Graduate Studies
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Item Prediction of Dengue Incidence Based on Time Series Modelling in the District of Colombo, Sri Lanka(International Postgraduate Research Conference 2019, Faculty of Graduate Studies, University of Kelaniya, Sri Lanka, 2019) Udayanga, L.; Herath, K.; Gunanthilaka, N.; Iqbal, M.C.M.; Abeyewickreme, W.Timely implementation of intervention activities, is essential in controlling dengue epidemics. This requires the prediction of dengue epidemics, while respecting the spatial and temporal trends in dengue incidence. However, such aspects are limitedly focused in dengue epidemic management of Sri Lanka. Therefore, the current study was conducted to develop a temporal prediction model for dengue incidence in the district of Colombo in Sri Lanka. Dengue cases reported from 2000 to 2018 in the district of Colombo were collected from the Epidemiology Unit, Sri Lanka. Selected meteorological parameters such as number of rainy days, monthly cumulative rainfall, minimum and maximum relative humidity and temperature corresponding to the same study period were collected from the Department of Meteorology, along with the Oceanic Niño Index (ONI) from the National Oceanic and Administration (NOAA) Centre. All the data were arranged at monthly level. After evaluation of the normality, seasonality, stationarity and seasonal stationarity of the epidemic data, a Seasonal Autoregressive Integrated Moving Average (SARIMA) model was fitted for the prediction of dengue by using the R statistical package. Subsequently, the meteorological factors and the dengue incidence was subjected to a cross correlation analysis to identify the most representative meteorological factors associated with dengue epidemic incidence and an Autoregressive Integrated Moving Average with Exogeneous Input (ARIMAX) model was fitted. The best fitted SARIMA (0, 1, 0) (3, 0, 0)12 model was characterized by an Akaike Information Criteria value (AIC) of -19.04, Bayesian information criterion (BIC) of -5.42, Mean error (ME) of 0.002 and Root Mean Square Error (RMSE) of 0.518. According to the cross correlation analysis, number of rainy days (RD) and Oceanic Niño Index (ONI) denoted a significant negative association with the reported dengue cases in Colombo, while monthly cumulative rainfall (RF), maximum relative humidity (Max_RH), maximum temperature (Max_T) and minimum temperature (Min_T) shared a positive correlation (P < 0.05 at 95% level of confidence). The best fitting ARIMAX model (as indicated below) was characterized by an AIC of -15.74, BIC of -11. 2, ME of 0.006 and RMSE of 0.171. ARIMA (0, 1, 1) + [-0.0006 RDt-3 + 0.0008 RFt-3 + 0.0260 Max_RHt-3 + 0.0766 Min_Tt—4 - 0.0661 ONIt-5] Based on the performance, the ARIMAX model is recommended to be used for the prediction of dengue incidence in the Colombo district to ensure rational allocation of resources for vector control and dengue epidemic managementItem A Statistical Approach to Define Thresholds for Dengue Epidemic Management in Akurana Medical Officer of Health Area, Kandy District of Sri Lanka(19th Conference on Postgraduate Research, International Postgraduate Research Conference 2018, Faculty of Graduate Studies,University of Kelaniya, Sri Lanka, 2018) Udayanga, N.W.B.A.L.; Gunathilaka, P.A.D.H.N.; Iqbal, M.C.M.; Fernando, M.A.S.T.; Abeyewickreme, W.Stegomyia indices, namely; Premise Index (PI), Breteau Index (BI) and Container Index (CI) are used forvector management approaches in Sri Lanka. Properly defined threshold values for larval indices are of higher importance to provide forecasts on dengue epidemics and also for effective larval management of dengue vectors. However, such critical thresholds are poorly defined for Sri Lanka. The present study aimed to define threshold values forabove larval indices for dengue epidemic management in the Akurana Medical Officer of Health (MOH) in the Kandy District. Larval surveys were conducted on a monthly basis from January, 2016 to June, 2018. Four larval indices, namely BI for Aedesaegypti (BIA) and Aedesalbopictus (BIB), PI and CI were calculated. Further, monthly larval indices of AkuranaMOH area from January, 2012 to December, 2015, were obtained from the MOH office, along with monthly reported dengue cases for the entire study