Bluetongue virus infection creates light averse Culicoides vectors and serious errors in transmission risk estimates.

BackgroundPathogen manipulation of host behavior can greatly impact vector-borne disease transmission, but almost no attention has been paid to how it affects disease surveillance. Bluetongue virus (BTV), transmitted by Culicoides biting midges, is a serious disease of ruminant livestock that can cause high morbidity and mortality and significant economic losses. Worldwide, the majority of surveillance for Culicoides to assess BTV transmission risk is done using UV-light traps. Here we show that field infection rates of BTV are significantly lower in midge vectors collected using traps baited with UV light versus a host cue (CO2).MethodsWe collected Culicoides sonorensis midges in suction traps baited with CO2, UV-light, or CO2 + UV on three dairies in southern California to assess differences in the resulting estimated infection rates from these collections. Pools of midges were tested for BTV by qRT-PCR, and maximum likelihood estimates of infection rate were calculated by trap. Infection rate estimates were also calculated by trapping site within a dairy. Colonized C. sonorensis were orally infected with BTV, and infection of the structures of the compound eye was examined using structured illumination microscopy.ResultsUV traps failed entirely to detect virus both early and late in the transmission season, and underestimated virus prevalence by as much as 8.5-fold. CO2 + UV traps also had significantly lower infection rates than CO2-only traps, suggesting that light may repel infected vectors. We found very high virus levels in the eyes of infected midges, possibly causing altered vision or light perception. Collecting location also greatly impacts our perception of virus activity.ConclusionsBecause the majority of global vector surveillance for bluetongue uses only light-trapping, transmission risk estimates based on these collections are likely severely understated. Where national surveillance programs exist, alternatives to light-trapping should be considered. More broadly, disseminated infections of many arboviruses include infections in vectors' eyes and nervous tissues, and this may be causing unanticipated behavioral effects. Field demonstrations of pathogen-induced changes in vector behavior are quite rare, but should be studied in more systems to accurately predict vector-borne disease transmission

Microclimatic temperatures increase the potential for vector-borne disease transmission in the Scandinavian climate

We quantified the difference between the meteorological temperature recorded by the Danish Meteorological Institute (DMI) weather stations and the actual microclimatic temperatures at two or three different heights at six potential insect habitats. We then compared the impact of the hourly temperature on the extrinsic incubation period (EIP) of six pathogens. Finally, we developed a regression model, enabling us to predict the microclimatic temperatures of different habitats based on five standard meteorological parameters readily available from any meteorological institution. Microclimatic habitats were on average 3.5–5 °C warmer than the DMI recorded temperatures during midday and 1–3 °C cooler at midnight. The estimated EIP for five of the six microclimatic habitats was shorter than the estimates based on DMI temperatures for all pathogens studied. The microclimatic temperatures also predicted a longer season for virus development compared to DMI temperatures. Based on DMI data of hourly temperature, solar radiation, wind speed, rain and humidity, we were able to predict the microclimatic temperature of different habitats with an R2 of 0.87–0.96. Using only meteorological temperatures for vector-borne disease transmission models may substantially underestimate both the daily potential for virus development and the duration of the potential transmission season

The impact of industrial activities on vector-borne disease transmission.

Industrial activities have produced profound changes in the natural environment, including the mass removal of trees, fragmentation of habitats, and creation of larval mosquito breeding sites, that have allowed the vectors of disease pathogens to thrive. We conducted a review of the literature to assess the impact of industrial activities on vector-borne disease transmission. Our study shows that industrial activities may be coupled with significant changes to human demographics that can potentially increase contact between pathogens, vectors and hosts, and produce a shift of parasites and susceptible populations between low and high disease endemic areas. Indeed, where vector-borne diseases and industrial activities intersect, large numbers of potentially immunologically naïve people may be exposed to infection and lack the knowledge and means to protect themselves from infection. Such areas are typically associated with inadequate access to quality health care, thus allowing industrial development and production sites to become important foci of transmission. The altered local vector ecologies, and the changes in disease dynamics that changes affect, create challenges for under-resourced health care and vector-control systems

Climate, Environmental and Socio-Economic Change: Weighing Up the Balance in Vector-Borne Disease Transmission

