Socioeconomic characteristics and constraints of participatory pond fish farmers in Mymensingh district, Bangladesh

The study was conducted to determine the socioeconomic characteristics and constraints of participatory pond fish farmers in Muktagachha upazila (sub-district) under Mymensingh district of Bangladesh. Data were collected by using a structured interview schedule during 01 to 31 October 2018 from a sample of 100 fish farmers (50% of total population) who were selected randomly from a population of 200. Data were analyzed using descriptive statistics, rank order and coefficient of correlation. The majority of the participatory pond fish farmers (90%) faced medium to low constraints. Among 22 constraints, lack of training on aquaculture was identified as the most critical one, followed by high price of various inputs. The least important constraint of the farmers was crisis of water in dry season. It was revealed that fish farming experience, annual family income and training exposure were significantly associated with the constraints of participatory pond fish farmers. It is therefore recommended that the Department of Fisheries (DOF) and other related organizations can offer credit facilities, proper training and suitable extension services to minimize the constraints of participatory pond fish farmers and meet the increasing demand of fish in Bangladesh

Exploring spatial and temporal patterns of visceral leishmaniasis in endemic areas of Bangladesh

Background: Visceral leishmaniasis is a considerable public health burden on the Indian subcontinent. The disease is highly endemic in the north-central part of Bangladesh, affecting the poorest and most marginalized communities. Despite the fact that visceral leishmaniasis (VL) results in mortality, severe morbidity, and socioeconomic stress in the region, the spatiotemporal dynamics of the disease have largely remained unexplored, especially in Bangladesh. Methods: Monthly VL cases between 2010 and 2014, obtained from subdistrict hospitals, were studied in this work. Both global and local spatial autocorrelation techniques were used to identify spatial heterogeneity of the disease. In addition, a spatial scan test was used to identify statistically significant space-time clusters in endemic locations of Bangladesh. Results: Global and local spatial autocorrelation indicated that the distribution of VL was spatially autocorrelated, exhibiting both contiguous and relocation-type of diffusion; however, the former was the main type of VL spread in the study area. The spatial scan test revealed that the disease had ten times higher incidence rate within the clusters than in non-cluster zones. Both tests identified clusters in the same geographic areas, despite the differences in their algorithm and cluster detection approach. Conclusion: The cluster maps, generated in this work, can be used by public health officials to prioritize areas for intervention. Additionally, initiatives to control VL can be handled more efficiently when areas of high risk of the disease are known. Because global environmental change is expected to shift the current distribution of vectors to new locations, the results of this work can help to identify potenti ally exposed populations so that adaptation strategies can be formulated