ABSTRAK Vaksinasi adalah salah satu cara pengendalian penyakit fl u burung pada usaha peternakan unggas. Terdapat beberapa faktor yang menentukan keputusan peternak dalam implementasi vaksinasi, yaitu: jenis unggas, pengalaman peternak dalam usaha peternakan unggas, pola pengelolaan usaha peternakan unggas, peran usaha peternakan unggas terhadap pendapatan rumah tangga, skala usaha peternakan unggas, tingkat kematian unggas, biaya kesehatan unggas, dan kasus penyakit fl u burung. Hasil analisis menunjukkan bahwa jenis unggas dan peran usaha peternakan unggas terhadap pendapatan rumah tangga berpengaruh nyata terhadap keputusan peternak dalam implementasi vaksinasi fl u burung. Kenyataannya, implementasi vaksinasi fl u burung lebih efektif pada usaha peternakan unggas mandiri karena risiko penyakit ditanggung sendiri oleh peternak. Selain itu, implementasi vaksinasi fl u burung juga lebih efektif pada usaha peternakan unggas yang belum pernah terkena penyakit fl u burung, khususnya usaha peternakan unggas petelur. Hal yang harus diperhatikan adalah bahwa implementasi vaksinasi fl u burung lebih efektif jika didukung penerapan biosekuriti pada usaha peternakan unggas.
Background: Assessing the vulnerability of an infectious disease such as dengue among endemic population is an important requirement to design proactive programmes in order to improve resilience capacity of vulnerable communities. Despite the significance in decision making process especially for rational resource allocation, recognition of actual burden of dengue, the vulnerability of dengue has been limitedly addressed in many countries including Sri Lanka, due to some in a holistic methodology.Methods: A total of 42 variables (entomological, epidemiological, meteorological parameters, landuse practices and socio-demographic data) of all the 38 Medical Officer of Health (MOH) areas in the districts of Colombo and Kandy were considered as candidate variables for composite index based vulnerability assessment. The Principal Component Analysis (PCA) was used in selecting and setting the weight for each indicator. Exposure, Sensitivity, Adaptive Capacity and Vulnerability of all the MOH areas for dengue incidence were calculated.Results: Out of 42 candidate variables, only 23 parameters (Exposure Index: 6 variables; Sensitivity Index: 11 variables; Adaptive Capacity Index: 6 variables) were selected as the indicators to assess climate change vulnerability to dengue. Colombo Municipal Council (CMC) MOH area denoted the highest values for exposure (0.89: exceptionally high exposure), sensitivity (0.86: exceptionally high sensitivity) in the district of Colombo, while Kandy Municipal Council (KMC) area reported the highest exposure (0.79: high exposure) and sensitivity (0.77: high sensitivity) in Kandy. Piliyandala MOH area denoted the highest level of adaptive capacity (0.66) in the district of Colombo followed by Menikhinna (0.68) in Kandy. The highest vulnerability (0.45: moderate vulnerability) to dengue was receded from CMC and the lowest indicated from Galaha MOH (0.15; very low vulnerability) in Kandy. Interestingly the Kandy Municipal Council MOH area had a notable vulnerability of 0.41 (moderate vulnerability), which remained the highest within Kandy.Conclusions: In general, vulnerability for dengue was relatively higher within the MOH areas of Colombo, than in Kandy, suggesting a higher degree of potential susceptibility to dengue within among local communities of Colombo. The VCE are recommended to consider the spatial variations in vulnerability of local communities to dengue for decision making, especially in allocation of limited financial, human and mechanical resources for dengue epidemic management.
Background: Assessing the vulnerability of an infectious disease such as dengue among endemic population is an important requirement to design proactive programmes in order to improve resilience capacity of vulnerable communities. Despite the significance in decision making process especially for rational resource allocation, the recognition of actual burden of dengue and the vulnerability towards dengue, has been limitedly addressed in many countries including Sri Lanka, due to deficiencies in a holistic methodology. Methods: A total of 42 variables (entomological, epidemiological, meteorological parameters, land-use practices and socio-demographic data) of all the 38 Medical Officer of Health (MOH) areas in the districts of Colombo and Kandy were considered as candidate variables for a composite index based vulnerability assessment. The Principal Component Analysis (PCA) was used in selecting and setting the weight for each indicator. Exposure, Sensitivity, Adaptive Capacity and Vulnerability of all the MOH areas for dengue incidence were calculated. Results: Out of 42 candidate variables, only 23 parameters (Exposure Index: 6 variables; Sensitivity Index: 11 variables; Adaptive Capacity Index: 6 variables) were selected as indicators to assess climate change vulnerability to dengue. Colombo Municipal Council (CMC) MOH area denoted the highest values for exposure (0.89: exceptionally high exposure), sensitivity (0.86: exceptionally high sensitivity) in the district of Colombo, while Kandy Municipal Council (KMC) area reported the highest exposure (0.79: high exposure) and sensitivity (0.77: high sensitivity) in Kandy. Piliyandala MOH area denoted the highest level of adaptive capacity (0.66) in the district of Colombo followed by Menikhinna (0.68) in Kandy. The highest vulnerability (0.45: moderate vulnerability) to dengue was indicated from CMC and the lowest indicated from Galaha MOH (0.15; very low vulnerability) in Kandy. Interestingly the Kandy Municipal Council MOH area had a notable vulnerability of 0.41 (moderate vulnerability), which was the highest within Kandy. Conclusions: In general, vulnerability for dengue was relatively higher within the MOH areas of Colombo, than in Kandy, suggesting a higher degree of potential susceptibility to dengue within and among local communities of Colombo. The Vector Controlling Entities (VCE) are recommended to consider the spatial variations in vulnerability of local communities to dengue for decision making, especially in allocation of limited financial, human and mechanical resources for dengue epidemic management
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