Number Of Dengue Fever Cases Research Articles

Climate change and dengue fever knowledge, attitudes and practices in Bangladesh: a social media-based cross-sectional survey.

Bangladesh experienced its worst dengue fever (DF) outbreak in 2019. This study investigated the knowledge, attitudes and practices (KAP) among university students in Bangladesh and significant factors associated with their prevention practices related to climate change and DF. A social media-based (Facebook) cross-sectional KAP survey was conducted and secondary data of reported DF cases in 2019 extracted. Logistic regression and spatial analysis were run to examine the data. Of 1500 respondents, 76% believed that climate change can affect DF transmission. However, participants reported good climate change knowledge (76.7%), attitudes (87.9%) and practices (39.1%). The corresponding figures for DF were knowledge (47.9%), attitudes (80.3%) and practices (25.9%). Good knowledge and attitudes were significantly associated with good climate change adaptation or mitigation practices (p<0.05). Good knowledge, attitudes and previous DF experiences were also found to be significantly associated with good DF prevention practices (p<0.001). There was no significant positive correlation between climate change and DF KAP scores and the number of DF cases. Findings from this study provide baseline data that can be used to promote educational campaigns and intervention programs focusing on climate change adaptation and mitigation and effective DF prevention strategies among various communities in Bangladesh and similar dengue-endemic countries.

Comparison of exponential smoothing method and autoregressive integrated moving average (ARIMA) method in predicting dengue fever cases in the city of Palembang

Forecasting is the process of making a statement about an event where the event has not been known or observed. For pharmaceutical students, learning about forecasting techniques can help determine the treatment of various diseases, one of which is dengue fever. Dengue fever is an acute disease caused by the dengue virus. Dengue fever is still a public health issue in major cities in Indonesia, one of which is Palembang. Based on the profile done by Palembang City’s Public Health Office in 2017, dengue fever cases in the area from year to year tend to fluctuates. To get the overview of the number of dengue fever cases in the upcoming years, time series forecasting methods are used, namely the Exponential Smoothing method and the Autoregressive Integrated Moving Average (ARIMA) method. Afterward, the results of predictions from the two methods are compared. Forecasting using the ARIMA method gives the smallest MSE and MAE results of 108077.877 and 172.424, respectively, compared to the Exponential Smoothing method. This means that the ARIMA method is better at predicting the number of dengue fever cases in Palembang in the coming years.

Incidence Rate of Dengue Fever in Saudi Arabia 2011-2018, a Retrospective

Background: Dengue fever is the most unexpectedly spreading mosquito-borne viral disease inside the world. In the last 50 years, incidence rate has accelerated 30-fold with growing geographic expansion to new nations and, in the gift decade from urban to rural settings. Method: A retrospective cross-sectional study was conducted to assess the magnitude of dengue fever in Saud Arabia. Secondary data was collected from the statistical books from 2011 – 2018, the incidence rate per 100,000 persons was calculated and analyzed .The variables collected included age, sex, nationality and incidence rate distribution by years, month and cities. Results: The result indicates that the incidence rate of dengue fever was comparatively low in the year 2012 and 2014 than in other years. The number of dengue fever cases started to rise in January, reach its peak between April, May and June. Incidence rate of non-Saudis was greater than that of Saudis, males were more affected than females. Also, the look at indicates that there is an association among occurrence of dengue fever and age distribution. Conclusion: Dengue fever cases found in Saudi Arabia during the month of January and the number of cases seems to increase more in the month of April, May and June. It is an endemic in cities like Jeddah, Makah, Medina and Jazan. Recommendations: Mosquito control programs and effective health education programs regarding prevention and control of dengue fever needed.

Hematological Parameters in Dengue fever cases in a tertiarycare center-A Retrospective Study.

