Exploring vector-borne infection ecology in multi-host communities: A case study of West Nile virus

A stochastic multi-host model for West Nile virus transmission

When initially introduced into a susceptible population, a disease may die out or result in a major outbreak. We present a Continuous-Time Markov Chain model for enzootic WNV transmission between two avian host species and a single vector, and use multitype branching process theory to determine the probability of disease extinction based upon the type of infected individual initially introducing the disease into the population - an exposed vector, infectious vector, or infectious host of either species. We explore how the likelihood of disease extinction depends on the ability of each host species to transmit WNV, vector biting rates on host species, and the relative abundance of host species, as well as vector abundance. Theoretical predictions are compared to the outcome of stochastic simulations. We find the community composition of hosts and vectors, as well as the means of disease introduction, can greatly affect the probability of disease extinction.

Countering Zoonotic Diseases: Current Scenario and Advances in Diagnostics, Monitoring, Prophylaxis and Therapeutic Strategies

Human life and health have interacted reciprocally with the surrounding environment and animal fauna for ages. This relationship is evident in developing nations, where human life depends more on the animal population for food, transportation, clothing, draft power, and fuel sources, among others. This inseparable link is a potent source of public health issues, especially in outbreaks of zoonotic diseases transmitted from animals to humans. Zoonotic diseases are referred to as diseases that are naturally transmitted between vertebrate animals and humans. Among the globally emerging diseases in the last decade, 75% are of animal origin, most of which are life-threatening. Since most of them are caused by potent new pathogens capable of long-distance transmission, the impact is widespread and has serious public health and economic consequences. Various other factors also contribute to the transmission, spread, and outbreak of zoonotic diseases, among which industrialization-led globalization followed by ecological disruption and climate change play a critical role. In this regard, all the possible strategies, including advances in rapid and confirmatory disease diagnosis and surveillance/monitoring, immunization/vaccination, therapeutic approaches, appropriate prevention and control measures to be adapted, and awareness programs, need to be adopted collaboratively among different health sectors in medical, veterinary, and concerned departments to implement the necessary interventions for the effective restriction, minimization, and timely control of zoonotic threats. The present review focuses on the current scenario of zoonotic diseases and their counteracting approaches to safeguard their health impact on humans.

Mechanistic models for West Nile virus transmission: a systematic review of features, aims and parametrization

Mathematical models within the Ross-Macdonald framework increasingly play a role in our understanding of vector-borne disease dynamics and as tools for assessing scenarios to respond to emerging threats. These threats are typically characterized by a high degree of heterogeneity, introducing a range of possible complexities in models and challenges to maintain the link with empirical evidence. We systematically identified and analysed a total of 77 published papers presenting compartmental West Nile virus (WNV) models that use parameter values derived from empirical studies. Using a set of 15 criteria, we measured the dissimilarity compared with the Ross-Macdonald framework. We also retrieved the purpose and type of models and traced the empirical sources of their parameters. Our review highlights the increasing refinements in WNV models. Models for prediction included the highest number of refinements. We found uneven distributions of refinements and of evidence for parameter values. We identified several challenges in parametrizing such increasingly complex models. For parameters common to most models, we also synthesize the empirical evidence for their values and ranges. The study highlights the potential to improve the quality of WNV models and their applicability for policy by establishing closer collaboration between mathematical modelling and empirical work.

Ecological Niche and Positive Clusters of Two West Nile Virus Vectors in Ontario, Canada

West Nile virus (WNV) is a mosquito-borne pathogen associated with uncommon but severe neurological complications in humans, especially among the elderly and immune-compromised. In Northeastern North America, the Culex pipiens/restuans complex and Aedes vexans are the two principal vector mosquito species/species groups of WNV. Using a 10-year surveillance dataset of WNV vector captures at 118 sites across an area of 40,000 km2 in Eastern Ontario, Canada, the ecological niches of Cx. pipiens/restuans and Aedes vexans were modeled by random forest analysis. Spatiotemporal clusters of WNV-positive mosquito pools were identified using Kulldorf's spatial scan statistic. The study region encompasses land cover types and climate representative of highly populated Southeastern Canada. We found highest vector habitat suitability in the eastern half of the study area, where temperatures are generally warmer (variable importance > 0.40) and residential and agricultural cropland cover is more prominent (variable importance > 0.25). We found spatiotemporal clusters of high WNV infection rates around the city of Ottawa in both mosquito vector species. These results support the previous literature in the same region and elsewhere suggesting areas surrounding highly populated areas are also high-risk areas for vector-borne zoonoses such as the WNV.

