Theses - Faculty of Medicine

Permanent URI for this collectionhttp://repository.kln.ac.lk/handle/123456789/6564

Browse

Search Results

Now showing 1 - 2 of 2
  • Item
    Establishment of a geographic information system (GIS) based mathematical model for prediction of dengue epidemics within Colombo and Kandy districts of Sri Lanka.
    (University of Kelaniya, 2019) Udayanga, N.W.B.A.L.
    Dengue fever, which is primarily transmitted by Aedes aegypti and Aedes albopictus, is responsible for approximately 390 million infections globally per annum. The current study was conducted to characterize the dengue risk within the districts of Colombo and Kandy. Information on socio-economic and demographic status, and knowledge, attitudes and practices (KAP) were gathered from 1000 randomly selected patients and 1000 non-dengue reported households within each district using an interviewer administered questionnaire. Routine entomological surveillance was conducted from February 2016 to July 2018 at monthly intervals within 10 high risk Medical Officer of Health (MOH) areas in both districts. Monthly vector indices, [Premise Index (PI), Container Index (CI) and Breteau Index (BI)], meteorological parameters (monthly total rainfall, minimum and maximum temperature and relative humidity), landuse practices and socio-demographic data from all the 39 MOH areas relevant to the period of January, 2012 to December, 2018 were collected as secondary data. The socio-economic attribute. were statistically analysed by using the Chi-square test of independence and cluster analysis. Receiver Operating Characteristic (ROC) curves analysis was used to develop thresholds for dengue epidemic management. Principal Component based Linear Regression (PCLR) and Principal Component based Poisson Regression (PCPR) approaches were used to develop a spatial risk characterization model for dengue, while Seasonal Autoregressive Integrated Moving Average (SARIMA) approach was used to develop a temporal dengue prediction model. The climate change vulnerability of the local communities to dengue was evaluated by using the composite index method. Significant differences were identified among the test and control groups for basic demographic factors, living standards, knowledge, attitude and practices. The test group indicated similar risk factors, while the control group also shared more or less similar characteristics as depicted by the findings of cluster analysis. Further, improvement in key infrastructural facilities such as urbanization and waste collection, community education, public motivation, coordination and integration of control programmes, were recognized to be vital. Only PI and BI for Ae. aeopti (Blagp) were significantly associated with dengue epidemics at lag periods of one and two months. Based on Ae. aegypti, average threshold values were defined for Colombo as Low Risk (Blagp ≤2.4), Moderate Risk (3.8 ≤ Blagp ≥5), High Risk (Blagp ≥ 5), along with Blagp ≤ 3.0 (Low Risk), 4.2 ≤ Blagp < 5.3 (Moderate Risk) and Blagp ≥ 5.3 (High Risk) for Kandy. Further, PI ≤ 5.5, 8.9 ≤ PI ≥ 11.9 and PI ≥11.9 were defined as Low Risk, Moderate Risk and High Risk average thresholds for PI in Colombo, while PI ≤ 6.9 (Low Risk), 9.1≤ PI ≥ 11.8 (Moderate Risk) and PI ≥ 11.8 (High Risk) were defined for Kandy. The best fitting model converged by PCPR was the best risk characterization model, with higher levels of goodness of fit indicators such as R2 and Adjusted R2 values of 90.08% and 89.88%, with an AIC value of 205.86. The best fitting forecasting models fitted for Colombo and Kandy are SARIMA (0,1,0) (3,0,0) and SARIMA (2,1,2) (1,0,0)12 respectively. Colombo Municipal Council MOH area had the highest vulnerability (0.49: moderate vulnerability) to dengue, while the Galaha MOH showed the lowest (0.15; very low vulnerability). KEYWORDS: Dengue, Risk prediction, GIS, Spatial model, threshold.
  • Item
    Determination of risk factors and development of mathematical models to forecast case incidence of dengue in Gampaha District, Sri Lanka.
    (University of Kelaniya, 2019) Withanage, G. P. W. K.
    ABSTRACT: Dengue is one of the most important mosquito-borne viral infection in Sri Lanka and the disease is caused by any of the four antigenically distinct Dengue Viruses (DENV). Aedes aegypti (Linnaeus) and Ae. albopictus (Skuse) are considered as vectors transmitting the virus in the country. The second highest number of dengue incidences are reported from the District of Gampaha, next to Colombo, since 2010. Overall objective of the current study was identification of risk factors, development of risk maps and prediction models for transmission of dengue and identification of efficacy of lethal ovitraps to control dengue vectors in the District of Gampaha. During the COMPONENT 1 of the study, identification of risk