Background Dengue is an acute infectious viral disease which is caused by infection with 1 of the 4 serotypes of dengue virus DENV1 2 3 4. Dengue fever is an epidemic illness in tropical country like India and many have thrombocytopenia and leucopenia. Common symptoms include high fever intense headache retro-orbital pain anorexia joint painand characteristic skin rash. Hence this study was undertaken to document the hematological change in dengue fever.Objectives To analyze the hematological parameters of dengue fever cases admitted to Sapthagirimedical college and Hospital Bengaluru India.Methodology A retrospective study was conducted in the department of pathology carried out on 201 patients aged more than 18 years admitted to Sapthagiri hospital between the periods of January 2019 to July 2019. Anticoagulated EDTA blood of 2 ml was collected and complete blood count was done by using 5 part differential cell counter sysmex XN 550 . The various parameters included in the studies are Hemoglobin Platelets count Hematocrit and Leukocyte count.Results From the 201 patients studied the most common hematogical abnormally was leucopenian38.8 followed by thrombocytopenia n21.89 in present study. Among 201 cases 126 n62.68 cases were males and 75 n37.31 were females. Maximum number of dengue fever cases was noted in the month of July 145 n72.14 followed by June 45 n22.38.Conclusion Hematological parameters are very helpful for disease monitoring and can be helpful in prediction of prognosis. These parameters if rightly performed and assessed can be of great importance for better patient care in complicated cases.

Role of climatic factors in the incidence of dengue in Port Sudan City, Sudan.

Dengue fever outbreaks have occurred in Port Sudan City, Sudan, during the last 2 decades. Climatic factors may play a role in dengue incidence. This study aimed at discribing the relationship between climatic factors and dengue fever incidence in Port Sudan during 2008-2013. This ecological study entailed secondary data analysis of dengue fever cases and climate information to explore which climatic factors predict the incidence of dengue fever. The Wilcoxon rank sum test and multiple linear regression examined the association between number of dengue fever cases and climatic factors during lag times of 1-6 months. Relative humidity and maximum and minimum temperatures were correlated with dengue incidence in Port Sudan at different time intervals during 2008-2010. Precipitation and relative humidity were correlated with dengue fever during 2011-2013. However, 3-5-month lagged relative humidity was the strongest explanatory variable for the incidence of dengue. Dengue transmission appears sensitive to climatic variability. Elucidating the role of climatic factors in dengue fever helps in risk assessment and prevention of epidemics.

Modeling Dengue Fever Cases by Using GSTAR(1;1) Model with Outlier Factor

Dengue fever is an endemic disease transmitted through the Aedes Aegypti mosquitos. Dengue virus can be transmitted from human hosts who have been infected by the virus to the mosquitoes to be transmitted back to other humans. So that, it is possible for the virus to be transmitted to several surrounding locations. Aedes Aegypti is one of the dengue mosquitoes that likes a warm climate and not too wet or dry. In addition, many un-expected factors can cause a significant increase in the number of dengue fever cases. So that the number of dengue fever cases can increase significantly far different from other data. An observation data that has different characteristics from others is called outlier. The existence of outliers can indicate individuals or groups that have very different behavior from the most of the individuals of the dataset. Outlier data in a data set are often encountered in various kinds of data analysis. Frequently, outliers are removed to improve accuracy of the estimators. But sometimes the presence of an outlier has a certain meaning, which explanation can be lost if the outlier is removed. In this paper, modeling dengue fever cases using GSTAR(1;1) with outlier factors was firstly proposed.

An IoT Based Ovitrap System Applied for Aedes Mosquito Surveillance

Since the number of dengue fever cases has become the endemic disease in Malaysia, it is urgently need for rapid and efficient calculation of mosquito populations particularly for early detection and control measures. An ovitrap surveillance is used to determine the density of Aedes mosquito and it is one of the implemented method for vector control application. In this study, the prototype of an IoT-based ovitrap system was developed to automatically and simultaneously detect the Aedes mosquitoes using NodeMCU as the main IoT platform. The existing sticky ovitrap was modified to integrate the selected IoT components and to ensure its functionality for automatic detection. There are two phases were conducted in this study, with phase 1 evaluating the right IoT components to be selected and applied for automatic detection. Integrating the selected IoT components and modification of present ovitrap was carried out in phase 2 and the final revised design was considered. SWOT analysis and Pugh chart analysis also known as decision matrix method were used to select the best IoT components and final ovitrap design. It has been observed that the prototype D was the best design and be able to detect the adult mosquitoes. The lessons learned in the development of the IoT-based ovitrap were discussed in order to be employed for Aedes mosquitoes surveillance in the future.

