A cultura do tomateiro (Solanum lycopersicum L.) é importante mundialmente devido ao alto consumo de seus frutos. Nos últimos anos surgiram nesta cultura no Brasil alguns vírus emergentes com altas taxas de disseminação, como begomovírus e crinivírus, transmitidos pela Bemisia tabaci biótipo B, que podem causar danos à produção do tomateiro. A espécie de begomovírus atualmente mais encontrada no Brasil, em plantios de tomateiro, é o Tomato severe rugose virus (ToSRV). De 2002 a 2004, pesquisadores relataram incidências desse vírus em mais da metade das amostras com sintomas de geminiviroses coletadas em vários estados brasileiros e sua presença continua sendo verificada frequentemente. No ano de 2006, um crinivírus, o Tomato chlorosis virus (ToCV), foi relatado no Brasil, infectando plantas de tomate no Estado de São Paulo e atualmente encontra-se presente em diveros estados brasileiros. Os objetivos desse trabalho foram: determinar os períodos mínimos de acesso à aquisição e à inoculação do ToSRV e do ToCV pela B. tabaci biótipo B; identificar o período de retenção do ToSRV no inseto e a interação do ToSRV e do ToCV na aquisição e na transmissão por esse aleirodídeo. Também foi avaliada a eficiência do inseticida cloridrato de cartape no controle da disseminação primária e secundária do ToSRV pela B. tabaci biótipo B em tomateiros em gaiolas em casa de vegetação. Finalmente avaliou-se a eficiência do aleirodídeo Trialeurodes vaporariorum na transmissão de um isolado brasileiro do ToCV. Os períodos mínimos de acesso à aquisição e à inoculação de ambos os vírus pela B. tabaci biótipo B foram de cinco minutos. O tempo de retenção do ToSRV em B. tabaci biótipo B foi de 25 dias. A eficiência de um único adulto de B. tabaci na transmissão simultânea do ToSRV e do ToCV para tomateiros foi de 44,7%, similar àquela da transmissão isolada do ToRSV (47,4%) e do ToCV (44,7%). A eficiência de T. vaporariorum na transmissão do ToCV foi inferior à da B. tabaci biótipo B. Usando 40 insetos por vaso com duas plantas as eficiências de transmissão foram 57,7% e 100%, respectivamente. O inseticida cloridrato de cartape reduziu a infecção secundária do ToSRV pela B. tabaci biótipo B, mas não foi eficiente para reduzir a infecção primária em tomateiros. / Tomato (Solanum lycopersicum) is one of the leading vegetables grown and consumed in Brazil and in the world, after potato. The importance of tomato is related to its high consumption worldwide and also its nutritive value. Presently the most important virus diseases responsible for yield losses on tomato crops in Brazil are those caused by begomovirus and crinivirus, both transmitted by Bemisia tabaci biotype B. At the moment the prevalent species of begomovirus is Tomato severe rugose virus (ToSRV). From 2002 to 2004, researchers reported incidence of this virus in more than half of the symptomatic tomato samples collected in several Brazilian states. In 2006, a crinivirus, Tomato chlorosis virus (ToCV), was reported for the first time in Brazil, infecting tomato plants in the State of São Paulo and at present the virus occurs in several Brazilian states. The objectives of this study were to determine the minimum acquisition and inoculation access periods of ToSRV and ToCV by B. tabaci biotype B; identify the retention period of ToSRV in the insect; and the interaction of ToSRV and ToCV on the transmission by this aleyrodidae. It was also evaluated the effectiveness of the insecticide cartap hydrochloride in controlling the primary and secondary spread of ToSRV by B. tabaci biotype B on tomato plants in a greenhouse. Finally, it was evaluated the efficiency of Trialeurodes vaporariorum in the transmission of a Brazilian isolate of ToCV. The minimum acquisition and inoculation access periods for both viruses by B. tabaci biotype B were five minutes. The maximum retention time of ToSRV in B. tabaci biotype B was 25 days. The efficiency of a single adult of B. tabaci to simultaneously transmit ToSRV and ToCV to tomato plants was 44.7%, similar to the transmission of ToRSV (47.4%), and ToCV (44.7%) separately. T. vaporariorum was less efficient than B. tabaci on the transmission of ToCV. Using 40 insects per pot with two plants, transmission efficiencies were 57.7% and 100%, respectively. The insecticide cartap hydrochloride reduced secondary infection of ToSRV transmitted by B. tabaci biotype B, but was not effective in reducing the primary infection in tomato.

