It has been more than 10 months since the first COVID-19 case was reported in Wuhan, China, still menacing the world with a possible second wave. This study aimed to analyze how meteorological variables can affect the spread of local COVID-19 transmission in Bangladesh. Nine spatial units were considered from a meteorological standpoint to characterize COVID-19 transmission in Bangladesh. The daily COVID-19 incidence and meteorological variable (e.g., mean temperature, relative humidity, precipitation, and wind speed) data from April 5 to September 20, 2020, were collected. The Spearman rank correlation, heat maps, and multivariate quasi-Poisson regression were employed to understand their association. The effect of meteorological variables on COVID-19 transmission was modeled using a lag period of 10 days. Results showed that mean temperature, relative humidity, and wind speed are substantially associated with an increased risk of COVID-19. On the other hand, daily precipitation is significantly associated with a decreased risk of COVID-19 incidence. The relative risks (RR) of mean temperature for daily COVID-19 incidences were 1.222 (95% confidence interval [CI], 1.214–1.232). For wind speed, the RR was 1.087 (95% CI, 1.083–1.090). For relative humidity, the RR was 1.027 (95% CI, 1.025–1.029). Overall, this study found the profound effect of meteorological parameters on COVID-19 incidence across selected nine areas in Bangladesh. This study is probably the first study to explore the impact of region-specific meteorological conditions on COVID-19 incidence in Bangladesh. Moreover, adjustments on the areal-aggregated and regional levels were made for three confounding factors, including lockdown, population density, and potential seasonal effects. The study’s findings suggest that SARS-CoV-2 can be transmitted in high temperatures and humidity conditions, which contradicts many other countries’ prior studies. The research outcomes will provide implications for future control and prevention measures in Bangladesh and other countries with similar climate conditions and population density.

On December 31, 2019, the World Health Organization (WHO) was informed that atypical pneumonia-like cases have emerged in Wuhan City, Hubei province, China. WHO identified it as a novel coronavirus and declared a global pandemic on March 11th, 2020. At the time of writing this, the COVID-19 claimed more than 440 thousand lives worldwide and led to the global economy and social life into an abyss edge in the living memory. As of now, the confirmed cases in Bangladesh have surpassed 100 thousand and more than 1343 deaths putting startling concern on the policymakers and health professionals; thus, prediction models are necessary to forecast a possible number of cases in the future. To shed light on it, in this paper, we presented data-driven estimation methods, the Long Short-Term Memory (LSTM) networks, and Logistic Curve methods to predict the possible number of COVID-19 cases in Bangladesh for the upcoming months. The results using Logistic Curve suggests that Bangladesh has passed the inflection point on around 28-30 May 2020, a plausible end date to be on the 2nd of January 2021 and it is expected that the total number of infected people to be between 187 thousand to 193 thousand with the assumption that stringent policies are in place. The logistic curve also suggested that Bangladesh would reach peak COVID-19 cases at the end of August with more than 185 thousand total confirmed cases, and around 6000 thousand daily new cases may observe. Our findings recommend that the containment strategies should immediately implement to reduce transmission and epidemic rate of COVID-19 in upcoming days.

Background Bangladesh is going through an unprecedented crisis since the onset of the COVID-19 pandemic. Throughout the COVID-19 pandemic, the reproduction number of COVID-19 swarmed in the scientific community and public media due to its simplicity in explaining an infectious disease dynamic. This paper aims to estimate the effective reproduction number (Rt) for COVID-19 over time in Bangladesh and its districts using reported cases. Methods Adapted methods derived from Bettencourt and Ribeiro (2008), which is a sequential Bayesian approach using the compartmental Susceptible-Infectious-Recovered (SIR) model, have been used to estimate Rt. Findings As of July 21, the mean Rt is 1.32(0.98-1.70, 90% HDI), with a median of 1.16(0.99-1.34 90% HDI). The initial Rt of Bangladesh was 3, whereas the Rt on the day of imposing nation-wide lockdown was 1.47, at the end of lockdown phase 1 was 1.06, at the end of lockdown phase 2 was 1.33. Each phase of nation-wide lockdown has contributed to the decline of effective reproduction number (Rt) for Bangladesh by 28.44%, and 26.70%, respectively, implying moderate effectiveness of the epidemic response strategies. Interpretation and Conclusion The mean Rt fell by 13.55% from May 31 to July 21, 2020, despite easing of lockdown in Bangladesh. The Rt continued to fall below the threshold value one steadily from the beginning of July and sustained around 1. The mean Rt fell by 13.55% from May 31 to July 21, 2020, despite easing of lockdown in Bangladesh. As of July 21, the current estimate of Rt is 1.07(0.92-1.15: 90% HDI), meaning that an infected individual is spreading the virus to an average of one other, with 0.07 added chance of infecting a second individual. This whole research recommends two things- broader testing and careful calibration of measures to keep Rt a long way below the crucial threshold one.

Experts have been searching for ways to mitigate the impacts of climate change on resources since the early 20th century. In response, the World Economic Forum introduced the concept of a “nexus”, which involves the simultaneous, systematic collaboration of multiple individuals or sectors, such as water, energy, and food, in order to create an integrated approach to reducing resource scarcity through a multi-disciplinary framework. In contrast, a circular economy (CE) involves restructuring material flows from a linear economic system and closing the loop on resource exploitation. Both the nexus and CE have been developed to address the overexploitation of resources, but they also contribute to the Sustainable Development Goals (SDGs) and decouple carbon emissions from economic growth. This study explores the potential of combining the nexus and CE to pursue the SDGs on a global scale. Our findings reveal significant research gaps and policy implementation challenges in developing countries, as well as the potential consequences of adopting integrative scenarios. Finally, we propose a system dynamics model as a way to address the difficulties of coupling policies and to better understand the interdependencies between different parts of the economy.

Community confidence in institutional approaches to emergency management directs how they cooperate and comply with public policy responses. In the context of emerging COVID-19 pandemic risk management, this study aims to assess public confidence in the Government of Bangladesh (GoB) and private sector entities for the activities undertaken during preparedness, prevention, and response phases. A survey was conducted with 307 respondents who willingly took part in the study. Cronbach's alpha was calculated to assess the internal reliability and the Mann-Whitney U test was conducted to estimate the mean score difference between the observations. A confirmatory factor analysis (CFA) was applied in the study. The findings suggest that the participants were highly positive about the GoB efforts to organize and provide PPE for doctors in time as a safeguard against COVID-19 and coordination and informed decision making in relation to facing COVID-19. Overall, the participants showed a lower-level confidence in the preparedness and response measures taken by authorities in Bangladesh. The results explored how the GoB failed to reach the public satisfaction level regarding provision of food and financial support to low income and middle income people. A lack of collaboration and coordination among different inter-GoB and private sectors makes mitigation and recovery process difficult. This research provides a set of policy recommendations for future public health emergency management based on the participants' concerns and suggestions, and a review of consequences of policy responses in the early stage.