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Anne-Mieke Vandamme

Anne-Mieke Vandamme
annemie.vandamme@kuleuven.be
Laboratory for Clinical and Evolutionary Virology
Rega - Herestraat 49 - box 1040
3000 Leuven
Belgium
room: 10.A306

tel: +32 16 32 13 95 or +32 16 3 79 020
fax: +32 16 3 30 026
contact

Curriculum vitae: 

   

Publications

query=user:U0004051 year:[2000 TO 2020] &institution=lirias&from=1&step=20&sort=scdate
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  • journal-article
    Pingarilho, Marta; Pimentel, Victor; Diogo, Isabel; Fernandes, Sandra; Miranda, Mafalda; Pineda-Pena, Andrea; Libin, Pieter; Theys, Kristof; Martins, M Rosário O; Vandamme, Anne-Mieke; Camacho, Ricardo; Gomes, Perpétua; Abecasis, Ana; 2020. Increasing Prevalence of HIV-1 Transmitted Drug Resistance in Portugal: Implications for First Line Treatment Recommendations.. Viruses; 2020; Vol. 12; iss. 11
    LIRIAS3264101
    description
    INTRODUCTION: Treatment for All recommendations have allowed access to antiretroviral (ARV) treatment for an increasing number of patients. This minimizes the transmission of infection but can potentiate the risk of transmitted (TDR) and acquired drug resistance (ADR). OBJECTIVE: To study the trends of TDR and ADR in patients followed up in Portuguese hospitals between 2001 and 2017. METHODS: In total, 11,911 patients of the Portuguese REGA database were included. TDR was defined as the presence of one or more surveillance drug resistance mutation according to the WHO surveillance list. Genotypic resistance to ARV was evaluated with Stanford HIVdb v7.0. Patterns of TDR, ADR and the prevalence of mutations over time were analyzed using logistic regression. RESULTS AND DISCUSSION: The prevalence of TDR increased from 7.9% in 2003 to 13.1% in 2017 (p < / 0.001). This was due to a significant increase in both resistance to nucleotide reverse transcriptase inhibitors (NRTIs) and non-nucleotide reverse transcriptase inhibitors (NNRTIs), from 5.6% to 6.7% (p = 0.002) and 2.9% to 8.9% (p < / 0.001), respectively. TDR was associated with infection with subtype B, and with lower viral load levels (p < / 0.05). The prevalence of ADR declined from 86.6% in 2001 to 51.0% in 2017 (p < / 0.001), caused by decreasing drug resistance to all antiretroviral (ARV) classes (p < / 0.001). CONCLUSIONS: While ADR has been decreasing since 2001, TDR has been increasing, reaching a value of 13.1% by the end of 2017. It is urgently necessary to develop public health programs to monitor the levels and patterns of TDR in newly diagnosed patients.

    Published online
  • Pourkarim, Mahmoud Reza; Thijssen, Marijn; Lemey, Philippe; Vandamme, Anne-Mieke; Van Ranst, Marc; 2020. Air conditioning system usage and SARS-CoV-2 transmission dynamics in Iran. Medical Hypotheses; 2020; Vol. 143; pp. -
    LIRIAS3176544
    description

