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.
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.
MethodsTo 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
ResultsThe 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
ConclusionTo 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.
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.
Throughout history, the human race has often faced pandemics with substantial numbers of fatalities. As the COVID-19 pandemic has now affected the whole planet, even countries with moderate to strong healthcare support and expenditure have struggled to contain disease transmission and casualties. Countries affected by COVID-19 have different demographics, socioeconomic, and lifestyle health indicators. In this context, it is important to find out to what extent these parametric variations are modulating disease outcomes. To answer this, this study selected demographic, socioeconomic, and health indicators e.g., population density, percentage of the 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 positive tests, case fatality, and case recovery rates were statistically analyzed. The results suggested that countries with variable median age had a significantly different outcome on positive test rate (P < 0.01). Both the median age (P = 0.0397) and health expenditure per capita (P = 0.0041) showed a positive relation with case recovery. An increasing number of tests per 100 K of the population showed a positive and negative relationship with the number of positives per 100 K population (P = 0.0001) and the percentage of positive tests (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 a statistical relation to the 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 a better recovery rate. Investment in the health sector alone is insufficient in controlling the severity of the pandemic. Intelligent and sustainable healthcare both in urban and rural settings and healthy lifestyle acquired immunity may reduce disease transmission and comorbidity induced fatalities, respectively.
BackgroundCOVID-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.
MethodsTo 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
ResultsThe 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
ConclusionTo 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.
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