Two decades of endemic dengue in Bangladesh (2000-2022): trends, seasonality, and impact of temperature and rainfall patterns on transmission dynamics.

The objectives of this study were to compare dengue virus (DENV) cases, deaths, case-fatality ratio [CFR], and meteorological parameters between the first and the recent decades of this century (2000-2010 vs. 2011-2022) and to describe the trends, seasonality, and impact of change of temperature and rainfall patterns on transmission dynamics of dengue in Bangladesh. For the period 2000-2022, dengue cases and death data from Bangladesh's Ministry of Health and Family Welfare's website, and meteorological data from the Bangladesh Meteorological Department were analyzed. A Poisson regression model was performed to identify the impact of meteorological parameters on the monthly dengue cases. A forecast of dengue cases was performed using an autoregressive integrated moving average model. Over the past 23 yr, a total of 244,246 dengue cases were reported including 849 deaths (CFR = 0.35%). The mean annual number of dengue cases increased 8 times during the second decade, with 2,216 cases during 2000-2010 vs. 18,321 cases during 2011-2022. The mean annual number of deaths doubled (21 vs. 46), but the overall CFR has decreased by one-third (0.69% vs. 0.23%). Concurrently, the annual mean temperature increased by 0.49 °C, and rainfall decreased by 314 mm with altered precipitation seasonality. Monthly mean temperature (Incidence risk ratio [IRR]: 1.26), first-lagged rainfall (IRR: 1.08), and second-lagged rainfall (IRR: 1.17) were significantly associated with monthly dengue cases. The increased local temperature and changes in rainfall seasonality might have contributed to the increased dengue cases in Bangladesh.

Corrigendum: Association of household fuel with acute respiratory infection (ARI) under-five years children in Bangladesh.

[This corrects the article DOI: 10.3389/fpubh.2022.985445.].

The 2022 dengue outbreak in Bangladesh: hypotheses for the late resurgence of cases and fatalities.

Bangladesh reported the highest number of annual deaths (n = 281) related to dengue virus infection in 2022 since the virus reappeared in the country in 2000. Earlier studies showed that >92% of the annual cases occurred between the months of August and September. The 2022 outbreak is characterized by late onset of dengue cases with unusually higher deaths in colder months, that is, October-December. Here we present possible hypotheses and explanations for this late resurgence of dengue cases. First, in 2022, the rainfall started late in the season. Compared to the monthly average rainfall for September and October between 2003 and 2021, there was 137 mm of additional monthly rainfall recorded in September and October 2022. Furthermore, the year 2022 was relatively warmer with a 0.71°C increased temperature than the mean annual temperature of the past 20 yr. Second, a new dengue virus serotype, DENV-4, had recently reintroduced/reappeared in 2022 and become the dominant serotype in the country for a large naïve population. Third, the post-pandemic return of normalcy after 2 yr of nonpharmaceutical social measures facilitates extra mosquito breeding habitats, especially in construction sites. Community engagement and regular monitoring and destruction of Aedes mosquitoes' habitats should be prioritized to control dengue virus outbreaks in Bangladesh.

Early childhood developmental status and its associated factors in Bangladesh: a comparison of two consecutive nationally representative surveys.

