Nearly one million Rohingya refugees of Myanmar have fled to neighboring Bangladesh for seeking shelter from systematic oppression since 25 August 2017. The speed and scale of the influx has led to unprecedented growth of the Kutupalong refugee camp of eastern coast of Bangladesh within few months. There is a few study focused on environmental degradation of the refugee camp, however, no study has been done so far to estimate the impact of camp expansion on ecosystem services loss. This study, therefore, made an attempt to estimate the changes of Ecosystem Services Value (ESV) in response to camp expansion for the year July 2017 (pre-camp) and July 2018 by GIS technique and corresponding global value coefficient developed by Costanza et.al. (1997). Land cover map of the study area was prepared by using Landsat 8 satellite data. Results show an overall decrease of vegetation of 2486 hectares, of which 20% were used to expand the camp and 80% were deforested. Total ecosystem service values of the study area reduced dramatically, from 51.53×106 US$ to 49.12×106 US$ in the study period. This represents a 4.63% net decline in annual value of ecosystem services in the study area. In terms of 2 km buffer of the camp, the net decline rate is found 32.58%. The significant changes are also recorded in individual ecosystem services function of the area. Hence, the findings of this study may motivate the Bangladesh government to develop better plans to protect the ecologically sensitive forested land and wildlife habitats surrounding the refugee camps and assist in more sustainable resource mobilization for the Rohingya refugees.

The COVID-19 pandemic has increased the risk of global public health and has the potential to cause severe food and water insecurity due to economic recession during lockdown for people living in low-middle income countries like Bangladesh where capital resources are scarce. There is growing evidence that household food and water insecurity has been associated with poor psychological outcomes. The objective of this study was to determine the association between household food and water insecurity with mental health and whether these differed among urban-rural households. A cross-sectional online survey was conducted with 545 participants immediately after the COVID-19 lockdown period in Bangladesh (August 1-September 30, 2020). Household food and water security were determined using a 9-item Household Food Insecurity Access Scale (HFIAS) (score range 0-27) and a 12-item Household Water Insecurity Experiences (HWISE) scale (score range 0-36), respectively. The Perceived Stress Scale (PSS) was used to evaluate mental health. Multivariable logistic regression examined the association between household food and water insecurity with perceived stress, adjusting socioeconomic characteristics. An urban-rural stratified analysis was also performed. About 72.84% (397) respondents reported high stress and more than 70% of households suffered from food and water insecurity during the lockdown period. After adjusting covariates, logistic regression model results show that food insecurity was associated with a 1.07-point increase in high perceived stress (OR=1.07, 95% CI=1.01-1.11, p<0.01) while water insecurity was associated with 1.03 times greater odds of high perceived stress (OR=1.03, 95% CI=0.93-1.23, p<0.05). In stratified analysis, only food insecurity was associated with high perceived stress in the urban household (OR=1.08, 95% CI=1.00-1.11, p<0.05). However, none of the household insecurity was associated with perceived stress in rural households. Interventions that promote equal access to resources for low-income individuals will likely to be more effective to alleviate economic burden of pandemic.

A flu-like disease (COVID-19) caused by a novel coronavirus has emerged in Wuhan, China in December, 2019 that is shortly turned into a public health concern globally. The effect of climatic variables on COVID-19 transmission is of paramount importance. However, the interactions are still controversial. This study investigated the association between climatic factors and COVID-19 spread in Dhaka megacity, Bangladesh. Data on the daily confirmed new cases of COVID-19 and climate parameters were collected from March 8, 2020 to April 30, 2020 in Dhaka City, Bangladesh. A log-linked negative binomial regression model was applied to estimate the association between climatic factors and transmission of COVID-19 cases. The daily new confirmed cases of COVID-19 were found positively associated with 14-days moving average of the daily average temperature (AvgT) and Relative Humidity (RH). Each 1°C increase of AvgT was associated with 2.76 times increase of daily confirmed new cases whereas 1% increase of RH was linked to an increase of 18% of the daily confirmed new cases of COVID-19. The study also found RH to be the stronger predictor and moderator between the AvgT and the daily cases of COVID-19 in Dhaka City. The results provide no evidence that COVID-19 could fade out itself when warmer season arrives. Thus, effective public health control measures must be implemented to prevent the further transmission of COVID-19.