Comparatively, HIV like most viruses is very minute, unadorned organism which cannot reproduce unaided. It remains the most deadly disease which has ever hit the planet since the last three decades. The spread of HIV has been very explosive and mercilessly on human population. It has tainted over 60 million people, with almost half of the human population suffering from AIDS related illnesses and death finally. Recent theoretical and computational breakthroughs in delay differential equations declare that, delay differential equations are proficient in yielding rich and plausible dynamics with reasonable parametric estimates. This paper seeks to unveil the niche of delay differential equation in harmonizing low HIV viral haul and thereby articulating the adopted model, to delve into structured treatment interruptions. Therefore, an ordinary differential equation is schemed to consist of three components such as untainted CD4+ T-cells, tainted CD4+ T-cells (HIV) and CTL. A discrete time delay is ushered to the formulated model in order to account for vital components, such as intracellular delay and HIV latency which were missing in previous works, but have been advocated for future research. It was divested that when the reproductive number was less than unity, the disease free equilibrium of the model was asymptotically stable. Hence the adopted model with or without the delay component articulates less production of virions, as per the decline rate. Therefore CD4+ T-cells in the blood remains constant at 𝛿1/𝛿3, hence declining the virions level in the blood. As per the adopted model, the best STI practice is intimated for compliance. / Mathematical Sciences / Ph.D. (Applied Mathematics)

During the 2013/16 Ebola virus disease outbreak in West Africa, numerous restrictions were placed on the movement and public gathering of local people, regardless of if the area had active Ebola cases or not. Specifically, the district of Koinadugu, Sierra Leone, preemptively enforced movement regulations before there were any cases within the district. This research demonstrates that ongoing regulations on movement and public gathering affected the livelihoods of those involved in agricultural markets in the short-term, while the outbreak was active, and in the long-term. The forthcoming thesis details the ways in which the Ebola outbreak international and national response affected locals involved in agricultural value chains in Koinadugu, Sierra Leone.

No description available.

Hepatitis C virus (HCV) is one of the leading causes of hepatocellular carcinoma worldwide. HCV-neutralizing antibody AP33 recognizes a linear, highly conserved epitope on the viral entry protein E2, disrupting the interaction with the cellular receptor CD81 that leads to viral entry. AP33-related anti-idiotypes (Ab₂s) have the potential to carry the internal image of the antigen E2, eliciting the production of AP33-like antibodies in humans. This study reports the mid-resolution structure of the Fab fragment of anti-idiotype A164.3 and the high-resolution structure of the Fab fragment of AP33 in complex with the Fv fragment of anti-idiotype B2.1A. Analysis of the structures and comparison with the previously published structure of AP33 in complex with a peptide corresponding to the E2 epitope, suggests that while A164.3 does not mimic the antigen E2, B2.1A is characterized by high surface complementarity with AP33 and functional antigen mimicry. Thus, B2.1A can be classified as an Ab₂-β, a subgroup of anti-idiotypes carrying the internal image of the antigen. Preliminary binding studies show that AP33 binds B2.1A with nanomolar affinity, supporting the role of B2.1A as an idiotypic vaccine candidate. Zaire ebola virus causes severe, often lethal hemorrhagic fever in humans. Ebola virus polymerase cofactor VP35 is a multifunctional protein involved in, among other functions, dsRNA binding and inhibition of the host's interferon pathways. VP35 contains an N-terminal oligomerization domain and a C-terminal dsRNA-binding domain (RBD). Preliminary results on the oligomerization domain of VP35 suggest that this region contains a coiled-coil motif, as previously reported. In order to validate a recently-discovered dsRNA end-capping pocket as a drug target, the structure of VP35 RBD I278A mutant was solved at high resolution, showing that even a small perturbation in the binding pocket can cause dramatic binding impairment due to loss of contacts with dsRNA.