BACKGROUND: Inadequate cognitive and socio-emotional development in children leads to physical and mental illness. We aimed to investigate the status of early childhood development (ECD) and its associated factors. Additionally, aimed to compare the changes of significantly associated factors using two multiple indicator cluster surveys (MICS) in Bangladesh. METHODS: We used data from the Multiple Indicator Cluster Surveys (MICS) 2012 and 2019 nationally representative surveys. A total of 17,494 children aged 36-59 months were included in the analysis. The outcome variable was ECD status: either developmentally on-track or not. We used bivariable analysis and crude and adjusted multivariable logistic models to assess the ECD status and its associated factors. RESULTS: Comparing both MICS surveys, the overall and individual domains of ECD status improved from 2012 (65.46%) to 2019 (74.86%), and the indicators of child literacy-numeracy domain improved from 21.2 to 28.8%, physical domain improved from 92.2 to 98.4%, and social-emotional domain improved from 68.4 to 72.7%. The learning approach domain was 87.5% in 2012 and increased to 91.4% in 2019. According to the adjusted logistic model in both surveys (2012 and 2019), the age of 4 years had an adjusted odds ratio (AOR) of 1.61 and 1.78 times higher developmentally on track than the age of 3. Female children were 1.42 (in 2012) and 1.44 (in 2019) times more developmentally on track than males. Compared to mothers with only primary education, children raised by mothers with secondary or higher education were 1.77 and 1.50 times more on track in their development. Moreover, Children from affluent families had 1.32- and 1.26 times higher odds- on track than those from the poorest families. Families with books had 1.50 and 1.53 times higher developmentally on track than their counterparts. CONCLUSION AND RECOMMENDATION: In summary, our study shows that the overall ECD status improved between MICS 2012 and MICS 2019. Important factors influence ECD status, including early childhood education programs, families' possession of children's books, mothers' educational level, and wealth index. The findings of our study will help making necessary public health-related initiatives in Bangladesh to improve ECD program.

Insight into vaccination and meteorological factors on daily COVID-19 cases and mortality in Bangladesh.

The ongoing COVID-19 contagious disease caused by SARS-CoV-2 has disrupted global public health, businesses, and economies due to widespread infection, with 676.41 million confirmed cases and 6.77 million deaths in 231 countries as of February 07, 2023. To control the rapid spread of SARS-CoV-2, it is crucial to determine the potential determinants such as meteorological factors and their roles. This study examines how COVID-19 cases and deaths changed over time while assessing meteorological characteristics that could impact these disparities from the onset of the pandemic. We used data spanning two years across all eight administrative divisions, this is the first of its kind--showing a connection between meteorological conditions, vaccination, and COVID-19 incidences in Bangladesh. We further employed several techniques including Simple Exponential Smoothing (SES), Auto-Regressive Integrated Moving Average (ARIMA), Auto-Regressive Integrated Moving Average with explanatory variables (ARIMAX), and Automatic forecasting time-series model (Prophet). We further analyzed the effects of COVID-19 vaccination on daily cases and deaths. Data on COVID-19 cases collected include eight administrative divisions of Bangladesh spanning March 8, 2020, to January 31, 2023, from available online servers. The meteorological data include rainfall (mm), relative humidity (%), average temperature (°C), surface pressure (kPa), dew point (°C), and maximum wind speed (m/s). The observed wind speed and surface pressure show a significant negative impact on COVID-19 cases (-0.89, 95% confidence interval (CI): 1.62 to -0.21) and (-1.31, 95%CI: 2.32 to -0.29), respectively. Similarly, the observed wind speed and surface pressure show a significant negative impact on COVID-19 deaths (-0.87, 95% CI: 1.54 to -0.21) and (-3.11, 95%CI: 4.44 to -1.25), respectively. The impact of meteorological factors is almost similar when vaccination information is included in the model. However, the impact of vaccination in both cases and deaths model is significantly negative (for cases: 1.19, 95%CI: 2.35 to -0.38 and for deaths: 1.55, 95%CI: 2.88 to -0.43). Accordingly, vaccination effectively reduces the number of new COVID-19 cases and fatalities in Bangladesh. Thus, these results could assist future researchers and policymakers in the assessment of pandemics, by making thorough efforts that account for COVID-19 vaccinations and meteorological conditions.

Correlation of Dengue and Meteorological Factors in Bangladesh: A Public Health Concern.

