Leptospirosis is a zoonotic infectious disease in the world. It is growing as a major public health threat in Sri Lanka. The records in Sri Lanka show that, over 4000 cases were reported in the year 2016 in which nearly one fourth of total cases was reported only from the Western province. The objective of this study is to model leptospirosis cases in Western province of Sri Lanka using time series analysis. Since the purpose of forecasting is to plan the future activities, this study will support in term of planning the programmes of control for future.Appropriate tests were employed for the preliminary analysis to study the behavior of provinces-wise and district-wise distribution of leptospirosis cases in Sri Lanka. Seasonal Autoregressive Integrated Moving Average (SARIMA) models were developed using standard techniques. Diagnostic tests for tentatively fitted models were checked. In addition, for the purpose of selecting the best model, usual selection criteria were used. Finally, mean absolute percentage error was used to measure the accuracy of forecasting.The results show that, Western province (28.41%) is the mostly affected part of the island by human leptospirosis. Moreover, Gampaha (10.78%), Kalutara (9.59%) and Colombo (8.04%) districts in Western province are ranked among the first 5 districts of Sri Lanka based on average number of recorded cases. The accuracy of the fitted SARIMA (1, 0, 0)(0, 1, 1)12 model is over 85%. Therefore, it can be used to forecast future leptospirosis cases in the Western province. Based on the fitted model, the expected number of new cases in the Western province for the year 2017 is estimated to be 1168.

Tourism is one of the vastly growing and largest industries in the world. Contribution of tourism to Sri Lanka's total foreign exchange earnings in 2016 amounted to 14.2%. After the civil strife in Sri Lanka, tourist arrivals continue to grow annually. Therefore, the post-conflict tourist arrivals were considered for this study. Forecasting is an essential analytical tool in tourism policy and planning. In all the regions at all times, there is no specific model that outperforms other models regularly. Therefore, the objective of this study is to compare Holt-Winter's and Box-Jenkin's methods of modeling the tourist arrivals and to recommend a better method to forecast the future tourist arrivals in Sri Lanka. Appropriate tests were applied in modeling exercises for both methods. The results demonstrate that, during June 2009 to June 2017, nearly 10.5 million of tourists had visited the island. Both models are adequate for forecasting tourist arrivals. However, based on the forecasting accuracy measures of the model, the Box-Jenkin's method outperforms the Holt-Winter's method. The Box-Jenkin's model gives approximately 90% forecasting accuracy and therefore it is recommended to forecast the tourist arrivals in Sri Lanka. S. R. GnanapragasamAccordingly, around 1.15 million of tourists arrived in Sri Lanka in the second half of the year 2017, and it is about 5.7% increase compared to the same period in 2016. Further, over 235,000 tourists arrived in December 2017, which was the highest monthly arrival in the history of Sri Lanka tourism so far.

Tourism plays a big role in terms of economics in the development of a country. The arrivals were less during the war period in Sri Lanka

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