Browsing by Author "Premarathna, L. P. N. D."

Now showing 1 - 3 of 3

A mathematical model to analyze the dynamics of Dengue transmission: A case study based on Western Province, Sri Lanka
(4th International Research Symposium on Pure and Applied Sciences, Faculty of Science, University of Kelaniya, Sri Lanka, 2019) Gammune, D. H. V.; Premarathna, L. P. N. D.
Dengue fever, which is a rapidly spreading mosquito-borne viral disease, has become a major public health problem in the world, including Sri Lanka. The Western Province of Sri Lanka has been experiencing a very high number of Dengue incidences throughout the past few decades. According to literature, considerations have not been paid on the dynamics of Dengue transmission and interplay of climate changes with mosquito biting rates. Therefore, a mathematical model is to be introduced to integrate the behavior of the climate changes as well as the mosquito biting rates with the dynamics of dengue transmission. Dengue is transmitted only through the bites of the infected mosquitoes, and the number of mosquito bites during a certain period is directly proportional with the number of Dengue cases reported during the same period. The aims of the research are, therefore, to identify the behavior of the climate factors on the dynamics of Dengue transmission, to develop a mathematical model to analyze the dynamics of spread of Dengue and to predict the future Dengue outbreaks of the Western province of Sri Lanka, using the developed model. Since the climate variables play a greater role in Dengue transmission, the correlation between the number of Dengue incidences and the climatic variables is analyzed. The vector-borne compartmental models have been used in the literature to understand the dynamics of different types of epidemic diseases. Hence, in this study, a similar approach is used to analyze the Dengue transmission, which considers the influences of climate changes on the Dengue transmission dynamics via the time-varying mosquito biting rate. A significant positive correlation is found between the reported number of Dengue incidences and the average temperature. According to the analysis, the developed model, together with the estimated mosquito biting rates, gives a statistically significant goodness of fit between the simulation results and the reported number of Dengue incidences. The analysis highlights that the dynamics of Dengue transmission are less sensitive to the variation in the mosquito population size than the changes in the mosquito-biting rate. The proposed model is validated by comparing the predictions with the data, which are not used in the model calibration. The model validation exhibits that there is a statistically significant fit between the model predictions and the actual data. The proposed vector-borne compartmental model along with the estimated mosquito biting rates, therefore, can be used to predict the dynamics of Dengue transmission with a high accuracy
Modeling and forecasting inflation in Sri Lanka using VAR models
(Faculty of Science, University of Kelaniya, Sri Lanka, 2021) Dissanayake, D. M. I. R.; Premarathna, L. P. N. D.
Inflation is one of the key macroeconomic variables of the country’s economy since maintaining economic and price stability is the core objective of the Central Bank of Sri Lanka (CBSL). It is essential to know about future inflation since there is a transmission lag of monetary policy actions. Quantitative inflation forecasting methods will give helpful information on future developments in the economy. Therefore, the development of accurate forecasting models that can be used to describe the dynamic movements of the economy is important in an inflation- targeted regime. Empirical studies have shown that low and stable inflation helps the growth of most economies. The main objective of this study is to model and forecast inflation in Sri Lanka using both the monthly Colombo Consumer Price Index (CCPI) and National Consumer Price Index (NCPI) from January 2009 to December 2020. This study examined the short-term and the long-term forecasts by using both univariate and multivariate models. A descriptive analysis and time series analysis were employed to model and forecast inflation in Sri Lanka. Historical data were obtained from CBSL and the Department of Census & Statistics (DCS). R-studio and E- Views statistical packages were used to develop the models. According to the time series analysis using CCPI, results revealed that there is a short run and long run significant relationship among CCPI, Money Supply (MS), and Gross Domestic Product (GDP). Similarly, forecasting inflation using NCPI, results show that there is a short run and long run significant relationship among NCPI, MS, GDP and Rice Price (RICEP). In this analysis, two models were obtained for CCPI and NCPI. According to the finding of the study, VAR (3) which gives the lowest Root Mean Square Error (RMSE), is the best model to forecast short run as well as long run inflation for Sri Lanka. All roots have modulus less than one and lie inside the unit circle. Therefore, the estimated VAR (3) is stationary. Moreover, the residuals are normally distributed. By incorporation of NCPI to forecast inflation, the accuracy of the results has been further increased in the NCPI than in the CCPI.
A study on Dengue spread in Western province: using Spatial and Cluster analysis.
(4th International Research Symposium on Pure and Applied Sciences, Faculty of Science, University of Kelaniya, Sri Lanka, 2019) Kethmi, G. A. P.; Premarathna, L. P. N. D.
Dengue virus is transmitted to humans through the bite of infected Aedes mosquitoes, mostly Aedes aegypti. According to National dengue control unit of Sri Lanka, the recent outbreak of dengue fever in the country was reported on July 2017. Since the life cycle of a mosquito is short, it is highly influenced by the variations in the environment. Also, Sri Lanka has a changing weather over time, hence the spread of dengue mosquito is time dependant. Considering these facts objectives of the study were to identify the correlation between number of dengue incidences and the environmental factors such as temperature, rainfall and humidity, recognize homogeneous areas of dengue and discover dengue dense area and non-dense area in Western province. Agglomerative hierarchical clustering method used to observe homogenous areas in the study area. In this method, initially each observation is considered as a cluster and continue the procedure by connecting most similar observations. Several linkage methods that can be used to join observations into clusters. From literature, Ward’s method proposed as the best linkage method in clustering where total within-cluster variance calculated and at every step clusters with minimum between cluster variance connected. After constructing the cluster dendrogram by connecting appropriate clusters, the optimum number of clusters identified using Elbow method. Spatial analysis explains a behaviour or a pattern of a variable geographically. Geographical maps are used to find the dengue dense and dengue non-dense areas. Number of dengue incidences and environmental factors for the period 2013 to 2017 of three districts in Western province were used for this study. R statistical software used to conduct the analysis. A descriptive analysis was carried out and outliers were treated using Winsorizing method. Normality of each variable was examined. Pearson’s correlation coefficient calculated when variables are normally distributed otherwise; Spearman correlation coefficient calculated. According to the results obtained, rainfall and humidity have a negative correlation with number of dengue incidences while temperature has a positive correlation. Three clusters identified as follows; first two months and last three months fell into one cluster, March and April were the next and remaining months as another cluster. Cluster analysis showed that, during the first period of monsoon season of the year, there is an increase in the spread of dengue virus in the Western province. Spatial analysis showed that the Colombo as the dengue dense and Kalutara as the dengue non-dense area in the Western province