period. Receiver Operating Characteristic (ROC) curves in SPSS (version 23) were used to assess the discriminative power of the larval indices in determiningdengue epidemics and thresholds based on larval indices. As indicated by the area of ROC curve (AUC), the BIA (0.661) and PI (0.637) were having a notable discriminative power to forecast dengue epidemics at a two-month lag period. Both BIB (0.397) and CI (0.526) were non-informative influencers at one and two-month lag periods. The BIA and PI were better predictors of dengue incidence than BIB and CI. Based on the ROC curve, three risk thresholds were defined for BIA as Low Risk (BIA≤2.1), Moderate Risk (3.9≤BIA<4.85), and High Risk (BIA≥4.85), with respect to Ae. aegypti. According to the PI, thresholds were defined as Low Risk (PI≤6.2), Moderate Risk (7.7≤ PI<9.9), and High Risk (PI≥ 9.9). Threshold values defined for BI of Ae. aegypti and PI, could be recommended to be considered in implementing vector control efforts in the above study area for effective dengue epidemic management, through pre planned entomological management of dengue vectors.Item Laboratory Evaluation of the Bio-control Efficacy of Selected Copepods on Dengue Vectors of Sri Lanka(19th Conference on Postgraduate Research, International Postgraduate Research Conference 2018, Faculty of Graduate Studies,University of Kelaniya, Sri Lanka, 2018) Udayanga, N.W.B.A.L.; Ranathunge, R.M.T.; Iqbal, M.C.M.; Abeyewickreme, W.; Hapugoda, M.Among variety of alternatives for management of dengue vectors, biological control remains as a promising approach, due to its high efficacy, sustainability and low impacts on human and ecosystem health. Copepods are considered asa leading predator of mosquito larvae including Aedes vectors. However, the predatory potential of different copepods on bio-control of dengue vectors has been less studied in Sri Lanka. Therefore, the current study aimed to evaluate the predatory success of five locally abundant copepods on both AedesaegyptiandAe. albopictus. Copepod collections were made from water bodies and rock pools located in the Kandy and Gampaha districts by using a plankton net. After morphological identification, single gravid copepods of different species were used to establish copepod cultures under standard laboratory conditions. Five adult copepods of each species were transferred into containers and groups of 200 first instar Ae. Aegypti larvae were introduced in to each container, separately. The number of surviving larvae in each container was recorded at 3 hour intervals up to 24 hours. Five replicates were conducted for each copepod species. Same experimental design was followed for Ae. albopictus. General Linear Modelling technique (GLM) followed by Tukey’s pair-wise comparison was used to make statistical inferences on the significance of average larvalconsumption rates by studied copepod species. SPSS (version 23) was used for the statistical analysis. Five species of copepods, namely Cyclops languides, C. varicans, C. vernalis, Mesocyclopleuckarti and M. scrassus were considered during the study. Average predation rates of 34.9±1.80 and 33.5±1.06 for Ae. aegypti and Ae. albopictus, respectively, were indicated by M. leuckartias the highest predation rates. Meanwhile, M. scrassus showed the second highest predation rates for both Aedes vectors. On the other hand, the lowest predatory efficacy was shown by C. languides with 10.6+1.60 and 8.4+1.10 for Ae. aegypti and Ae. albopictus, respectively. The average consumption rates of different copepod species varied significantly (p<0.05 at 5% level of significance). The type of Aedes species had a significant influence on the predatory efficacy of studied copepods (p< 0.05) under laboratory conditions. In conclusion, M. leuckartiand M. scrassus that reported the highest predation efficacies on both Aedes larvae could be suggested as potential bio-control agents for dengue vector management approaches in Sri Lanka after semi field and field settings.Item Role of Larval Indices on the Incidence of Dengue Epidemics in Akurana, Medical Officer of Health (MOH) Area, Kandy.