Medicine
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This repository contains the published and unpublished research of the Faculty of Medicine by the staff members of the faculty
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Item Comprehensive evaluation of demographic, socio-economic and other associated risk factors affecting the occurrence of dengue incidence among Colombo and Kandy Districts of Sri Lanka: a cross-sectional study(BioMed Central, 2018) Udayanga, L.; Gunathilaka, N.; Iqbal, M.C.M.; Lakmal, K.; Amarasinghe, U.S.; Abeyewickreme, W.BACKGROUND: Comprehensive understanding of risk factors related to socio-economic and demographic status and knowledge, attitudes and practices (KAP) of local communities play a key role in the design and implementation of community-based vector management programmes, along with the identification of gaps in existing control activities. METHODS: A total of 10 Medical Officers of Health (MOH) areas recording high dengue incidence over the last five years were selected from Colombo (n = 5) and Kandy (n = 5) Districts, Sri Lanka. From each MOH area, 200 houses reporting past dengue incidence were selected randomly as test group (n = 1000 for each district) based on the dengue case records available at relevant MOH offices. Information on socio-economic and demographic status and knowledge, attitudes and practices were gathered using an interviewer administered questionnaire. The control group contained 200 households from each MOH area that had not reported any dengue case and the same questionnaire was used for the assessment (n = 1000 for each district). Statistical comparisons between the test and control groups were carried out using the Chi-square test of independence, cluster analysis, analysis of similarities (ANOSIM) and multi-dimensional scaling (MDS) analysis. RESULTS: Significant differences among the test and control groups in terms of basic demographic and socio-economic factors, living standards, knowledge, attitude and practices, were recognized (P < 0.05 at 95% level of confidence). 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 and ANOSIM. Findings of the present study highlight the importance of further improvement in community education, motivation and communication gaps, proper coordination and integration of control programmes with relevant entities. Key infrastructural risk factors such as urbanization and waste collection, should be further improved, while vector controlling entities should focus more on the actual conditions represented by the public on knowledge, attitudes and personal protective practices. CONCLUSIONS: The design of flexible and community friendly intervention programmes to ensure the efficacy and sustainability of controlling dengue vectors through community based integrated vector management strategies, is recommended.Item Empirical optimization of risk thresholds for dengue: an approach towards entomological management of Aedes mosquitoes based on larval indices in the Kandy District of Sri Lanka(BioMed Central, 2018) Udayanga, L.; Gunathilaka, N.; Iqbal, M.C.M.; Najim, M.M.M.; Pahalagedara, K.; Abeyewickreme, W.BACKGROUND: Larval indices such as Premise Index (PI), Breteau Index (BI) and Container Index (CI) are widely used to interpret the density of dengue vectors in surveillance programmes. These indices may be useful for forecasting disease outbreaks in an area. However, use of the values of these indices as alarm signals is rarely considered in control programmes. Therefore, the current study aims to propose threshold values for vector indices based on an empirical modeling approach for the Kandy District of Sri Lanka. METHODS: Monthly vector indices, viz PI, BI and CI, for Aedes aegypti and Aedes albopictus, of four selected dengue high risk Medical Officer of Health (MOH) areas in the Kandy District from January 2010 to August 2017, were used in the study. Gumbel frequency analysis was used to calculate the exceedance probability of quantitative values for each individual larval index within the relevant MOH area, individually and to set up the threshold values for the entomological management of dengue vectors. RESULTS: Among the study MOH areas, Akurana indicated a relatively high density of both Ae. aegypti and Ae. albopictus, while Gangawata Korale MOH area had the lowest. Based on Ae. aegypti, threshold values were defined for Kandy as low risk (BIagp > 1.77), risk (BIagp > 3.23), moderate risk (BIagp > 4.47) and high risk (BIagp > 6.23). In addition, PI > 6.75 was defined as low risk, while PI > 9.43 and PI>12.82 were defined as moderate and high risk, respectively as an average. CONCLUSIONS: Threshold values recommended for Ae. aegypti (primary vector for dengue) along with cut-off values for PI (for Ae. aegypti and Ae. albopictus), could be suggested as indicators for decision making in vector control efforts. This may also facilitate the rational use of financial allocations, technical and human resources for vector control approaches in Sri Lanka in a fruitful manner.Item Evaluation of the spatial and temporal trends of dengue outbreaks in Gampola, Central Province, Sri Lanka(University of Peradeniya, 