factors affecting transmission of dengue in selected sites in the District of Gampaha was performed. Based on epidemiological situation during the period of 2005-2014, four Medical Officer of Health (MOH) areas with highest number of dengue incidences reported, namely Kelaniya, Mahara, Negombo and Wattala, were selected as study areas. Mirigama MOH area, which had a very low level of dengue incidence, was selected as the control area. Differences in entomological indices were observed in study areas during the analysis of studied risk factors, however the study variables in high risk study areas were clustered together when compared to the control area. Broadly, socio-economic factors viz. size of the homestead, years of living in the same area, number of persons in household, monthly family income and type of premise, Entomological factors, viz. surrounding cleanliness, vegetation coverage and source of water and Knowledge, Attitude and Practices (KAP) measures, viz. waste disposal method, mosquito control measures, effects of previous dengue control projects and role of Public Health Inspector (PHI) play significant role in transmission of dengue in the high risk study areas. Transmission of DENV serotype/s and genotype/s by field-caught dengue vector mosquitoes was detected using molecular-based assays. Phylogenetic analysis of the positive mosquito pools, collected during the dengue epidemic in 2017, revealed that the causative agent for the epidemic is a migrated virus belongs to DENV-2 Cosmopolitan Clade lb strain. Under the COMPONENT 2 of the study, development of mathematical and Geographic Information System (GlS)-based models to forecast impending dengue epidemics and GIS-based risk maps to study on transmission of dengue in the District of Gampaha were performed. During mathematical modelling, rainfall, rainy days, temperature and Relative Humidity (RH) were identified as significant climatic factors affecting for the transmission of dengue. Further, number of dengue incidence in the previous month exponentially contributed to the dengue incidence in the current month. The best time series regression model developed forecasted correctly with mean absolute errors of 95.65 and 532.39 for training and validation periods, respectively. The Pierce skill score of the model was 0.49. Receiver operating characteristic of the selected model was 86% and the sensitivity was 92%. The developed random forest model forecasted dengue incidences correctly with mean absolute errors of 90.73 and 1308.56 for training and validation periods and the model demonstrated the increase of dengue incidences since March, 2017 which lead to the epidemic peak in July. GIS-based risk maps were developed to identify dengue risks in each MOH area in the district and models were developed to identify risk localities in the studied dengue high-risk areas. Positive correlations were observed with breeding containers, roads and land use during spatial correlation analysis in the high risk study areas. During COMPONENT 3 of the study, identification of dengue vector mosquito species and other mosquito species was performed. Different mosquito species were collected from the field and complete 'Folmer region' Cytochrome c Oxidase (COI) DNA barcodes were developed for 21 species of mosquitoes belong to six genera in Sri Lanka. When COI barcodes analyses utilizing distance and phylogenetic methods compared with morphological identification revealed that the mean inter-species Kimura-2-parameter pairwise divergence ranged from 7.0% to 25.4%, while that for intra-species ranged from 0.0% to 1.4%. The developed COI-based DNA barcoding approach can be used to discriminate mosquito species in the district and the study reported the presence of Culex pipiens mosquito for the first time in Sri Lanka. During COMPONENT 4 of the study, development of an Autocidal Gravid Ovitraps (AGO) with an Insect Growth Regulator (IGR) to control dengue vector mosquitoes was performed. The optimum field dosage of Novaluron in the developed Autocidal Gravid Ovitraps (AGO) was 2 ppm and the residual effect was 28 days. In the field experiments, significantly higher mortality counts of mosquito larvae were recorded in the treated area in both indoor and outdoor ovitraps. Two factor repeated measures Analysis of Variation (ANOVA) followed by the Tukey’s test confirmed that the mean mortality count is high for the developed AGOs in both indoor and outdoor settings. - Even though the mode of action of Novaluron is 100% clear, molecular docking experiments indicated that Novaluron shows greater affinity towards chitin synthase and interacts with tryptophan (try) residue at 872 position. KEYWORDS: Dengue, District of Gampaha, Phylogeny and phylogeography, Mathematical and GIS modelling, DNA barcoding, Autocidal Gravid Ovitrap, Molecular modelling