The incidence of many arboviral diseases is largely associated with social and environmental conditions. Ross River virus (RRV) is the most prevalent arboviral disease in Australia. It has long been recognised that the transmission pattern of RRV is sensitive to socio-ecological factors including climate variation, population movement, mosquito-density and vegetation types. This study aimed to assess the relationships between socio-environmental variability and the transmission of RRV using spatio-temporal analytic methods. Computerised data files of daily RRV disease cases and daily climatic variables in Brisbane, Queensland during 1985-2001 were obtained from the Queensland Department of Health and the Australian Bureau of Meteorology, respectively. Available information on other socio-ecological factors was also collected from relevant government agencies as follows: 1) socio-demographic data from the Australia Bureau of Statistics; 2) information on vegetation (littoral wetlands, ephemeral wetlands, open freshwater, riparian vegetation, melaleuca open forests, wet eucalypt, open forests and other bushland) from Brisbane City Council; 3) tidal activities from the Queensland Department of Transport; and 4) mosquito-density from Brisbane City Council. Principal components analysis (PCA) was used as an exploratory technique for discovering spatial and temporal pattern of RRV distribution. The PCA results show that the first principal component accounted for approximately 57% of the information, which contained the four seasonal rates and loaded highest and positively for autumn. K-means cluster analysis indicates that the seasonality of RRV is characterised by three groups with high, medium and low incidence of disease, and it suggests that there are at least three different disease ecologies. The variation in spatio-temporal patterns of RRV indicates a complex ecology that is unlikely to be explained by a single dominant transmission route across these three groupings. Therefore, there is need to explore socio-economic and environmental determinants of RRV disease at the statistical local area (SLA) level. Spatial distribution analysis and multiple negative binomial regression models were employed to identify the socio-economic and environmental determinants of RRV disease at both the city and local (ie, SLA) levels. The results show that RRV activity was primarily concentrated in the northeast, northwest and southeast areas in Brisbane. The negative binomial regression models reveal that RRV incidence for the whole of the Brisbane area was significantly associated with Southern Oscillation Index (SOI) at a lag of 3 months (Relative Risk (RR): 1.12; 95% confidence interval (CI): 1.06 - 1.17), the proportion of people with lower levels of education (RR: 1.02; 95% CI: 1.01 - 1.03), the proportion of labour workers (RR: 0.97; 95% CI: 0.95 - 1.00) and vegetation density (RR: 1.02; 95% CI: 1.00 - 1.04). However, RRV incidence for high risk areas (ie, SLAs with higher incidence of RRV) was significantly associated with mosquito density (RR: 1.01; 95% CI: 1.00 - 1.01), SOI at a lag of 3 months (RR: 1.48; 95% CI: 1.23 - 1.78), human population density (RR: 3.77; 95% CI: 1.35 - 10.51), the proportion of indigenous population (RR: 0.56; 95% CI: 0.37 - 0.87) and the proportion of overseas visitors (RR: 0.57; 95% CI: 0.35 - 0.92). It is acknowledged that some of these risk factors, while statistically significant, are small in magnitude. However, given the high incidence of RRV, they may still be important in practice. The results of this study suggest that the spatial pattern of RRV disease in Brisbane is determined by a combination of ecological, socio-economic and environmental factors. The possibility of developing an epidemic forecasting system for RRV disease was explored using the multivariate Seasonal Auto-regressive Integrated Moving Average (SARIMA) technique. The results of this study suggest that climatic variability, particularly precipitation, may have played a significant role in the transmission of RRV disease in Brisbane. This finding cannot entirely be explained by confounding factors such as other socio-ecological conditions because they have been unlikely to change dramatically on a monthly time scale in this city over the past two decades. SARIMA models show that monthly precipitation at a lag 2 months (=0.004,p=0.031) was statistically significantly associated with RRV disease. It suggests that there may be 50 more cases a year for an increase of 100 mm precipitation on average in Brisbane. The predictive values in the model were generally consistent with actual values (root-mean-square error (RMSE): 1.96). Therefore, this model may have applications as a decision support tool in disease control and risk-management planning programs in Brisbane. The Polynomial distributed lag (PDL) time series regression models were performed to examine the associations between rainfall, mosquito density and the occurrence of RRV after adjusting for season and auto-correlation. The PDL model was used because rainfall and mosquito density can affect not merely RRV occurring in the same month, but in several subsequent months. The rationale for the use of the PDL technique is that it increases the precision of the estimates. We developed an epidemic forecasting model to predict incidence of RRV disease. The results show that 95% and 85% of the variation in the RRV disease was accounted for by the mosquito density and rainfall, respectively. The predictive values in the model were generally consistent with actual values (RMSE: 1.25). The model diagnosis reveals that the residuals were randomly distributed with no significant auto-correlation. The results of this study suggest that PDL models may be better than SARIMA models (R-square increased and RMSE decreased). The findings of this study may facilitate the development of early warning systems for the control and prevention of this widespread disease. Further analyses were conducted using classification trees to identify major mosquito species of Ross River virus (RRV) transmission and explore the threshold of mosquito density for RRV disease in Brisbane, Australia. The results show that Ochlerotatus vigilax (RR: 1.028; 95% CI: 1.001 - 1.057) and Culex annulirostris (RR: 1.013, 95% CI: 1.003 - 1.023) were significantly associated with RRV disease cycles at a lag of 1 month. The presence of RRV was associated with average monthly mosquito density of 72 Ochlerotatus vigilax and 52 Culex annulirostris per light trap. These results may also have applications as a decision support tool in disease control and risk management planning programs. As RRV has significant impact on population health, industry, and tourism, it is important to develop an epidemic forecast system for this disease. The results of this study show the disease surveillance data can be integrated with social, biological and environmental databases. These data can provide additional input into the development of epidemic forecasting models. These attempts may have significant implications in environmental health decision-making and practices, and may help health authorities determine public health priorities more wisely and use resources more effectively and efficiently.

