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.
The ongoing COVID-19 pandemic has caused unprecedented public health concern in Bangladesh. This study investigated the role of Non-Pharmaceutical Interventions on COVID-19 transmission and post-lockdown scenarios of 64 administrative districts and the country as a whole based on the spatiotemporal variations of effective reproduction number ( R t ) of COVID-19 incidences. The daily confirmed COVID-19 data of Bangladesh and its administrative districts from March 8, 2020, to March 10, 2021, were used to estimate R t . This study finds that the maximum value of R t reached 4.15 (3.43, 4.97, 95% CI) in late March 2020, which remained above 1 afterwards in most of the districts. Containment measures are moderately effective in reducing transmission by 24.03%. The R t was established below 1 from early December 2020 for overall Bangladesh and a gradual increase of R t above 1 has been seen from early February 2021. The basic reproduction number ( R 0 ) in Bangladesh probably varied around 2.02 (1.33–3.28, 95% CI). This study finds a significant positive correlation (r = 0.75) between population density and COVID-19 incidence and explaining 56% variation in Bangladesh. The findings of this study are expected to support the policymakers to adopt appropriate measures for curbing the COVID-19 transmission effectively.
The development of a dengue (DENV) vaccine remains challenging due to the heteroserotypic infection, which can result in a potentially deadly hemorrhagic fever or dengue shock syndrome, and only a tetravalent vaccine can overcome this issue. Here, we report the immunogenicity of DENV envelope protein domain 3 (ED3) from all four DENV serotypes (DENV1–4) in Swiss albino and BALB/c mice models. Firstly, we observed that despite having very similar sequences and structures, both the humoral and cellular immunogenicity of ED3s varied significantly, with strength ranging from DENV2 ED3 (2ED3)~3ED3 > 1ED3 > 4ED3, which was assessed through anti-ED3 IgG titers, and DENV1 ED3 (1ED3) > 2ED3~3ED3 > 4ED3 as determined by monitoring T-cell memory (CD44+CD62L+ T cells with IL-4 and IFN-γ expression). Secondly, anti-1ED3 sera cross-reacted with 2ED3 and 3ED3; anti-2ED3 and anti-3ED3 sera cross-reacted with each other, but anti-4ED3 was completely serotype-specific. The lack of reciprocity of anti-1ED3’s cross-reaction was unanticipated. Such disparity in the ED3 responses and cross-reaction might underlie the appearance of hemorrhagic fever and dengue shock syndrome. Hence, the development of an ED3-based tetravalent subunit vaccine would require understanding the aforementioned disparities.
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