Use of ProMED as a Surveillance System for Emerging and Re-Emerging Infectious Diseases in Brazil from 2015 to 2020

Viruses, Journal Year: 2025, Volume and Issue: 17(1), P. 93 - 93

Published: Jan. 13, 2025

Emerging and re-emerging infectious diseases have been frequently reported in Brazil. The Program for Monitoring Diseases (ProMED) is a virtual system with expert curation monitoring health events, including those occurring This study aimed to describe the ProMED as complementary surveillance emerging It has retrospective descriptive design, was conducted using ProMED-PORT reports that cited Brazil were published from 1 January 2015, 31 December 2020. In total, 220 new identified during period. Most of these between June. Reports on humans predominant (n = 177), comprised 78 kinds most which related arboviruses. animals second prevalent 35), encompassed 18 particularly yellow fever non-human primates, rabies different mammals, sporotrichosis felines. Six (2.7%) animals, while two (0.9%) plants or environment. Southeast Northeast regions. leading reemerging Brazil, serving an information source local international authorities.

Language: Английский

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Emerging horizons in predictive biogeography

Ecography, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 10, 2025

The notion that different branches of biological sciences – including ecology, macroecology, and biogeography should adopt a predictive focus rather than merely aiming to describe understand the natural world has gained traction over past decades (Peters 1991, Shrader-Frechette McCoy 1993). This trend been enabled both by technological advancement leading new frameworks, pressing societal demands anticipate mitigate effects global change on biodiversity associated ecosystem services. An early example this is work Sánchez-Cordero et al. (2004) who contributed chapter for conservation applications in seminal volume (Lomolino Heaney 2004). While authors did not explicitly define term biogeography, their discussion emphasized how developments statistical ecology mapping had allowed description species distributions at large spatial scales. Similarly, Thuiller (2006) employed concept restricted context describing use stacked distribution models (SDMs) predicting plant richness South Africa. Dawson (2011) subsequently highlighted SDMs as most widely used method but also called attention importance establishing broader frameworks changes biodiversity, from ecosystems, response climate change. There are other biogeographic patterns context. Most notably, area relationships (SARs), which have important predict extinctions (Drakare 2006) driven anthropogenic habitat fragmentation example. However, widespread SDMs, along with fact they remain choice scales repeatedly (Bellard 2012, Araújo 2019, Zurell 2020, Soley-Guardia 2024). Mapping remains an essential component large-scale planning (Margules 2002). It critical only delineating statuses, trends, management strategies regional scales, interpreting geological, historical, causes consequences (Whittaker 2005). Therefore, modelling will probably biogeography. many studies emphasize need move beyond individual encompass range spatio-temporal issues interface between society, such services, human health agricultural systems. expanded scope inevitably calls wider definition In special issue, we aim broaden application moving confines spotlight cutting edge research across dimensions field. deliberate opposed or reflects our intent include more diverse array approaches statistical, evolutionary, contribute understanding forecasting distribution, abundance, diversity broad and/or temporal includes systems productive (e.g. agroecosystems). We propose subdiscipline uses known ecological evolutionary processes diversity, whether it be species, intra-, inter-specific levels, biotic interactions relationship environment, Over two decades, field experienced exponential growth, increasing availability digital data genetic variability within them, well proliferation spatially explicit environmental layers increasingly fine resolutions. rapid evolution catalysed development syntheses theories, alongside advancements methodologies computational capabilities. As result, undergoing transformation primarily descriptive discipline championed likes Alexander von Humboldt (1769–1859), Augustin Pyramus de Candolle (1778–1841), Alfred Russel Wallace (1823–1913), Philip Lutley Sclater (1829–1913), amongst others, science, capable informing fundamental practical conservation, resource management, beyond. emergence demand (Dietze 2018, Enquist growing challenges decline rising food demands, far-reaching impacts recent pandemics paired ongoing threaten security, public health, made ability these existential priority humanity. time, expanded. Initially, 1990s, its centred largely past, present, future biodiversity. Today, evolved address directly linked societies, production (Enquist relevance positioned underpinning wide fields (Araújo Peterson 2012). These biology 2011, Fordham 2013), agriculture (Meynard 2017, Gerber 2024, Soubeyrand 2024), forestry (Zhang 2022, Rosa fisheries (Cheung 2010, Boavida-Portugal 2018), epidemiology (Aliaga-Samanez Mestre paleobiology (Metcalf 2014, 2022), reflecting versatility addressing contemporary issues. advances all areas biology, computer science translated into vast high-resolution information geographic areas, landscapes, countries, continents, even globally. Technological molecular sequencing, make monitoring, microscopic life, possible (Beng Corlett 2020). DNA recovery efforts can go so far sequence ancient samples, allowing exploration old specimens stored museum collections (Raxworthy Smith 2021), recovering trophic through samples (Pereira 2023). Sequencing, analytical theoretical advances, makes integrate history, rates diversification (Morlon Kergoat 2018) predictions Remote sensing follow land (Cavender-Bares integrating chemical properties phylogenetic functional 2020), microclimate resolutions (Lembrechts 2020) among promising allow fine-grain mechanisms models. Statistical methods computing (Record 2023), technology allows sharing globally, curated occurrence, trait, phylogenetic, any type datasets. just few expanding extent fine-resolution gathered. When combined, applied, greatly advance future. Within bounds, identify least three components framework (Fig. 1): data, must fall domain biogeography; one scenarios establish relevant predictions; formal model theory translates