An Integrative Eco-Epidemiological Analysis of West Nile Virus Transmission

West Nile disease, caused by the West Nile virus (WNV), is a mosquito-borne zoonotic disease affecting humans and horses that involves wild birds as amplifying hosts. The mechanisms of WNV transmission remain unclear in Europe where the occurrence of outbreaks has dramatically increased in recent years. We used a dataset on the competence, distribution, abundance, diversity and dispersal of wild bird hosts and mosquito vectors to test alternative hypotheses concerning the transmission of WNV in Southern France. We modelled the successive processes of introduction, amplification, dispersal and spillover of WNV to incidental hosts based on host–vector contact rates on various land cover types and over four seasons. We evaluated the relative importance of the mechanisms tested using two independent serological datasets of WNV antibodies collected in wild birds and horses. We found that the same transmission processes (seasonal virus introduction by migratory birds, Culex modestus mosquitoes as amplifying vectors, heterogeneity in avian host competence, absence of ‘dilution effect’) best explain the spatial variations in WNV seroprevalence in the two serological datasets. Our results provide new insights on the pathways of WNV introduction, amplification and spillover and the contribution of bird and mosquito species to WNV transmission in Southern France.     

Dynamics of West Nile Virus Persistence in House Sparrows (Passer domesticus)

West Nile Virus (WNV) is now endemic throughout North America, with annual recurrence dependent upon successful overwintering when cold temperatures drive mosquito vectors into inactivity and halt transmission. To investigate whether avian hosts may serve as an overwintering mechanism, groups of eight to ten House Sparrows were experimentally infected with a WN02 genotype of WNV and then held until necropsy at 3, 5, 7, 9, 12, 15, or 18 weeks post-infection (pi) when they were assessed for the presence of persistent infection. Blood was collected from all remaining birds every two weeks pi, and sera tested for WNV RNA and WNV neutralizing antibodies. West Nile virus RNA was present in the sera of some birds up to 7 weeks pi and all birds retained neutralizing antibodies throughout the experiment. The detection of persistently infected birds decreased with time, from 100% (n = 13) positive at 3 weeks post-infection (pi) to 12.5% (n = 8) at 18 weeks pi. Infectious virus was isolated from the spleens of birds necropsied at 3, 5, 7 and 12 weeks pi. The current study confirmed previous reports of infectious WNV persistence in avian hosts, and further characterized the temporal nature of these infections. Although these persistent infections supported the hypothesis that infected birds may serve as an overwintering mechanism, mosquito-infectious recrudescent viremias have yet to be demonstrated thereby providing proof of principle.     

西尼罗病毒研究进展

西尼罗病毒 (West Nile virus,WNV) 首先在1937年乌干达的西尼罗地区的Omogo镇的一位发热病人血液中分离到,从而得名[1].西尼罗病毒属于黄病毒科黄病毒属.     

Seasonality and Outbreaks in West Nile Virus Infection

In this paper we analyze the impact of seasonal variations on the dynamics of West Nile Virus infection. We are interested in the generation of new epidemic peaks starting from an endemic state. In many cases, the oscillations generated by seasonality in the dynamics of the infection are too small to be observable. The interplay of this seasonality with the epidemic oscillations can generate new outbreaks starting from the endemic state through a mechanism of parametric resonance. Using experimental data we present specific cases where this phenomenon is numerically observed.     

