ScMV under current and future (2041-2060 and 2081-2100) climate scenarios by using MaxEnt software to explore changes in this system.

RESULTS

The Heihe-Tengchong line (an imaginary separation line of human population density) can divide China into main (east of the line) and secondary (west of the line) habitats for the three species. With climate change, rapid expansion in suitable areas is projected for ScMV and the aphid vector R. maidis. Taking species interactions into consideration, our overlaying analyses show that most areas east of the Heihe-Tengchong line (optimal for maize and suitable for R. maidis) will become increasingly highly suitable for ScMV, suggesting that the prevention and control of this plant virus and its aphid vector in China's main maize-growing areas (e.g. northeast) will become an increasing challenge in the future.

CONCLUSION

Climate change will profoundly affect ScMV-vector-maize interactions, which may contribute favorably to invasion of this virus into new areas. Our comprehensive and in-depth analyses on shifts in this multi-species system under climate change provide useful and insightful information for devising strategies for the prevention and control of plant viruses and aphid vectors on maize in the future. © 2022 Society of Chemical Industry.

Coinfection with a virus constrains within-host infection load but increases transmission potential of a highly virulent fungal plant pathogen

The trade-off between within-host infection rate and transmission to new hosts is predicted to constrain pathogen evolution, and to maintain polymorphism in pathogen populations. Pathogen life-history stages and their correlations that underpin infection development may change under coinfection with other parasites as they compete for the same limited host resources. Cross-kingdom interactions are common among pathogens in both natural and cultivated systems, yet their impacts on disease ecology and evolution are rarely studied. The host plant Plantago lanceolata is naturally infected by both Phomopsis subordinaria, a seed killing fungus, as well as Plantago lanceolata latent virus (PlLV) in the Åland Islands, SW Finland. We performed an inoculation assay to test whether coinfection with PlLV affects performance of two P. subordinaria strains, and the correlation between within-host infection rate and transmission potential. The strains differed in the measured life-history traits and their correlations. Moreover, we found that under virus coinfection, within-host infection rate of P. subordinaria was smaller but transmission potential was higher compared to strains under single infection. The negative correlation between within-host infection rate and transmission potential detected under single infection became positive under coinfection with PlLV. To understand whether within-host and between-host dynamics are correlated in wild populations, we surveyed 260 natural populations of P. lanceolata for P. subordinaria infection occurrence. When infections were found, we estimated between-hosts dynamics by determining pathogen population size as the proportion of infected individuals, and within-host dynamics by counting the proportion of infected flower stalks in 10 infected plants. In wild populations, the proportion of infected flower stalks was positively associated with pathogen population size. Jointly, our results suggest that the trade-off between within-host infection load and transmission may be strain specific, and that the pathogen life-history that underpin epidemics may change depending on the diversity of infection, generating variation in disease dynamics.

Efficiency and Persistence of Movento® Treatment against Myzus persicae and the Transmission of Aphid-Borne Viruses

Neonicotinoids are widely used to protect fields against aphid-borne viral diseases. The recent ban of these chemical compounds in the European Union has strongly impacted rapeseed and sugar beet growing practices. The poor sustainability of other insecticide families and the low efficiency of prophylactic methods to control aphid populations and pathogen introduction strengthen the need to characterize the efficiency of new plant protection products targeting aphids. In this study, the impact of Movento^® (Bayer S.A.S., Leverkusen, Germany), a tetrameric acid derivative of spirotetramat, on Myzus persicae and on viral transmission was analyzed under different growing temperatures. The results show (i) the high efficiency of Movento^® to protect rapeseed and sugar beet plants against the establishment of aphid colonies, (ii) the impact of temperature on the persistence of the Movento^® aphicid properties and (iii) a decrease of approximately 10% of the viral transmission on treated plants. These observations suggest a beneficial effect of Movento^® on the sanitary quality of treated crops by directly reducing primary infections and indirectly altering, through aphid mortality, secondary infections on which the spread of disease within field depends. These data constitute important elements for the future development of management strategies to protect crops against aphid-transmitted viruses.

