Assessing Dengue Risk Globally Using Non-Markovian Models

Dengue is a vector-borne disease transmitted by Aedes mosquitoes. The worldwide spread of these mosquitoes and the increasing disease burden have emphasized the need for a spatio-temporal risk map capable of assessing dengue outbreak conditions and quantifying the outbreak risk. Given that the life cycle of Aedes mosquitoes is strongly influenced by habitat temperature, numerous studies have utilized temperature-dependent development rates of these mosquitoes to construct virus transmission and outbreak risk models. In this study, we advance existing research by developing a mechanistic model for the mosquito life cycle that accurately accounts for the non-Markovian nature of the process. By fitting the model to data on human dengue cases, we estimate several model parameters, allowing the development of a global spatiotemporal dengue risk map. This risk model employs temperature and precipitation data to assess the environmental suitability for dengue outbreaks in a given area. Furthermore, we demonstrate how to reduce the model to the corresponding differential equations, enabling us to utilize existing methods for analyzing the system and fitting the model to observations. This approach can be further applied to similar non-Markovian processes that are currently described with less accurate Markovian models

Understanding the role of sexual transmission in the spread of ZIKA virus using an individual-based interconnected population model

Citation: Tanver, F., Lee, C., Mcvey, D., & Scoglio, S. (2018). Understanding the role of sexual transmission in the spread of ZIKA virus using an individual-based interconnected population model. Pre-Print, Unpublished Manuscript.Zika virus has affected the world as a long-term threat. Modeling its transmission is important in order to facilitate forecasts and control measures. We propose a novel node-based interconnected population model to simulate both vectored and sexual transmission of Zika virus. Using a sexual contact network, we incorporate heterogeneous mixing in the host population with stochastic transmission for realistic predictions. We also incorporate climatic variations in our model, which affect the mosquito vector population and consequently the arbovirus transmission. We perform extensive simulations to understand the effects of sexual transmission rate and network topology on the spreading of infections. Sexual transmission contributes to the epidemic spread and under certain conditions, can sustain it up to several months without vectors. This can potentially lead to recurrences once the mosquitoes overwinter. We also find that sexual transmission can have a stronger effect when vectored transmission is relatively weaker due to climatic conditions. Our results show that vectored and sexual transmission affect the disease dynamics differently

Understanding the survival of Zika virus in a vector interconnected sexual contact network

Citation: Ferdousi, T., Cohnstaedt, L. W., McVey, D. S., & Scoglio, C. M. (2019). Understanding the survival of Zika virus in a vector interconnected sexual contact network. Scientific Reports, 9(1), 7253. https://doi.org/10.1038/s41598-019-43651-3The recent outbreaks of the insect-vectored Zika virus have demonstrated its potential to be sexually transmitted, which complicates modeling and our understanding of disease dynamics. Autochthonous outbreaks in the US mainland may be a consequence of both modes of transmission, which affect the outbreak size, duration, and virus persistence. We propose a novel individual-based interconnected network model that incorporates both insect-vectored and sexual transmission of this pathogen. This model interconnects a homogeneous mosquito vector population with a heterogeneous human host contact network. The model incorporates the seasonal variation of mosquito abundance and characterizes host dynamics based on age group and gender in order to produce realistic projections. We use a sexual contact network which is generated on the basis of real world sexual behavior data. Our findings suggest that for a high relative transmissibility of asymptomatic hosts, Zika virus shows a high probability of sustaining in the human population for up to 3 months without the presence of mosquito vectors. Zika outbreaks are strongly affected by the large proportion of asymptomatic individuals and their relative transmissibility. The outbreak size is also affected by the time of the year when the pathogen is introduced. Although sexual transmission has a relatively low contribution in determining the epidemic size, it plays a role in sustaining the epidemic and creating potential endemic scenarios

Evaluation of light attraction for the stored-product psocid, \u3ci\u3eLiposcelis bostrychophila\u3c/i\u3e

The psocid, Liposcelis bostrychophila Badonnel (Psocoptera: Liposcelididae), is the most widespread psocid pest of stored products. Because L. bostrychophila has developed resistance to several chemical insecticides, it is important to investigate other integrated pest management (IPM) approaches, and a critical part of IPM programs is an effective monitoring program, Monitoring tools for psocids are limited, and few studies have been conducted on monitoring of psocids, with none on the attraction of lights for psocids. Therefore, we studied the response of L. bostrychophila adults to eight wavelengths of light-emitting diodes (LED) in paired-choice pitfall test. Among the LEDs evaluated, the strongest response by L. bostrychophila adults was to 351 nm UV. When LEDs were tested against brewer’s yeast (the most preferred attractant for L. bostrychophila among more than 20 potential attractants found in previous studies), the 351 nm UV wavelength was the only light that attracted more psocids than brewer’s yeast. These results suggest that the use of LEDs might be useful in psocid-monitoring programs for L. bostrychophila and other psocid species

Trapping of Rift Valley Fever (RVF) vectors using Light Emitting Doide (LED) CDC traps in two arboviral disease hot spots in Kenya

