Molecular epidemiology of dengue viruses from complete genome sequences

The availability of the complete genetic blueprint of the dengue virus is essential in molecular epidemiological studies to uncover the role of the virus in dengue pathogenesis. During the course of this project, over two hundred complete genomes of the dengue virus were generated from clinical samples collected in three dengue-endemic Southeast Asian countries. In addition, a bioinformatics platform integrating a sequence database, sequence retrieval tools, sequence annotation data and a variety of analysis tools was developed for easy management, manipulation and analysis of dengue virus sequence data. Whereas previous studies have mostly focused on epidemiological events in the Americas and Thailand, sequence data recovered from dengue epidemics in Indonesia, Malaysia and Singapore in this study have uncovered some of the dengue virus diversity circulating in the region. The three countries appear to share similar pool of dengue viruses, with some viral lineages in sustained circulation since at least the 1970s. Sequencing of historical virus isolates prior to the 2004/2005 epidemics in Indonesia and Singapore revealed that adaptive viral evolution played little or no role in triggering those epidemics. Lastly, a method that utilised all available sequence data from Malaysia was devised to reconstruct the history of dengue virus in that country since the 1960s

Natural, persistent oscillations in a spatial multi-strain disease system with application to dengue.

This is a freely-available open access publication. Please cite the published version which is available via the DOI link in this record.Many infectious diseases are not maintained in a state of equilibrium but exhibit significant fluctuations in prevalence over time. For pathogens that consist of multiple antigenic types or strains, such as influenza, malaria or dengue, these fluctuations often take on the form of regular or irregular epidemic outbreaks in addition to oscillatory prevalence levels of the constituent strains. To explain the observed temporal dynamics and structuring in pathogen populations, epidemiological multi-strain models have commonly evoked strong immune interactions between strains as the predominant driver. Here, with specific reference to dengue, we show how spatially explicit, multi-strain systems can exhibit all of the described epidemiological dynamics even in the absence of immune competition. Instead, amplification of natural stochastic differences in disease transmission, can give rise to persistent oscillations comprising semi-regular epidemic outbreaks and sequential dominance of dengue's four serotypes. Not only can this mechanism explain observed differences in serotype and disease distributions between neighbouring geographical areas, it also has important implications for inferring the nature and epidemiological consequences of immune mediated competition in multi-strain pathogen systems.Fundacao para a Ciencia e TecnologiaSiemens PortugalRoyal Societ

Migration induced epidemics: Dynamics of flux-based multipatch models

Classical disease models use a mass action term as the interaction between infected and susceptible people in separate patches. We derive the equations when this interaction is a migration of people between patches. The results model what happens when a new population is moved into a region with endemic disease.Comment: 25 page

Fractional diffusion emulates a human mobility network during a simulated disease outbreak

From footpaths to flight routes, human mobility networks facilitate the spread of communicable diseases. Control and elimination efforts depend on characterizing these networks in terms of connections and flux rates of individuals between contact nodes. In some cases, transport can be parameterized with gravity-type models or approximated by a diffusive random walk. As a alternative, we have isolated intranational commercial air traffic as a case study for the utility of non-diffusive, heavy-tailed transport models. We implemented new stochastic simulations of a prototypical influenza-like infection, focusing on the dense, highly-connected United States air travel network. We show that mobility on this network can be described mainly by a power law, in agreement with previous studies. Remarkably, we find that the global evolution of an outbreak on this network is accurately reproduced by a two-parameter space-fractional diffusion equation, such that those parameters are determined by the air travel network.Comment: 26 pages, 4 figure

Phylogenetic, epidemiological and clinical studies on dengue and dengue virus in Vitória, Espírito Santo state, Brazil

Background: Vitória is an endemic area in Brazil for dengue. This thesis presents the phylogeny of dengue virus serotype 4, the evaluation of dengue dispersion and the influence of serotypes and demographics to severe dengue outcomes in Vitória. Methods: Sequences of envelope (n = 8) and NS1 (n = 4) gene of dengue virus serotype 4 were used to construct phylogenetic trees (2013). Spatial variation in temporal trends was analyzed (2012-2013). Cross-sectional studies were performed to assess associations of serotypes (2009-2013) and demographics (2007-2013) with severe outcomes. Results: Dengue virus serotype 4 genotype I (n = 2) related to a strain from Bahia, and genotype II (n = 8) related to strains from Roraima, Mato Grosso and São Paulo were detected. Five space-time clusters with lower Time Trend Increase presented higher risk for dengue transmission and lower income than the six space-time clusters with higher Time Trend Increase. In 6,703 dengue cases, 11.3% presented severe dengue, which was significantly higher among males (13.0%) than females (10.0%), and among elderlies (15.5%) than children (8.8%), adolescents (12.5%), and adults (10.5%). Children with severe dengue presented hemorrhage (68.8%-86.4%) and plasma leakage (52.4%-62.5%) in a higher proportion than other age groups. Serotype was determined for 485 cases and severe dengue affected 6.6% of them. Severe dengue occurred at a significantly higher frequency in infections caused by dengue virus serotype 2 (32.3%) than in those caused by dengue virus serotype 4 (6.4%) or by dengue virus serotype 1 (4.5%). Conclusion: Apparently, Vitória is not an international route for dengue introduction in Brazil. Living in low-income areas increased the chance of dengue infection. Dengue virus serotype 2 was associated with an elevated occurrence of severe dengue, which also affected more males and elderlies. Manifestations of severe dengue were worse in children than in other age group