Arguably one of the most important effects of climate change is the potential impact on human health. While this is likely to take many forms, the implications for future transmission of vector-borne diseases (VBDs), given their ongoing contribution to global disease burden, are both extremely important and highly uncertain. In part, this is owing not only to data limitations and methodological challenges when integrating climate-driven VBD models and climate change projections, but also, perhaps most crucially, to the multitude of epidemiological, ecological and socio-economic factors that drive VBD transmission, and this complexity has generated considerable debate over the past 10-15 years. In this review, we seek to elucidate current knowledge around this topic, identify key themes and uncertainties, evaluate ongoing challenges and open research questions and, crucially, offer some solutions for the field. Although many of these challenges are ubiquitous across multiple VBDs, more specific issues also arise in different vector-pathogen systems

The Role of Vector Trait Variation in Vector-Borne Disease Dynamics

Many important endemic and emerging diseases are transmitted by vectors that are biting arthropods. The functional traits of vectors can affect pathogen transmission rates directly and also through their effect on vector population dynamics. Increasing empirical evidence shows that vector traits vary significantly across individuals, populations, and environmental conditions, and at time scales relevant to disease transmission dynamics. Here, we review empirical evidence for variation in vector traits and how this trait variation is currently incorporated into mathematical models of vector-borne disease transmission. We argue that mechanistically incorporating trait variation into these models, by explicitly capturing its effects on vector fitness and abundance, can improve the reliability of their predictions in a changing world. We provide a conceptual framework for incorporating trait variation into vector-borne disease transmission models, and highlight key empirical and theoretical challenges. This framework provides a means to conceptualize how traits can be incorporated in vector borne disease systems, and identifies key areas in which trait variation can be explored. Determining when and to what extent it is important to incorporate trait variation into vector borne disease models remains an important, outstanding question

Vector control population health driver diagram

AIM: To decrease the presence of vectors and prevent vector borne disease transmission in a communityGoals:\ue2\u20ac\ua2 Increase efficiency and effectiveness of vector control program services\ue2\u20ac\ua2 Build vector control program infrastructure and capacity\ue2\u20ac\ua2 Reduce environmental factors that lead to vector borne disease\ue2\u20ac\ua2 Improve preparedness for responding to vector borne disease outbreaksThis work was funded through a cooperative agreement with the U.S. Centers for Disease Control and Prevention. The project is managed by the Environmental Health Services Branch, Division of Emergency Health and Services, National Center for Environmental Health.Vector%20Control%20Driver%20Diagram,%201.15.pd

Multi-agent systems in epidemiology: a first step for computational biology in the study of vector-borne disease transmission

<p>Abstract</p> <p>Background</p> <p>Computational biology is often associated with genetic or genomic studies only. However, thanks to the increase of computational resources, computational models are appreciated as useful tools in many other scientific fields. Such modeling systems are particularly relevant for the study of complex systems, like the epidemiology of emerging infectious diseases. So far, mathematical models remain the main tool for the epidemiological and ecological analysis of infectious diseases, with SIR models could be seen as an implicit standard in epidemiology. Unfortunately, these models are based on differential equations and, therefore, can become very rapidly unmanageable due to the too many parameters which need to be taken into consideration. For instance, in the case of zoonotic and vector-borne diseases in wildlife many different potential host species could be involved in the life-cycle of disease transmission, and SIR models might not be the most suitable tool to truly capture the overall disease circulation within that environment. This limitation underlines the necessity to develop a standard spatial model that can cope with the transmission of disease in realistic ecosystems.</p> <p>Results</p> <p>Computational biology may prove to be flexible enough to take into account the natural complexity observed in both natural and man-made ecosystems. In this paper, we propose a new computational model to study the transmission of infectious diseases in a spatially explicit context. We developed a multi-agent system model for vector-borne disease transmission in a realistic spatial environment.</p> <p>Conclusion</p> <p>Here we describe in detail the general behavior of this model that we hope will become a standard reference for the study of vector-borne disease transmission in wildlife. To conclude, we show how this simple model could be easily adapted and modified to be used as a common framework for further research developments in this field.</p