Knowledge of Brazilian dentists and students in treating dentine hypersensitivity

Objective: To evaluate knowledge of undergraduates and qualified dentists from a Brazilian Dental School in treating Dentine Hypersensitivity (DH). Methodology: Data obtained from a 22-item questionnaire were analysed and arranged in distribution figures. Results: Of 100 respondents, 66.3% indicated that up to 25% of their patients had DH; 41.7%, that the duration of discomfort was up to eight weeks; 78.4%, that they examined a patient with DH within the last two-four weeks; and 70.4%, that this was done after the patient initiated the conversation on DH. Most of participants responded DH affects patients’ quality of life, and its aetiology was attrition, exposed dentine, occlusal interference, gingival recession or abrasion. The most common ways to diagnose DH were sensitivity history analysis, clinical examination, clinical testing and probing; and conflicting conditions were fractured restoration, bleaching sensitivity, marginal leakage, chipped tooth and periodontal disease. Furthermore, 82.5% and 78.7% of respondents indicated they were confident in diagnosing DH and providing advice to patients, but only 38.8% identified hydrodynamic theory as its underlying mechanism. To evaluate pain from DH they considered self-assessment, dental examination, dietary analysis and thermal assessment; and as recommendations, the use of desensitizing dentifrices, education on toothbrushing, in-office application of desensitizing products, and restorations. Conclusion: There is still confusion concerning the aetiology, the diagnosis and the subsequent management of DH, and both students and qualified dentists need better education

Knowledge and Attitudes on Preventing and Treating Dentin Hypersensitivity and Its Predicting Factors: A Cross-sectional Study with Brazilian Citizens.

OBJECTIVES:  Most dental schools have included dentin hypersensitivity (DH) as part of their taught curriculum to educate undergraduates; however, it is possible that the public still does not recognize its symptoms and the factors that predispose to the onset of this condition. Thus, the aim of this study was to assess the knowledge of a Brazilian population regarding the prevention and treatment of DH and to identify what self-reported factors can serve as predictors of the frequency of DH. MATERIALS AND METHODS:  An online questionnaire investigated the demographic characteristics, oral health self-perception and attitudes, and DH prevention and treatment measures of 226 participants. STATISTICAL ANALYSIS:  Data were analyzed descriptively and by a multiple linear regression with DH frequency score as the dependent variable (α < 0.05). RESULTS:  Total 61.1% of females (n = 138) and 38.9% of males (n = 88) (mean age: 35.1 ± 12.2 years) completed the questionnaire. The sample's mean DH frequency score (minimum 0; maximum 20) was 4.2 and classified as low, with 19.1% using desensitizing products and 22.1% reporting having noncarious cervical lesions (NCCLs). When experiencing DH episodes, 21.2% never and 30.1% rarely scheduled dental appointments. Regression analysis retrieved a significant final model (F [5,220] = 12.047; p < 0.001; R 2 = 0.215). CONCLUSION:  This study identified that 36.7% and 18.6% of the sample were unaware that DH can be both prevented and treated, respectively. Moreover, the presence of NCCLs, frequency of daily toothbrushing, use of desensitizing products, presence of DH modulating factors, and the presence of parafunctional habits symptoms served as predictors of DH frequency

Climate-Based Models for Understanding and Forecasting Dengue Epidemics

Dengue fever is a major public health problem in the tropics and subtropics. Since no vaccine exists, understanding and predicting outbreaks remain of crucial interest. Climate influences the mosquito-vector biology and the viral transmission cycle. Its impact on dengue dynamics is of growing interest. We analyzed the epidemiology of dengue in Noumea (New Caledonia) from 1971 to 2010 and its relationships with local and remote climate conditions using an original approach combining a comparison of epidemic and non epidemic years, bivariate and multivariate analyses. We found that the occurrence of outbreaks in Noumea was strongly influenced by climate during the last forty years. Efficient models were developed to estimate the yearly risk of outbreak as a function of two meteorological variables that were contemporaneous (explicative model) or prior (predictive model) to the outbreak onset. Local threshold values of maximal temperature and relative humidity were identified. Our results provide new insights to understand the link between climate and dengue outbreaks, and have a substantial impact on dengue management in New Caledonia since the health authorities have integrated these models into their decision making process and vector control policies. This raises the possibility to provide similar early warning systems in other countries

Modeling the Dynamic Transmission of Dengue Fever: Investigating Disease Persistence

Dengue is the most rapidly spreading mosquito-borne viral disease in the world and approximately 2.5 billion people live in dengue endemic countries. In Brazil it is mainly transmitted by Aedes aegypti mosquitoes. The wide clinical spectrum ranges from asymptomatic infections or mild illness, to the more severe forms of infection such as dengue hemorrhagic fever or dengue shock syndrome. The spread and dramatic increase in the occurrence of dengue cases in tropical and subtropical countries has been blamed on uncontrolled urbanization, population growth and international traveling. Vaccines are under development and the only current disease control strategy is trying to keep the vector quantity at the lowest possible levels. Mathematical models have been developed to help understand the disease's epidemiology. These models aim not only to predict epidemics but also to expand the capacity of phenomena explanation. We developed a spatially explicit model to simulate the dengue transmission in a densely populated area. The model involves the dynamic interactions between humans and mosquitoes and takes into account human mobility as an important factor of disease spread. We investigated the importance of human population size, human renewal rate, household infestation and ratio of vectors per person in the maintenance of sustained viral circulation