Construction and application of joinpoint regression model for series cumulative data

Based on the principle of Joinpoint regression (JPR) model and the additivity of Poisson distribution, this paper constructed a JPR model for series cumulative data. The notifiable incidence number of dengue fever cases per week and weekly cumulative data in Guangdong province from 2008 to 2017 were analyzed, using (mean squared errors) MSE and (mean absolute percentage error) MAPE to evaluate different models. Except for 2015, the MSE and MAPE produced from the logarithmic linear JPR model based on weekly cumulative incidence number were smaller than those based on the weekly data. The fitting accuracy of JPR model for series cumulative data for trend analysis had been improved significantly. This model could be applied to the analysis of the trend change and the prediction of staged cumulative incidence.

Spatiotemporal Transmission Patterns and Determinants of Dengue Fever: A Case Study of Guangzhou, China.

Dengue fever is one of the most common vector-borne diseases in the world and is mainly affected by the interaction of meteorological, human and land-use factors. This study aims to identify the impact of meteorological, human and land-use factors on dengue fever cases, involving the interplay between multiple factors. The analyses identified the statistically significant determinants affecting the transmission of dengue fever, employing cross-correlation analysis and the geo-detector model. This study was conducted in Guangzhou, China, using the data of confirmed cases of dengue fever, daily meteorological records, population density distribution and land-use distribution. The findings highlighted that the dengue fever hotspots were mainly distributed in the old city center of Guangzhou and were significantly shaped by meteorological, land-use and human factors. Meteorological factors including minimum temperature, maximum temperature, atmospheric pressure and relative humidity were correlated with the transmission of dengue fever. Minimum temperature, maximum temperature and relative humidity presented a statistically significant positive correlation with dengue fever cases, while atmospheric pressure presented statistically significant negative correlation. Minimum temperature, maximum temperature, atmospheric pressure and humidity have lag effects on the transmission of dengue fever. The population, community age, subway network density, road network density and ponds presented a statistically significant positive correlation with the number of dengue fever cases, and the interaction among land-use and human factors could enhance dengue fever transmission. The ponds were the most important interaction factors, which might strengthen the influence of other factors on dengue fever transmission. Our findings have implications for pre-emptive dengue fever control.

Implementation of Fuzzy Inference System for Classification of Dengue Fever on the villages in Malang

Dengue fever is a disease that must be watched out and early preventive measures are taken so the spread of this disease can be reduced. An early preventive dengue fever can be controlled by a mathematical model. The article proposes a model of fuzzy inference system with optimal fuzzy rule bases generated by fuzzy c-means and optimized by ordinary least square (OLS). The developing system is done by forming a data structure in the form of input-output pairs. Factors that influence the number of dengue fever cases are used as the system input and the number of dengue fever cases as the system output. Based on the input-output pairs, the fuzzy rule bases is generated by using the fuzzy c-means method. The consequent part of the rule bases is optimized by the OLS method to produce the optimal rule bases. The resulted system is able to predict the level of dengue fever in the villages with an accuracy of 90% and can be used to predict the level of dengue fever in a village by inputting factors that influence the level of dengue fever.

A novel entomological index, Aedes aegypti Breeding Percentage, reveals the geographical spread of the dengue vector in Singapore and serves as a spatial risk indicator for dengue

BackgroundAedes aegypti is an efficient primary vector of dengue, and has a heterogeneous distribution in Singapore. Aedes albopictus, a poor vector of dengue, is native and ubiquitous on the island. Though dengue risk follows the dispersal of Ae. aegypti, the spatial distribution of the vector is often poorly characterized. Here, based on the ubiquitous presence of Ae. albopictus, we developed a novel entomological index, Ae. aegypti Breeding Percentage (BP), to demonstrate the expansion of Ae. aegypti into new territories that redefined the dengue burden map in Singapore. We also determined the thresholds of BP that render the specific area higher risk of dengue transmission.MethodsWe performed analysis of dengue fever incidence and Aedes mosquito breeding in Singapore by utilizing island-wide dengue cases and vector surveillance data from 2003 to 2013. The percentage of Ae. aegypti breeding among the total Aedes breeding habitats (BP), and the reported number of dengue fever cases in each year were calculated for each residential grid.ResultsThe BP of grids, for every year over the 11-year study period, had a consistent positive correlation with the annual case counts. Our findings suggest that the geographical expansion of Ae. aegypti to previously “non-dengue” areas have contributed substantially to the recent dengue fever incidence in Singapore. Our analysis further indicated that non-endemic areas in Singapore are likely to be at risk of dengue fever outbreaks beyond an Ae. aegypti BP of 20%.ConclusionsOur analyses indicate areas with increasing Ae. aegypti BP are likely to become more vulnerable to dengue outbreaks. We propose the usage of Ae. aegypti BP as a factor for spatial risk stratification of dengue fever in endemic countries. The Ae. aegypti BP could be recommended as an indicator for decision making in vector control efforts, and also be used to monitor the geographical expansion of Ae. aegypti.