current biodiversity–environment considered. Note often pertain land-use scenarios), scenarios, extinction strategies, behaviour, driving predictions. Importantly, view dynamic static. Advances scenario lead updates models, turn, outputs requirements guide collection refinement creating positive feedback loop 2018). Conceptual summary framework. Every effort ingredients (a) theories models; (b) shows several indicators measures, feeding each ways. Although usually combination occurrence (SDM) predictions), depend sought; very related change, evolution, resilience, extinction, kind changes. Finally, set combining needed, although main desired scope. compared, validated, measured against real patterns. A panoply higher spatial, temporal, taxonomic resolution, facets genetics, phenotypic, functional, phenological) key larger Examples shown (c), no means exhaustive list. Each involve plethora elements. For example, gene expression profiles, intra-specific intra- traits, others 1). Despite significant progress, technologies enabling measurement, characterization continue evolve. considerable potential innovation relating environment factors, imagining enhancing curating papers aimed interdisciplinary integration. compiled revolve around core tool Boom Kissling (2024) tracking complement traditional improving SDM Chronister demonstrate automated acoustic detectors monitor distinguish juvenile adult great horned owls, opening door estimating demographic parameters By incorporating researchers explore life cycle stages factor consider when setting priorities. Goicolea employ hierarchical refine locally calibrated nested regionally constrained ones. approach mitigates common problem truncating calibrating local (Thuiller Mowry account constraints disease vector ticks, case resulting improved estimates. Several featured issue leverage interplay differentiation populations distributions. Naughtin structure SDM-based reconstructions ranges infer, via approximate Bayesian computation (ABC) likely combinations matches structure. argue help rank otherwise indistinguishable using standard validation methods. another application, Mascarenhas Carnaval random forest relates history particularly dispersal characteristics. Their results highlight traits arthropod phylogeography. Hernández linking suitability, modelled deep time intervals, diversity. integration produces interesting regarding stability paleological periods structures, identification endemic regions poorly surveyed Along similar lines, Formoso-Freire relate abundance distributions, investigating long-term informs present-day community stability. modelling. Sharma niche evolution. utility study hummingbirds. Verdon eDNA estimate soil taxa traditionally overlooked monitoring. ambitious incorporates numerous amplicon variants (ASVs), revealing capabilities limitations approaches. discussed authors, dynamics require better estimates enhanced soil-related Another recurring theme incorporation success adapting changing climates hinges Luoto 2007). Poggiato (2025) tackled while González-Trujillo phenomenological structures proposed Mendoza (2019, 2022). hindcast guild latitudes, interactions. Predictive represented issue. Park present simulation demonstrating median flowering dates mean temperatures onset termination periods. offers valuable inferring phenology strong representation, thus helping phenological shifts Siders capitalize comprehensive literature review extract shark devices comparing vertical without depth-weighted information. show depth preference add sharks, components. Adding third dimension marine seems like venue research, recently available thanks accumulation biotelemetry 3-D ocean (Fragkopoulou Lertzman-Lepofsky take advantage databases role explaining correlations taxa. analysis demonstrates co-variations well-documented enhances time. summary, exemplify innovations reshaping monitor, understand, various From population taxonomic, evolving rapidly. Emerging now previously invisible challenging-to-monitor aspects facilitated tools eDNA, detection (sound telemetry), modelling, big exciting direction involves utilizing deep-time inform forecast sequencing opened possibilities examining variation forging compelling connections there gaps publications (Maldonado 2015, Nuñez focused tropical (Mascarenhas Moreover, small subset those illustrated Fig. 1c. plays crucial monitoring scale, features limited scaling contexts. underscore number unexplored advancing could combine text mining, citizen engaging individuals everyday cell phones multi-modal real-time analysis? Such enable declines shifts. Could genomics epigenetics offer deeper insights genotype-to-phenotype relationships, adaptation prioritizing level? Furthermore, facilitate 'macroscope' (Gonzalez bridging gap leaves Global underrepresented datasets? questions scratch surface what achieved push boundaries does represent exhaustively literature, prevalence absence certain biases state none (Lagerholm Raxworthy 2021) environments middens pollen deposits, pre-human baselines, shifts, influenced intervention. lack coherent uncertainties. ensemble become practice 2007, 2019), equivalent identifying reporting Citizen underrepresented, despite prominence artificial intelligence assisted Pl@ntNet (Joly 2016). Links error estimation further applied development. dominance limitations. To static mechanistic Functional though promising, here. empirical elusive (but see Violle Díaz Neyret developed scaled extents scenarios. incorporate regulation, productivity, stability, functions focusing solely species. Dynamic weather remote Near-term identified making timely decisions play retroactive role, lessons learned improve forecasts Lewis Achieving requires fully replicable pipelines near-real-time data. highlights open programming literacy (Mandeville 2021). Open ensure reproducibility democratize easily adapted settings 2015). Additionally, system archiving synthesizing 2023) needed build based experiences. points out, given us toolkit learn about levels organization, datasets detailed equally informative reconciling scientific cultures: values detail specificity, emphasizes experimentation explanations, simplifies discern generalizable Striking right balance challenging yet worthwhile endeavour science. CNM was funded her salary French servant national institution. Christine Meynard: Conceptualization (equal), Validation Writing - original draft (lead), editing (lead). Sydne Record: (supporting), (supporting). Nuria Galiana: Dominique Gravel: Miguel Araújo:

Language: Английский

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Revealing microbial consortia that interfere with grapevine downy mildew through microbiome epidemiology

Environmental Microbiome, Journal Year: 2025, Volume and Issue: 20(1)

Published: March 27, 2025

Abstract Background Plant and soil microbiomes can interfere with pathogen life cycles, but their influence on disease epidemiology remains understudied. Here, we analyzed the relationships between plant long-term epidemiological records of grapevine downy mildew, a major caused by oomycete Plasmopara viticola . Results We found that certain microbial taxa were consistently more abundant in plots lower incidence severity community composition could predict severity. Microbial diversity was not strongly linked to records, suggesting is related abundance specific taxa. These key identified topsoil, where pathogen’s oospores overwinter, phyllosphere, zoospores infect leaves. By contrast, leaf endosphere, mycelium develops, contained few interest. Surprisingly, microbiota better predictor than microbiota, microbiome be indicator dynamics this primarily aerial disease. Conclusion Our study integrates data profiles healthy plants reveal fungi bacteria relevant for biocontrol mildew. The resulting database provides valuable resource designing consortia potential activity. framework applied other crop systems guide development strategies reduce pesticide use agriculture.

Language: Английский

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Two-Level Distributed Multi-Source Information Fusion Model for Aphid Monitoring and Forecasting in the Greenhouse

Agronomy, Journal Year: 2025, Volume and Issue: 15(5), P. 1044 - 1044

Published: April 26, 2025

Aphids are the main agricultural pests that affect quality and yield of peppers in greenhouse. Efficient early prediction aphid occurrence is great significance for development digitization information technology intelligent agriculture. Forecasting accuracy could be improved by incorporation feature interactions into pest forecasting. This study integrates multiple environmental factors to efficiently predict number aphids strain rate We propose a two-level distributed multi-source fusion approach, which one-dimensional convolutional neural network (1D CNN) Long Short-Term Memory (LSTM). To enhance regional parameters, weighted average algorithm employs sensor data first level fusion. In second level, heterogeneous allows integration model connection between dynamics. Finally, 1D CNN-LSTM other models were tested verify effectiveness robustness proposed model. The experimental results show total root mean square error 1.503, obviously better than networks. test set, predicting 1.378 0.337, respectively, compared with existing such as CNN, LSTM, back propagation (BP). has obvious advantages rate. It provides promising step forward management, offering precise, environmentally friendly solutions crop quality.

Language: Английский

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Hotspot mapping of pest introductions in the EU: A regional analysis of environmental, anthropogenic and spatial effects

Biological Invasions, Journal Year: 2024, Volume and Issue: 27(1)

Published: Dec. 3, 2024

Plant pests may pose a significant threat to global agriculture, natural ecosystems and biodiversity, causing severe ecological economic damage. Identifying regions more susceptible pest introductions is crucial for developing effective prevention, early detection outbreak response strategies. While historical data on in the European Union (EU) exist, they are typically reported at regional level. This broad aggregation has posed challenge accurate analysis plant health research. study addresses this gap by leveraging existing identify hotspots of within EU UK, through Bayesian hierarchical spatial model. Specifically, we employed Besag, York, Mollié (BYM) model higher risk (NUTS2) incorporating covariates effects consider information from neighbouring areas. The results showed positive effect annual average temperature, precipitation, human population density introduction, highlighting relevance component. Our pinpoints high-risk southern Europe, particularly northern Italy. Additionally, high documented Netherlands contributed its elevated risk. limitations exist due nature data, represents methodological advancement, demonstrating effectiveness models offering robust framework future studies using data. It also provides insights that can inform targeted preparedness strategies, ultimately contributing safeguarding biodiversity UK.

Language: Английский

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