Biologically Informed Individual-Based Network Model for Rift Valley Fever in the US and Evaluation of Mitigation Strategies

Citation: Scoglio, C. M., Bosca, C., Riad, M. H., Sahneh, F. D., Britch, S. C., Cohnstaedt, L. W., & Linthicum, K. J. (2016). Biologically Informed Individual-Based Network Model for Rift Valley Fever in the US and Evaluation of Mitigation Strategies. Plos One, 11(9), 26. doi:10.1371/journal.pone.0162759Rift Valley fever (RVF) is a zoonotic disease endemic in sub-Saharan Africa with periodic outbreaks in human and animal populations. Mosquitoes are the primary disease vectors; however, Rift Valley fever virus (RVFV) can also spread by direct contact with infected tissues. The transmission cycle is complex, involving humans, livestock, and multiple species of mosquitoes. The epidemiology of RVFV in endemic areas is strongly affected by climatic conditions and environmental variables. In this research, we adapt and use a network-based modeling framework to simulate the transmission of RVFV among hypothetical cattle operations in Kansas, US. Our model considers geo-located livestock populations at the individual level while incorporating the role of mosquito populations and the environment at a coarse resolution. Extensive simulations show the flexibility of our modeling framework when applied to specific scenarios to quantitatively evaluate the efficacy of mosquito control and livestock movement regulations in reducing the extent and intensity of RVF outbreaks in the United States

Role of Culex and Anopheles mosquito species as potential vectors of rift valley fever virus in Sudan outbreak, 2007

<p>Abstract</p> <p>Background</p> <p>Rift Valley fever (RVF) is an acute febrile arthropod-borne viral disease of man and animals caused by a member of the <it>Phlebovirus </it>genus, one of the five genera in the family <it>Bunyaviridae</it>. RVF virus (RVFV) is transmitted between animals and human by mosquitoes, particularly those belonging to the <it>Culex, Anopheles </it>and <it>Aedes </it>genera.</p> <p>Methods</p> <p>Experiments were designed during RVF outbreak, 2007 in Sudan to provide an answer about many raised questions about the estimated role of vector in RVFV epidemiology. During this study, adult and immature mosquito species were collected from Khartoum and White Nile states, identified and species abundance was calculated. All samples were frozen individually for further virus detection. Total RNA was extracted from individual insects and RVF virus was detected from <it>Culex, Anopheles </it>and <it>Aedes </it>species using RT-PCR. In addition, data were collected about human cases up to November 24^th, 2007 to asses the situation of the disease in affected states. Furthermore, a historical background of the RVF outbreaks was discussed in relation to global climatic anomalies and incriminated vector species.</p> <p>Results</p> <p>A total of 978 mosquitoes, belonging to 3 genera and 7 species, were collected during Sudan outbreak, 2007. <it>Anopheles gambiae arabiensis </it>was the most frequent species (80.7%) in White Nile state. Meanwhile, <it>Cx. pipiens </it>complex was the most abundant species (91.2%) in Khartoum state. RT-PCR was used and successfully amplified 551 bp within the M segment of the tripartite negative-sense single stranded RNA genome of RVFV. The virus was detected in female, male and larval stages of <it>Culex </it>and <it>Anopheles </it>species. The most affected human age interval was 15-29 years old followed by ≥ 45 years old, 30-44 years old, and then 5-14 years old. Regarding to the profession, housewives followed by farmers, students, shepherd, workers and the free were more vulnerable to the infection. Furthermore, connection between human and entomological studies results in important human case-vulnerability relatedness findings.</p> <p>Conclusion</p> <p>Model performance, integrated with epidemiologic and environmental surveillance systems should be assessed systematically for RVF and other mosquito-borne diseases using historical epidemiologic and satellite monitoring data. Case management related interventions; health education and vector control efforts are extremely effective in preparedness for viral hemorrhagic fever and other seasonal outbreaks.</p

Species composition, larval habitats, seasonal occurrence and distribution of potential malaria vectors and associated species of Anopheles (Diptera: Culicidae) from the Republic of Korea