A spatio-temporal analysis of dengue spread in a Brazilian dry climate region

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A Case-study Approach to Investigate Transmission, Co-infection, and Clinical Sequelae During Epidemics of Dengue and Ebola Virus Disease

From within their ecologic niches, zoonotic viruses emerge from animal reservoirs into the edges and centers of human habitation to exploit opportunities for unabated transmission within immunologically–naïve populations. Our understanding of where, in whom, and how these viruses emerge is under direct challenge, driving the evolution of modern infectious disease epidemiology within a rapidly-connected global community. The studies presented herein are based on analyses of both aggregate and case-level data, which, we argue, provide unique insight into the complexities of transmission, co-infection, and clinical sequelae occurring within, and arising from, epidemics of emerging zoonotic viruses. In Chapter II, we investigate differences in disease severity between single- and multi-serotype dengue virus infections, and examine the clinical presentation of patients with dengue versus patients with dengue virus-Leptospira co-infection. Our objective was to construct a diagnostic algorithm to aid clinicians in the early recognition and treatment of patients with multi-pathogen infections. In Chapter III, we reconstruct a six-person transmission chain of Ebola virus disease in Liberia. We analyze the individual behaviors and epidemic control measures that contributed to, and interrupted, transmission. Finally, in Chapter IV, we present a case series of pain profiles and functional disability among survivors of Ebola virus disease, a contribution to the newly-recognized post-Ebola virus disease syndrome. Our research contributes three principal implications for clinical and public health practice. In Norte de Santander, Colombia, we provide the first prevalence estimates of dengue virus multi-serotype infection and dengue virus-Leptospira co-infection. Identifying the reservoirs of pathogenic Leptospira spp. in Los Patios, and initiating public and clinical education campaigns, will be important interventions to mitigate environmental persistence, prevent additional cases, and encourage early initiation of antibiotic therapy. From case investigations in Liberia, we identify sweat as an under-recognized driver of the Ebola virus disease epidemic, and discuss the importance of social distancing to interrupt transmission. Finally, we describe the clinical symptoms and longitudinal disability experience of three Ebola virus disease survivors to contribute to the growing evidence of a post-viral syndrome in survivors

Weather, climate change and dengue in Mexico

Many studies have estimated empirical relationships between dengue, weather, and El Ni˜no in several regions of the world. Some of these studies used their model estimations to predict the potential impacts of climate change on the future distribution of dengue. Often, these studies have sidestepped elements that are key to the estimation of the effects of climate variables on dengue with statistical confidence. For example, they fail to incorporate covariates that may confound the empirical associations between dengue, weather, El Ni˜no, and climate undermining their model estimations. Additionally, several studies used nationally or supra-nationally aggregated data which remove the spatial variability in all variables making it difficult to detect complex associations between dengue and climate variables. Other studies were conducted in small geographical areas with the problem of having low numbers of disease cases posing problems for their analysis with statistical confidence. Here, we used the most comprehensive dengue-related datasets analysed to date and several statistical methods to investigate the effects of weather, climate, and El Ni˜no on dengue incidence. We demonstrate that such effects are robust to the confounding effects of socioeconomic development and other non-climatic factors such as seasonal trends and inter-annual variability. Our results reveal that the effects weather and El Ni˜no are significantly heterogeneous between provinces influenced by the underlying climate. With the exception of access to piped water, we could not identify significant effects of socioeconomic status on dengue occurrence. This result is likely related to human behaviour or the lack of protective measures against mosquitoes. We used our model estimations to project the potential impacts of climate change on dengue incidence by 2030, 2050 and 2080 with greater statistical confidence than previous studies. Our projections indicate that climate change is likely to increase dengue incidence mainly in already endemic areas