Effective hand hygiene is essential for reducing healthcare associated infections. However, compliance of healthcare workers to hand hygiene guidelines are reportedly poor. It is important therefore to instill adequate knowledge and good attitudes and practices at the time of primary training of the healthcare workers. This study was done to identify gaps in knowledge, attitudes and practices to improve existing training programs and enhance good practices and working ethics in the future. A self-administered questionnaire based cross sectional study was done to compare the knowledge, attitudes, practices and satisfaction (KAPS) of facilities between final year medical and nursing students of the Faculty of Medical Sciences, University of Sri Jayewardenepura. Participants had moderate knowledge (77%) but attitudes, practices and satisfaction of facilities of all the participants was overall poor (<50%). However the nursing students had better knowledge (p=0.023), attitudes (p<0.001), practices (p<0.001) and satisfaction of facilities (p<0.001) compared with the medical students. The knowledge, attitudes, practices and satisfaction of facilities of medical and nursing students are unsatisfactory. The study shows the need for further improvement of the existing hand hygiene training programs to address the gaps in knowledge, attitudes and practices. Further, there is a need to improve the facilities available for hand hygiene and make them readily accessible for students at their training centers to enable them to engage in good practices which will be beneficial for them as doctors and nurses in the future.

Aims: Methods:Results: Conclusions: Keywords:Dengue is a major public health concern in Sri Lanka. In the recent dengue epidemics, majority of cases of dengue were reported from the Colombo district.To determine the knowledge attitudes and practices (KAP) regarding dengue fever (DF) in a suburban population in the Colombo District.The study was a prospective, cross sectional study and was conducted in 2005/2006 in a suburb of Colombo district. Data was collected using a pre-tested interviewer-administered questionnaire to assess the knowledge, attitudes and practices of 349 randomly selected residents in the Boralesgamuwa MOH area.Almost all the participants had heard of DF (98%), the media being the most quoted source of information. Based on the scoring system, only 58% had satisfactory knowledge on the symptoms, management and transmission of dengue. Furthermore, 37% of the participants demonstrated satisfactory attitudes and 85% claimed to have used good practices towards dengue.The participants demonstrated gaps in knowledge and poor attitude which may affect the level and frequency of preventive practices. Our findings highlight the need for further information, education and communication programs in the community.

Introduction: Gallstone disease is a major health problem throughout the world. Apart from surgery prompt administration of appropriate antibiotics to control the biliary tract infection is important.

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Introduction:Approximately, 33% patients with diabetes are afflicted with onychomycosis. In the past, nondermatophyte molds have been regarded as opportunistic pathogens; recently, Aspergillus species are considered as emerging pathogens of toenail infections. In Sri Lanka, the prevalence of Aspergillus species in onychomycosis among diabetics is not well documented.Objective:To determine the proportion of Aspergillus onychomycosis, risk factors and knowledge among diabetics.Materials and Methods:This was descriptive cross-sectional study. Three hundred diabetic patients were included. Clinical examinations of patients’ toenails were performed by a clinical microbiologist. Laboratory identification was done, and pathogens were identified to the species level by morpho-physiological methods. All inferential statistics were tested at P < 0.05.Results:Among clinically suspected patients, 85% (255/300) were mycologically confirmed to have onychomycosis. Aspergillus species were most commonly isolated n = 180 (71%) followed by dermatophytes, yeasts, and other molds n = 75 (29%). Of the patients having Aspergillus onychomycosis, 149 (83%) were in the > age group. In men, Aspergillus onycomycosis was seen in 82%. Among patients who had Aspergillus nail infection, 114 (63%) had diabetes for a period of > years. Among patients who were engaged in agricultural activities, 77% were confirmed to have infected nails due to Aspergillus species.Conclusion:Aspergillus niger was the most common pathogen isolated from toenail infection. Aspergillus species should be considered as an important pathogen in toenail onychomycosis in diabetic patients. Risk factors associated with Aspergillus onychomycosis were age, gender, duration of diabetes, length of exposure to fungi, and occupation.

The discovery that Helicobacter pylori (H. pylori) infection is the main cause of most gastro duodenal diseases has dramatically changed the management of these diseases. Antibiotics are the mainstay of treatment. However, prevalence of H. pylori antibiotic resistance is increasing worldwide, and is the main factor affecting the efficacy of current therapeutic regimens.In Sri Lanka, although eradication therapy for H. pylori by antibiotics is commonly advocated, due to a lack of susceptibility data, it has not been possible to formulate suitable guidelines for clinical use.

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Researchers have explored many methods and techniques for human detection and identification in diverse contexts. One such approach is studying variations of Radio Frequency (RF) signals (e.g., Received Signal Strength Indicator (RSSI)). RSSI based techniques have been widely used in human detection, but not for unique human identification due to its noisy nature. This research focused on investigating the possibilities and limitations of device-free human identification using Wi-Fi RSSI data with machine learning-based classification techniques. To inspect the characteristics of Wi-Fi RSSI data, the authors have conducted statistical analysis techniques. A Kalman filter was applied to minimize the noise in Wi-Fi RSSI data, followed by a feature extraction process. Furthermore, the authors have conducted multiple research experiments in different configurations of receivers and participant numbers. The experimental results show that the human identification accuracy level increases with the number of receivers used for the data collection. Moreover, the authors have identified that human identification accuracy can be further improved by leveraging proper noise reduction methods and feature extraction processes. For a Kalman filter applied and feature-extracted Wi-Fi RSSI dataset of 20 people, the Support Vector Machine (SVM) - Radial Kernel model recorded the highest average accuracy of 99.58%.