Summary: Severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) enters the host cell by binding to angiotensin‐converting enzyme 2 (ACE2) receptor. Other important proteins involved in this process include disintegrin and metalloproteinase domain‐containing protein 17 (ADAM17) also known as tumour necrosis factor‐α‐converting enzyme and transmembrane serine protease 2. ACE2 converts angiotensin II (Ang II) to angiotensin (1–7), to balance the renin angiotensin system. Membrane‐bound ACE2 ectodomain shedding is mediated by ADAM17 upon viral spike binding, Ang II overproduction and in several diseases. The shed soluble ACE2 (sACE2) retains its catalytic activity, but its precise role in viral entry is still unclear. Therapeutic sACE2 is claimed to exert dual effects; reduction of excess Ang II and blocking viral entry by masking the spike protein. Nevertheless, the paradox is why SARS‐CoV‐2 comorbid patients struggle to attain such benefit in viral infection despite having a high amount of sACE2. In this review, we discuss the possible detrimental role of sACE2 and speculate on a series of events where protease primed or non‐primed virus–sACE2 complex might enter the host cell. As extracellular virus can bind many sACE2 molecules, sACE2 level could be reduced drastically upon endocytosis by the host cell. A consequential rapid rise in Ang II level could potentially aggravate disease severity through Ang II‐angiotensin II receptor type 1 (AT1R) axis in comorbid patients. Hence, monitoring sACE2 and Ang II level in coronavirus disease 2019 comorbid patients are crucial to ensure safe and efficient intervention using therapeutic sACE2 and vaccines.

The COVID19 pandemic has been transmitted worldwide rapidly. The best ways of preventing this virus are to know about and act accordingly. An online cross sectional survey was conducted to know the knowledge, attitude and practices towards COVID19 and to assess the risks of infections among Bangladeshi population. Among 2045 respondents, 54·87% respondents kept good knowledge. Knowledge was significantly diverged across age, gender, education levels, residences, income groups, and marital status. Despite the knowledge, the attitude and practices of Bangladeshi people are not impressive. Among population, 32·08%, and 44·30% people were in high, and in medium risk of infection respectively. Everybody is in risk. Reasons for the mediocre attitude and practices could be the poor knowledge, nonscientific and orthodox religious believe. Government and policy makers must consider these knowledge levels, attitude & practices and the risk of infection assessment to implement productive interventions for preventing the COVID19.

Background: COVID-19 is transmitting worldwide drastically and infected nearly two and half million of people so far. Till date 2144 cases of COVID-19 is confirmed in Bangladesh till 18 ^th April though the stage-3/4 transmission is not validated yet. Methods: To project the final infection numbers in Bangladesh we used the SIR mathematical model. Confirmed cases of infection data were obtained from Institute of Epidemiology, Disease Control and Research (IEDCR) of Bangladesh Results: The confirmed cases in Bangladesh follow our SIR model prediction cases. By the end of April the predicted cases of infection will be 17450 to 21616 depending on the control strategies. Due to large population and socio-economic characteristics, we assumed 60% social distancing and lockdown can be possible. Assuming that, the predicated final size of infections will be 3782558 on the 92th day from the first infections and steadily decrease to zero infection after 193 days Conclusion: To estimate the impact of social distancing we assumed eight different scenarios, the predicted results confirmed the positive impact of this type of control strategies suggesting that by strict social distancing and lockdown, COVID-19 infection can be under control and then the infection cases will steadily decrease down to zero.

Background: Since its first report on March 08, COVID-19 positive cases and number of deaths are increasing in Bangladesh. In the first month of COVID-19 infection, incidence of daily positive cases did follow the susceptible, infected and recovered (SIR) based predictions we reported in April, but started to deviate in the following months. COVID-19 transmission and disease progression depends on multifaceted determinants e.g. viral genetics, host immunity, social distancing, co-morbidity, socio-demographic and environmental parameters. Therefore deviation in confirmed cases from predicted model may appear and warrant thorough investigation. Methods: In this short report, we compared real data with SIR model and analyzed the possible factors associated with the deviation which included preventive intervention strategies, socioeconomic capabilities, climatic and meteorological indexes, acquired immunity of Bangladeshi population, demographic characteristics, health indicators and food habits. Results: The key factor responsible for the observed deviation was found to be the number of tests performed. Having population with low median age, young age groups are being mostly infected. Low prevalence of non-communicable diseases among them and strong immunity compared to the elderly might have kept most of them asymptomatic with silent recovery. Warm temperature, humidity and UV index of Bangladesh during this summer period might have contributed to the slow progression of infection. Longer daylight mediated immunity, fresh air circulations and ventilation, less population density in rural areas and certain food habits perhaps helped the large number of populations to restrict the infection up to a level. Conclusion: Despite all these helpful determinants in Bangladesh, person to person contact is still the leading risk factor for COVID-19 transmission. Infection may increase rapidly if safe distance and preventive measures are not strictly followed while resuming the normal social and work life. Expanding test capacity, strong collaborative action plans, strategies and implementation are needed immediately to prevent catastrophe. Highlights: Limited number of tests compared to large population was the key reason for possible low daily positive cases reported in Bangladesh. Controlled interventions viz. official leave; transport ban and social distancing had helped initially to slow down the transmission. Warm weather, high humidity and UV index, sunlight mediated immunity, fresh air circulations, low pollutions, food habit and heterologous immunity might have reduced the transmission capabilities of SARS-CoV-2. Having large number of young people with strong immunity might have kept most of the infected asymptomatic who recovered silently. Person to person contact still remain as key risk factor in COVID-19 transmission, so strict health measures should be in place even after reopening social activities to contain further transmission.

Human race has often faced pandemic with substantial number of fatalities. As COVID-19 pandemic reached and endured in every corner on earth, countries with moderate to strong healthcare support and expenditure seemed to struggle in containing disease transmission and casualties. COVID-19 affected countries have variability in demographic, socioeconomic and life style health indicators. At this context it is important to find out at what extent these parametric variations are actually modulating disease outcomes. To answer this, we have selected demographic, socioeconomic and health indicators e.g. population density, percentage of urban population, median age, health expenditure per capita, obesity, diabetes prevalence, alcohol intake, tobacco use, case fatality of non communicable diseases (NCDs) as independent variables. Countries were grouped according to these variables and influence on dependent variables e.g. COVID-19 test positive, case fatality and case recovery rates were statistically analyzed. The results suggest that countries with variable median age has significantly different outcome on test positive rate ( P <0.01). Both median age ( P =0.0397) and health expenditure per capita ( P =0.0041) has positive relation with case recovery. Increasing number of test per 100K population showed positive and negative relation with number of positives per 100K population ( P =0.0001) and percentage of test positives ( P <0.0001) respectively. Alcohol intake per capita in liter ( P =0.0046), diabetes prevalence ( P =0.0389) and NCDs mortalities ( P =0.0477) also showed statistical relation with case fatality rate. Further analysis revealed that countries with high healthcare expenditure along with high median age and increased urban population showed more case fatality but also had better recovery rate. Investment in health sector alone is insufficient in controlling pandemic severity. Intelligent and sustainable healthcare both in urban and rural settings and healthy lifestyle acquired immunity may reduce disease transmission and comorbidity induced fatalities respectively.