Exploring the influence of competition on arbovirus invasion risk in communities

Arbovirus outbreaks in communities are affected by how vectors, hosts and non-competent species interact. In this study, we investigate how ecological interactions between species and epidemiological processes influence the invasion potential of a vector-borne disease. We use an eco-epidemiological model to explore the basic reproduction number R0 for a range of interaction strengths in key processes, using West Nile virus infection to parameterize the model. We focus our analysis on intra and interspecific competition between vectors and between hosts, as well as competition with non-competent species. We show that such ecological competition has non-linear effects on R0 and can greatly impact invasion risk. The presence of multiple competing vector species results in lower values for R0 while host competition leads to the highest values of risk of disease invasion. These effects can be understood in terms of how the competitive pressures influence the vector-to-host ratio, which has a positive relationship with R0. We also show numerical examples of how vector feeding preferences become more relevant in high competition conditions between hosts. Under certain conditions, non-competent hosts, which can lead to a dilution effect for the pathogen, can have an amplification effect if they compete strongly with the competent hosts, hence facilitating pathogen invasion in the community.

Host competence, interspecific competition and vector preference interact to determine the vector-borne infection ecology

Understanding how ecological interactions affect vector-borne disease dynamics is crucial in the context of rapid biodiversity loss and increased emerging vector-borne diseases. Although there have been many studies on the impact of interspecific competition and host competence on disease dynamics, few of them have addressed the case of a vector-borne disease. Using a simple compartment model with two competing host species and one vector, we investigated the combined effects of vector preference, host competence, and interspecific competition on disease risk in a vector-borne system. Our research demonstrated that disease transmission dynamics in multi-host communities are more complex than anticipated. Vector preference and differences in host competence shifted the direction of the effect of competition on community disease risk, yet interspecific competition quantitatively but not qualitatively changed the effect of vector preference on disease risk. Our work also identified the conditions of the dilution effect and amplification effect in frequency-dependent transmission mode, and we discovered that adding vector preference and interspecific competition into a simple two-host-one-vector model altered the outcomes of how increasing species richness affects disease risk. Our work explains some of the variation in outcomes in previous empirical and theoretical studies on the dilution effect.

The dynamics of disease mediated invasions by hosts with immune reproductive tradeoff

The modern world involves both increasingly frequent introduction of novel invasive animals into new habitat ranges and novel epidemic-causing pathogens into new host populations. Both of these phenomena have been well studied. Less well explored, however, is how the success of species invasions may themselves be affected by the pathogens they bring with them. In this paper, we construct a simple, modified Susceptible-Infected-Recovered model for a vector-borne pathogen affecting two annually reproducing hosts. We consider an invasion scenario in which a susceptible native host species is invaded by a disease-resistant species carrying a vector-borne infection. We assume the presence of abundant, but previously disease-free, competent vectors. We find that the success of invasion is critically sensitive to the infectivity of the pathogen. The more the pathogen is able to spread, the more fit the invasive host is in competition with the more vulnerable native species; the pathogen acts as a ‘wingman pathogen,’ enhancing the probability of invader establishment. While not surprising, we provide a quantitative predictive framework for the long-term outcomes from these important coupled dynamics in a world in which compound invasions of hosts and pathogens are increasingly likely.

Vector Surveillance, Host Species Richness, and Demographic Factors as West Nile Disease Risk Indicators

West Nile virus (WNV) is the most common arthropod-borne virus (arbovirus) in the United States (US) and is the leading cause of viral encephalitis in the country. The virus has affected tens of thousands of US persons total since its 1999 North America introduction, with thousands of new infections reported annually. Approximately 1% of humans infected with WNV acquire neuroinvasive West Nile Disease (WND) with severe encephalitis and risk of death. Research describing WNV ecology is needed to improve public health surveillance, monitoring, and risk assessment. We applied Bayesian joint-spatiotemporal modeling to assess the association of vector surveillance data, host species richness, and a variety of other environmental and socioeconomic disease risk factors with neuroinvasive WND throughout the conterminous US. Our research revealed that an aging human population was the strongest disease indicator, but climatic and vector-host biotic interactions were also significant in determining risk of neuroinvasive WND. Our analysis also identified a geographic region of disproportionately high neuroinvasive WND disease risk that parallels the Continental Divide, and extends southward from the US-Canada border in the states of Montana, North Dakota, and Wisconsin to the US-Mexico border in western Texas. Our results aid in unraveling complex WNV ecology and can be applied to prioritize disease surveillance locations and risk assessment.

