Insights into intercontinental spread of Zika virus.
Ontology highlight
ABSTRACT:
SUBMITTER: Liang D
PROVIDER: S-EPMC5407806 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:We use a data-driven global stochastic epidemic model to analyze the spread of the Zika virus (ZIKV) in the Americas. The model has high spatial and temporal resolution and integrates real-world demographic, human mobility, socioeconomic, temperature, and vector density data. We estimate that the first introduction of ZIKV to Brazil likely occurred between August 2013 and April 2014 (90% credible interval). We provide simulated epidemic profiles of incident ZIKV infections for several countries in the Americas through February 2017. The ZIKV epidemic is characterized by slow growth and high spatial and seasonal heterogeneity, attributable to the dynamics of the mosquito vector and to the characteristics and mobility of the human populations. We project the expected timing and number of pregnancies infected with ZIKV during the first trimester and provide estimates of microcephaly cases assuming different levels of risk as reported in empirical retrospective studies. Our approach represents a modeling effort aimed at understanding the potential magnitude and timing of the ZIKV epidemic and it can be potentially used as a template for the analysis of future mosquito-borne epidemics.
| S-EPMC5465916 | biostudies-literature
Project description:BackgroundZika virus transmission dynamics in urban environments follow a complex spatiotemporal pattern that appears unpredictable and barely related to high mosquito density areas. In this context, human activity patterns likely have a major role in Zika transmission dynamics. This paper examines the effect of host variability in the amount of time spent outdoors on Zika epidemiology in an urban environment.Methodology/principal findingsFirst, we performed a survey on time spent outdoors by residents of Miami-Dade County, Florida. Second, we analyzed both the survey and previously published national data on outdoors time in the U.S. to provide estimates of the distribution of the time spent outdoors. Third, we performed a computational modeling evaluation of Zika transmission dynamics, based on the time spent outdoors by each person. Our analysis reveals a strong heterogeneity of the host population in terms of time spent outdoors-data are well captured by skewed gamma distributions. Our model-based evaluation shows that in a heterogeneous population, Zika would cause a lower number of infections than in a more homogenous host population (up to 4-fold differences), but, at the same time, the epidemic would spread much faster. We estimated that in highly heterogeneous host populations the timing of the implementation of vector control measures is the major factor for limiting the number of Zika infections.Conclusions/significanceOur findings highlight the need of considering host variability in exposure time for managing mosquito-borne infections and call for the revision of the triggers for vector control strategies, which should integrate mosquito density data and human outdoor activity patterns in specific areas.
| S-EPMC5598931 | biostudies-literature
Project description:Although the recent Zika virus (ZIKV) epidemic in the Americas and its link to birth defects have attracted a great deal of attention, much remains unknown about ZIKV disease epidemiology and ZIKV evolution, in part owing to a lack of genomic data. Here we address this gap in knowledge by using multiple sequencing approaches to generate 110 ZIKV genomes from clinical and mosquito samples from 10 countries and territories, greatly expanding the observed viral genetic diversity from this outbreak. We analysed the timing and patterns of introductions into distinct geographic regions; our phylogenetic evidence suggests rapid expansion of the outbreak in Brazil and multiple introductions of outbreak strains into Puerto Rico, Honduras, Colombia, other Caribbean islands, and the continental United States. We find that ZIKV circulated undetected in multiple regions for many months before the first locally transmitted cases were confirmed, highlighting the importance of surveillance of viral infections. We identify mutations with possible functional implications for ZIKV biology and pathogenesis, as well as those that might be relevant to the effectiveness of diagnostic tests.
| S-EPMC5563848 | biostudies-literature
Project description:The Americas are presently experiencing the most serious known outbreak of Zika virus (ZIKV). Here, we present a novel set of analyses using environmental characteristics, vector mosquito distributions, and socioeconomic risk factors to develop the first map to detail global ZIKV transmission risk in multiple dimensions based on ecological niche models. Our model predictions were tested against independent evaluation data sets, and all models had predictive ability significantly better than random expectations. The study addresses urgent knowledge gaps regarding (1) the potential geographic scope of the current ZIKV epidemic, (2) the global potential for spread of ZIKV, and (3) drivers of ZIKV transmission. Our analysis of potential drivers of ZIKV distributions globally identified areas vulnerable in terms of some drivers, but not for others. The results of these analyses can guide regional education and preparedness efforts, such that medical personnel will be better prepared for diagnosis of potential ZIKV cases as they appear.