    Publisher: Elsevier
    Published
  • Torneri, Andrea; Libin, Pieter; Vanderlocht, Joris; Vandamme, Anne-Mieke; Neyts, Johan; Hens, Niel; 2020. A prospect on the use of antiviral drugs to control local outbreaks of COVID-19. Bmc Medicine; 2020; Vol. 18; iss. 1; pp. -
    LIRIAS3067832
    description
    BACKGROUND: Current outbreaks of COVID-19 are threatening the health care systems of several countries around the world. Control measures, based on isolation, contact tracing, and quarantine, can decrease and delay the burden of the ongoing epidemic. With respect to the ongoing COVID-19 epidemic, recent modeling work shows that these interventions may be inadequate to control local outbreaks, even when perfect isolation is assumed. The effect of infectiousness prior to symptom onset combined with asymptomatic infectees further complicates the use of contact tracing. We aim to study whether antivirals, which decrease the viral load and reduce infectiousness, could be integrated into control measures in order to augment the feasibility of controlling the epidemic. METHODS: Using a simulation-based model of viral transmission, we tested the efficacy of different intervention measures to control local COVID-19 outbreaks. For individuals that were identified through contact tracing, we evaluate two procedures: monitoring individuals for symptoms onset and testing of individuals. Additionally, we investigate the implementation of an antiviral compound combined with the contact tracing process. RESULTS: For an infectious disease in which asymptomatic and presymptomatic infections are plausible, an intervention measure based on contact tracing performs better when combined with testing instead of monitoring, provided that the test is able to detect infections during the incubation period. Antiviral drugs, in combination with contact tracing, quarantine, and isolation, result in a significant decrease of the final size and the peak incidence, and increase the probability that the outbreak will fade out. CONCLUSION: In all tested scenarios, the model highlights the benefits of control measures based on the testing of traced individuals. In addition, the administration of an antiviral drug, together with quarantine, isolation, and contact tracing, is shown to decrease the spread of the epidemic. This control measure could be an effective strategy to control local and re-emerging outbreaks of COVID-19.
    Publisher: BioMed Central
    Published
  • Mavian, Carla; Pond, Sergei Kosakovsky; Marini, Simone; Magalis, Brittany Rife; Vandamme, Anne-Mieke; Dellicour, Simon; Scarpino, Samuel V; Houldcroft, Charlotte; Villabona-Arenas, Julian; Paisie, Taylor K; Trovao, Nidia S; Boucher, Christina; Zhang, Yun; Scheuermann, Richard H; Gascuel, Olivier; Lam, Tommy Tsan-Yuk; Suchard, Marc A; Abecasis, Ana; Wilkinson, Eduan; de Oliveira, Tulio; Bento, Ana I; Schmidt, Heiko A; Martin, Darren; Hadfield, James; Faria, Nuno; Grubaugh, Nathan D; Neher, Richard A; Baele, Guy; Lemey, Philippe; Stadler, Tanja; Albert, Jan; Crandall, Keith A; Leitner, Thomas; Stamatakis, Alexandros; Prosperi, Mattia; Salemi, Marco; 2020. Sampling bias and incorrect rooting make phylogenetic network tracing of SARS-COV-2 infections unreliable. Proceedings Of The National Academy Of Sciences Of The United States Of America; 2020; Vol. 117; iss. 23; pp. 12522 - 12523
    LIRIAS3036871
    description