Some Epidemic models with fractional derivatives were proved to be well-defined, well-posed and more accurate [34, 51, 116], compared to models with the conventional derivative. An Ebola epidemic model with non-linear transmission is fully analyzed. The model is expressed with the conventional time derivative with a new parameter included, which happens to be fractional (that derivative is called the 􀀀derivative). We proved that the model is well-de ned and well-posed. Moreover, conditions for boundedness and dissipativity of the trajectories are established. Exploiting the generalized Routh-Hurwitz Criteria, existence and stability analysis of equilibrium points for the Ebola model are performed to show that they are strongly dependent on the non-linear transmission. In particular, conditions for existence and stability of a unique endemic equilibrium to the Ebola system are given. Numerical simulations are provided for particular expressions of the non-linear transmission, with model's parameters taking di erent values. The resulting simulations are in concordance with the usual threshold behavior. The results obtained here may be signi cant for the ght and prevention against Ebola haemorrhagic fever that has so far exterminated hundreds of families and is still a ecting many people in West-Africa and other parts of the world. The full comprehension and handling of the phenomenon of shattering, sometime happening during the process of polymer chain degradation [129, 142], remains unsolved when using the traditional evolution equations describing the degradation. This traditional model has been proved to be very hard to handle as it involves evolution of two intertwined quantities. Moreover, the explicit form of its solution is, in general, impossible to obtain. We explore the possibility of generalizing evolution equation modeling the polymer chain degradation and analyze the model with the conventional time derivative with a new parameter. We consider the general case where the breakup rate depends on the size of the chain breaking up. In the process, the alternative version of Sumudu integral transform is used to provide an explicit form of the general solution representing the evolution of polymer sizes distribution. In particular, we show that this evolution exhibits existence of complex periodic properties due to the presence of cosine and sine functions governing the solutions. Numerical simulations are performed for some particular cases and prove that the system describing the polymer chain degradation contains complex and simple harmonic poles whose e ects are given by these functions or a combination of them. This result may be crucial in the ongoing research to better handle and explain the phenomenon of shattering. Lastly, it has become a conjecture that power series like Mittag-Le er functions and their variants naturally govern solutions to most of generalized fractional evolution models such as kinetic, di usion or relaxation equations. The question is to say whether or not this is always true! Whence, three generalized evolution equations with an additional fractional parameter are solved analytically with conventional techniques. These are processes related to stationary state system, relaxation and di usion. In the analysis, we exploit the Sumudu transform to show that investigation on the stationary state system leads to results of invariability. However, unlike other models, the generalized di usion and relaxation models are proven not to be governed by Mittag-Le er functions or any of their variants, but rather by a parameterized exponential function, new in the literature, more accurate and easier to handle. Graphical representations are performed and also show how that parameter, called ; can be used to control the stationarity of such generalized models. / Mathematical Sciences / Ph. D. (Applied Mathematics)

Master of Science / Department of Electrical and Computer Engineering / Faryad Darabi Sahneh / Recent experience of Ebola outbreak of 2014 highlighted the importance of immediate response to impede Ebola transmission at its very early stage. To this aim, efficient and effective allocation of limited resources is crucial. Among standard interventions is the practice of following up with physical contacts of individuals diagnosed with Ebola virus disease -- known as contact tracing. In an effort to objectively understand the effect of possible contact tracing protocols, we explicitly develop a model of Ebola transmission incorporating contact tracing. Our modeling framework has several features to suit early–stage Ebola transmission: 1) the network model is patient–centric because when number of infected cases are small only the myopic networks of infected individuals matter and the rest of possible social contacts are irrelevant, 2) the Ebola disease model is individual–based and stochastic because at the early stages of spread, random fluctuations are significant and must be captured appropriately, 3) the contact tracing model is parameterizable to analyze the impact of critical aspects of contact tracing protocols. Notably, we propose an activity driven network approach to contact tracing, and develop a Monte-Carlo method to compute the basic reproductive number of the disease spread in different scenarios. Exhaustive simulation experiments suggest that while contact tracing is important in stopping the Ebola spread, it does not need to be done too urgently. This result is due to rather long incubation period of Ebola disease infection. However, immediate hospitalization of infected cases is crucial and requires the most attention and resource allocation. Moreover, to investigate the impact of mitigation strategies in the 2014 Ebola outbreak, we consider reported data in Guinea, one the three West Africa countries that had experienced the Ebola virus disease outbreak. We formulate a multivariate sequential Monte Carlo filter that utilizes mechanistic models for Ebola virus propagation to simultaneously estimate the disease progression states and the model parameters according to reported incidence data streams. This method has the advantage of performing the inference online as the new data becomes available and estimating the evolution of the basic reproductive ratio R₀(t) throughout the Ebola outbreak. Our analysis identifies a peak in the basic reproductive ratio close to the time of Ebola cases reports in Europe and the USA.