Abstract. Global leptospirosis disease burden estimates are hampered by the lack of scientifically sound data from countries with probable high endemicity and limited diagnostic capacities. We describe the seroepidemiologic and clinical characteristics of the leptospirosis outbreak in 2008 in Sri Lanka. Definitive/presumptive case definitions proposed by the World Health Organization Leptospirosis Epidemiology Reference Group were used for case confirmation. Of the 404 possible cases, 155 were confirmed to have leptospirosis. Highest titers of patient seum samples reacted with serovars Pyrogenes (28.7%), Hardjo (18.8%), Javanica (11.5%), and Hebdomadis (11.5%). Sequencing of the 16S ribosomal DNA gene identified six infections: five with Leptospira interrogans and one with L. weilli . In this patient population, acute renal failure was the main complication (14.8%), followed by myocarditis (7.1%) and heart failure (3.9%). The case-fatality rate was 1.3%. This report strengthens the urgent need for increasing laboratory diagnostic capabilities to determine the causes of epidemic and endemic infectious diseases in Sri Lanka, a finding relevant to other tropical regions.

The ongoing COVID-19 outbreak that originated in the city of Wuhan, China, has caused a significant damage to the world population and the global economy. It has claimed more than 0.8 million lives worldwide, and more than 27 million people have been infected as of 07th September 2020. In Sri Lanka, the first case of COVID-19 was reported late January 2020 which was a Chinese national and the first local case was identified in the second week of March. Since then, the government of Sri Lanka introduced various sequential measures to improve social distancing such as closure of schools and education institutes, introducing work from home model to reduce the public gathering, introducing travel bans to international arrivals, and more drastically, imposed island wide curfew expecting to minimize the burden of the disease to the Sri Lankan health system and the entire community. Currently, there are 3123 cases with 12 fatalities and also, it was reported that 2925 patients have recovered and are discharged from hospitals, according to the Ministry of Health, Sri Lanka. In this study, we use the SEIR conceptual model and its modified version by decomposing infected patients into two classes: patients who show mild symptoms and patients who tend to face severe respiratory problems and are required to be treated in intensive care units. We numerically simulate the models for about a five-month period reflecting the early stage of the epidemic in the country, considering three critical parameters of COVID-19 transmission mainly in the Sri Lankan context: efficacy of control measures, rate of overseas imported cases, and time to introduce social distancing measures by the respective authorities.

Aims. Predicting the risk of severity at an early stage in an individual patient will be invaluable in preventing morbidity and mortality caused by dengue. We hypothesized that such predictions are possible by analyzing multiple parameters using mathematical modeling. Methodology. Data from 11 adult patients with dengue fever (DF) and 25 patients with dengue hemorrhagic fever (DHF) were analyzed. Multivariate statistical analysis was performed to study the characteristics and interactions of parameters using dengue NS1 antigen levels, dengue IgG antibody levels, platelet counts, and lymphocyte counts. Fuzzy logic fundamentals were used to map the risk of developing severe forms of dengue. The cumulative effects of the parameters were incorporated using the Hamacher and the OWA operators. Results. The operator classified the patients according to the severity level during the time period of 96 hours to 120 hours after the onset of fever. The accuracy ranged from 53% to 89%. Conclusion. The results show a robust mathematical model that explains the evolution from dengue to its serious forms in individual patients. The model allows prediction of severe cases of dengue which could be useful for optimal management of patients during a dengue outbreak. Further analysis of the model may also deepen our understanding of the pathways towards severe illness.

Factor structure and internal consistency of the current Sinhalese version of the self reported SDQ is not satisfactory. Revalidation of this version of SDQ is recommended to capture the intended objectives of the SDQ.

COVID-19 global outbreak has been significantly damaging the human well-being, life style of people and the global economy. It is clear that the entire world is moving into a dangerous phase of this epidemic at the moment. With absence of a preventive vaccine, the governments across world implement, monitor and manage various public health and social distancing measures to control the spread of this extremely contagious disease and it is found that most of these responses have been critical results of numerous mathematical and decision support models. In this study, SEIR compartment structure is used to model the COVID-19 transmission in Sri Lanka. Reported cases data during the first 80 days of the outbreak is used to model the time dependent transmission rate of the disease. Optimal transmission rates and initial size of the exposed and infected sizes of the populations are then estimated matching between clinically identified cases to model based simulated outcomes.