The ongoing COVID-19 pandemic has caused unprecedented public health concern in Bangladesh. This study investigated the role of Non-Pharmaceutical Interventions on COVID-19 transmission and post-lockdown scenarios of 64 administrative districts and the country as a whole based on the spatiotemporal variations of effective reproduction number ( R t ) of COVID-19 incidences. The daily confirmed COVID-19 data of Bangladesh and its administrative districts from March 8, 2020, to March 10, 2021, were used to estimate R t . This study finds that the maximum value of R t reached 4.15 (3.43, 4.97, 95% CI) in late March 2020, which remained above 1 afterwards in most of the districts. Containment measures are moderately effective in reducing transmission by 24.03%. The R t was established below 1 from early December 2020 for overall Bangladesh and a gradual increase of R t above 1 has been seen from early February 2021. The basic reproduction number ( R 0 ) in Bangladesh probably varied around 2.02 (1.33–3.28, 95% CI). This study finds a significant positive correlation (r = 0.75) between population density and COVID-19 incidence and explaining 56% variation in Bangladesh. The findings of this study are expected to support the policymakers to adopt appropriate measures for curbing the COVID-19 transmission effectively.

In recent time, landslide has become the major concern in the southeast part of Bangladesh. The study aims to develop comprehensive landslide risk mapping by applying the analytical hierarchy process (AHP) and geospatial techniques in Ukhiya and Teknaf Upazilas (highly populated Rohingya Refugee Settlement area) located in the southeast part of Bangladesh. To assess the landslide risk, 12 influencing criteria of hazard, vulnerability and exposure such as precipitation intensity, landslide inventory, distance to fault line, stream density, distance to stream network, elevation, aspect, slope, geology, normalized difference vegetation index (NDVI), landuse-landcover (LULC), and population density have been selected under the relevant components of risk. The spatial criteria were weighted using AHP, and the weighted overlay techniques were used to produce the risk map. The findings demonstrate that 2.19% of the total area is classified as a very-high risk zone and 12.74% is categorized as a high-risk zone. Moderate risk areas cover 23.08% of the total area. The risk map is validated by the landslides inventory. The outcomes can be used by any of the concerned authorities to take the necessary steps to reduce the impact of landslides.