2015) Udayanaga, N.W.B.A.L.; Gunathilaka, H.N.; Iqbal, M.C.M.; Abeyewickreme, W.Dengue is the world's fastest growing vector borne disease, and it has become one of the major health concerns in many countries including Sri Lanka. Despite immense efforts and control strategies it claims 30,000 - 35,000 deaths per year, making dengue a priority heath issue in Sri Lanka. Investigation of the recent trends of dengue outbreaks on both a spatial and temporal scale is of high importance in drafting and implementing effective management/action plans to ensure successful management and control of dengue epidemics on a regional scale. Hence, a statistic and geo informatics based analysis of the recent trends in dengue distribution was carried out to identify spatial and temporal trends in distribution patterns of dengue in the Gampola Medical Officer of Health (MOH) division. Monthly records of reported dengue cases from 2009 to 2013 of the Gampola MOH division were collected. A scatter plot analysis in MINITAB (version 14.12.0) was devised to identify the temporal patterns in the reported dengue cases. Arc GIS (version 10.1) was devised to develop spatial maps (at the GND level) of the recorded dengue case distribution for each month and for the whole study period, for Gampola. Furthermore, spatial (at GND level) and temporal (annual) variations in dengue outbreak distribution within the Gampola MOH were analyzed to recognize the recent trends in dengue distribution. Gampola East, Gampola West, Illawathura, Keerapane, Kahatapitiya, Egodakalugamuwa and Pussellawa localities emerged as high-risk areas, while Polkumbura, Kurukude, Galgediyawa, Amuhena and Hunukotugama emerged as low risk areas for dengue outbreaks. Further localities, namely Godagama, Kalugalhinna, Kekulanda, Millagaspitiya, Sinhapitiya North, Sinhapitiya South, Pussellawagama, Ranawala and Wanahapuwa remained unchallenged by dengue throughout 2009 - 2013. The paired-Chi square test revealed significant spatial and temporal variations in the emergence of dengue outbreaks within the Gampola MOH throughout the study period \>x2 w. 0.95} = 65.156]. Regionalized evaluation of recent trends in temporal and spatial distribution of dengue outbreaks are recommended in the design and implementation of management plans to control the rise of dengue, and also in the evaluation of the effectiveness of already implemented practices taken to reduce and control dengue outbreaks, by the government sector and other relevant entities.Item Evaluation of the spatial and temporal trends of dengue outbreaks in Akurana, Central Province, Sri Lanka(Sri Lanka Association for the Advancement of Science, 2015) Udayanga, N.W.B.A.L.; Gunathilaka, P.A.D.H.N.; Iqbal, M.C.M.; Kusumawathie, P.H.D.; Najim, M.M.M.; Amerasinghe, U.S.; Abeyewickreme, W.Renowned as the world's fastest growing vector borne disease, dengue has become one of the major health issues in Sri Lanka leading to an alarming concern due to recent outbreaks throughout the country. Despite the immense efforts taken by the relevant authorities to reduce the rate of mortality, the average number of dengue cases recorded in each year remains around 30,000-35,000 without being changed significantly over time in Sri Lanka. Investigation of the trends in spatial and temporal distribution patterns of dengue is often treasured in the drafting and implementation of management/action plans to ensure effective management of dengue epidemics at regional scale. Thus, a statistical and geo informatics based analysis of the recent trends in dengue distribution was carried out to identify spatial and temporal trends in distribution patterns of Dengue in the Akurana Medical Officer of Health (MOH) area. Monthly records of reported dengue cases from 2010 to 2014 of the Akurana MOH area were obtained and were subjected to a scatter plot analysis in MINITAB (version 14.12.0) to identify the temporal patterns in the recorded dengue cases. Spatial maps of the recorded dengue case distribution in each GND for each month and for the whole study period were prepared by using Arc GIS 10.1. The spatial and temporal variations of dengue outbreak distribution within the Akurana MOH (at GND level) were analyzed to identify the recent trends in dengue incidence. Akurana, Bulugahathenna, Dippitiya, Dunuwila, Konakalagala and Neeralla localities could be identified as areas with relatively high risk to dengue outbreaks throughout the study period, while localities such as Balakanduwa, Delgasgoda, Delgasthenna, Malgamandeniya, Marahela, Palleweliketiya and Udawelikatiya emerged as areas with low risk. As suggested by the results of the paired-Chi square test [>Χ2 (30, 0.95) = 43.773], the emergence of dengue outbreaks indicated a significantly declining trend of recorded dengue cases in most of the GNDs (Aswadduma, Delgasgoda, Kurugoda, Malgamandeniya, Palleweliketiya and Walahena etc.) during the recent years. The evaluation of the trends in temporal and spatial distribution of dengue outbreaks at the localized level, could be recommended as a useful tool in the planning and implementation of action plans to control the rise of dengue, while evaluating the efficacy of already implemented control measures at regional scale.