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In recent years, special attention has been given to emission research that led to the deposition of toxicants from road traffic. Thus, it is imperative to focus on heavy metal (HM) stressors in food items, their source contribution, and health risk assessment providing insight into their spatial role at the population level. In this study, heavy metal in the street vended noodles was studied while correlating the quality of noodle with different environmental origins. The samples were prepared using acid digestion and analysed by flame atomic absorption spectrophotometer, except Hg which was analysed by direct mercury analyser. The results showed that some heavy metals like Cr, Pb, Mn, Cd, and Hg exceed their permissible limits established by the international legislation for food products. In the noodle samples, the concentration of heavy metal ranged from < 0.1 to 0.904 mg/kg for Pb, < 0.09 to 0.843 mg/kg for Ni, < 0.004 to 0.201 mg/kg for Cd, < 0.0001 to 0.004 mg/kg for Hg, < 0.01 to 1.388 mg/kg for Cu, < 0.015 to 8.049 mg/kg for Mn, and < 0.02 to 16.514 mg/kg for Cr. Noodle samples vended on high traffic density streets are directly associated with increased HM content due to atmospheric deposition from the surrounding. Source apportionment study determines that HM contamination belongs to the same source of origin, except Cr. Based on the cluster analysis, these samples fall into three major groups that were further validated by the canonical discriminant function. Health risk prediction by Monte Carlo simulation revealed an elevated non-carcinogenic health hazard risk to consumers with a hazard index (HI) shift from 71 to 75%. Health hazard analysis showed that consumers of high traffic density street vended food are at higher risk of developing health-related issues. This study is important to evaluate the health risk of the population exposed to heavy metals due to ingestion of street vended food., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

The Coronavirus Disease 2019 (COVID-19) spread rapidly from China to most other countries around the world in early 2020 killing millions of people. To prevent virus spread, world governments implemented a variety of response measures. This paper's objectives were to discuss the country's adopted measures to combat the virus through June 2020, identify gaps in the measures' effectiveness, and offer possible mitigations to those gaps. The measures taken included screening device deployment across international air and land ports, flight suspensions and closures from COVID-19 affected countries, and declaration and extension of a national public holiday (equivalent to lockdowns in other countries). Identified gaps were test kit, PPE, ICU beds, and ventilator shortages, limited public awareness, and insufficient coordination and collaboration among national and international partners. Proper and timely risk mapping, preparedness, communication, coordination, and collaboration among governments and organizations, and public awareness and engagement would have provided sufficient COVID-19 mitigation in Bangladesh., (© 2022. The Author(s).)

The outbreak of coronavirus disease 2019 (COVID-19), caused by the virus severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has already created emergency situations in almost every country of the world. The disease spreads all over the world within a very short period of time after its first identification in Wuhan, China in December, 2019. In India, the outbreak, starts on 2 nd March, 2020 and after that the cases are increasing exponentially. Very high population density, the unavailability of specific medicines or vaccines, insufficient evidences regarding the transmission mechanism of the disease also make it more difficult to fight against the disease properly in India. Mathematical models have been used to predict the disease dynamics and also to assess the efficiency of the intervention strategies in reducing the disease burden. In this work, we propose a mathematical model to describe the disease transmission mechanism between the individuals. Our proposed model is fitted to the daily new reported cases in India during the period 2 nd March, 2020 to 12 th November, 2020. We estimate the basic reproduction number, effective reproduction number and epidemic doubling time from the incidence data for the above-mentioned period. We further assess the effect of implementing preventive measures in reducing the new cases. Our model projects the daily new COVID-19 cases in India during 13 th November, 2020 to 25 th February, 2021 for a range of intervention strength. We also investigate that higher intervention effort is required to control the disease outbreak within a shorter period of time in India. Moreover, our analysis reveals that the strength of the intervention should be increased over the time to eradicate the disease effectively., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier Ltd. All rights reserved.)