| S-EPMC5027865 | biostudies-literature
Project description:Current methods for differentiating isolates of predominant lineages of pathogenic bacteria often do not provide sufficient resolution to define precise relationships. Here, we describe a high-throughput genomics approach that provides a high-resolution view of the epidemiology and microevolution of a dominant strain of methicillin-resistant Staphylococcus aureus (MRSA). This approach reveals the global geographic structure within the lineage, its intercontinental transmission through four decades, and the potential to trace person-to-person transmission within a hospital environment. The ability to interrogate and resolve bacterial populations is applicable to a range of infectious diseases, as well as microbial ecology.
| S-EPMC2821690 | biostudies-literature
Project description:Zika virus (ZIKV), a disease spread primarily through the Aedes aegypti mosquito, was identified in Brazil in 2015 and was declared a global health emergency by the World Health Organization (WHO). Epidemiologists often use common state-level attributes such as population density and temperature to determine the spread of disease. By applying techniques from topological data analysis, we believe that epidemiologists will be able to better predict how ZIKV will spread. We use the Vietoris-Rips filtration on high-density mosquito locations in Brazil to create simplicial complexes, from which we extract homology group generators. Previously epidemiologists have not relied on topological data analysis to model disease spread. Evaluating our model on ZIKV case data in the states of Brazil demonstrates the value of these techniques for the improved assessment of vector-borne diseases.
| S-EPMC5810985 | biostudies-literature
Project description:The recent Zika virus (ZIKV) outbreak in the Americas surprised all of us because of its rapid spread and association with neurologic disorders including fetal microcephaly, brain and ocular anomalies, and Guillain?Barré syndrome. In response to this global health crisis, unprecedented and world-wide efforts are taking place to study the ZIKV-related human diseases. Much has been learned about this virus in the areas of epidemiology, genetic diversity, protein structures, and clinical manifestations, such as consequences of ZIKV infection on fetal brain development. However, progress on understanding the molecular mechanism underlying ZIKV-associated neurologic disorders remains elusive. To date, we still lack a good understanding of; (1) what virologic factors are involved in the ZIKV-associated human diseases; (2) which ZIKV protein(s) contributes to the enhanced viral pathogenicity; and (3) how do the newly adapted and pandemic ZIKV strains alter their interactions with the host cells leading to neurologic defects? The goal of this review is to explore the molecular insights into the ZIKV?host interactions with an emphasis on host cell receptor usage for viral entry, cell innate immunity to ZIKV, and the ability of ZIKV to subvert antiviral responses and to cause cytopathic effects. We hope this literature review will inspire additional molecular studies focusing on ZIKV?host Interactions.
| S-EPMC5977226 | biostudies-literature
Project description:The question of how Zika virus (ZIKV) changed from a seemingly mild virus to a human pathogen capable of microcephaly and sexual transmission remains unanswered. The unexpected emergence of ZIKV's pathogenicity and capacity for sexual transmission may be due to genetic changes, and future changes in phenotype may continue to occur as the virus expands its geographic range. Alternatively, the sheer size of the 2015-16 epidemic may have brought attention to a pre-existing virulent ZIKV phenotype in a highly susceptible population. Thus, it is important to identify patterns of genetic change that may yield a better understanding of ZIKV emergence and evolution. However, because ZIKV has an RNA genome and a polymerase incapable of proofreading, it undergoes rapid mutation which makes it difficult to identify combinations of mutations associated with viral emergence. As next generation sequencing technology has allowed whole genome consensus and variant sequence data to be generated for numerous virus samples, the task of analyzing these genomes for patterns of mutation has become more complex. However, understanding which combinations of mutations spread widely and become established in new geographic regions versus those that disappear relatively quickly is essential for defining the trajectory of an ongoing epidemic. In this study, multiscale analysis of the wealth of genomic data generated over the course of the epidemic combined with in vivo laboratory data allowed trends in mutations and outbreak trajectory to be assessed. Mutations were detected throughout the genome via deep sequencing, and many variants appeared in multiple samples and in some cases become consensus. Similarly, amino acids that were previously consensus in pre-outbreak samples were detected as low frequency variants in epidemic strains. Protein structural models indicate that most of the mutations associated with the epidemic transmission occur on the exposed surface of viral proteins. At the macroscale level, consensus data was organized into large and interactive databases to allow the spread of individual mutations and combinations of mutations to be visualized and assessed for temporal and geographical patterns. Thus, the use of multiscale modeling for identifying mutations or combinations of mutations that impact epidemic transmission and phenotypic impact can aid the formation of hypotheses which can then be tested using reverse genetics.