Metagenomic Studies of Viruses in Weeds and Wild Plants: A Powerful Approach to Characterise Variable Virus Communities

High throughput sequencing (HTS) has revolutionised virus detection and discovery, allowing for the untargeted characterisation of whole viromes. Viral metagenomics studies have demonstrated the ubiquity of virus infection - often in the absence of disease symptoms - and tend to discover many novel viruses, highlighting the small fraction of virus biodiversity described to date. The majority of the studies using high-throughput sequencing to characterise plant viromes have focused on economically important crops, and only a small number of studies have considered weeds and wild plants. Characterising the viromes of wild plants is highly relevant, as these plants can affect disease dynamics in crops, often by acting as viral reservoirs. Moreover, the viruses in unmanaged systems may also have important effects on wild plant populations and communities. Here, we review metagenomic studies on weeds and wild plants to show the benefits and limitations of this approach and identify knowledge gaps. We consider key genomics developments that are likely to benefit the field in the near future. Although only a small number of HTS studies have been performed on weeds and wild plants, these studies have already discovered many novel viruses, demonstrated unexpected trends in virus distributions, and highlighted the potential of metagenomics as an approach.

Emerging strains of watermelon mosaic virus in Southeastern France: model-based estimation of the dates and places of introduction

Where and when alien organisms are successfully introduced are central questions to elucidate biotic and abiotic conditions favorable to the introduction, establishment and spread of invasive species. We propose a modelling framework to analyze multiple introductions by several invasive genotypes or genetic variants, in competition with a resident population, when observations provide knowledge on the relative proportions of each variant at some dates and places. This framework is based on a mechanistic-statistical model coupling a reaction–diffusion model with a probabilistic observation model. We apply it to a spatio-temporal dataset reporting the relative proportions of five genetic variants of watermelon mosaic virus (WMV, genus Potyvirus, family Potyviridae) in infections of commercial cucurbit fields. Despite the parsimonious nature of the model, it succeeds in fitting the data well and provides an estimation of the dates and places of successful introduction of each emerging variant as well as a reconstruction of the dynamics of each variant since its introduction.

Metapopulation Structure Predicts Population Dynamics in the Cakile maritima-Alternaria brassicicola Host-Pathogen Interaction

AbstractIn symbiotic interactions, spatiotemporal variation in the distribution or population dynamics of one species represents spatial and temporal heterogeneity of the landscape for the other. Such interdependent demographic dynamics result in situations where the relative importance of biotic and abiotic factors in determining ecological processes is complicated to decipher. Using a detailed survey of three metapopulations of the succulent plant Cakile maritima and the necrotrophic fungus Alternaria brassicicola located along the southeastern Australian coast, we developed a series of statistical analyses-namely, synchrony analysis, patch occupancy dynamics, and a spatially explicit metapopulation model-to understand how habitat quality, weather conditions, dispersal, and spatial structure determine metapopulation dynamics. Climatic conditions are important drivers, likely explaining the high synchrony among populations. Host availability, landscape features facilitating dispersal, and habitat conditions also impact the occurrence and spread of disease. Overall, we show that the collection of extensive data on host and pathogen population dynamics, in combination with spatially explicit epidemiological modeling, makes it possible to accurately predict disease dynamics-even when there is extreme variability in host population dynamics. Finally, we discuss the importance of genetic information for predicting demographic dynamics in this pathosystem.