<p>Abstract</p> <p>Background</p> <p>Larval mosquito habitats of potential malaria vectors and related species of <it>Anopheles </it>from three provinces (Gyeonggi, Gyeongsangbuk, Chungcheongbuk Provinces) of the Republic of Korea were surveyed in 2007. This study aimed to determine the species composition, seasonal occurrence and distributions of <it>Anopheles </it>mosquitoes. Satellite derived normalized difference vegetation index data (NDVI) was also used to study the seasonal abundance patterns of <it>Anopheles </it>mosquitoes.</p> <p>Methods</p> <p>Mosquito larvae from various habitats were collected using a standard larval dipper or a white plastic larval tray, placed in plastic bags, and were preserved in 100% ethyl alcohol for species identification by PCR and DNA sequencing. The habitats in the monthly larval surveys included artificial containers, ground depressions, irrigation ditches, drainage ditches, ground pools, ponds, rice paddies, stream margins, inlets and pools, swamps, and uncultivated fields. All field-collected specimens were identified to species, and relationships among habitats and locations based on species composition were determined using cluster statistical analysis.</p> <p>Results</p> <p>In about 10,000 specimens collected, eight species of <it>Anopheles </it>belonging to three groups were identified: Hyrcanus Group - <it>Anopheles sinensis</it>, <it>Anopheles kleini</it>, <it>Anopheles belenrae</it>, <it>Anopheles pullus</it>, <it>Anopheles lesteri</it>, <it>Anopheles sineroides</it>; Barbirostris Group - <it>Anopheles koreicus</it>; and Lindesayi Group - <it>Anopheles lindesayi japonicus</it>. Only <it>An. sinensis </it>was collected from all habitats groups, while <it>An. kleini, An. pullus </it>and <it>An. sineroides </it>were sampled from all, except artificial containers. The highest number of <it>Anopheles </it>larvae was found in the rice paddies (34.8%), followed by irrigation ditches (23.4%), ponds (17.0%), and stream margins, inlets and pools (12.0%). <it>Anopheles sinensis </it>was the dominant species, followed by <it>An. kleini, An. pullus </it>and <it>An. sineroides</it>. The monthly abundance data of the <it>Anopheles </it>species from three locations (Munsan, Jinbo and Hayang) were compared against NDVI and NDVI anomalies.</p> <p>Conclusion</p> <p>The species composition of <it>Anopheles </it>larvae varied in different habitats at various locations. <it>Anopheles </it>populations fluctuated with the seasonal dynamics of vegetation for 2007. Multi-year data of mosquito collections are required to provide a better characterization of the abundance of these insects from year to year, which can potentially provide predictive capability of their population density based on remotely sensed ecological measurements.</p

Integration of decision support systems to improve decision support performance

Decision support system (DSS) is a well-established research and development area. Traditional isolated, stand-alone DSS has been recently facing new challenges. In order to improve the performance of DSS to meet the challenges, research has been actively carried out to develop integrated decision support systems (IDSS). This paper reviews the current research efforts with regard to the development of IDSS. The focus of the paper is on the integration aspect for IDSS through multiple perspectives, and the technologies that support this integration. More than 100 papers and software systems are discussed. Current research efforts and the development status of IDSS are explained, compared and classified. In addition, future trends and challenges in integration are outlined. The paper concludes that by addressing integration, better support will be provided to decision makers, with the expectation of both better decisions and improved decision making processes

Investigation of the Climatic and Environmental Context of Hendra Virus Spillover Events 1994–2010

Hendra virus is a recently emerged bat-borne zoonotic agent with high lethality in horses and humans in Australia. This is a rare disease and the determinants of bat to horse transmission, including the factors that bring these hosts together at critical times, are poorly understood. In this cross-disciplinary study climatic and vegetation primary productivity variables are compared for the dispersed and heterogenic 1994–2010 outbreak sites. The significant occurrence of spillover events within the dry season (p =  0.013, 95% CI (0.57–0.98)) suggests seasonal forcing of transmission across species, or seasonal forcing of virus excretion by the reservoir host. We explore the evidence for both. Preliminary investigations of the spatial determinants of Hendra disease locations are also presented. We find that postal areas in the Australian state of Queensland in which pteropid fruit bat (flying fox) roosts occur are approximately forty times more likely (OR = 40.5, (95% CI (5.16, 317.52)) to be the location of Hendra spillover events. This appears to be independent of density of horses at these locations. We consider issues of scale of host resource use, land use change and limitations of existing data that challenge analysis and limit further conclusive outcomes. This investigation of a broad range of potential climatic and environmental influences provides a good base for future investigations. Further understanding of cross-species Hendra virus transmission requires better understanding of flying fox resource use in the urban-rural landscape

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

Pitfalls in the diagnosis of acoustic neuroma

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/71894/1/j.1365-2273.1984.tb01490.x.pd