Proposal to minimize the difficulty of recording abortion data in sheep

Background: The most frequent viral diseases which can cause abortion in sheep are Blue tongue, Border disease virus, Cache Valley fever and Schmallenberg virus. The diagnosis of abortion, namely virus-induced represents a challenge to field clinicians, since clinical signs presented by the dam are discrete, non-specific and variable (Agerhom et al., 2015). On the other hand, while some foetuses reveal characteristic and visible malformations, others do not reveal any lesions. In face of it, definitive diagnosis requires an appropriate history collection, as well as sending fresh samples, namely abortion material, foetus, placenta and umbilical cord, to a specialty laboratory, to obtain a precise diagnosis. Objectives: The authors suggest a registration method of all mandatory data, in order to further assist the diagnosis of viral diseases at the laboratories, including the most frequent congenital malformations reported in sheep abortions. Methods: Abortion samples of suspected viral origin were collected and all data were registered, in worktables optimized for this purpose. Results: The authors document, using macroscopic figures lesions of malformations in abortions, emphasizing the frequency and the importance of documenting each case, proposing practical and effective worktables to assist the fieldwork. Conclusions: Field clinician’s awareness of the importance of early detection of viral diseases causing abortion outbreaks stimulates a proper data collection for each case of abortion, in order to contribute to a precise diagnosis and posterior consistent epidemiological studies, which may allow diminishing of economic losses.

Estudo de parâmetros clínicos, imunitários e do proteinograma sérico da vacinação contra a doença de Newcastle em gansos-da-China (Anser cygnoides): pesquisa do estado portador do vírus e sua importância epidemiológica

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Immunization with DNA vaccines encoding glycoprotein D or glycoprotein B, alone or in combination, induces protective immunity in animal models of herpes simplex virus-2 disease.

DNA vaccines expressing herpes simplex virus type 2 (HSV-2) full-length glycoprotein D (gD), or a truncated form of HSV-2 glycoprotein B (gB) were evaluated for protective efficacy in two experimental models of HSV-2 infection. Intramuscular (i.m.) injection of mice showed that each construction induced neutralizing serum antibodies and protected the mice from lethal HSV-2 infection. Dose-titration studies showed that low doses (< or = 1 microgram) of either DNA construction induced protective immunity, and that a single immunization with the gD construction was effective. The two DNAs were then tested in a low-dosage combination in guinea pigs. Immune sera from DNA-injected animals had antibodies to both gD and gB, and virus neutralizing activity. When challenged by vaginal infection with HSV-2, the DNA-immunized animals were significantly protected from primary genital disease.

Equal IgG antibody response to pneumococcal vaccination in all stages of human immunodeficiency virus disease.

To evaluate the immunogenicity and safety of a 23-valent pneumococcal vaccine in human immunodeficiency virus (HIV)-seropositive patients, 80 men and 18 women received 1 dose of the vaccine (Pneumo 23; Pasteur Mérieux MSD, Brussels). The total IgG antibody response against all 23 Streptococcus pneumoniae capsular antigens was measured. Antibody levels were expressed in arbitrary units per microliter, referring to a standard curve. Geometric mean titers of the total IgG capsular antibodies on the day of vaccination and 30-45 days later were compared. The ratios of titers after and before vaccination in patients with > 500, 200-500, and < 200 CD4 lymphocytes/microL were 10, 10, and 12.6, respectively. Nonresponse (ratio < 4) occurred in 17% of patients and was unrelated to CD4 cell count. The vaccine was well tolerated; no serious side effects occurred. In 83% of the patients with HIV infection, the total antipneumococcal IgG level was higher after vaccination.

West Nile virus vaccines

West Nile virus (WNV) is a mosquito-borne flavivirus that is emerging as a global pathogen. In the last decade, virulent strains of the virus have been associated with significant outbreaks of human and animal disease in Europe, the Middle East and North America. Efforts to develop human and veterinary vaccines have taken both traditional and novel approaches. A formalin-inactivated whole virus vaccine has been approved for use in horses. DNA vaccines coding for the structural WNV proteins have also been assessed for veterinary use and have been found to be protective in mice, horses and birds. Live attenuated yellow fever WNV chimeric vaccines have also been successful in animals and are currently undergoing human trials. Additional studies have shown that immunisation with a relatively benign Australian variant of WNV, the Kunjin virus, also provides protective immunity against the virulent North American strain. Levels of efficacy and safety, as well as logistical, economic and environmental issues, must all be carefully considered before vaccine candidates are approved and selected for large-scale manufacture and distribution.