The Epidemiology of Plant Virus Disease: Towards a New Synthesis

Epidemiology is the science of how disease develops in populations, with applications in human, animal and plant diseases. For plant diseases, epidemiology has developed as a quantitative science with the aims of describing, understanding and predicting epidemics, and intervening to mitigate their consequences in plant populations. Although the central focus of epidemiology is at the population level, it is often necessary to recognise the system hierarchies present by scaling down to the individual plant/cellular level and scaling up to the community/landscape level. This is particularly important for diseases caused by plant viruses, which in most cases are transmitted by arthropod vectors. This leads to range of virus-plant, virus-vector and vector-plant interactions giving a distinctive character to plant virus epidemiology (whilst recognising that some fungal, oomycete and bacterial pathogens are also vector-borne). These interactions have epidemiological, ecological and evolutionary consequences with implications for agronomic practices, pest and disease management, host resistance deployment, and the health of wild plant communities. Over the last two decades, there have been attempts to bring together these differing standpoints into a new synthesis, although this is more apparent for evolutionary and ecological approaches, perhaps reflecting the greater emphasis on shorter often annual time scales in epidemiological studies. It is argued here that incorporating an epidemiological perspective, specifically quantitative, into this developing synthesis will lead to new directions in plant virus research and disease management. This synthesis can serve to further consolidate and transform epidemiology as a key element in plant virus research.

Aphid Transmission of Potyvirus: The Largest Plant-Infecting RNA Virus Genus

Potyviruses are the largest group of plant infecting RNA viruses that cause significant losses in a wide range of crops across the globe. The majority of viruses in the genus Potyvirus are transmitted by aphids in a non-persistent, non-circulative manner and have been extensively studied vis-à-vis their structure, taxonomy, evolution, diagnosis, transmission, and molecular interactions with hosts. This comprehensive review exclusively discusses potyviruses and their transmission by aphid vectors, specifically in the light of several virus, aphid and plant factors, and how their interplay influences potyviral binding in aphids, aphid behavior and fitness, host plant biochemistry, virus epidemics, and transmission bottlenecks. We present the heatmap of the global distribution of potyvirus species, variation in the potyviral coat protein gene, and top aphid vectors of potyviruses. Lastly, we examine how the fundamental understanding of these multi-partite interactions through multi-omics approaches is already contributing to, and can have future implications for, devising effective and sustainable management strategies against aphid-transmitted potyviruses to global agriculture.

Transmission modes affect the population structure of potato virus Y in potato

Transmission is a crucial part of a viral life cycle and transmission mode can have an important impact on virus biology. It was demonstrated that transmission mode can influence the virulence and evolution of a virus; however, few empirical data are available to describe the direct underlying changes in virus population structure dynamics within the host. Potato virus Y (PVY) is an RNA virus and one of the most damaging pathogens of potato. It comprises several genetically variable strains that are transmitted between plants via different transmission modes. To investigate how transmission modes affect the within-plant viral population structure, we have used a deep sequencing approach to examine the changes in the genetic structure of populations (in leaves and tubers) of three PVY strains after successive passages by horizontal (aphid and mechanical) and vertical (via tubers) transmission modes. Nucleotide diversities of viral populations were significantly influenced by transmission modes; lineages transmitted by aphids were the least diverse, whereas lineages transmitted by tubers were the most diverse. Differences in nucleotide diversities of viral populations between leaves and tubers were transmission mode-dependent, with higher diversities in tubers than in leaves for aphid and mechanically transmitted lineages. Furthermore, aphid and tuber transmissions were shown to impose stronger genetic bottlenecks than mechanical transmission. To better understand the structure of virus populations within the host, transmission mode, movement of the virus within the host, and the number of replication cycles after transmission event need to be considered. Collectively, our results suggest a significant impact of virus transmission modes on the within-plant diversity of virus populations and provide quantitative fundamental data for understanding how transmission can shape virus diversity in the natural ecosystems, where different transmission modes are expected to affect virus population structure and consequently its evolution.