Characterizing the Transmission Dynamics and Control of Ebola Virus Disease

Carefully calibrated transmission models have the potential to guide public health officials on the nature and scale of the interventions required to control epidemics. In the context of the ongoing Ebola virus disease (EVD) epidemic in Liberia, Drake and colleagues, in this issue of PLOS Biology, employed an elegant modeling approach to capture the distributions of the number of secondary cases that arise in the community and health care settings in the context of changing population behaviors and increasing hospital capacity. Their findings underscore the role of increasing the rate of safe burials and the fractions of infectious individuals who seek hospitalization together with hospital capacity to achieve epidemic control. However, further modeling efforts of EVD transmission and control in West Africa should utilize the spatial-temporal patterns of spread in the region by incorporating spatial heterogeneity in the transmission process. Detailed datasets are urgently needed to characterize temporal changes in population behaviors, contact networks at different spatial scales, population mobility patterns, adherence to infection control measures in hospital settings, and hospitalization and reporting rates.Ebola virus disease (EVD) is caused by an RNA virus of the family Filoviridae and genus Ebolavirus. Five different Ebolavirus strains have been identified, namely Zaire ebolavirus (EBOV), Sudan ebolavirus (SUDV), Tai Forest ebolavirus (TAFV), Bundibugyo ebolavirus (BDBV), and Reston ebolavirus (RESTV). The great majority of past Ebola outbreaks in humans have been linked to three Ebola strains: EBOV, SUDV, and BDBV [1]. The Ebola virus ([EBOV] formerly designated Zaire ebolavirus) derived its name from the Ebola River, located near the epicenter of the first outbreak identified in 1976 in Zaire (now the Democratic Republic of Congo). EVD outbreaks among humans have been associated with direct human exposure to fruit bats—the most likely reservoir of the virus—or through contact with intermediate infected hosts, which include gorillas, chimpanzees, and monkeys. Outbreaks have been reported on average every 1.5 years [2]. Past EVD outbreaks have occurred in relatively isolated areas and have been limited in size and duration (Fig. 1). It has been recently estimated that about 22 million people living in areas of Central and West Africa are at risk of EVD [3].Open in a separate windowFigure 1Time series of the temporal progression of four past EVD outbreaks in Congo (1976, 1995, 2014) [4–6] and Uganda (2000) [7].An epidemic of EVD (EBOV) has been spreading in West Africa since December 2013 in Guinea, Liberia, and Sierra Leone [8]. A total of 18,603 cases, with 6,915 deaths, have been reported to the World Health Organization as of December 17, 2014 [9]. While the causative strain associated with this epidemic is closely related to that of past outbreaks in Central Africa [10], three key factors have contributed disproportionately to this unprecedented epidemic: (1) substantial delays in detection and implementation of control efforts in a region characterized by porous borders; (2) limited public health infrastructure including epidemiological surveillance systems and diagnostic testing [11], which are necessary for the timely diagnosis of symptomatic individuals, effective isolation of infectious individuals, contact tracing to rapidly identify new cases, and providing supportive care to increase the chances of survival to EVD infection; and (3) cultural practices that involve touching the body of the deceased and the association of illness with witchcraft or conspiracy theories.EBOV is transmitted by direct human-to-human contact via body fluids or indirect contact with contaminated surfaces, but it is not spread through the airborne route. Individuals become symptomatic after an average incubation period of 10 days (range 2–21 days) [12], and infectiousness is increased during the later stages of disease [13]. The characteristic symptoms of EVD are nonspecific and include sudden onset of fever, weakness, vomiting, diarrhea, headache, and a sore throat, while only a fraction of the symptomatic individuals present with hemorrhagic manifestations [14]. The case fatality risk (CFR), calculated as the proportion of deaths among the total number of EVD cases with known outcomes, has been estimated from data of the first 9 months of the epidemic in West Africa at 70.8% (95% CI 68.6–72.8), in broad agreement with estimates from past outbreaks [12].Two important quantities to understand in the transmission dynamics of EVD are the serial interval and the basic reproduction number. The serial interval is defined as the time from illness onset in a primary case to illness onset in a secondary case [15] and has been estimated at 15 days on average for the ongoing epidemic [12]. The basic reproduction number, R ₀, quantifies transmission potential at the beginning of an epidemic and is defined as the average number of secondary cases generated by a typical infected individual during the early phase of an epidemic, before interventions are put in place [16]. If R ₀ < 1, transmission is not sufficient to generate a major epidemic. In contrast, a major epidemic is likely to occur whenever R ₀ > 1. When transmission potential is measured over time t, the effective reproduction number R_t, can be helpful to quantify the time-dependent transmission potential resulting from the effect of control interventions and behavior changes [17]. Estimates of R ₀ for the ongoing epidemic in West Africa have fluctuated around 2 with some uncertainty (e.g., [12, 18–22]), which are in good agreement with estimates from past EVD outbreaks [23]. R ₀ could also vary across regions as a function of the local public health infrastructure (e.g., availability of health care settings and infection control protocols), such that an outbreak may be very unlikely to unfold in developed countries simply as a result of baseline infection control measures in place (i.e., R ₀ < 1) while poor countries with extremely weak or absent public health systems may be unable to control an Ebola outbreak (i.e., R ₀ > 1).Mathematical models of disease transmission have proved to be useful tools to characterize the transmission dynamics of infectious diseases and evaluate the effects of control intervention strategies in order to inform public health policy [16, 24, 25]. There are a limited number of mathematical models for the transmission and control of EVD, but a number of efforts are underway in the context of the epidemic in West Africa. The transmission dynamics of EVD have been modeled on the basis of the simple compartmental susceptible-exposed-infectious-removed (SEIR) model that assumes a homogenously mixed population [23]. The modeled population can be structured according to the contributions of community, hospital, and unsafe burials to transmission as EVD transmission has been amplified in health care settings with ineffective infection control measures and during unsafe burials [23]. A schematic representation of the main transmission pathways of EVD is shown in Fig. 2.Open in a separate windowFigure 2Schematic representation of the transmission dynamics of Ebola virus disease.A recent study published in PLOS Biology by Drake and colleagues [26] presents an interesting and flexible modeling framework