| S-EPMC6897431 | biostudies-literature
Project description:BackgroundZika virus (ZIKV) emerged as a global epidemic in 2015-2016 from Latin America with its true geographical extent remaining unclear due to widely presumed underreporting. The identification of locations with potential and unknown spread of ZIKV is a key yet understudied component for outbreak preparedness. Here, we aim to identify locations at a high risk of cryptic ZIKV spread during 2015-2016 to further the understanding of the global ZIKV epidemiology, which is critical for the mitigation of the risk of future epidemics.MethodsWe developed an importation simulation model to estimate the weekly number of ZIKV infections imported in each susceptible spatial unit (i.e. location that did not report any autochthonous Zika cases during 2015-2016), integrating epidemiological, demographic, and travel data as model inputs. Thereafter, a global risk model was applied to estimate the weekly ZIKV transmissibility during 2015-2016 for each location. Finally, we assessed the risk of onward ZIKV spread following importation in each susceptible spatial unit to identify locations with a high potential for cryptic ZIKV spread during 2015-2016.ResultsWe have found 24 susceptible spatial units that were likely to have experienced cryptic ZIKV spread during 2015-2016, of which 10 continue to have a high risk estimate within a highly conservative scenario, namely, Luanda in Angola, Banten in Indonesia, Maharashtra in India, Lagos in Nigeria, Taiwan and Guangdong in China, Dakar in Senegal, Maputo in Mozambique, Kinshasa in Congo DRC, and Pool in Congo. Notably, among the 24 susceptible spatial units identified, some have reported their first ZIKV outbreaks since 2017, thus adding to the credibility of our results (derived using 2015-2016 data only).ConclusionOur study has provided valuable insights into the potentially high-risk locations for cryptic ZIKV circulation during the 2015-2016 pandemic and has also laid a foundation for future studies that attempt to further narrow this key knowledge gap. Our modelling framework can be adapted to identify areas with likely unknown spread of other emerging vector-borne diseases, which has important implications for public health readiness especially in resource-limited settings.
| S-EPMC7744256 | biostudies-literature
Project description:Zika Virus (ZIKV) is a flavivirus that is transmitted predominantly by the Aedes species of mosquito, but also through sexual contact, blood transfusions, and congenitally from mother to child. Although approximately 80% of ZIKV infections are asymptomatic and typical symptoms are mild, multiple studies have demonstrated a causal link between ZIKV and severe diseases such as Microcephaly and Guillain Barré Syndrome. Two goals of this study are to improve ZIKV models by considering the spread dynamics of ZIKV as both a vector-borne and sexually transmitted disease, and also to approximate the degree of under-reporting. In order to accomplish these objectives, we propose a compartmental model that allows for the analysis of spread dynamics as both a vector-borne and sexually transmitted disease, and fit it to the ZIKV incidence reported to the National System of Public Health Surveillance in 27 municipalities of Colombia between January 1 2015 and December 31 2017. We demonstrate that our model can represent the infection patterns over this time period with high confidence. In addition, we argue that the degree of under-reporting is also well estimated. Using the model we assess potential viability of public health scenarios for mitigating disease spread and find that targeting the sexual pathway alone has negligible impact on overall spread, but if the proportion of risky sexual behavior increases then it may become important. Targeting mosquitoes remains the best approach of those considered. These results may be useful for public health organizations and governments to construct and implement suitable health policies and reduce the impact of the Zika outbreaks.
| S-EPMC9803243 | biostudies-literature