RNA Virus Evolution: a Cross-scale, Disease Dynamic Perspective

RNA viruses are an important cause of global morbidity and mortality. The rapid evolutionary rates of RNA virus pathogens, caused by high replication rates and error-prone polymerases, can make the pathogens difficult to control. RNA viruses can undergo immune escape within their hosts and develop resistance to the treatment and vaccines we design to fight them. Understanding the spread and evolution of RNA pathogens is essential for reducing human suffering. In this dissertation, I make use of the rapid evolutionary rate of viral pathogens to answer several questions about how RNA viruses spread and evolve. To address each of the questions, I link mathematical techniques for modeling viral population dynamics with phylogenetic and coalescent techniques for analyzing and modeling viral genetic sequences and evolution. The first project uses multi-scale mechanistic modeling to show that decreases in viral substitution rates over the course of an acute infection, combined with the timing of infectious hosts transmitting new infections to susceptible individuals, can account for discrepancies in viral substitution rates in different host populations. The second project combines coalescent models with within-host mathematical models to identify driving evolutionary forces in chronic hepatitis C virus infection. The third project compares the effects of intrinsic and extrinsic viral transmission rate variation on viral phylogenies.

Ebola virus disease 2014

Ebola virus disease was irst described in 1976 originating from the Ebola River in the Democratic Republic of Congo. Since then, Ebola virus has become an important public health threat in Africa, and now it is of great concern worldwide due to the recent outbreaks (9216 cases with 4555 deaths up to October 20th, 2014), and it is so far the largest and deadliest recorded in history. Five Ebola virus species have been identiied (including Zaire, Sudan, Ivory Coast, Reston, and Bundibugyo Ebola virus), and four of them have proved to be highly pathogenic for both human and non-human primates, causing viral hemorrhagic fever with case fatality rates of up to 90%, for which no approved therapeutics or vaccines are currently available. Ebola virus infections are characterized by immune suppression and a systemic inlammatory response that causes impairment of the vascular, coagulation, and immune systems, leading to multiorgan failure and shock, and thus, in some ways, resembling septic shock. The major affected countries, Sierra Leone, Guinea, Liberia, and Nigeria, have been struggling to contain and to mitigate the outbreak. Gene sequencing of the 2014 virus (2014WA) outbreak has demonstrated 98% homology with the Zaire Ebola virus, with a 49% case fatality ratio across the affected countries. In this review the characteristics of the viruses, pathogenesis, diagnosis, treatment, and the cases reported in health care workers (HCW) are described, as well as a summary of outbreaks of the virus since its discovery, including these last two outbreaks in Africa.

Weather variability, tides, and Barmah Forest Virus Disease in the Gladstone region, Australia

In this study we examined the impact of weather variability and tides on the transmission of Barmah Forest virus (BFV) disease and developed a weather-based forecasting model for BFV disease in the Gladstone region, Australia. We used seasonal autoregressive integrated moving-average (SARIMA) models to determine the contribution of weather variables to BFV transmission after the time-series data of response and explanatory variables were made stationary through seasonal differencing. We obtained data on the monthly counts of BFV cases, weather variables (e.g., mean minimum and maximum temperature, total rainfall, and mean relative humidity), high and low tides, and the population size in the Gladstone region between January 1992 and December 2001 from the Queensland Department of Health, Australian Bureau of Meteorology, Queensland Department of Transport, and Australian Bureau of Statistics, respectively. The SARIMA model shows that the 5-month moving average of minimum temperature (β = 0.15, p-value < 0.001) was statistically significantly and positively associated with BFV disease, whereas high tide in the current month (β = −1.03, p-value = 0.04) was statistically significantly and inversely associated with it. However, no significant association was found for other variables. These results may be applied to forecast the occurrence of BFV disease and to use public health resources in BFV control and prevention.

Estimation on disease burden related to hepatitis B virus infection in Shandong province of China [山东省乙型肝炎病毒感染所致相关疾病的疾病负担研究]

Objective: To comprehensively measure the burden of hepatitis B, liver cirrhosis and liver cancer in Shandong province, using disability-adjusted life years (DALYs) to estimate the disease burden attribute to hepatitis B virus (HBV)infection. Methods: Based on the mortality data of hepatitis B, liver cirrhosis and liver cancer derived from the third National Sampling Retrospective Survey for Causes of Death during 2004 and 2005, the incidence data of hepatitis B and the prevalence and the disability weights of liver cancer gained from the Shandong Cancer Prevalence Sampling Survey in 2007, we calculated the years of life lost (YLLs), years lived with disability (YLDs) and DALYs of three diseases following the procedures developed for the global burden of disease (GBD) study to ensure the comparability. Results: The total burden for hepatitis B, liver cirrhosis and liver cancer were 211 616 (39 377 YLLs and 172 239 YLDs), 16 783 (13 497 YLLs and 3286 YLDs) and 247 795 (240 236 YLLs and 7559 YLDs) DALYs in 2005 respectively, and men were 2.19, 2.36 and 3.16 times as that for women, respectively in Shandong province. The burden for hepatitis B was mainly because of disability (81.39%). However, most burden on liver cirrhosis and liver cancer were due to premature death (80.42% and 96.95%). The burden of each patient related to hepatitis B, liver cirrhosis and liver cancer were 4.8, 13.73 and 11.11 respectively. Conclusion: Hepatitis B, liver cirrhosis and liver cancer caused considerable burden to the people living in Shandong province, indicating that the control of hepatitis B virus infection would bring huge potential benefits.