for the transmission and control of EVD in Liberia. Their framework is based on a multi-type branching process model in which “multi-type” refers to the consideration of two types of settings where transmission can occur, while “branching process” is the mathematical term to specify a probabilistic model. For instance, in the case of a single-type branching process, the transmission dynamics are simply described using a single reproduction number, i.e., the average number of secondary cases produced by a single primary case. However, when two types of hosts are considered in the transmission process, two reproduction numbers are needed to characterize within-group mixing (e.g., within-hospital and within-community transmission) and two reproduction numbers characterize transmission between groups (e.g., transmission from hospital to community and vice versa).Drake and colleague’s elegant modeling approach describes EVD transmission according to infection generations by calculating probability distributions of the number of secondary cases that arise in the community via nursing care or during unsafe burials and in health care settings via infections to health care workers and visitors. The model explicitly accounts for the hospitalization rate—the fraction of infectious individuals in the community seeking hospitalization (estimated in this study at 60%). However, the number of effectively isolated infectious individuals is constrained by the number of available beds in treatment centers—which are assumed in this study to operate at twice their regular capacity. It is important to note that the number of beds available to treat EVD patients was severely limited in Liberia prior to mid August 2014 (Fig. 1 in [26]). Moreover, the rate of safe burials that reduces the force of infection is included in their model as an increasing function of time. The model was calibrated by tuning six parameters to fit the trajectories of the number of reported cases in the community and among health care workers during the period 4 July to 2 September 2014 for a total of four infection generations during which the effective reproduction number was estimated to decline on average from about 2.8 to 1.4. The model was able to effectively capture heterogeneity in transmission of EVD in both the community and hospital settings.Drake and colleagues [26] employed their calibrated model to forecast the epidemic trajectory in Liberia from 3 September to 31 December 2014 under different scenarios that account for an increasing fraction of cases seeking hospitalization and a surge in the number of beds available to isolate and treat EVD patients. Their results indicate that allocating 1,700 additional beds (100 new beds every 4 days) in new Ebola treatment centers committed by US aid reduces the mean epidemic size to ~51,000 (60% reduction with respect to the baseline scenario), while epidemic control by mid-March is only plausible through a 4-fold increase in the number of beds committed by US aid and enhancing the hospitalization rate from 60% to 99% for a final epidemic size of 12,285. Moreover, an additional epidemic forecast incorporating data up to 1 December 2014 indicated that containment could be achieved between March and June 2015.Other interventions were not explicitly incorporated in their model because it is difficult to parameterize them in the absence of datasets that permit statistical estimation of their impact on the transmission dynamics. These additional interventions include the use of household protection kits, designed to reduce transmission in the community; improvements in infection control protocols in health care settings that reduce transmission among health care workers; and the impact of rapid diagnostic kits in Ebola treatment centers, which reduce the time to isolation for infectious individuals seeking hospitalization. Increasing awareness and education of the population about the disease could have also yielded further reductions in case incidence by reducing the size of the at-risk susceptible population (Fig. 3) [27]. Nevertheless, some of these effects could have been indirectly captured implicitly by the time-dependent safe burial rate parameter in their model.Open in a separate windowFigure 3Contrasting epidemic growth in the presence and absence of behavior changes that reduce the transmission rate.Importantly, prior models of EVD transmission [23, 28, 29] and the model by Drake and colleagues have not incorporated spatial heterogeneity in the transmission dynamics. In particular, the EVD epidemic in West Africa can be characterized as a set of asynchronous local (e.g., district) epidemics that exhibit sub-exponential growth, which could be driven by a highly clustered underlying contact network or population behavior changes induced by the accumulation of morbidity and mortality rates (see Fig. 4 and [30]). EVD contagiousness is most pronounced in the later and more severe stages of Ebola infection when infectious individuals are confined at home or health care settings and mostly exposed to caregivers (e.g., health care workers, family members) [30]. This characterization would lead to EVD transmission over a network of contacts that is highly clustered (e.g., individuals are likely to share a significant fraction of their contacts), which is associated with significantly slower spread relative to the common random mixing assumption as illustrated in Fig. 5. The development of transmission models that incorporate spatial heterogeneity (e.g., by modeling spatial coupling or human migration) is currently limited by the shortage of detailed datasets from the EVD-affected areas about the geographic distribution of households, health care settings, reporting and hospitalization rates across urban and rural areas, and patterns of population mobility in the region. Some of these limitations may be overcome in the near future. For instance, cell phone data could provide a basis to characterize population mobility in the region at a refined spatial scale.Open in a separate windowFigure 4Representative time series of the cumulative number of EVD cases (in log scale) at the district level in Guinea, Sierra Leone, and Liberia.Open in a separate windowFigure 5Epidemic growth in two populations characterized by two different underlying contact networks.The ongoing epidemic in West Africa offers a unique opportunity to improve our current understanding of the transmission characteristics of EVD in humans. To achieve this goal, it is crucial to collect spatial-temporal data on population behaviors, contact networks, social distancing measures, and education campaigns. Datasets comprising detailed demographic, socio-economic, contact rates, and population mobility estimates in the region (e.g., commuting networks, air traffic) need to be integrated and made publicly available in order to develop highly resolved transmission models, which could guide control strategies with greater precision in the context of the EVD epidemic in West Africa. Although recent data from Liberia indicates that the epidemic is on track for eventual control, the epidemic in Sierra Leone continues an increasing trend, and in Guinea, case incidence roughly follows a steady trend. The potential impact of vaccines should also be incorporated in future modeling efforts as these pharmaceutical interventions are expected to become available in the upcoming months.     