    Publisher: National Academy of Sciences
    Published
  • Capina, Rupert; Li, Katherine; Kearney, Levon; Vandamme, Anne-Mieke; Harrigan, P Richard; Van Laethem, Kristel; 2020. Quality Control of Next-Generation Sequencing-Based HIV-1 Drug Resistance Data in Clinical Laboratory Information Systems Framework. Viruses-Basel; 2020; Vol. 12; iss. 6; pp. -
    LIRIAS3056751
    description
    Next-generation sequencing (NGS) in HIV drug resistance (HIVDR) testing has the potential to improve both clinical and public health settings, however it challenges the normal operations of quality management systems to be more flexible due to its complexity, massive data generation, and rapidly evolving protocols. While guidelines for quality management in NGS data have previously been outlined, little guidance has been implemented for NGS-based HIVDR testing. This document summarizes quality control procedures for NGS-based HIVDR testing laboratories using a laboratory information systems (LIS) framework. Here, we focus in particular on the quality control measures applied on the final sequencing product aligned with the recommendations from the World Health Organization HIV Drug Resistance Laboratory Network.
    Publisher: Multidisciplinary Digital Publishing Institute (MDPI)
    Published
  • Decock, Kristof; Debackere, Koenraad; Vandamme, Anne Mieke; Van Looy, Bart; 2020. Scenario-driven forecasting: Modeling peaks and paths. Insights from the COVID-19 Pandemic in Belgium. Scientometrics Publisher: KU Leuven - Faculty of Economics and Business; Leuven (Belgium)
    LIRIAS3042082
    description
    The recent ‘outburst’ of COVID-19 spurred efforts to model and forecast its diffusion patterns, either in terms of infections, people in need of medical assistance (ICU occupation) or casualties. Forecasting patterns and their implied end states remains cumbersome when few (stochastic) data points are available during the early stage of diffusion processes. Extrapolations based on compounded growth rates do not account for inflection points nor end-states. In order to remedy this situation, we advance a set of heuristics which combine forecasting and scenario thinking. Inspired by scenario thinking we allow for a broad range of end states (and their implied growth dynamics, parameters) which are consecutively being assessed in terms of how well they coincide with actual observations. When applying this approach to the diffusion of COVID-19, it becomes clear that combining potential end states with unfolding trajectories provides a better-informed decision space as short term predictions are accurate, while a portfolio of different end states informs the long view. The creation of such a decision space requires temporal distance. Only to the extent that one refrains from incorporating more recent data, more plausible end states become visible. Such dynamic approach also allows one to assess the potential effects of mitigating measures. As such, our contribution implies a plea for dynamically blending forecasting algorithms and scenario-oriented thinking, rather than conceiving them as substitutes or complements.

    Published
  • Vandamme, A; Nguyen, ToTran; DENIS, M; Kiekens, Anneleen; Nova Blanco, J; Pourkarim, MahmoudReza; Van Ranst, Marc; Naesens, Lieve; Depypere, Maxiem; Ronse, Maya; Peeters, Koen; Vandaele, Nico; Schuerman, Lode; Van den Cruyce, Nele; Van Hoof, Elke; Vercauteren, Sara; Vandermeulen, Corinne; 2020. Belgium - concerns about coronavirus contact-tracing apps. Nature; 2020; Vol. 581; pp. 384 - 384
    LIRIAS3176467
    description

    Publisher: Nature Research
    Published
  • Decock, Kristof; Bergamini, Michela; Debackere, Koenraad; Lupi, Enrico; Vandamme, Anne Mieke; Van Looy, Bart; 2020. Predicting when peaks will occur, ex ante. Insights from the COVID-19 Pandemic in Italy and Belgium. FEB Research Report MSI_2009 Publisher: KU Leuven - Faculty of Economics and Business
    LIRIAS3039136
    description
    In this paper we advance a set of heuristics which allow to predict ex ante the peak of diffusion curves and apply these heuristics on the COVID-19 pandemic (casualties). The heuristics build on innovation diffusion models and combine an extensive grid search with a loss function. The grid search is designed such that multi-finality (different end states) can unfold; the loss function takes into account the fit with a limited set of available observations. No assumptions are made ex ante in terms of the timing of inflection points. As such, these heuristics combine scenario thinking with forecasting algorithms (scenario driven forecasting). The heuristics have been applied for both Italy and Belgium as a whole as well as for decomposed time series based on policy relevant cohorts (regions (IT); hospital / residential care centers (BE)). While actually observed peaks (including Black Friday in Italy) are consistently falling into the predicted time range, we also observe that the predictive validity increases when decomposed time series – coinciding with cohorts displaying different, but policy relevant, diffusion dynamics– are being introduced. As the heuristics implied are agnostic in terms of epidemiological parameters – which are unknown in the case of a novel pathogen – they provide a decision-making space which is highly informative in situations characterized by levels of Knightian uncertainty. As such, scenario driven forecasting might become a valuable alternative and complement both for more qualitative approaches as well as for hope (and guesses) in decision making contexts characterized by such profound uncertainty. Acknowledgment: This contribution benefited from useful input and reflections by Jorge Ricardo Blanco Nova (KU Leuven), Sien Luyten (Flanders Business School), Xiaoyan Song (KU Leuven) and Stijn Kelchtermans (KU Leuven) and feedback from our students at Flanders Business School (MBA; Panther Program) and KU Leuven (Strategy and Innovation; Technology Trends and Opportunities). We want to express our gratitude to the Rega Institute and the Institute for the Future for providing a context to validate our models, and to EURO POOL GROUP for funding part of the research reported here.

