Molecular characterization of lumpy skin disease virus (LSDV) emerged in Bangladesh reveals unique genetic features compared to contemporary field strains.

BACKGROUND: Lumpy skin disease (LSD) is a contagious viral disease of cattle caused by lumpy skin disease virus (LSDV). LSD has recently spread in Asia following outbreaks in the Middle East and Europe. The disease emerged in Bangladesh in July 2019 in the Chattogram district, then rapidly spread throughout the entire country. We investigated six LSD outbreaks in Bangladesh to record the clinical signs and collect samples for diagnostic confirmation. Furthermore, we performed the molecular characterization of Bangladesh isolates, analyzing the full RPO30 and GPCR genes and the partial EEV glycoprotein gene. RESULTS: Clinical observations revealed common LSD clinical signs in the affected cattle. PCR and real-time PCR, showed the presence of the LSDV genome in samples from all six districts. Phylogenetic analysis and detailed inspection of multiple sequence alignments revealed that Bangladesh isolates differ from common LSDV field isolates encountered in Africa, the Middle East, and Europe, as well as newly emerged LSDV variants in Russia and China. Instead, they were closely related to LSDV KSGP-0240, LSDV NI2490, and LSDV Kenya. CONCLUSIONS: These results show the importance of continuous monitoring and characterization of circulating strains and the need to continually refine the strategies for differentiating vaccine strains from field viruses.

Clinical and laboratory characteristics and outcome predictors of cerebral venous sinus thrombosis in a referral neurology hospital in Bangladesh.

OBJECTIVE: We aimed to describe clinical and laboratory characteristics and determine the predictors of outcome in patients with cerebral venous sinus thrombosis. METHODS: This prospective study was conducted over 2 years among hospitalized patients with cerebral venous sinus thrombosis. Patient outcome was assessed using the Modified Rankin Scale (mRS) score at 3 months. Outcome predictors were identified using logistic regression analysis. RESULTS: Eighty-one patients were included in this study. The median mRS outcome at 3 months was 1 (interquartile range 1-3). Poor outcomes were observed in 27.2% of patients, and the mortality rate was 9.8%. Factors associated with poor outcomes were age >60 years (relative risk [RR] 5.1), hemiparesis (RR 5.4), altered level of consciousness (RR 7.1), and transverse sinus involvement (RR 1.1). In general, mRS scores were not associated with D-dimer levels (RR 2.4). However, older patients with elevated D-dimer levels showed a significant association with poor outcomes (1.6) according to mRS scores. CONCLUSION: Older age, hemiparesis, and altered consciousness levels were independent predictors of poor outcomes in patients with cerebral venous sinus thrombosis. High D-dimer level showed no association with functional disability, except in older patients.

Association of climate factors with dengue incidence in Bangladesh, Dhaka City: A count regression approach.

Background: In Bangladesh, particularly in Dhaka city, dengue fever is a major factor in serious sickness and hospitalization. The weather influences the temporal and geographical spread of the vector-borne disease dengue in Dhaka. As a result, rainfall and ambient temperature are considered macro factors influencing dengue since they have a direct impact on Aedes aegypti population density, which changes seasonally dependent on these critical variables. This study aimed to clarify the relationship between climatic variables and the incidence of dengue disease. Methods: A total of 2253 dengue and climate data were used for this study. Maximum and minimum temperature (°C), humidity (grams of water vapor per kilogram of air g.kg-1), rainfall (mm), sunshine hour (in (average) hours per day), and wind speed (knots (kt)) in Dhaka were considered as the independent variables for this study which trigger the dengue incidence in Dhaka city, Bangladesh. Missing values were imputed using multiple imputation techniques. Descriptive and correlation analyses were performed for each variable and stationary tests were observed using Dicky Fuller test. However, initially, the Poisson model, zero-inflated regression model, and negative binomial model were fitted for this problem. Finally, the negative binomial model is considered the final model for this study based on minimum AIC values. Results: The mean of maximum and minimum temperature, wind speed, sunshine hour, and rainfall showed some fluctuations over the years. However, a mean number of dengue cases reported a higher incidence in recent years. Maximum and minimum temperature, humidity, and wind speed were positively correlated with dengue cases. However, rainfall and sunshine hours were negatively associated with dengue cases. The findings showed that factors such as maximum temperature, minimum temperature, humidity, and windspeed are crucial in the transmission cycles of dengue disease. On the other hand, dengue cases decreased with higher levels of rainfall. Conclusion: The findings of this study will be helpful for policymakers to develop a climate-based warning system in Bangladesh.