Modeling Dynamics of Culex pipiens Complex Populations and Assessing Abatement Strategies for West Nile Virus

The primary mosquito species associated with underground stormwater systems in the United States are the Culex pipiens complex species. This group represents important vectors of West Nile virus (WNV) throughout regions of the continental U.S. In this study, we designed a mathematical model and compared it with surveillance data for the Cx. pipiens complex collected in Beaufort County, South Carolina. Based on the best fit of the model to the data, we estimated parameters associated with the effectiveness of public health insecticide (adulticide) treatments (primarily pyrethrin products) as well as the birth, maturation, and death rates of immature and adult Cx. pipiens complex mosquitoes. We used these estimates for modeling the spread of WNV to obtain more reliable disease outbreak predictions and performed numerical simulations to test various mosquito abatement strategies. We demonstrated that insecticide treatments produced significant reductions in the Cx. pipiens complex populations. However, abatement efforts were effective for approximately one day and the vector mosquitoes rebounded until the next treatment. These results suggest that frequent insecticide applications are necessary to control these mosquitoes. We derived the basic reproductive number (ℜ₀) to predict the conditions under which disease outbreaks are likely to occur and to evaluate mosquito abatement strategies. We concluded that enhancing the mosquito death rate results in lower values of ℜ₀, and if ℜ₀<1, then an epidemic will not occur. Our modeling results provide insights about control strategies of the vector populations and, consequently, a potential decrease in the risk of a WNV outbreak.     

