ASSESS THE EFFECTIVENESS OF STRUCTURED TEACHING PROGRAMME ON KNOWLEDGE REGARDING DENGUE FEVER AMONG HIGH SCHOOL CHILDREN.

Disease is any harmful deviation from the normal structural or functional state of an organism, generally associated with certain signs and symptoms. One of the most important tropical infectious disease is dengue. Dengue fever is commonly known as ‘Break Bone Fever’. It is an infectious disease caused by a virus Arbovirus from the genus Flavivirus. It is transmitted by mosquito, Aedes aegypti closely associated with human habitation. Dengue fever is caused by four antigenically related but distinct dengue virus transmitted by infected mosquitoes.

Dengue Outbreak Prediction using Regression Model in Chittoor District, Andhra Pradesh, India

Dengue fever is one of the tropical diseases, also called as break bone fever. It is caused by transmission of dengue virus through bite from Aedes mosquitoes. Dengue fever is previously predicted regionally using gradient descent algorithm. Annually 50 million to 528 million people get affected by dengue fever and 10,000 to 20,000 die. Reason behind this paper is to predict outbreak of dengue fever regionally by using features such as temperature, rainfall, humidity because breeding of Aedes mosquitoes is related to these features. Bagging and boosting techniques are used with gradient descent to predict more accurately the occurrence of dengue in a region. Data is collected from regional government weather office. Data is pre-processed like filling missing values and normalizing values. Feature selection processes like dimensionality reduction is done on pre-processed dataset. Gradient descent is applied with bagging and boosting. Accuracy is calculated by plotting graphs and by calculating Mean Standard Deviation (MSD) and Mean Absolute Error (MAE). By prediction of dengue fever before its occurrence in a region, makes it easy to vaccinate people in that region and dengue can be controlled and stopped from becoming an outbreak.

Dengue (Break bone fever): An Emerging Disease in Nepal

No abstract available.J-GMC-N | Volume 11 | Issue 01 | January-June 2018

Dengue: The break-bone fever outbreak in Kerala, India

Recently a shocking intensification of dengue cases has also been seen in India in 2017. The common serotype of Dengue Asian genotype of DENV-1 was detected in South India in 2012.

Model of Break-Bone Fever via Beta-Derivatives

Using the new derivative called beta-derivative, we modelled the well-known infectious disease called break-bone fever or the dengue fever. We presented the endemic equilibrium points under certain conditions of the physical parameters included in the model. We made use of an iteration method to solve the extended model. To show the efficiency of the method used, we have presented in detail the stability and the convergence of the method for solving the system (2). We presented the uniqueness of the special solution of system (2) and finally the numerical simulations were presented for various values of beta.

Comparative Evaluation of Two Types of Immediately Loaded Implants Using Biomechanical and Histomorphometric Tests: An Animal Case Study

Introduction. In order to minimize the required time to regain esthetic and function, immediately loaded implants were suggested. The aim of this study was to comparatively evaluate the Nisastan and XIve implants using biomechanical and histomorphometric tests. Materials and Methods. In this experimental study, 6 Nisastan one-piece immediately loaded screw type implant (OPILS) and 6 Xive implants with 3.4 mm diameter and 11 mm long were used. The implants were immediately loaded with temporary coating. After three months, the torque required to break bone-implant contact was measured and was recorded. All implants were extracted with surrounding bone and histologically were evaluated. The data were inputted into the SPSS 11.5 to run student T-test statistical analyses (). Results. The success rates of both types of implants was 100%, and none of them failed due to mobility or bone loss. The mean removal torque value (RTV) was 142.08 and 40 N/Cm for Xive and Nisastan implants, respectively, and their RTVs showed a significant difference between two mentioned implants (). None of the histomorphometric values showed significant differences between the two implants (). Discussion. both systems have the capability to induce osseointegration under immediate loads but that Xive implants showed higher capability for bone contact.