    Published
  • Vandamme, Anne-Mieke; Nguyen, ToTran; 2020. Can public trust coronavirus apps?. Nature; 2020; Vol. 581; iss. 7809; pp. 384 - 384
    LIRIAS3049064
    description

    Publisher: Nature Research
    Published
  • Pimentel, Victor; Pingarilho, Marta; Alves, Daniela; Diogo, Isabel; Fernandes, Sandra; Miranda, Mafalda; Pineda-Pena, Andrea-Clemencia; Libin, Pieter; Martins, M Rosario O; Vandamme, Anne-Mieke; Camacho, Ricardo; Gomes, Perpetua; Abecasis, Ana; 2020. Molecular Epidemiology of HIV-1 Infected Migrants Followed Up in Portugal: Trends between 2001-2017. Viruses-Basel; 2020; Vol. 12; iss. 3; pp. -
    LIRIAS2996625
    description
    Migration is associated with HIV-1 vulnerability. OBJECTIVES: To identify long-term trends in HIV-1 molecular epidemiology and antiretroviral drug resistance (ARV) among migrants followed up in Portugal Methods: 5177 patients were included between 2001 and 2017. Rega, Scuel, Comet, and jPHMM algorithms were used for subtyping. Transmitted drug resistance (TDR) and Acquired drug resistance (ADR) were defined as the presence of surveillance drug resistance mutations (SDRMs) and as mutations of the IAS-USA 2015 algorithm, respectively. Statistical analyses were performed. RESULTS: HIV-1 subtypes infecting migrants were consistent with the ones prevailing in their countries of origin. Over time, overall TDR significantly increased and specifically for Non-nucleoside reverse transcriptase inhibitor (NNRTIs) and Nucleoside reverse transcriptase inhibitor (NRTIs). TDR was higher in patients from Mozambique. Country of origin Mozambique and subtype B were independently associated with TDR. Overall, ADR significantly decreased over time and specifically for NRTIs and Protease Inhibitors (PIs). Age, subtype B, and viral load were independently associated with ADR. CONCLUSIONS: HIV-1 molecular epidemiology in migrants suggests high levels of connectivity with their country of origin. The increasing levels of TDR in migrants could indicate an increase also in their countries of origin, where more efficient surveillance should occur.
    Publisher: Multidisciplinary Digital Publishing Institute (MDPI)
    Published
  • El Mahmoudi, Faysal; Gaillard, Julie; Spiessens, Reine; Vandamme, Anne-Mieke; Nova Blanco, Jorge Ricardo; Van den Eede, Astrid; 2019. Prosumers everywhere: investigating the driving forces behind prosumer behavior in different socioeconomic strata. Transdisciplinary Insights; 2019; Vol. 3; iss. 1; pp. 198 - 218
    LIRIAS2959184
    description

    Publisher: Leuven University Press
    Published
  • Kiekens, Anneleen; Dehens, Joram; de Hemptinne, Maud; Galouchka, Michaël; Vanhoorebeeck, Cedric; van Otzel, Reinier Petrus; Wyszkowska, Magorzata; Baert, Saar; Bernard, Edwin J; Nova Blanco, Jorge Ricardo; Dierckx, Tim; Mosha, Fausta; Sangeda, Raphael Zozimus; Theys, Kristof; Van den Eede, Astrid; Jordan, Michael R; Vandamme, Anne-Mieke; 2019. HIV-related Peer Support in Dar es Salaam: A Pilot Questionnaire Inquiry. Transdisciplinary Insights; 2019; Vol. 3; iss. 1; pp. 1 - 18
    LIRIAS2959183
    description

