The effects of weather and climate change on dengue

There is much uncertainty about the future impact of climate change on vector-borne diseases. Such uncertainty reflects the difficulties in modelling the complex interactions between disease, climatic and socioeconomic determinants. We used a comprehensive panel dataset from Mexico covering 23 years of province-specific dengue reports across nine climatic regions to estimate the impact of weather on dengue, accounting for the effects of non-climatic factors

Ears of the Armadillo: Global Health Research and Neglected Diseases in Texas

Neglected tropical diseases (NTDs) have\ud been recently identified as significant public\ud health problems in Texas and elsewhere in\ud the American South. A one-day forum on the\ud landscape of research and development and\ud the hidden burden of NTDs in Texas\ud explored the next steps to coordinate advocacy,\ud public health, and research into a\ud cogent health policy framework for the\ud American NTDs. It also highlighted how\ud U.S.-funded global health research can serve\ud to combat these health disparities in the\ud United States, in addition to benefiting\ud communities abroad

Waterborne Outbreak of Gastroenteritis: Effects on Sick Leaves and Cost of Lost Workdays

We examined the acute and cumulative effects of this incidence on sick leaves among public sector employees residing in the clean and contaminated areas, and the additional costs of lost workdays due to the incidence.Daily information on sick leaves of 1789 Finnish Public Sector Study participants was obtained from employers' registers. Global Positioning System-coordinates were used for linking participants to the clean and contaminated areas. Prevalence ratios (PR) for weekly sickness absences were calculated using binomial regression analysis. Calculations for the costs were based on prior studies.Among those living in the contaminated areas, the prevalence of participants on sick leave was 3.54 (95% confidence interval (CI) 2.97–4.22) times higher on the week following the incidence compared to the reference period. Those living and working in the clean area were basically not affected, the corresponding PR for sick leaves was 1.12, 95% CI 0.73–1.73. No cumulative effects on sick leaves were observed among the exposed. The estimated additional costs of lost workdays due to the incidence were 1.8–2.1 million euros.The prevalence of sickness absences among public sector employees residing in affected areas increased shortly after drinking water distribution system was contaminated, but no long-term effects were observed. The estimated costs of lost workdays were remarkable, thus, the cost-benefits of better monitoring systems for the water distribution systems should be evaluated

Spatio-temporal modelling of climate-sensitive disease risk: Towards an early warning system for dengue in Brazil

NOTICE: this is the author’s version of a work that was accepted for publication in Computers and Geosciences. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Computers and Geosciences, Vol. 37, Issue 3, (2011), DOI: 10.1016/j.cageo.2010.01.008This paper considers the potential for using seasonal climate forecasts in developing an early warning system for dengue fever epidemics in Brazil. In the first instance, a generalised linear model (GLM) is used to select climate and other covariates which are both readily available and prove significant in prediction of confirmed monthly dengue cases based on data collected across the whole of Brazil for the period January 2001 to December 2008 at the microregion level (typically consisting of one large city and several smaller municipalities). The covariates explored include temperature and precipitation data on a 2.5°×2.5°2.5°×2.5° longitude–latitude grid with time lags relevant to dengue transmission, an El Niño Southern Oscillation index and other relevant socio-economic and environmental variables. A negative binomial model formulation is adopted in this model selection to allow for extra-Poisson variation (overdispersion) in the observed dengue counts caused by unknown/unobserved confounding factors and possible correlations in these effects in both time and space. Subsequently, the selected global model is refined in the context of the South East region of Brazil, where dengue predominates, by reverting to a Poisson framework and explicitly modelling the overdispersion through a combination of unstructured and spatio-temporal structured random effects. The resulting spatio-temporal hierarchical model (or GLMM—generalised linear mixed model) is implemented via a Bayesian framework using Markov Chain Monte Carlo (MCMC). Dengue predictions are found to be enhanced both spatially and temporally when using the GLMM and the Bayesian framework allows posterior predictive distributions for dengue cases to be derived, which can be useful for developing a dengue alert system. Using this model, we conclude that seasonal climate forecasts could have potential value in helping to predict dengue incidence months in advance of an epidemic in South East Brazil

Time series analysis of dengue fever and weather in Guangzhou, China

<p>Abstract</p> <p>Background</p> <p>Monitoring and predicting dengue incidence facilitates early public health responses to minimize morbidity and mortality. Weather variables are potential predictors of dengue incidence. This study explored the impact of weather variability on the transmission of dengue fever in the subtropical city of Guangzhou, China.</p> <p>Methods</p> <p>Time series Poisson regression analysis was performed using data on monthly weather variables and monthly notified cases of dengue fever in Guangzhou, China for the period of 2001-2006. Estimates of the Poisson model parameters was implemented using the Generalized Estimating Equation (GEE) approach; the quasi-likelihood based information criterion (QICu) was used to select the most parsimonious model.</p> <p>Results</p> <p>Two best fitting models, with the smallest QICu values, are selected to characterize the relationship between monthly dengue incidence and weather variables. Minimum temperature and wind velocity are significant predictors of dengue incidence. Further inclusion of minimum humidity in the model provides a better fit.</p> <p>Conclusion</p> <p>Minimum temperature and minimum humidity, at a lag of one month, are positively associated with dengue incidence in the subtropical city of Guangzhou, China. Wind velocity is inversely associated with dengue incidence of the same month. These findings should be considered in the prediction of future patterns of dengue transmission.</p

A New Approach to Monitoring Dengue Activity

Discusses informal surveillance tools for monitoring dengue activity, such as ProMED, GPHIN HealthMap and BioCaster

Abscisic Acid Insensitive 4 transcription factor is an important player in the response of Arabidopsis thaliana to two-spotted spider mite (Tetranychus urticae) feeding.

Plants growing in constantly changeable environmental conditions are compelled to evolve regulatory mechanisms to cope with biotic and abiotic stresses. Effective defence to invaders is largely connected with phytohormone regulation, resulting in the production of numerous defensive proteins and specialized metabolites. In our work, we elucidated the role of the Abscisic Acid Insensitive 4 (ABI4) transcription factor in the plant response to the two-spotted spider mite (TSSM). This polyphagous mite is one of the most destructive herbivores, which sucks mesophyll cells of numerous crop and wild plants. Compared to the wild-type (Col-0) Arabidopsis thaliana plants, the abi4 mutant demonstrated increased susceptibility to TSSM, reflected as enhanced female fecundity and greater frequency of mite leaf damage after trypan blue staining. Because ABI4 is regarded as an important player in the plastid-to-nucleus retrograde signalling process, we investigated the plastid envelope membrane dynamics using stroma-associated fluorescent marker. Our results indicated a clear increase in the number of stroma-filled tubular structures deriving from the plastid membrane (stromules) in the close proximity of the site of mite leaf damage, highlighting the importance of chloroplast-derived signals in the response to TSSM feeding activity

Dengue Fever Seroprevalence and Risk Factors, Texas–Mexico Border, 2004

High seroprevalence of dengue was found on both sides of the border