Prediction of Spread and Regional Development of Hop Powdery Mildew: A Network Analysis

Dispersal is a fundamental aspect of epidemic development at multiple spatial scales, including those that extend beyond the borders of individual fields and to the landscape level. In this research, we used the powdery mildew of the hop pathosystem (caused by Podosphaera macularis) to formulate a model of pathogen dispersal during spring (May to June) and early summer (June to July) at the intermediate scale between synoptic weather systems and microclimate (mesoscale) based on a census of commercial hop yards during 2014 to 2017 in a production region in western Oregon. This pathosystem is characterized by a low level of overwintering of the pathogen as a result of absence of the ascigerious stage of the fungus and consequent annual cycles of localized survival via bud perennation and pathogen spread by windborne dispersal. An individual hop yard was considered a node in the model, whose disease status in a given month was expressed as a nonlinear function of disease incidence in the preceding month, susceptibility to two races of the fungus, and disease spread from other nodes as influenced by their disease incidence, area, distance away, and wind run and direction in the preceding month. Parameters were estimated by maximum likelihood over all 4 years but were allowed to vary for time transition periods from May to June and from June to July. The model accounted for 34 to 90% of the observed variation in disease incidence at the field level, depending on the year and season. Network graphs and analyses suggest that dispersal was dominated by relatively localized dispersal events (<2 km) among the network of fields, being mostly restricted to the same or adjacent farms. When formed, predicted disease attributable to dispersal from other hop yards (edges) associated with longer distance dispersal was more frequent in the June to July time transition. Edges with a high probability of disease transmission were formed in instances where yards were in close proximity or where disease incidence was relatively high in large hop yards, as moderated by wind run. The modeling approach provides a flexible and generalizable framework for understanding and predicting pathogen dispersal at the regional level as well as the implications of network connectivity on epidemic development.

Improving Management Strategies of Plant Diseases Using Sequential Sensitivity Analyses

Improvement of management strategies of epidemics is often hampered by constraints on experiments at large spatiotemporal scales. A promising approach consists of modeling the biological epidemic process and human interventions, which both impact disease spread. However, few methods enable the simultaneous optimization of the numerous parameters of sophisticated control strategies. To do so, we propose a heuristic approach (i.e., a practical improvement method approximating an optimal solution) based on sequential sensitivity analyses. In addition, we use an economic improvement criterion based on the net present value, accounting for both the cost of the different control measures and the benefit generated by disease suppression. This work is motivated by sharka (caused by Plum pox virus), a vector-borne disease of prunus trees (especially apricot, peach, and plum), the management of which in orchards is mainly based on surveillance and tree removal. We identified the key parameters of a spatiotemporal model simulating sharka spread and control and approximated optimal values for these parameters. The results indicate that the current French management of sharka efficiently controls the disease, but it can be economically improved using alternative strategies that are identified and discussed. The general approach should help policy makers to design sustainable and cost-effective strategies for disease management.

Analyzing the Influence of Landscape Aggregation on Disease Spread to Improve Management Strategies

Epidemiological models are increasingly used to predict epidemics and improve management strategies. However, they rarely consider landscape characteristics although such characteristics can influence the epidemic dynamics and, thus, the effectiveness of disease management strategies. Here, we present a generic in silico approach which assesses the influence of landscape aggregation on the costs associated with an epidemic and on improved management strategies. We apply this approach to sharka, one of the most damaging diseases of Prunus trees, for which a management strategy is already applied in France. Epidemic simulations were carried out with a spatiotemporal stochastic model under various management strategies in landscapes differing in patch aggregation. Using sensitivity analyses, we highlight the impact of management parameters on the economic output of the model. We also show that the sensitivity analysis can be exploited to identify several strategies that are, according to the model, more profitable than the current French strategy. Some of these strategies are specific to a given aggregation level, which shows that management strategies should generally be tailored to each specific landscape. However, we also identified a strategy that is efficient for all levels of landscape aggregation. This one-size-fits-all strategy has important practical implications because of its simple applicability at a large scale.

Biopesticides improve efficiency of the sterile insect technique for controlling mosquito-driven dengue epidemics

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.