Dengue virus (DENV) is an enveloped, single-stranded RNA virus, a member of the Flaviviridae family (which causes Dengue fever), and an arthropod-transmitted human viral infection. Bangladesh is well known for having some of Asia's most vulnerable Dengue outbreaks, with climate change, its location, and it's dense population serving as the main contributors. For speculation about DENV outbreak characteristics, it is crucial to determine how meteorological factors correlate with the number of cases. This study used five time series models to observe the trend and forecast Dengue cases. Current data-based research has also applied four statistical models to test the relationship between Dengue-positive cases and meteorological parameters. Datasets were used from NASA for meteorological parameters, and daily DENV cases were obtained from the Directorate General of Health Service (DGHS) open-access websites. During the study period, the mean of DENV cases was 882.26 ± 3993.18, ranging between a minimum of 0 to a maximum of 52,636 daily confirmed cases. The Spearman's rank correlation coefficient between climatic variables and Dengue incidence indicated that no substantial relationship exists between daily Dengue cases and wind speed, temperature, and surface pressure (Spearman's rho; r = -0.007, p > 0.05; r = 0.085, p > 0.05; and r = -0.086, p > 0.05, respectively). Still, a significant relationship exists between daily Dengue cases and dew point, relative humidity, and rainfall (r = 0.158, p < 0.05; r = 0.175, p < 0.05; and r = 0.138, p < 0.05, respectively). Using the ARIMAX and GA models, the relationship for Dengue cases with wind speed is -666.50 [95% CI: -1711.86 to 378.86] and -953.05 [-2403.46 to 497.36], respectively. A similar negative relation between Dengue cases and wind speed was also determined in the GLM model (IRR = 0.98). Dew point and surface pressure also represented a negative correlation in both ARIMAX and GA models, respectively, but the GLM model showed a positive association. Additionally, temperature and relative humidity showed a positive correlation with Dengue cases (105.71 and 57.39, respectively, in the ARIMAX, 633.86, and 200.03 in the GA model). In contrast, both temperature and relative humidity showed negative relation with Dengue cases in the GLM model. In the Poisson regression model, windspeed has a substantial significant negative connection with Dengue cases in all seasons. Temperature and rainfall are significantly and positively associated with Dengue cases in all seasons. The association between meteorological factors and recent outbreak data is the first study where we are aware of the use of maximum time series models in Bangladesh. Taking comprehensive measures against DENV outbreaks in the future can be possible through these findings, which can help fellow researchers and policymakers.

Variant-specific deleterious mutations in the SARS-CoV-2 genome reveal immune responses and potentials for prophylactic vaccine development.

Introduction: Coronavirus disease 2019 (COVID-19), caused by SARS-CoV-2, has had a disastrous effect worldwide during the previous three years due to widespread infections with SARS-CoV-2 and its emerging variations. More than 674 million confirmed cases and over 6.7 million deaths have been attributed to successive waves of SARS-CoV-2 infections as of 29th January 2023. Similar to other RNA viruses, SARS-CoV-2 is more susceptible to genetic evolution and spontaneous mutations over time, resulting in the continual emergence of variants with distinct characteristics. Spontaneous mutations of SARS-CoV-2 variants increase its transmissibility, virulence, and disease severity and diminish the efficacy of therapeutics and vaccines, resulting in vaccine-breakthrough infections and re-infection, leading to high mortality and morbidity rates. Materials and methods: In this study, we evaluated 10,531 whole genome sequences of all reported variants globally through a computational approach to assess the spread and emergence of the mutations in the SARS-CoV-2 genome. The available data sources of NextCladeCLI 2.3.0 (https://clades.nextstrain.org/) and NextStrain (https://nextstrain.org/) were searched for tracking SARS-CoV-2 mutations, analysed using the PROVEAN, Polyphen-2, and Predict SNP mutational analysis tools and validated by Machine Learning models. Result: Compared to the Wuhan-Hu-1 reference strain NC 045512.2, genome-wide annotations showed 16,954 mutations in the SARS-CoV-2 genome. We determined that the Omicron variant had 6,307 mutations (retrieved sequence:1947), including 67.8% unique mutations, more than any other variant evaluated in this study. The spike protein of the Omicron variant harboured 876 mutations, including 443 deleterious mutations. Among these deleterious mutations, 187 were common and 256 were unique non-synonymous mutations. In contrast, after analysing 1,884 sequences of the Delta variant, we discovered 4,468 mutations, of which 66% were unique, and not previously reported in other variants. Mutations affecting spike proteins are mostly found in RBD regions for Omicron, whereas most of the Delta variant mutations drawn to focus on amino acid regions ranging from 911 to 924 in the context of epitope prediction (B cell & T cell) and mutational stability impact analysis protruding that Omicron is more transmissible. Discussion: The pathogenesis of the Omicron variant could be prevented if the deleterious and persistent unique immunosuppressive mutations can be targeted for vaccination or small-molecule inhibitor designing. Thus, our findings will help researchers monitor and track the continuously evolving nature of SARS-CoV-2 strains, the associated genetic variants, and their implications for developing effective control and prophylaxis strategies.