    Publisher: Leuven University Press
    Published
  • Vrancken, Bram; Cuypers, Lize; Belen Perez, Ana; Chueca, Natalia; Anton-Basantas, Joaquin; de la Iglesia, Alberto; Fuentes, Javier; Antonio Pineda, Juan; Tellez, Francisco; Bernal, Enrique; Rincon, Pilar; Von Wichman, Miguel Angel; Fuentes, Ana; Vera, Francisco; Rivero-Juarez, Antonio; Jimenez, Miguel; Vandamme, Anne-Mieke; Garcia, Federico; 2019. Cross-country migration linked to people who inject drugs challenges the long-term impact of national HCV elimination programmes. Journal Of Hepatology; 2019; Vol. 71; iss. 6; pp. 1270 - 1272
    LIRIAS2861195
    description

    Publisher: Elsevier
    Published
  • Ceulemans, Griet; Nova Blanco, Jorge Ricardo; De Block, Andreas; Vandamme, Annemie; 2019. Transforming education and research through an Honours Programme. Case: Transdisciplinary Insights KU Leuven.
    LIRIAS2912750
    description


    Published
  • Theys, Kristof; Lemey, Philippe; Vandamme, Anne-Mieke; Baele, Guy; 2019. Advances in Visualization Tools for Phylogenomic and Phylodynamic Studies of Viral Diseases. Frontiers In Public Health; 2019; Vol. 7; pp. -
    LIRIAS2834247
    description
    Genomic and epidemiological monitoring have become an integral part of our response to emerging and ongoing epidemics of viral infectious diseases. Advances in high-throughput sequencing, including portable genomic sequencing at reduced costs and turnaround time, are paralleled by continuing developments in methodology to infer evolutionary histories (dynamics/patterns) and to identify factors driving viral spread in space and time. The traditionally static nature of visualizing phylogenetic trees that represent these evolutionary relationships/processes has also evolved, albeit perhaps at a slower rate. Advanced visualization tools with increased resolution assist in drawing conclusions from phylogenetic estimates and may even have potential to better inform public health and treatment decisions, but the design (and choice of what analyses are shown) is hindered by the complexity of information embedded within current phylogenetic models and the integration of available meta-data. In this review, we discuss visualization challenges for the interpretation and exploration of reconstructed histories of viral epidemics that arose from increasing volumes of sequence data and the wealth of additional data layers that can be integrated. We focus on solutions that address joint temporal and spatial visualization but also consider what the future may bring in terms of visualization and how this may become of value for the coming era of real-time digital pathogen surveillance, where actionable results and adequate intervention strategies need to be obtained within days.
    Publisher: Frontiers Media
    Published
  • Vasylyeva, Tetyana I; du Plessis, Louis; Pineda-Pena, Andrea C; Kuehnert, Denise; Lemey, Philippe; Vandamme, Anne-Mieke; Gomes, Perpetua; Camacho, Ricardo J; Pybus, Oliver G; Abecasis, Ana B; Faria, Nuno R; 2019. Tracing the Impact of Public Health Interventions on HIV-1 Transmission in Portugal Using Molecular Epidemiology. Journal Of Infectious Diseases; 2019; Vol. 220; iss. 2; pp. 233 - 243
    LIRIAS2372230
    description
    BACKGROUND: Estimation of temporal changes in human immunodeficiency virus (HIV) transmission patterns can help to elucidate the impact of preventive strategies and public health policies. METHODS: Portuguese HIV-1 subtype B and G pol genetic sequences were appended to global reference data sets to identify country-specific transmission clades. Bayesian birth-death models were used to estimate subtype-specific effective reproductive numbers (Re). Discrete trait analysis (DTA) was used to quantify mixing among transmission groups. RESULTS: We identified 5 subtype B Portuguese clades (26-79 sequences) and a large monophyletic subtype G Portuguese clade (236 sequences). We estimated that major shifts in HIV-1 transmission occurred around 1999 (95% Bayesian credible interval [BCI], 1998-2000) and 2000 (95% BCI, 1998-2001) for subtypes B and G, respectively. For subtype B, Re dropped from 1.91 (95% BCI, 1.73-2.09) to 0.62 (95% BCI,.52-.72). For subtype G, Re decreased from 1.49 (95% BCI, 1.39-1.59) to 0.72 (95% BCI, .63-.8). The DTA suggests that people who inject drugs (PWID) and heterosexuals were the source of most (>80%) virus lineage transitions for subtypes G and B, respectively. CONCLUSIONS: The estimated declines in Re coincide with the introduction of highly active antiretroviral therapy and the scale-up of harm reduction for PWID. Inferred transmission events across transmission groups emphasize the importance of prevention efforts for bridging populations.
    Publisher: Oxford University Press (OUP)
    Published
  • other
    Hendrickx, DM; Sousa, JD; Libin, PJK; Delva, W; Liesenborgs, J; Hens, N; Müller, V; Vandamme, AM; 2019. Comparison of two individual-based model simulators for HIV epidemiology in a population with HSV-2 using as case study Yaoundé-Cameroon, 1980-2005.
    LIRIAS2804137
    description
    Abstract Model comparisons have been widely used to guide intervention strategies to control infectious diseases. Agreement between different models is crucial for providing robust evidence for policy-makers because differences in model properties can influence their predictions. In this study, we compared models generated with two individual-based model simulators for HIV epidemiology in a population with HSV-2. For each model simulator, we constructed four models, starting from a simplified model and stepwise including more model complexity. For the resulting eight models, the predictions of the impact of behavioural interventions on the HIV epidemic in Yaoundé (Cameroon) were compared. The results show that differences in model assumptions and model complexity can influence the size of the predicted impact of the intervention, as well as the predicted qualitative behaviour of the HIV epidemic after the intervention. Moreover, two models that agree in their predictions of the HIV epidemic in absence of an intervention can have different outputs when predicting the impact of interventions. These findings highlight the importance of making more data available for the calibration and validation of epidemiological models.