Transmission Dynamics of the West Nile Virus in Mosquito Vector Populations under the Influence of Weather Factors in the Danube Delta,Romania

EcoHealth - Mosquitoes were collected in the Danube Delta during the active seasons of 2011–2013. For Culex spp. mosquitoes, the abundance was calculated. Culex pipiens (sensu lato), (s.l.)...     

西尼罗病毒易感性研究现状

西尼罗病毒可引起鼠、人类及其他动物严重脑炎,近年来再度流行。基因研究分析表明近年来西尼罗病毒突变的速度逐渐加快,突变主要发生在基因编码区,这些突变可导致病毒蛋白E区、NS1区、NS2区及NS5区氨基酸序列的改变。西尼罗病毒感染主要发生于老龄及免疫缺陷动物或人群。西尼罗病毒的易感染性除与突变有重要关系外,与CCR5、OAS及CXCL10等受体及因子也有一定的关系。     

Modelling the dynamics of West Nile Virus

In this work we formulate and analyze a mathematical model for the transmission of West Nile Virus (WNV) infection between vector (mosquito) and avian population. We find the Basic Reproductive Number in terms of measurable epidemiological and demographic parameters. is the threshold condition that determines the dynamics of WNV infection: if the disease fades out, and for the disease remains endemic. Using experimental and field data we estimate for several species of birds. Numerical simulations of the temporal course of the infected bird proportion show damped oscillations approaching the endemic value.     

West Nile Virus in the British Virgin Islands

West Nile virus (WNV) first emerged in the US in 1999 and has since spread across the Americas. Here, we report the continued expansion of WNV to the British Virgin Islands following its emergence in a flock of free-roaming flamingos. Histologic review of a single chick revealed lesions consistent with WNV infection, subsequently confirmed with PCR, immunohistochemistry and in situ hybridization. Full genome analysis revealed 99% sequence homology to strains circulating in the US over the past decade. This study highlights the need for rapid necropsy of wild bird carcasses to fully understand the impact of WNV on wild populations.     

West Nile Virus and California Breeding Bird Declines

Since it was first detected in 1999, West Nile virus (WNV) quickly spread, becoming the dominant vector-borne disease in North America. Sometimes fatal to humans, WNV is even more widespread among birds, with hundreds of species known to be susceptible to WNV infection in North America alone. However, despite considerable mortality and local declines observed in American crows (Corvus brachyrhynchos), there has been little evidence of a large regional association between WNV susceptibility and population declines of any species. Here we demonstrate a correlation between susceptibility to WNV measured by large-scale testing of dead birds and two indices of overall population change among bird species following the spread of WNV throughout California. This result was due primarily to declines in four species of Corvidae, including all species in this family except common ravens (Corvus corax). Our results support the hypothesis that susceptibility to WNV may have negative population consequences to most corvids on regional levels. They also provide confirmation that dead animal surveillance programs can provide important data indicating populations most likely to suffer detrimental impacts due to WNV.     

Threshold Conditions for West Nile Virus Outbreaks

In this paper, we study the stability and saddle-node bifurcation of a model for the West Nile virus transmission dynamics. The existence and classification of the equilibria are presented. By the theory of K-competitive dynamical systems and index theory of dynamical systems on a surface, sufficient and necessary conditions for local stability of equilibria are obtained. We also study the saddle-node bifurcation of the system. Explicit subthreshold conditions in terms of parameters are obtained beyond the basic reproduction number which provides further guidelines for accessing control of the spread of the West Nile virus. Our results suggest that the basic reproductive number itself is not enough to describe whether West Nile virus will prevail or not and suggest that we should pay more attention to the initial state of West Nile virus. The results also partially explained the mechanism of the recurrence of the small scale endemic of the virus in North America. Supported by the Chinese NSF grants 10531030 and 10671143. Supported by the Chinese NSF grants 10801074. Supported by Canada Research Chairs Program, Mathematics for Information Technology and Complex Systems (MITACS), National Microbiology Laboratory, Natural Sciences and Engineering Research Council (NSERC), Canadian Foundation of Innovation (CFI) and Ontario Innovation Trust (OIT), Ontario Ministry of Health and Long-term Care, Peel, Toronto, Chat-Kent Health Units, and Public Health Agency of Canada (PHAC). Supported by NSERC, MITACS, CFI/OIT a new opportunity fund, Early Research Award of Ministry of Research and Innovation (ERA) of Ontario, Infectious Diseases Branch of Ministry of Health and Long Term Care (MOH) of Ontario and PHAC.     