Spatial and temporal clusters of Barmah Forest virus disease in Queensland, Australia

Objective To identify the spatial and temporal clusters of Barmah Forest virus (BFV) disease in Queensland in Australia, using geographical information systems (GIS) and spatial scan statistic (SaTScan). Methods We obtained BFV disease cases, population and statistical local areas boundary data from Queensland Health and Australian Bureau of Statistics respectively during 1992-2008 for Queensland. A retrospective Poisson-based analysis using SaTScan software and method was conducted in order to identify both purely spatial and space-time BFV disease high-rate clusters. A spatial cluster size of a proportion of the population and a 200km circle radius and varying time windows from 1 month to 12 months were chosen (for the space-time analysis). Results The spatial scan statistic detected a most likely significant purely spatial cluster (including 23 SLAs) and a most likely significant space-time cluster (including 24 SLAs) in approximately the same location. Significant secondary clusters were also identified from both the analyses in several locations. Conclusions This study provides evidence of the existence of statistically significant BFV disease clusters in Queensland, Australia. The study also demonstrated the relevance and applicability of SaTScan in analysing on-going surveillance data to identify clusters to facilitate the development of effective BFV disease prevention and control strategies in Queensland, Australia.

Socio-environmental variability and Barmah Forest virus disease transmission : a review of epidemiological evidence and future prospects

Barmah Forest Virus (BFV) disease is the most rapidly emerging mosquito-borne disease in Australia. BFV transmission depends on factors such as climate, virus, vector and the human population. However, the impact of climatic and social factors on BFV remains to be determined. This paper provided an overview of current research and discusses the future research directions on the BFV transmission. These research findings could be regarded as an impetus towards BFV prevention and control strategies.

Spatio-temporal patterns of Barmah Forest virus disease in Queensland, Australia

Background Barmah Forest virus (BFV) disease is a common and wide-spread mosquito-borne disease in Australia. This study investigated the spatio-temporal patterns of BFV disease in Queensland, Australia using geographical information system (GIS) tools and geostatistical analysis. Methods/Principal Findings We calculated the incidence rates and standardised incidence rates of BFV disease. Moran's I statistic was used to assess the spatial autocorrelation of BFV incidences. Spatial dynamics of BFV disease was examined using semi-variogram analysis. Interpolation techniques were applied to visualise and display the spatial distribution of BFV disease in statistical local areas (SLAs) throughout Queensland. Mapping of BFV disease by SLAs reveals the presence of substantial spatio-temporal variation over time. Statistically significant differences in BFV incidence rates were identified among age groups (χ2 = 7587, df = 7327,p<0.01). There was a significant positive spatial autocorrelation of BFV incidence for all four periods, with the Moran's I statistic ranging from 0.1506 to 0.2901 (p<0.01). Semi-variogram analysis and smoothed maps created from interpolation techniques indicate that the pattern of spatial autocorrelation was not homogeneous across the state. Conclusions/Significance This is the first study to examine spatial and temporal variation in the incidence rates of BFV disease across Queensland using GIS and geostatistics. The BFV transmission varied with age and gender, which may be due to exposure rates or behavioural risk factors. There are differences in the spatio-temporal patterns of BFV disease which may be related to local socio-ecological and environmental factors. These research findings may have implications in the BFV disease control and prevention programs in Queensland.

A prime-boost immunisation regimen using recombinant BCG and Pr55 gag virus-like particle vaccines based on HIV type 1 subtype C successfully elicits Gag-specific responses in baboons

Mycobacterium bovis BCG is considered an attractive live bacterial vaccine vector. In this study, we investigated the immune response of baboons to a primary vaccination with recombinant BCG (rBCG) constructs expressing the gag gene from a South African HIV-1 subtype C isolate, and a boost with HIV-1 subtype C Pr55 gag virus-like particles (Gag VLPs). Using an interferon enzyme-linked immunospot assay, we show that although these rBCG induced only a weak or an undetectable HIV-1 Gag-specific response on their own, they efficiently primed for a Gag VLP boost, which strengthened and broadened the immune responses. These responses were predominantly CD8+ T cell-mediated and recognised similar epitopes as those targeted by humans with early HIV-1 subtype C infection. In addition, a Gag-specific humoral response was elicited. These data support the development of HIV-1 vaccines based on rBCG and Pr55 gag VLPs. © 2009 Elsevier Ltd. All rights reserved.