    Published
  • Dierckx, T; 2019. Quantifying chronic inflammatory burden from transcriptomes in viral and immune-mediated pathologies.
    LIRIAS2789486
    description
    Human T-Cell Leukemia Virus Type 1, HTLV-1, is a pathogenic retrovirus infecting approximately 10 million individuals worldwide. The virus causes two distinct pathologies: Adult T-cell leukemia/lymphoma (ATL) and HTLV-1 Associated Myelopathy / Tropical Spastic Paraparesis (HAM/TSP). The common treatment of ATL currently consists of combination therapy with interferon (IFN) α and zidovudine. However, early reports showed IFN-β was also an effective treatment strategy, though IFN-α treatment became the standard based on empirical results. To explore the potential viability of IFN-β treatment in ATL, we tested the differential effects of IFN-α and -β on short term PBMC cultures of ATL patients and concluded that IFN‑β has superior anti‑proliferative and pro‑apoptotic effects. Additional meta‑analysis in four ATL gene expression datasets revealed a consistent decrease in RORC transcript abundance. In addition, a robust negative correlation exists between IL17C gene expression and proliferative gene expression in ATL and in other lymphoid leukemias. The transcriptomic experiments used in these studies also showed that inflammation could serve a protective role in ATL. As HTLV-1's other major pathology, HAM/TSP, is a neuroinflammatory disorder, we aimed to find a robust way of quantifying the inflammatory burden in transcriptomic experiments. Glycoprotein Acetylation (GlycA) is a novel biomarker for inflammation quantified in blood serum or plasma using Nuclear Magnetic Resonance (NMR) spectroscopy. This marker is a summary measure associated with a broad range of inflammatory processes and can be interpreted as a patient's chronic inflammatory burden. Using various machine learning algorithms on a large collection of paired NMR measurements and blood gene expression profiles, we constructed a predictive model which quantifies relative GlycA concentration from the gene transcript abundance in a patient's blood. This predictive model was first shown to replicate published GlycA associations. Then, novel predictions were made using publicly available third‑party data, which were tested, and confirmed to be accurate, using new NMR experiments. The GlycA measurements in Inflammatory Bowel Disease (IBD) and Systemic Lupus Erythematosus (SLE) were studied in greater detail. In IBD, GlycA concentration in patient serum samples was found to be higher than what was measured in healthy controls. In patients that responded to treatment and achieved mucosal healing, GlycA fell back down to the levels observed in healthy controls. Patients that showed an endoscopic treatment response but did not achieve full mucosal healing showed a GlycA decrease but fell short of returning to the healthy control GlycA levels. Considering our data shows that GlycA tracks disease activity even in patients without elevated C-reactive protein, our results demonstrate that GlycA holds great promise as a serological biomarker for disease activity in IBD. In SLE, our results show that GlycA levels are higher in SLE patients than those observed in healthy controls and even in nephritic controls without lupus, despite the altered renal function of the latter. We find that GlycA is associated to the SLE disease activity index and that proliferative lupus nephritis patients have higher GlycA concentrations than non‑proliferative patients at time of renal biopsy. When comparing performance of GlycA to traditional biomarkers, we show that GlycA is the more informative biomarker. (IWT project 141614: A transcriptomic approach to determine immunomodulatory therapeutic strategies in current and novel viral epidemics)