Social Marketing on Dengue Hemorrhagic Fever and Tuberculosis Prevention and Control Program in Pati, Central Java, Indonesia

Indonesia has the highest number of dengue fever cases in Southeast Asia and the second highest TB cases in the world. Both diseases are related to behavior. Social marketing focuses on changes in health behaviors. This study aimed to apply social marketing on dengue mosquito vector control and TB case finding and to analyze the effect of social marketing training on the knowledge and skills of community health workers (CHWs). A mixed method design was conducted in Pati, Central Java, Indonesia. First, a case study was conducted using field observation, in-depth interviews, focus group discussions (FGD), and document review. In-depth interviews and FGD were conducted on 55 participants including 40 community leaders and 15 CHWs. Data were analyzed using content analysis. Second, intervention study was conducted on social marketing training of 30 CHWs. The independent variable was social marketing training. The dependent variables were knowledge and skill of dengue mosquito vector control and TB case finding. The effect of training was analyzed by paired t test. The results showed that knowledge (p&lt;0.001) and skill (p&lt;0.001) in dengue mosquito vector control and TB case finding increased significantly after training. Qualitative assessment showed that CHWs were more able to identify health problems in the community and to perform TB case finding and dengue mosquito breeding place eradication. After training they also became more knowledgeable in applying social marketing approach to address the health problem. In conclusion, social marketing strategy can be used to address community health problem.

Dengue fatality prediction using data mining

Dengue fever, a mosquito-borne tropical disease caused by the dengue virus is life-threatening. In Malaysia, although necessary control measures have been carried out, the number of dengue fever cases keeps increasing. Among the measures, dengue vector control appears to be the most effective way to control the spread of the dengue virus particularly in Malaysia. The aim of this research is to study the current implementation of dengue outbreak control in Malaysia and predict dengue fever cases using data mining techniques. Real data on dengue fever and weather are collected from the Ministry of Health in its Perak Tengah district office and Perak Meteorological office respectively. Different data mining classification techniques are applied onto these data with the performance of each technique is measured. The results highlight the best performance among techniques used.

RELATIONSHIPS OF THE IMPLEMENTATION OF A 3M PLUS PROGRAM AND THE EXISTENCE OF AEDES AEGYPTI LARVAE TOWARDS THE NUMBER OF DENGUE FEVER CASES IN THE PUBLIC HEALTH CENTER OF TIGO BALEH BUKITTINGGI, WEST SUMATERA, INDONESIA

Background: Dengue fever in Tigo baleh Bukittinggi community is one of the infectious diseases resulting in serious health problems. Understanding the factors associated with the disease is necessity.Objective: To determine the relationships of the implementation of 3M plus program and the existence of Aedes aegypti larvae towards the number of dengue fever cases in the public health center of Tigo Baleh Bukittinggi, West Sumatera, Indonesia.Methods: This was a case control study conducted between January and December 2016 in the Public Health Center of Tigo Baleh Bukittinggi. There were 78 samples recruited by total sampling, with 39 were assigned in the case and control group. House index (HI) and Container index (CI) were used to measure the presence of Aedes aegypti larvae. The implementation of 3M plus program was measured using questionnaire developed by the researcher. Chi Square was performed for data analysis. Result: Findings showed that house index value was 43.6% and container index was 17.9%. The presence of larvae at home contributes to 24 (61.5%) cases of DHF in the case group and 10 (25.6%) cases in the control group. Poor implementation of the program contributes to 27 (69.2%) cases in the case group and 17 (43.6%) in the control group. Chi square test showed p 0.040 (0.05) for the 3M plus implementation and p 0.03 (0.05) for the presence of Aedes aegypti. Conclusion: There were significant associations between the implementation of 3m plus program and the existence of Aedes aegypti larvae towards the number of dengue fever cases in the public health center of Tigo Baleh Bukittinggi, West Sumatera, Indonesia. It is suggested that the community should do more efforts to prevent the occurrence of DHF through mosquito nest eradication, such as the implementation of 3M Plus and sanitation efforts, and pay attention to any places that potentially become a breeding ground for Aedes aegypti mosquitoes.