BACKGROUND: Mosquitoes’ response to artificial lights including color has been exploited in trap designs for improved sampling of mosquito vectors. Earlier studies suggest that mosquitoes are attracted to specific wavelengths of light and thus the need to refine techniques to increase mosquito captures following the development of super-bright light-emitting diodes (LEDs) which emit narrow wavelengths of light or very specific colors. Therefore, we investigated if LEDs can be effective substitutes for incandescent lamps used in CDC light traps for mosquito surveillance, and if so, determine the best color for attraction of important Rift Valley Fever (RFV) vectors. METHODS: The efficiency of selected colored LED CDC light traps (red, green, blue, violet, combination of blue-green-red (BGR)) to sample RVF vectors was evaluated relative to incandescent light (as control) in a CDC light trap in two RVF hotspots (Marigat and Ijara districts) in Kenya. In field experiments, traps were baited with dry ice and captures evaluated for Aedes tricholabis, Ae. mcintoshi, Ae. ochraceus, Mansonia uniformis, Mn. africana and Culex pipiens, following Latin square design with days as replicates. Daily mosquito counts per treatment were analyzed using a generalized linear model with Negative Binomial error structure and log link using R. The incidence rate ratios (IRR) that mosquito species chose other treatments instead of the control, were estimated. RESULTS: Seasonal preference of Ae.mcintoshi and Ae. ochraceus at Ijara was evident with a bias towards BGR and blue traps respectively in one trapping period but this pattern waned during another period at same site with significantly low numbers recorded in all colored traps except blue relative to the control. Overall results showed that higher captures of all species were recorded in control traps compared to the other LED traps (IRR<1) although only significantly different from red and violet. CONCLUSION: Based on our trapping design and color, none of the LEDs outcompeted the standard incandescent light. The data however provides preliminary evidence that a preference might exist for some of these mosquito species based on observed differential attraction to these light colors requiring future studies to compare reflected versus transmitted light and the incorporation of colored light of varying intensities.Google.org for financial support and the German Academic Exchange Service (DAAD) for a studentship to DPT.http://www.parasitesandvectors.com/content/5/1/94ab201

A Network-Based Meta-Population Approach to Model Rift Valley Fever Epidemics

Rift Valley fever virus (RVFV) has been expanding its geographical distribution with important implications for both human and animal health. The emergence of Rift Valley fever (RVF) in the Middle East, and its continuing presence in many areas of Africa, has negatively impacted both medical and veterinary infrastructures and human health. Furthermore, worldwide attention should be directed towards the broader infection dynamics of RVFV. We propose a new compartmentalized model of RVF and the related ordinary differential equations to assess disease spread in both time and space; with the latter driven as a function of contact networks. The model is based on weighted contact networks, where nodes of the networks represent geographical regions and the weights represent the level of contact between regional pairings for each set of species. The inclusion of human, animal, and vector movements among regions is new to RVF modeling. The movement of the infected individuals is not only treated as a possibility, but also an actuality that can be incorporated into the model. We have tested, calibrated, and evaluated the model using data from the recent 2010 RVF outbreak in South Africa as a case study; mapping the epidemic spread within and among three South African provinces. An extensive set of simulation results shows the potential of the proposed approach for accurately modeling the RVF spreading process in additional regions of the world. The benefits of the proposed model are twofold: not only can the model differentiate the maximum number of infected individuals among different provinces, but also it can reproduce the different starting times of the outbreak in multiple locations. Finally, the exact value of the reproduction number is numerically computed and upper and lower bounds for the reproduction number are analytically derived in the case of homogeneous populations.Comment: published on Journal of Theoretical biolog

A hierarchical network approach for modeling Rift Valley fever epidemics with applications in North America

Rift Valley fever is a vector-borne zoonotic disease which causes high morbidity and mortality in livestock. In the event Rift Valley fever virus is introduced to the United States or other non-endemic areas, understanding the potential patterns of spread and the areas at risk based on disease vectors and hosts will be vital for developing mitigation strategies. Presented here is a general network-based mathematical model of Rift Valley fever. Given a lack of empirical data on disease vector species and their vector competence, this discrete time epidemic model uses stochastic parameters following several PERT distributions to model the dynamic interactions between hosts and likely North American mosquito vectors in dispersed geographic areas. Spatial effects and climate factors are also addressed in the model. The model is applied to a large directed asymmetric network of 3,621 nodes based on actual farms to examine a hypothetical introduction to some counties of Texas, an important ranching area in the United States of America (U.S.A.). The nodes of the networks represent livestock farms, livestock markets, and feedlots, and the links represent cattle movements and mosquito diffusion between different nodes. Cattle and mosquito (Aedes and Culex) populations are treated with different contact networks to assess virus propagation. Rift Valley fever virus spread is assessed under various initial infection conditions (infected mosquito eggs, adults or cattle). A surprising trend is fewer initial infectious organisms result in a longer delay before a larger and more prolonged outbreak. The delay is likely caused by a lack of herd immunity while the infections expands geographically before becoming an epidemic involving many dispersed farms and animals almost simultaneously

Mosquito-borne diseases in the livestock industry

Mosquito bites may result in increased stress and pain, which reduces livestock fitness, weight gain, and animal welfare. Furthermore, mosquito feeding may also result in pathogen transmission between livestock reservoirs (epizootics) and incidentally humans (zoonotic diseases). Not all mosquito species are disease vectors and not all individuals within a species will become infected post exposure and these important differences between mosquito genera and species are discussed. The epidemiology (hosts, environment, pathogen, and mosquito vectors) of most significant and frequent pathogens are explained, with particular emphasis on the viruses Rift Valley fever, Japanese encephalitis, West Nile, and the equine encephalitis (Western equine, Eastern equine, and Venezuelan equine). Increased globalization and anthropogenic landscape modification has resulted in widespread emergence and re-emergence of pathogens in old and new habitats. Furthermore, viral adaptation and global climate change will place more animal and human populations at risk of these pathogens