Reduced West Nile Virus Transmission Around Communal Roosts of Great-Tailed Grackle (Quiscalus mexicanus)

EcoHealth - West Nile virus has caused several outbreaks among humans in the Phoenix metropolitan area (Arizona, southwest USA) within the last decade. Recent ecologic studies have implicated Culex...     

IPS-1 Is Essential for the Control of West Nile Virus Infection and Immunity

The innate immune response is essential for controlling West Nile virus (WNV) infection but how this response is propagated and regulates adaptive immunity in vivo are not defined. Herein, we show that IPS-1, the central adaptor protein to RIG-I-like receptor (RLR) signaling, is essential for triggering of innate immunity and for effective development and regulation of adaptive immunity against pathogenic WNV. IPS-1^−/− mice exhibited increased susceptibility to WNV infection marked by enhanced viral replication and dissemination with early viral entry into the CNS. Infection of cultured bone-marrow (BM) derived dendritic cells (DCs), macrophages (Macs), and primary cortical neurons showed that the IPS-1-dependent RLR signaling was essential for triggering IFN defenses and controlling virus replication in these key target cells of infection. Intriguingly, infected IPS-1^−/− mice displayed uncontrolled inflammation that included elevated systemic type I IFN, proinflammatory cytokine and chemokine responses, increased numbers of inflammatory DCs, enhanced humoral responses marked by complete loss of virus neutralization activity, and increased numbers of virus-specific CD8+ T cells and non-specific immune cell proliferation in the periphery and in the CNS. This uncontrolled inflammatory response was associated with a lack of regulatory T cell expansion that normally occurs during acute WNV infection. Thus, the enhanced inflammatory response in the absence of IPS-1 was coupled with a failure to protect against WNV infection. Our data define an innate/adaptive immune interface mediated through IPS-1-dependent RLR signaling that regulates the quantity, quality, and balance of the immune response to WNV infection.     

Identification of Class I HLA T Cell Control Epitopes for West Nile Virus

The recent West Nile virus (WNV) outbreak in the United States underscores the importance of understanding human immune responses to this pathogen. Via the presentation of viral peptide ligands at the cell surface, class I HLA mediate the T cell recognition and killing of WNV infected cells. At this time, there are two key unknowns in regards to understanding protective T cell immunity: 1) the number of viral ligands presented by the HLA of infected cells, and 2) the distribution of T cell responses to these available HLA/viral complexes. Here, comparative mass spectroscopy was applied to determine the number of WNV peptides presented by the HLA-A*11:01 of infected cells after which T cell responses to these HLA/WNV complexes were assessed. Six viral peptides derived from capsid, NS3, NS4b, and NS5 were presented. When T cells from infected individuals were tested for reactivity to these six viral ligands, polyfunctional T cells were focused on the GTL9 WNV capsid peptide, ligands from NS3, NS4b, and NS5 were less immunogenic, and two ligands were largely inert, demonstrating that class I HLA reduce the WNV polyprotein to a handful of immune targets and that polyfunctional T cells recognize infections by zeroing in on particular HLA/WNV epitopes. Such dominant HLA/peptide epitopes are poised to drive the development of WNV vaccines that elicit protective T cells as well as providing key antigens for immunoassays that establish correlates of viral immunity.     

利用植物生产西尼罗河病毒抗体

西尼罗河病毒(West Nile vires,WNV)通常是由鸟类携带,经蚊子传播给人类.病毒感染者主要有发烧、肌肉疼痛等类似感冒的症状,其中有小部分人会出现脑炎和脊髓炎.常见于美国的48个州以及北、南美的温带区域.大多数人在感染病毒后会出现头疼等类似感冒的症状,但老人、慢性病患者和免疫力低的人会并发脑炎甚至导致死亡.