Impediments of reporting dengue cases in India.

Dengue has emerged as one of the most important mosquito-borne, fatal flaviviral disease, apparently expanding as a global health problem. An estimated 3.6 billion people are at risk for dengue, with 50 million infections per year occurring across 100 countries globally. The annual number of dengue fever cases in India is many times higher than it is officially reported. This under reporting would play a major role in the government's decision-making. Underestimating of the disease in India encumbers its people from taking preventive measures, discourages efforts to ensnare the sources of the disease and deliberates efforts for vaccine research. In this article, we highlight the probable impediments of under reporting leading to its impact on national and global public health and also offer key remedies to effectively address the issues across the clinics to the community level.

Modelling the association of dengue fever cases with temperature and relative humidity in Jeddah, Saudi Arabia—A generalised linear model with break-point analysis

The aim of this study was to examine the role of environmental factors in the temporal distribution of dengue fever in Jeddah, Saudi Arabia. The relationship between dengue fever cases and climatic factors such as relative humidity and temperature was investigated during 2006–2009 to determine whether there is any relationship between dengue fever cases and climatic parameters in Jeddah City, Saudi Arabia. A generalised linear model (GLM) with a break-point was used to determine how different levels of temperature and relative humidity affected the distribution of the number of cases of dengue fever. Break-point analysis was performed to modelled the effect before and after a break-point (change point) in the explanatory parameters under various scenarios. Akaike information criterion (AIC) and cross validation (CV) were used to assess the performance of the models. The results showed that maximum temperature and mean relative humidity are most probably the better predictors of the number of dengue fever cases in Jeddah. In this study three scenarios were modelled: no time lag, 1-week lag and 2-weeks lag. Among these scenarios, the 1-week lag model using mean relative humidity as an explanatory variable showed better performance. This study showed a clear relationship between the meteorological variables and the number of dengue fever cases in Jeddah. The results also demonstrated that meteorological variables can be successfully used to estimate the number of dengue fever cases for a given period of time. Break-point analysis provides further insight into the association between meteorological parameters and dengue fever cases by dividing the meteorological parameters into certain break-points.

A stage structured mosquito model incorporating effects of precipitation and daily temperature fluctuations

An outbreak of dengue fever in Guangdong province in 2014 was the most serious outbreak ever recorded in China. Given the known positive correlation between the abundance of mosquitoes and the number of dengue fever cases, a stage structured mosquito model was developed to investigate the cause of the large abundance of mosquitoes in 2014 and its implications for outbreaks of the disease. Data on the Breteau index (number of containers positive for larvae per 100 premises investigated), temperature and precipitation were used for model fitting. The egg laying rate, the development rate and the mortality rates of immatures and adults were obtained from the estimated parameters. Moreover, effects of daily fluctuations of temperature on these parameters were obtained and the effects of temperature and precipitation were analyzed by simulations. Our results indicated that the abundance of mosquitoes depended not only on the total annual precipitation but also on the distribution of the precipitation. The daily mean temperature had a nonlinear relationship with the abundance of mosquitoes, and large diurnal temperature differences can reduce the abundance of mosquitoes. In addition, effects of increasing precipitation and temperature were interdependent. Our findings suggest that the large abundance of mosquitoes in 2014 was mainly caused by the distribution of the precipitation. In the perspective of mosquito control, our results reveal that it is better to clear water early and spray insecticide between April and August in case of limited resources.