(In: Proceedings of the International Postgraduate Research Conference 2017 (IPRC – 2017), Faculty of Graduate Studies, University of Kelaniya, Sri Lanka., 2017) Udayanga, N.W.B.A.L.; Gunathilaka, P.A.D.H.N.; Iqbal, M.C.M.; Fernando, M.A.S.T.; Abeyewickreme, W.As in many other Asian countries, vector control entities in Sri Lanka also depend upon larval indices as the major driving factor of routine entomological surveillance and management of dengue vectors. However, studies aimed at defining the role of larval indices, which reflect the population dynamics of dengue vectors, on the incidence of dengue outbreaks are limited. This is mainly due to restrictions in long-term vector density related data. Hence, the current study attempts to evaluate the role of larval indices on the incidence of dengue epidemics in Akurana, Medical Officer of Health (MOH) area.Item Optimization of Critical Threshold Values for Aedes Mosquitoes based on Breteau Index in Kandy District of Sri Lanka.(In: Proceedings of the International Postgraduate Research Conference 2017 (IPRC – 2017), Faculty of Graduate Studies, University of Kelaniya, Sri Lanka., 2017) Udayanga, N.W.B.A.L.; Gunathilaka, P.A.D.H.N.; Iqbal, M.C.M.; Kusumawathie, P.H.D.; Abeyewickreme, W.Many countries, including Sri Lanka, mainly depend upon Stegomyia indices,such as Premise Index (PI), Breteau Index (BI),Container Index (CI), and Pupal Index (PI) for routine entomological surveillance of dengue. Among them, BI remain as the most widely used larval index for vector management prior to and during epidemic incidences. Properly defined threshold values for BI are of essence, to assist the prediction of dengue epidemics and as a leading indicator for vector control. However, Sri Lanka still lacks effective thresholds for BI to initiate and drive dengue vector management activities. Hence, the present study attempts to define threshold values for BI based on an empirical modelling approach for the Kandy District of Sri Lanka.Item Emerging Spatio-Temporal Trends in Dengue Incidence in Poojapitiya Medical Officer of Health (MOH), Central province, Sri Lanka(Faculty of Graduate Studies, University of Kelaniya, 2015) Udayanga, N.W.B.A.L.; Gunathilaka, P.A.D.H.N.; Iqbal, M.C.M.; Kusumawathie, P.H.D.; Abeyewickreme, W.Dengue has emerged as one of the major threats to the health sector of many countries including Sri Lanka, due to the increasing number of reported dengue cases over time. Therefore, a statistical and geo-informatics based analysis of the spatio-temporal trends in dengue distribution was carried out to identify recent spatial and temporal trends in dengue distribution patterns, while assessing the susceptibility of the population to dengue infection in the Poojapitiya Medical Officer of Health (MOH) area. Monthly records of reported dengue cases from 2009 to 2013 of the Poojapitiya MOH area were acquired and spatial maps of the recorded dengue case distribution in each Grama Niladhari Division (GND) were developed by using Arc GIS (version 10.2). Normal Chi square test coupled with Paired-Chi square test in MINITAB (version 14.12.0) were used to investigate the impact of gender and age on the infection. Galhinna GND indicated the highest susceptibility to dengue throughout the study period, while the rest of the GNDs indicate less (37 GNDs) or null (29 GNDs) susceptibilities. As suggested by the results of the Paired-Chi square test [>Χ 2 (66, 0.95) = 85.951], the emergence of dengue outbreaks indicated a significantly declining trend in recorded dengue cases in all of the GNDs (regardless of the outbreak in 2012) during recent years. The Percentage Infected Male : Female Ratio (PIMFR) suggested that the, males had a relatively high susceptibility for dengue infection than females with 63.9 : 36.1 of average PIMFER (p=0.00<0.05 at 95% of significance). According to the Paired-Chi square test, the vulnerability of the age groups shifts significantly throughout the study period [>Χ 2 (7, 0.95) = 14.067], where the age groups of 11 - 20 and 21 – 30 indicated high vulnerability to dengue, while >61 age group remained as the least vulnerable group for dengue infection. The identification of the potential high risk GNDs with high susceptibility to the infection of dengue along with the vulnerable age groups in the community would assist the relevant vector controlling agencies to concentrate their efforts, ensuring the effective controlling of dengue outbreak occurrence within the of Poojapitiya MOH.