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Background: Culex pipiens is the major vector of West Nile virus in Europe, and is causing frequent outbreaks throughout the southern part of the continent. Proper empirical modelling of the population dynamics of this species can help in understanding West Nile virus epidemiology, optimizing vector surveillance and mosquito control efforts. But modelling results may differ from place to place. In this study we look at which type of models and weather variables can be consistently used across different locations. Methods: Weekly mosquito trap collections from eight functional units located in France, Greece, Italy and Serbia for several years were combined. Additionally, rainfall, relative humidity and temperature were recorded. Correlations between lagged weather conditions and Cx. pipiens dynamics were analysed. Also seasonal autoregressive integrated moving-average (SARIMA) models were fitted to describe the temporal dynamics of Cx. pipiens and to check whether the weather variables could improve these models. Results: Correlations were strongest between mean temperatures at short time lags, followed by relative humidity, most likely due to collinearity. Precipitation alone had weak correlations and inconsistent patterns across sites. SARIMA models could also make reasonable predictions, especially when longer time series of Cx. pipiens observations are available. Conclusions: Average temperature was a consistently good predictor across sites. When only short time series (~ < 4 years) of observations are available, average temperature can therefore be used to model Cx. pipiens dynamics. When longer time series (~ > 4 years) are available, SARIMAs can provide better statistical descriptions of Cx. pipiens dynamics, without the need for further weather variables. This suggests that density dependence is also an important determinant of Cx. pipiens dynamics. [ABSTRACT FROM AUTHOR]

West Nile virus (WNV) represents a serious burden to human and animal health because of its capacity to cause unforeseen and large epidemics. Until 2004, only lineage 1 and 3 WNV strains had been found in Europe. Lineage 2 strains were initially isolated in 2004 (Hungary) and in 2008 (Austria) and for the first time caused a major WNV epidemic in 2010 in Greece with 262 clinical human cases and 35 fatalities. Since then, WNV lineage 2 outbreaks have been reported in several European countries including Italy, Serbia and Greece. Understanding the interaction of ecological factors that affect WNV transmission is crucial for preventing or decreasing the impact of future epidemics. The synchronous co-occurrence of competent mosquito vectors, virus, bird reservoir hosts, and susceptible humans is necessary for the initiation and propagation of an epidemic. Weather is the key abiotic factor influencing the life-cycles of the mosquito vector, the virus, the reservoir hosts and the interactions between them. The purpose of this paper is to review and compare mosquito population dynamics, and weather conditions, in three ecologically different contexts (urban/semi-urban, rural/agricultural, natural) across four European countries (Italy, France, Serbia, Greece) with a history of WNV outbreaks. Local control strategies will be described as well. Improving our understanding of WNV ecology is a prerequisite step for appraising and optimizing vector control strategies in Europe with the ultimate goal to minimize the probability of WNV infection. [ABSTRACT FROM AUTHOR]

Background: For nearly two decades now, various studies have reported detecting the Epstein-Barr virus (EBV) in breast cancer (BC) cases. Yet the results are unconvincing, and their interpretation has remained a matter of debate. We have now presented prospective data on the effect of EBV infection combined with survival in patients enrolled in a prospective study. Methods: We assessed 85 BC patients over an 87-month follow-up period to determine whether EBV infection, evaluated by qPCR in both peripheral blood mononuclear cells (PBMCs) and tumor biopsies, interacted with host cell components that modulate the evolution parameters of BC. We also examined the EBV replicating form by the titration of serum anti-ZEBRA antibodies. Immunological studies were performed on a series of 35 patients randomly selected from the second half of the survey, involving IFN-γ and TNF-α intracellular immunostaining tests performed via flow cytometry analysis in peripheral NK and T cells, in parallel with EBV signature. The effect of the EBV load in the blood or tumor tissue on patient survival was analyzed using univariate and multivariate analyses, combined with an analysis of covariance. Results: Our study represents the first ever report of the impact of EBV on the clinical outcome of BC patients, regardless of tumor histology or treatment regimen. No correlation was found between: (i) EBV detection in tumor or PBMCs and tumor characteristics; (ii) EBV and other prognostic factors. Notably, patients exhibiting anti-ZEBRA antibodies at high titers experienced poorer overall survival (p = 0.002). Those who recovered from their disease were found to have a measurable EBV DNA load, together with a high frequency of IFN-γ and TNF-α producing PBMCs (p = 0.04), which indicates the existence of a Th1-type polarized immune response in both the tumor and its surrounding tissue. Conclusions: The replicative form of EBV, as investigated using anti-ZEBRA titers, correlated with poorer outcomes, whereas the latent form of the virus that was measured and quantified using the EBV tumor DNA conferred a survival advantage to BC patients, which could occur through the activation of non-specific anti-tumoral immune responses. [ABSTRACT FROM AUTHOR]

Background: Tuberculosis (TB), an infectious disease caused by the Mycobacterium tuberculosis is endemic in Madagascar. The capital, Antananarivo is the most seriously affected area. TB had a non-random spatial distribution in this setting, with clustering in the poorer areas. The aim of this study was to explore this pattern further by a Bayesian approach, and to measure the associations between the spatial variation of TB risk and national control program indicators for all neighbourhoods. Methods: Combination of a Bayesian approach and a generalized linear mixed model (GLMM) was developed to produce smooth risk maps of TB and to model relationships between TB new cases and national TB control program indicators. The TB new cases were collected from records of the 16 Tuberculosis Diagnostic and Treatment Centres (DTC) of the city from 2004 to 2006. And five TB indicators were considered in the analysis: number of cases undergoing retreatment, number of patients with treatment failure and those suffering relapse after the completion of treatment, number of households with more than one case, number of patients lost to follow-up, and proximity to a DTC. Results: In Antananarivo, 43.23% of the neighbourhoods had a standardized incidence ratio (SIR) above 1, of which 19.28% with a TB risk significantly higher than the average. Identified high TB risk areas were clustered and the distribution of TB was found to be associated mainly with the number of patients lost to follow-up (SIR: 1.10, CI 95%: 1.02-1.19) and the number of households with more than one case (SIR: 1.13, CI 95%: 1.03-1.24). Conclusion: The spatial pattern of TB in Antananarivo and the contribution of national control program indicators to this pattern highlight the importance of the data recorded in the TB registry and the use of spatial approaches for assessing the epidemiological situation for TB. Including these variables into the model increases the reproducibility, as these data are already available for individual DTCs. These findings may also be useful for guiding decisions related to disease control strategies. [ABSTRACT FROM AUTHOR]