The disproportionate case-fatality ratio of COVID-19 between countries with the highest vaccination rates and the rest of the world.

Objectives: The global reported cumulative case-fatality ratios (rCFRs) and excess mortality rates of the 20 countries with the highest coronavirus disease 2019 (COVID-19) vaccination rates, the rest of the world and Sub-Saharan Africa (SSA) were compared before and after the commencement of vaccination programmes. Methods: A time series model was used to understand the trend of rCFR over time, and a generalized linear mixed model was used to understand the effect of vaccination on rCFR. Results: By 31 December 2022, an average of 260.3 doses of COVID-19 vaccine per 100 population had been administered in the top 20 vaccinated countries, compared with 152.1 doses in the rest of the world and 51.2 doses in SSA. The mean rCFR of COVID-19 had decreased by 69.0% in the top 20 vaccinated countries, 26.5% in the rest of the world and 7.6% in SSA. Excess mortality had decreased by 48.7% in the top 20 vaccinated countries, compared with 62.5% in the rest of the world and 60.7% in SSA. In a generalized linear mixed model, the reported number of vaccine doses administered (/100 population) (odds ratio 0.64) was associated with a steeper reduction in COVID-19 rCFR. Conclusions: Vaccine equity and faster roll-out across the world is critically important in reducing COVID-19 transmission and CFR.

A 30-day follow-up study on the prevalence of SARS-COV-2 genetic markers in wastewater from the residence of COVID-19 patient and comparison with clinical positivity.

Wastewater based epidemiology (WBE) is an important tool to fight against COVID-19 as it provides insights into the health status of the targeted population from a small single house to a large municipality in a cost-effective, rapid, and non-invasive way. The implementation of wastewater based surveillance (WBS) could reduce the burden on the public health system, management of pandemics, help to make informed decisions, and protect public health. In this study, a house with COVID-19 patients was targeted for monitoring the prevalence of SARS-CoV-2 genetic markers in wastewater samples (WS) with clinical specimens (CS) for a period of 30 days. RT-qPCR technique was employed to target nonstructural (ORF1ab) and structural-nucleocapsid (N) protein genes of SARS-CoV-2, according to a validated experimental protocol. Physiological, environmental, and biological parameters were also measured following the American Public Health Association (APHA) standard protocols. SARS-CoV-2 viral shedding in wastewater peaked when the highest number of COVID-19 cases were clinically diagnosed. Throughout the study period, 7450 to 23,000 gene copies/1000 mL were detected, where we identified 47 % (57/120) positive samples from WS and 35 % (128/360) from CS. When the COVID-19 patient number was the lowest (2), the highest CT value (39.4; i.e., lowest copy number) was identified from WS. On the other hand, when the COVID-19 patients were the highest (6), the lowest CT value (25.2 i.e., highest copy numbers) was obtained from WS. An advance signal of increased SARS-CoV-2 viral load from the COVID-19 patient was found in WS earlier than in the CS. Using customized primer sets in a traditional PCR approach, we confirmed that all SARS-CoV-2 variants identified in both CS and WS were Delta variants (B.1.617.2). To our knowledge, this is the first follow-up study to determine a temporal relationship between COVID-19 patients and their discharge of SARS-CoV-2 RNA genetic markers in wastewater from a single house including all family members for clinical sampling from a developing country (Bangladesh), where a proper sewage system is lacking. The salient findings of the study indicate that monitoring the genetic markers of the SARS-CoV-2 virus in wastewater could identify COVID-19 cases, which reduces the burden on the public health system during COVID-19 pandemics.