Dengue: Prevenção, Controle e Cuidados de Enfermagem - Revisão Integrativa da Literatura 2008-2013

Objective: To perform an integrative literature review about prevention and control of dengue fever and about the nursing care currently offered to patients infected by the virus. Material and Methods: This is a qualitative, descriptive literature review of national and international publications. The articles were extracted from the following virtual databases: Brazilian Health Virtual Library (BVSMS), SCIELO, LILACS, and PUBMED, using the descriptors “Dengue fever”, “Prevention”, and “Nursing Care”. The selected articles were published between the year 2008 and 2013. Results: The first search resulted in 134 articles. After multiple readings and elimination of duplicity, 14 articles were included in the final sample. The data showed that properly developed prevention is essential to achieve reduction in the number of dengue fever cases, ultimately helping to decrease the occurrence of acute forms of the disease. The control through combating the vector in its multiple stages of development and intensive epidemiologic vigilance over possible outbreak sites, are vital. Nursing care is focused on establishing diagnosis, interventions, predicting and evaluating outcomes, overall aiming to reestablish the health of patients infected by the dengue virus. Conclusion: This integrative literature review shows that efficiency in disease prevention and control are vital to decrease the number of dengue fever cases. Along with that, nursing care is essential for the reestablishment of the patient’s health as a result of diagnosis, interventions, and evaluation of outcomes. DESCRIPTORS Dengue Prevention and Control. Nursing Care.

Meteorologically Driven Simulations of Dengue Epidemics in San Juan, PR.

Meteorological factors influence dengue virus ecology by modulating vector mosquito population dynamics, viral replication, and transmission. Dynamic modeling techniques can be used to examine how interactions among meteorological variables, vectors and the dengue virus influence transmission. We developed a dengue fever simulation model by coupling a dynamic simulation model for Aedes aegypti, the primary mosquito vector for dengue, with a basic epidemiological Susceptible-Exposed-Infectious-Recovered (SEIR) model. Employing a Monte Carlo approach, we simulated dengue transmission during the period of 2010–2013 in San Juan, PR, where dengue fever is endemic. The results of 9600 simulations using varied model parameters were evaluated by statistical comparison (r2) with surveillance data of dengue cases reported to the Centers for Disease Control and Prevention. To identify the most influential parameters associated with dengue virus transmission for each period the top 1% of best-fit model simulations were retained and compared. Using the top simulations, dengue cases were simulated well for 2010 (r2 = 0.90, p = 0.03), 2011 (r2 = 0.83, p = 0.05), and 2012 (r2 = 0.94, p = 0.01); however, simulations were weaker for 2013 (r2 = 0.25, p = 0.25) and the entire four-year period (r2 = 0.44, p = 0.002). Analysis of parameter values from retained simulations revealed that rain dependent container habitats were more prevalent in best-fitting simulations during the wetter 2010 and 2011 years, while human managed (i.e. manually filled) container habitats were more prevalent in best-fitting simulations during the drier 2012 and 2013 years. The simulations further indicate that rainfall strongly modulates the timing of dengue (e.g., epidemics occurred earlier during rainy years) while temperature modulates the annual number of dengue fever cases. Our results suggest that meteorological factors have a time-variable influence on dengue transmission relative to other important environmental and human factors.

The Impacts of Mosquito Density and Meteorological Factors on Dengue Fever Epidemics in Guangzhou, China, 2006–2014: a Time-series Analysis

ObjectiveTo explore the associations between the monthly number of dengue fever(DF) cases and possible risk factors in Guangzhou, a subtropical city of China.1 MethodsThe monthly number of DF cases, Breteau Index (BI), and meteorological measures during 2006-2014 recorded in Guangzhou, China, were assessed. A negative binomial regression model was used to evaluate the relationships between BI, meteorological factors, and the monthly number of DF cases. ResultsA total of 39,697 DF cases were detected in Guangzhou during the study period. DF incidence presented an obvious seasonal pattern, with most cases occurring from June to November. The current month's BI, average temperature (Tave), previous month's minimum temperature (Tmin), and Tave were positively associated with DF incidence. A threshold of 18.25 °C was found in the relationship between the current month's Tmin and DF incidence. ConclusionMosquito density, Tave, and Tmin play a critical role in DF transmission in Guangzhou. These findings could be useful in the development of a DF early warning system and assist in effective control and prevention strategies in the DF epidemic.