A quantitative comparison of West Nile virus incidence from 2013 to 2018 in Emilia-Romagna, Italy

Background

West Nile virus (WNV) transmission was much greater in 2018 than in previous seasons in Europe. Focusing on Emilia-Romagna region (northern Italy), we analyzed detailed entomological and epidemiological data collected in 2013–2018 to quantitatively assess environmental drivers of transmission and explore hypotheses to better understand why the 2018 epidemiological season was substantially different than the previous seasons. In particular, in 2018 WNV was detected at least two weeks before the observed circulation in 2013–2017 and in a larger number of mosquito pools. Transmission resulted in 100 neuroinvasive human cases in the region, more than the total number of cases recorded between 2013 and 2017.

Methodology

We used temperature-driven mathematical models calibrated through a Bayesian approach to simulate mosquito population dynamics and WNV infection rates in the avian population. We then estimated the human transmission risk as the probability, for a person living in the study area, of being bitten by an infectious mosquito in a given week. Finally, we translated such risk into reported WNV human infections.

Principal findings

The estimated prevalence of WNV in the mosquito and avian populations were significantly higher in 2018 with respect to 2013–2017 seasons, especially in the eastern part of the region. Furthermore, peak avian prevalence was estimated to have occurred earlier, corresponding to a steeper decline towards the end of summer. The high mosquito prevalence resulted in a much greater predicted risk for human transmission in 2018, which was estimated to be up to eight times higher than previous seasons. We hypothesized, on the basis of our modelling results, that such greater WNV circulation might be partially explained by exceptionally high spring temperatures, which have likely helped to amplify WNV transmission at the beginning of the 2018 season.

West Nile virus (WNV) is one of the most recent emerging mosquito-borne diseases in Europe and North America. While most human infections are asymptomatic, about 1% of them can result in severe neurological diseases which might be fatal. WNV transmission was unusually greater in 2018 than in previous years in many European countries, resulting in a large number of human infections. Focusing on Emilia-Romagna region (Italy), we developed an epidemiological model informed by entomological data; through that we found that exceptionally high spring temperatures might have contributed at amplifying WNV transmission at the beginning of the season, causing greater WNV prevalence in mosquito and avian populations during the summer, which resulted in a higher estimated risk for human transmission. Thus, weather anomalies at the beginning of the mosquito breeding season, which are likely to become more common under the projected scenarios of climate change, might act as an early warning signal for public health authorities, enabling them to design efficient surveillance and prevention strategies.

Predicting West Nile virus transmission in North American bird communities using phylogenetic mixed effects models and eBird citizen science data

BACKGROUND

West Nile virus (WNV) is a mosquito-transmitted disease of birds that has caused bird population declines and can spill over into human populations. Previous research has identified bird species that infect a large fraction of the total pool of infected mosquitoes and correlate with human infection risk; however, these analyses cover small spatial regions and cannot be used to predict transmission in bird communities in which these species are rare or absent. Here we present a mechanistic model for WNV transmission that predicts WNV spread (R0) in any bird community in North America by scaling up from the physiological responses of individual birds to transmission at the level of the community. We predict unmeasured bird species' responses to infection using phylogenetic imputation, based on these species' phylogenetic relationships with bird species with measured responses.

RESULTS

We focused our analysis on Texas, USA, because it is among the states with the highest total incidence of WNV in humans and is well sampled by birders in the eBird database. Spatio-temporal patterns: WNV transmission is primarily driven by temperature variation across time and space, and secondarily by bird community composition. In Texas, we predicted WNV R0 to be highest in the spring and fall when temperatures maximize the product of mosquito transmission and survival probabilities. In the most favorable months for WNV transmission (April, May, September and October), we predicted R0 to be highest in the "Piney Woods" and "Oak Woods & Prairies" ecoregions of Texas, and lowest in the "High Plains" and "South Texas Brush County" ecoregions. Dilution effect: More abundant bird species are more competent hosts for WNV, and predicted WNV R0 decreases with increasing species richness. Keystone species: We predicted that northern cardinals (Cardinalis cardinalis) are the most important hosts for amplifying WNV and that mourning doves (Zenaida macroura) are the most important sinks of infection across Texas.

CONCLUSIONS

Despite some data limitations, we demonstrate the power of phylogenetic imputation in predicting disease transmission in heterogeneous host communities. Our mechanistic modeling framework shows promise both for assisting future analyses on transmission and spillover in heterogeneous multispecies pathogen systems and for improving model transparency by clarifying assumptions, choices and shortcomings in complex ecological analyses.