Effects of fine particulate matter (PM2.5) and meteorological factors on the daily confirmed cases of COVID-19 in Bangkok during 2020-2021, Thailand.

The ongoing global pandemic caused by the SARS-CoV-2 virus, known as COVID-19, has disrupted public health, businesses, and economies worldwide due to its widespread transmission. While previous research has suggested a possible link between environmental factors and increased COVID-19 cases, the evidence regarding this connection remains inconclusive. The purpose of this research is to determine whether or not there is a connection between the presence of fine particulate matter (PM2.5) and meteorological conditions and COVID-19 infection rates in Bangkok, Thailand. The study employs a statistical method called Generalized Additive Model (GAM) to find a positive and non-linear association between RH, AH, and R and the number of verified COVID-19 cases. The impacts of the seasons (especially summer) and rainfall on the trajectory of COVID-19 cases were also highlighted, with an adjusted R-square of 0.852 and a deviance explained of 85.60%, both of which were statistically significant (p < 0.05). The study results assist in preventing the future seasonal spread of COVID-19, and public health authorities may use these findings to make informed decisions and assess their policies.

Association of household fuel with acute respiratory infection (ARI) under-five years children in Bangladesh.

In developing countries, acute respiratory infections (ARIs) cause a significant number of deaths among children. According to Bangladesh Demographic and Health Survey (BDHS), about 25% of the deaths in children under-five years are caused by ARI in Bangladesh every year. Low-income families frequently rely on wood, coal, and animal excrement for cooking. However, it is unclear whether using alternative fuels offers a health benefit over solid fuels. To clear this doubt, we conducted a study to investigate the effects of fuel usage on ARI in children. In this study, we used the latest BDHS 2017-18 survey data collected by the Government of Bangladesh (GoB) and estimated the effects of fuel use on ARI by constructing multivariable logistic regression models. From the analysis, we found that the crude (the only type of fuel in the model) odds ratio (OR) for ARI is 1.69 [95% confidence interval (CI): 1.06-2.71]. This suggests that children in families using contaminated fuels are 69.3% more likely to experience an ARI episode than children in households using clean fuels. After adjusting for cooking fuel, type of roof material, child's age (months), and sex of the child-the effect of solid fuels is similar to the adjusted odds ratio (AOR) for ARI (OR: 1.69, 95% CI: 1.05-2.72). This implies that an ARI occurrence is 69.2% more likely when compared to the effect of clean fuel. This study found a statistically significant association between solid fuel consumption and the occurrence of ARI in children in households. The correlation between indoor air pollution and clinical parameters of ARI requires further investigation. Our findings will also help other researchers and policymakers to take comprehensive actions by considering fuel type as a risk factor as well as taking proper steps to solve this issue.

Association between Global Monkeypox Cases and Meteorological Factors.

The emergence of an outbreak of Monkeypox disease (MPXD) is caused by a contagious zoonotic Monkeypox virus (MPXV) that has spread globally. Yet, there is no study investigating the effect of climatic changes on MPXV transmission. Thus, studies on the changing epidemiology, evolving nature of the virus, and ecological niche are highly paramount. Determination of the role of potential meteorological drivers including temperature, precipitation, relative humidity, dew point, wind speed, and surface pressure is beneficial to understand the MPXD outbreak. This study examines the changes in MPXV cases over time while assessing the meteorological characteristics that could impact these disparities from the onset of the global outbreak. To conduct this data-based research, several well-accepted statistical techniques including Simple Exponential Smoothing (SES), Auto-Regressive Integrated Moving Average (ARIMA), Automatic forecasting time-series model (Prophet), and Autoregressive Integrated Moving Average with Explanatory Variables (ARIMAX) were applied to delineate the correlation of the meteorological factors on global daily Monkeypox cases. Data on MPXV cases including affected countries spanning from 6 May 2022, to 9 November 2022, from global databases and meteorological data were used to evaluate the developed models. According to the ARIMAX model, the results showed that temperature, relative humidity, and surface pressure have a positive impact [(51.56, 95% confidence interval (CI): -274.55 to 377.68), (17.32, 95% CI: -83.71 to 118.35) and (23.42, 95% CI: -9.90 to 56.75), respectively] on MPXV cases. In addition, dew/frost point, precipitation, and wind speed show a significant negative impact on MPXD cases. The Prophet model showed a significant correlation with rising MPXD cases, although the trend predicts peak values while the overall trend increases. This underscores the importance of immediate and appropriate preventive measures (timely preparedness and proactive control strategies) with utmost priority against MPXD including awareness-raising programs, the discovery, and formulation of effective vaccine candidate(s), prophylaxis and therapeutic regimes, and management strategies.