    Published
  • other
    Parczewski, M; Cielniak, I; Kordek, J; Aksak-Was, B; Urbanska, A; Leszczyszyn-Pynka, M; Siwak, E; Bociaga-Jasik, M; Nowak, A; Szymczak, A; Zalewska, M; Lojewski, W; Vandamme, AM; Lubke, N; Cuypers, L; 2019. Transmission Networks of HCV Genotype 1a Enriched With Pre-existing Polymorphism Q80K Among HIV-Infected Patients With Acute Hepatitis C in Poland (vol 77, pg 514, 2018). Jaids-Journal Of Acquired Immune Deficiency Syndromes; 2019; Vol. 81; iss. 1; pp. E27 - E27 Publisher: Lippincott, Williams & Wilkins
    LIRIAS2842700
    description


    Published
  • Fonseca, Vagner; Libin, Pieter JK; Theys, Kristof; Faria, Nuno R; Nunes, Marcio RT; Restovic, Maria I; Freire, Murilo; Giovanetti, Marta; Cuypers, Lize; Nowe, Ann; Abecasis, Ana; Deforche, Koen; Santiago, Gilberto A; de Siqueira, Isadora C; San, Emmanuel J; Machado, Kaliane CB; Azevedo, Vasco; Bispo-de Filippis, Ana Maria; da Cunha, Rivaldo Venancio; Pybus, Oliver G; Vandamme, Anne-Mieke; Alcantara, Luiz CJ; de Oliveira, Tulio; 2019. A computational method for the identification of Dengue, Zika and Chikungunya virus species and genotypes. Plos Neglected Tropical Diseases; 2019; Vol. 13; iss. 5; pp. -
    LIRIAS2800908
    description
    In recent years, an increasing number of outbreaks of Dengue, Chikungunya and Zika viruses have been reported in Asia and the Americas. Monitoring virus genotype diversity is crucial to understand the emergence and spread of outbreaks, both aspects that are vital to develop effective prevention and treatment strategies. Hence, we developed an efficient method to classify virus sequences with respect to their species and sub-species (i.e. serotype and/or genotype). This tool provides an easy-to-use software implementation of this new method and was validated on a large dataset assessing the classification performance with respect to whole-genome sequences and partial-genome sequences. Available online: http://krisp.org.za/tools.php.
    Publisher: Public Library of Science
    Published