One-year delayed effect of fog on malaria transmission : a time-series analysis in the rain forest area of Mengla County, south-west China

Background: Malaria is a major public health burden in the tropics with the potential to significantly increase in response to climate change. Analyses of data from the recent past can elucidate how short-term variations in weather factors affect malaria transmission. This study explored the impact of climate variability on the transmission of malaria in the tropical rain forest area of Mengla County, south-west China. Methods: Ecological time-series analysis was performed on data collected between 1971 and 1999. Auto-regressive integrated moving average (ARIMA) models were used to evaluate the relationship between weather factors and malaria incidence. Results: At the time scale of months, the predictors for malaria incidence included: minimum temperature, maximum temperature, and fog day frequency. The effect of minimum temperature on malaria incidence was greater in the cool months than in the hot months. The fog day frequency in October had a positive effect on malaria incidence in May of the following year. At the time scale of years, the annual fog day frequency was the only weather predictor of the annual incidence of malaria. Conclusion: Fog day frequency was for the first time found to be a predictor of malaria incidence in a rain forest area. The one-year delayed effect of fog on malaria transmission may involve providing water input and maintaining aquatic breeding sites for mosquitoes in vulnerable times when there is little rainfall in the 6-month dry seasons. These findings should be considered in the prediction of future patterns of malaria for similar tropical rain forest areas worldwide.

Genetic analysis of maize streak virus isolates from Uganda reveals widespread distribution of a recombinant variant

Maize streak virus (MSV) contributes significantly to the problem of extremely low African maize yields. Whilst a diverse range of MSV and MSV-like viruses are endemic in sub-Saharan Africa and neighbouring islands, only a single group of maize-adapted variants - MSV subtypes A1 -A6 - causes severe enough disease in maize to influence yields substantially. In order to assist in designing effective strategies to control MSV in maize, a large survey covering 155 locations was conducted to assess the diversity, distribution and genetic characteristics of the Ugandan MSV-A population. PCR-restriction fragment-length polymorphism analyses of 391 virus isolates identified 49 genetic variants. Sixty-two full-genome sequences were determined, 52 of which were detectably recombinant. All but two recombinants contained predominantly MSV-A1-like sequences. Of the ten distinct recombination events observed, seven involved inter-MSV-A subtype recombination and three involved intra-MSV-A1 recombination. One of the intra-MSV-A1 recombinants, designated MSV-A1 UgIII, accounted for >60% of all MSV infections sampled throughout Uganda. Although recombination may be an important factor in the emergence of novel geminivirus variants, it is demonstrated that its characteristics in MSV are quite different from those observed in related African cassava-infecting geminivirus species. © 2007 SGM.

Comparative analysis of panicum streak virus and maize streak virus diversity, recombination patterns and phylogeography

Background: Panicum streak virus (PanSV; Family Geminiviridae; Genus Mastrevirus) is a close relative of Maize streak virus (MSV), the most serious viral threat to maize production in Africa. PanSV and MSV have the same leafhopper vector species, largely overlapping natural host ranges and similar geographical distributions across Africa and its associated Indian Ocean Islands. Unlike MSV, however, PanSV has no known economic relevance. Results: Here we report on 16 new PanSV full genome sequences sampled throughout Africa and use these together with others in public databases to reveal that PanSV and MSV populations in general share very similar patterns of genetic exchange and geographically structured diversity. A potentially important difference between the species, however, is that the movement of MSV strains throughout Africa is apparently less constrained than that of PanSV strains. Interestingly the MSV-A strain which causes maize streak disease is apparently the most mobile of all the PanSV and MSV strains investigated. Conclusion: We therefore hypothesize that the generally increased mobility of MSV relative to other closely related species such as PanSV, may have been an important evolutionary step in the eventual emergence of MSV-A as a serious agricultural pathogen. The GenBank accession numbers for the sequences reported in this paper are GQ415386-GQ415401. © 2009 Varsani et al; licensee BioMed Central Ltd.

Factor analysis of the Self Report Version of the Strengths and Difficulties Questionnaire in a sample of children with intellectual disability

The rate of emotional and behavioral disturbance in children with intellectual disability (ID) is up to four times higher than that of their typically developing peers. It is important to identify these difficulties in children with ID as early as possible to prevent the chronic co-morbidity of ID and psychopathology. Children with ID have traditionally been assessed via proxy reporting, but appropriate and psychometrically rigorous instruments are needed so that children can report on their own emotions and behaviors. In this study, the factor structure of the self-report version of the Strengths and Difficulties Questionnaire (SDQ) was examined in a population of 128 children with ID (mean age = 12 years). Exploratory and Confirmatory Factor Analysis showed a three factor model (comprising Positive Relationships, Negative Behavior and Emotional Competence) to be a better measure than the original five factor SDQ model in this population.

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.

Efficacy of oral or intrauterine device-delivered progestin in patients with complex endometrial hyperplasia with atypia or early endometrial adenocarcinoma : a meta-analysis and systematic review of the literature

Objectives: To investigate the efficacy of progestin treatment to achieve pathological complete response (pCR) in patients with complex atypical endometrial hyperplasia (CAH) or early endometrial adenocarcinoma (EC). Methods: A systematic search identified 3245 potentially relevant citations. Studies containing less than ten eligible CAH or EC patients in either oral or intrauterine treatment arm were excluded. Only information from patients receiving six or more months of treatment and not receiving other treatments was included. Weighted proportions of patients achieving pCR were calculated using R software. Results: Twelve studies met the selection criteria. Eleven studies reported treatment of patients with oral (219 patients, 117 with CAH, 102 with grade 1 Stage I EC) and one reported treatment of patients with intrauterine progestin (11 patients with grade 1 Stage IEC). Overall, 74% (95% confidence interval [CI] 65-81%) of patients with CAH and 72% (95% CI 62-80%) of patients with grade 1 Stage I EC achieved a pCR to oral progestin. Disease progression while on oral treatment was reported for 6/219 (2.7%), and relapse after initial complete response for 32/159 (20.1%) patients. The weighted mean pCR rate of patients with grade 1 Stage I EC treated with intrauterine progestin from one prospective pilot study and an unpublished retrospective case series from the Queensland Centre of Gynaecologic Oncology (QCGC) was 68% (95% CI 45- 86%). Conclusions: There is a lack of high quality evidence for the efficacy of progestin in CAH or EC. The available evidence however suggests that treatment with oral or intrauterine progestin is similarly effective. The risk of progression during treatment is small but longer follow-up is required. Evidence from prospective controlled clinical trials is warranted to establish how the efficacy of progestin for the treatment of CAH and EC can be improved further.