Knowledge of HIV/AIDS among married women in Bangladesh: analysis of three consecutive multiple indicator cluster surveys (MICS).

Married women have a higher risk of contracting human immunodeficiency virus (HIV) or develop acquired immune deficiency syndrome (AIDS) than men. Knowledge of HIV/AIDS contributes significantly to describing the prevalence and consequences of such virus/disease. The study aimed to investigate the level of HIV/AIDS knowledge and the socio-demographic variables that influence HIV/AIDS knowledge among married women in Bangladesh. We used three waves of Multiple Indicator Cluster Survey (MICS), which included 33,843, 20,727, and 29,724 married women from 2006, 2012, and 2019 MICS. A score was prepared through their interrogation to determine the level of knowledge and logistic regression models were used for analyzing the data. This study found that the prevalence of knowledge level of HIV/AIDS in different questions increased from 55.20% in 2006 to 58.69% in 2019. In our study, respondents having highest education had 4.03 (95% CI 3.50-4.64) times more chance to obtain "High Score" in 2019 MICS which is 5.30 times in 2012 MICS (95% CI 4.41-6.37) and 2.58 times in 2006 MICS (95% CI 2.28-2.93) compared to illiterate married women. Moreover, respondents from urban area were 1.13 times more likely to obtain "High Score" in 2019 MICS which is 1.14 times in 2012 MICS and 1.16 times in 2006 MICS, respectively than the rural married women. This study also found respondent's age, division, mass media access, and wealth status have played an important role in HIV/AIDS knowledge. Although a significant proportion of women had adequate knowledge of HIV/AIDS, more knowledge is still required to protect against such viruses/diseases. Thus, we advocate for the implementation of educational program in the curriculum, counselling, particularly in rural areas, and mass media access to ensure quality knowledge throughout the country.

An opinion on Wastewater-Based Epidemiological Monitoring (WBEM) with Clinical Diagnostic Test (CDT) for detecting high-prevalence areas of community COVID-19 Infections.

Wastewater-Based Epidemiological Monitoring (WBEM) is an efficient surveillance tool during the COVID-19 pandemic as it meets all requirements of a complete monitoring system including early warning, tracking the current trend, prevalence of the disease, detection of genetic diversity as well asthe up-surging SARS-CoV-2 new variants with mutations from the wastewater samples. Subsequently, Clinical Diagnostic Test is widely acknowledged as the global gold standard method for disease monitoring, despite several drawbacks such as high diagnosis cost, reporting bias, and the difficulty of tracking asymptomatic patients (silent spreaders of the COVID-19 infection who manifest nosymptoms of the disease). In this current reviewand opinion-based study, we first propose a combined approach) for detecting COVID-19 infection in communities using wastewater and clinical sample testing, which may be feasible and effective as an emerging public health tool for the long-term nationwide surveillance system. The viral concentrations in wastewater samples can be used as indicatorsto monitor ongoing SARS-CoV-2 trends, predict asymptomatic carriers, and detect COVID-19 hotspot areas, while clinical sampleshelp in detecting mostlysymptomaticindividuals for isolating positive cases in communities and validate WBEM protocol for mass vaccination including booster doses for COVID-19.

Knowledge, attitude, and practice towards blood donation among residential students and teachers of religious institutions in Bangladesh - A cross-sectional study.