Parasites and wildlife in a changing world: The vector-host- pathogen interaction as a learning case

In the Anthropocene context, changes in climate, land use and biodiversity are considered among the most important anthropogenic factors affecting parasites-host interaction and wildlife zoonotic diseases emergence. Transmission of vector borne pathogens are particularly sensitive to these changes due to the complexity of their cycle, where the transmission of a microparasite depends on the interaction between its vector, usually a macroparasite, and its reservoir host, in many cases represented by a wildlife vertebrate. The scope of this paper focuses on the effect of some major, fast-occurring anthropogenic changes on the vectorial capacity for tick and mosquito borne pathogens. Specifically, we review and present the latest advances regarding two emerging vector-borne viruses in Europe: Tick-borne encephalitis virus (TBEV) and West Nile virus (WNV). In both cases, variation in vector to host ratio is critical in determining the intensity of pathogen transmission and consequently infection hazard for humans. Forecasting vector-borne disease hazard under the global change scenarios is particularly challenging, requiring long term studies based on a multidisciplinary approach in a One-Health framework.

Linking Bird and Mosquito Data to Assess Spatiotemporal West Nile Virus Risk in Humans

West Nile virus (WNV; family Flaviviridae) causes a disease in humans that may develop into a deadly neuroinvasive disease. In North America, several peridomestic bird species can develop sufficient viremia to infect blood-feeding mosquito vectors without succumbing to the virus. Mosquito species from the genus Culex, Aedes and Ochlerotatus display variable host preferences, ranging between birds and mammals, including humans, and may bridge transmission among avian hosts and contribute to spill-over transmission to humans. In this study, we aimed to test the effect of density of three mosquito species and two avian species on WNV mosquito infection rates and investigated the link between spatiotemporal clusters of high mosquito infection rates and clusters of human WNV cases. We based our study around the city of Ottawa, Canada, between the year 2007 and 2014. We found a large effect size of density of two mosquito species on mosquito infection rates. We also found spatiotemporal overlap between a cluster of high mosquito infection rates and a cluster of human WNV cases. Our study is innovative because it suggests a role of avian and mosquito densities on mosquito infection rates and, in turn, on hotspots of human WNV cases.

Mathematical analysis of a model for zoonotic visceral leishmaniasis

Zoonotic visceral leishmaniasis (ZVL), caused by the protozoan parasite Leishmania infantum and transmitted to humans and reservoir hosts by female sandflies, is endemic in many parts of the world (notably in Africa, Asia and the Mediterranean). This study presents a new mathematical model for assessing the transmission dynamics of ZVL in human and non-human animal reservoir populations. The model undergoes the usual phenomenon of backward bifurcation exhibited by similar vector-borne disease transmission models. In the absence of such phenomenon (which is shown to arise due to the disease-induced mortality in the host populations), the nontrivial disease-free equilibrium of the model is shown to be globally-asymptotically stable when the associated reproduction number of the model is less than unity. Using case and demographic data relevant to ZVL dynamics in Arac̣atuba municipality of Brazil, it is shown, for the default case when systemic insecticide-based drugs are not used to treat infected reservoir hosts, that the associated reproduction number of the model ( ℛ 0 ) ranges from 0.3 to 1.4, with a mean of ℛ 0 = 0.85 . Furthermore, when the effect of such drug treatment is explicitly incorporated in the model (i.e., accounting for the additional larval and sandfly mortality, following feeding on the treated reservoirs), the range of ℛ 0 decreases to ℛ 0 ∈ [ 0.1 , 0.6 ] , with a mean of ℛ 0 = 0.35 (this significantly increases the prospect of the effective control or elimination of the disease). Thus, ZVL transmission models (in communities where such treatment strategy is implemented) that do not explicitly incorporate the effect of such treatment may be over-estimating the disease burden (as measured in terms of ℛ 0 ) in the community. It is shown that ℛ 0 is more sensitive to increases in sandfly lifespan than that of the animal reservoir (so, a strategy that focuses on reducing sandflies, rather than the animal reservoir (e.g., via culling), may be more effective in reducing ZVL burden in the community). Further sensitivity analysis of the model ranks the sandfly removal rate (by natural death or by feeding from insecticide-treated reservoir hosts), the biting rate of sandflies on the reservoir hosts and the progression rate of exposed reservoirs to active ZVL as the three parameters with the most effect on the disease dynamics or burden (as measured in terms of the reproduction number ℛ 0 ). Hence, this study identifies the key parameters that play a key role on the disease dynamics, and thereby contributing in the design of effective control strategies (that target the identified parameters).