Spatial and temporal analysis of Barmah Forest virus disease in Queensland, Australia

Barmah Forest virus (BFV) disease is one of the most widespread mosquito-borne diseases in Australia. The number of outbreaks and the incidence rate of BFV in Australia have attracted growing concerns about the spatio-temporal complexity and underlying risk factors of BFV disease. A large number of notifications has been recorded continuously in Queensland since 1992. Yet, little is known about the spatial and temporal characteristics of the disease. I aim to use notification data to better understand the effects of climatic, demographic, socio-economic and ecological risk factors on the spatial epidemiology of BFV disease transmission, develop predictive risk models and forecast future disease risks under climate change scenarios. Computerised data files of daily notifications of BFV disease and climatic variables in Queensland during 1992-2008 were obtained from Queensland Health and Australian Bureau of Meteorology, respectively. Projections on climate data for years 2025, 2050 and 2100 were obtained from Council of Scientific Industrial Research Organisation. Data on socio-economic, demographic and ecological factors were also obtained from relevant government departments as follows: 1) socio-economic and demographic data from Australian Bureau of Statistics; 2) wetlands data from Department of Environment and Resource Management and 3) tidal readings from Queensland Department of Transport and Main roads. Disease notifications were geocoded and spatial and temporal patterns of disease were investigated using geostatistics. Visualisation of BFV disease incidence rates through mapping reveals the presence of substantial spatio-temporal variation at statistical local areas (SLA) over time. Results reveal high incidence rates of BFV disease along coastal areas compared to the whole area of Queensland. A Mantel-Haenszel Chi-square analysis for trend reveals a statistically significant relationship between BFV disease incidence rates and age groups (ƒÓ2 = 7587, p<0.01). Semi-variogram analysis and smoothed maps created from interpolation techniques indicate that the pattern of spatial autocorrelation was not homogeneous across the state. A cluster analysis was used to detect the hot spots/clusters of BFV disease at a SLA level. Most likely spatial and space-time clusters are detected at the same locations across coastal Queensland (p<0.05). The study demonstrates heterogeneity of disease risk at a SLA level and reveals the spatial and temporal clustering of BFV disease in Queensland. Discriminant analysis was employed to establish a link between wetland classes, climate zones and BFV disease. This is because the importance of wetlands in the transmission of BFV disease remains unclear. The multivariable discriminant modelling analyses demonstrate that wetland types of saline 1, riverine and saline tidal influence were the most significant risk factors for BFV disease in all climate and buffer zones, while lacustrine, palustrine, estuarine and saline 2 and saline 3 wetlands were less important. The model accuracies were 76%, 98% and 100% for BFV risk in subtropical, tropical and temperate climate zones, respectively. This study demonstrates that BFV disease risk varied with wetland class and climate zone. The study suggests that wetlands may act as potential breeding habitats for BFV vectors. Multivariable spatial regression models were applied to assess the impact of spatial climatic, socio-economic and tidal factors on the BFV disease in Queensland. Spatial regression models were developed to account for spatial effects. Spatial regression models generated superior estimates over a traditional regression model. In the spatial regression models, BFV disease incidence shows an inverse relationship with minimum temperature, low tide and distance to coast, and positive relationship with rainfall in coastal areas whereas in whole Queensland the disease shows an inverse relationship with minimum temperature and high tide and positive relationship with rainfall. This study determines the most significant spatial risk factors for BFV disease across Queensland. Empirical models were developed to forecast the future risk of BFV disease outbreaks in coastal Queensland using existing climatic, socio-economic and tidal conditions under climate change scenarios. Logistic regression models were developed using BFV disease outbreak data for the existing period (2000-2008). The most parsimonious model had high sensitivity, specificity and accuracy and this model was used to estimate and forecast BFV disease outbreaks for years 2025, 2050 and 2100 under climate change scenarios for Australia. Important contributions arising from this research are that: (i) it is innovative to identify high-risk coastal areas by creating buffers based on grid-centroid and the use of fine-grained spatial units, i.e., mesh blocks; (ii) a spatial regression method was used to account for spatial dependence and heterogeneity of data in the study area; (iii) it determined a range of potential spatial risk factors for BFV disease; and (iv) it predicted the future risk of BFV disease outbreaks under climate change scenarios in Queensland, Australia. In conclusion, the thesis demonstrates that the distribution of BFV disease exhibits a distinct spatial and temporal variation. Such variation is influenced by a range of spatial risk factors including climatic, demographic, socio-economic, ecological and tidal variables. The thesis demonstrates that spatial regression method can be applied to better understand the transmission dynamics of BFV disease and its risk factors. The research findings show that disease notification data can be integrated with multi-factorial risk factor data to develop build-up models and forecast future potential disease risks under climate change scenarios. This thesis may have implications in BFV disease control and prevention programs in Queensland.