The availability of voluntary nonremunerated blood donors is a major concern in low- and middle-income countries because there is a substantial scarcity of safe blood supply against the expected demand. This study explores the status of knowledge, attitude, and practice regarding blood donation among students and teachers of residential religious academic institutions in Jamalpur district in Bangladesh. Religious institutions were selected through simple random sampling, and the cross-sectional survey included 512 participants. Descriptive and inferential statistics were performed with statistical significance defined as p < 0.05. Over 90% of the participants were students, non-smokers, and aged 18-30 years. The majority (92%) did not ever donate blood to anyone, yet over 42% wanted to be regular donors. More than 80% considered blood donation a moral responsibility and an Islamic act. The common reasons for not donating blood were lack of knowledge (40%), lack of opportunity (20%), thinking it was harmful to health (21%), fearing needles (16%), and no financial benefit (6%). Interestingly, more than 67% did not know their blood group, and about 61% of the respondents said they did not hear of or could not remember any blood donation program. The participants had poor knowledge of general eligibility criteria but an overall positive attitude towards blood donation. There was a weak positive correlation between knowledge, attitude, and practice scores. Participants willing to donate blood to strangers were four times more likely to do so regularly. Those who considered blood donation a religious act and a moral responsibility were twice as likely to become regular blood donors. This study reveals that many potential donors are being neglected, although they may be a valuable resource in addressing the ongoing blood donation issue.

Knowledge, Attitude and Practices Toward Coronavirus Disease (COVID- 19) in Southeast and South Asia: A Mixed Study Design Approach.

Background: Coronavirus has spread to almost every country since its emergence in Wuhan, China and countries have been adopted an array of measures to control the rapid spread of the epidemic. Here, we aimed to assess the person's knowledge, attitude and practices (KAP) toward the COVID-19 epidemic in Southeast and South Asia applying the mixed study design (cross-sectional and systematic review). Methods: In the cross-sectional study, 743 respondents' socio-demographic and KAP-related information was collected through an online population-based survey from the Malaysian population. In the systematic review, the database PubMed, Web of Science and Google Scholar search engine were searched and related published articles from South and Southeast Asia were included. Frequency distribution, Chi-square association test and binary logistic regression were fitted using cross-sectional data whereas random effect model and study bias were performed in meta-analysis. We used 95% confidence interval and P <0.05 as statistical significances. Results: The prevalence of good knowledge, positive attitude and frequent practice toward COVID-19 epidemic were 52.6%, 51.8% and 57.1%, respectively, obtained by cross-sectional data analysis. The KAP prevalence were ranged from 26.53% (Thailand) to 95.4% (Nepal); 59.3% (Turkey) to 92.5% (Pakistan); and 50.2 (Turkey) to 97% (Afghanistan), respectively, obtained by 18 studies included in the meta-analysis. The prevalence of KAP was higher [84% vs. 79%, Pheterogeneity <0.001; 83% vs. 80%, Pheterogeneity <0.001; 85% vs. 83%, Pheterogeneity <0.001] in South Asia compared to Southeast Asia, obtained by subgroup analysis. Some studies reported mean level instead of the proportion of the KAP where the score varied from 8.15-13.14; 2.33-33.0; and 1.97-31.03, respectively. Having more knowledge and attitude were encouraged more likely to practice toward COVID-19. Study suggests age, gender, education, place of residence and occupation as the most frequent significant risk factors of KAP toward COVID-19. Conclusion: The study sufficiently informs how other countries in Southeast and South Asia enriches their KAP behaviors during the pandemic which may help health professionals and policymakers to develop targeted interventions and effective practices.

Wastewater-based epidemiological surveillance to monitor the prevalence of SARS-CoV-2 in developing countries with onsite sanitation facilities.

Wastewater-based epidemiology (WBE) has emerged as a valuable approach for forecasting disease outbreaks in developed countries with a centralized sewage infrastructure. On the other hand, due to the absence of well-defined and systematic sewage networks, WBE is challenging to implement in developing countries like Bangladesh where most people live in rural areas. Identification of appropriate locations for rural Hotspot Based Sampling (HBS) and urban Drain Based Sampling (DBS) are critical to enable WBE based monitoring system. We investigated the best sampling locations from both urban and rural areas in Bangladesh after evaluating the sanitation infrastructure for forecasting COVID-19 prevalence. A total of 168 wastewater samples were collected from 14 districts of Bangladesh during each of the two peak pandemic seasons. RT-qPCR commercial kits were used to target ORF1ab and N genes. The presence of SARS-CoV-2 genetic materials was found in 98% (165/168) and 95% (160/168) wastewater samples in the first and second round sampling, respectively. Although wastewater effluents from both the marketplace and isolation center drains were found with the highest amount of genetic materials according to the mixed model, quantifiable SARS-CoV-2 RNAs were also identified in the other four sampling sites. Hence, wastewater samples of the marketplace in rural areas and isolation centers in urban areas can be considered the appropriate sampling sites to detect contagion hotspots. This is the first complete study to detect SARS-CoV-2 genetic components in wastewater samples collected from rural and urban areas for monitoring the COVID-19 pandemic. The results based on the study revealed a correlation between viral copy numbers in wastewater samples and SARS-CoV-2 positive cases reported by the Directorate General of Health Services (DGHS) as part of the national surveillance program for COVID-19 prevention. The findings of this study will help in setting strategies and guidelines for the selection of appropriate sampling sites, which will facilitate in development of comprehensive wastewater-based epidemiological systems for surveillance of rural and urban areas of low-income countries with inadequate sewage infrastructure.

Exploring Two Pandemics in Academic Arena: Physical Activity and Sedentary Behaviors Profile of University Students in Bangladesh.

The overlay of the COVID-19 pandemic on the pandemic of physical inactivity has become a great concern. Both types of pandemics can decrease the health protection capacity and consequently increase complexity in human lives. This cross-sectional study intended to examine changes in physical activity and sedentary behaviors during the COVID-19 pandemic among university students in a second-tier city of Bangladesh. Two hundred and nine students responded to an online questionnaire administered via Google Survey. In addition to descriptive statistics, parametric and non-parametric tests for comparing means, medians and distributions were used to assess differences in activity traits before and during the COVID-19 pandemic. Results show that the occurrence of COVID-19 has significantly reduced the practice of walking and physical activities among the students. They are commonly motivated by introjected regulation. Father's occupation and the type of family of a student have significant influences on the total physical activity in either situation. Bangladeshi university students have, particularly, been perceived as not generally used to vigorous physical activities. They are inactive compared to students from other countries. Thus, the public health policymakers and the corresponding authority should inspire the students to be more physically active by implementing different strategies such as increasing bicycling and walking facilities on the campus.

The Global Case-Fatality Rate of COVID-19 Has Been Declining Since May 2020.

The objective of this study was to evaluate the trend of reported case fatality rate (rCFR) of COVID-19 over time, using globally reported COVID-19 cases and mortality data. We collected daily COVID-19 diagnoses and mortality data from the WHO's daily situation reports dated January 1 to December 31, 2020. We performed three time-series models [simple exponential smoothing, auto-regressive integrated moving average, and automatic forecasting time-series (Prophet)] to identify the global trend of rCFR for COVID-19. We used beta regression models to investigate the association between the rCFR and potential predictors of each country and reported incidence rate ratios (IRRs) of each variable. The weekly global cumulative COVID-19 rCFR reached a peak at 7.23% during the 17th week (April 22-28, 2020). We found a positive and increasing trend for global daily rCFR values of COVID-19 until the 17th week (pre-peak period) and then a strong declining trend up until the 53rd week (post-peak period) toward 2.2% (December 29-31, 2020). In pre-peak of rCFR, the percentage of people aged 65 and above and the prevalence of obesity were significantly associated with the COVID-19 rCFR. The declining trend of global COVID-19 rCFR was not merely because of increased COVID-19 testing, because COVID-19 tests per 1,000 population had poor predictive value. Decreasing rCFR could be explained by an increased rate of infection in younger people or by the improvement of health care management, shielding from infection, and/or repurposing of several drugs that had shown a beneficial effect on reducing fatality because of COVID-19.