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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.

Here, we report the coding-complete genome sequences of 40 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) strains of the newly emerged recombinant Omicron variants XBB, XBB.1, and XBB.2. The strains were isolated from nasopharyngeal swab samples that had been collected from symptomatic patients in Bangladesh between September and October 2022 and were sequenced using an Oxford Nanopore Technologies (ONT) system.

We describe an investigation to identify the causative agent and risk factors for a cluster of Guillain-Barre Syndrome (GBS) reported in northern Bangladesh, November 2018. Medical record review and verbal autopsies were conducted. We actively searched for and interviewed other GBS cases in the hospital to gather demographic and clinical information. Blood samples were collected for serological testing for campylobacter and molecular testing for dengue, Zika, and Chikungunya and stool samples for poliovirus. We identified 13 GBS patients of which eight were males. The case fatality rate was 23%. We found development of respiratory muscle paralysis in 10 patients; three had rapid involvement within 48 hours and eventually died in the acute progressive phase without mechanical ventilation support. Serological tests confirmed the presence of antibodies against Campylobacter jejuni in three of seven patients. All other tests were negative. The high case fatality rate was due to rapid onset of respiratory muscle paralysis. We recommend establishing a surveillance system to timely capture and report GBS patients and to enhance investigation capacity. We also recommend that sufficient quantity of mechanical ventilators be present in peripheral tertiary hospitals.

We report the coding-complete genome sequences of 25 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sublineage B.1.1.529 Omicron strains obtained from Bangladeshi individuals in samples collected between December 2021 and January 2022. Genomic data were generated by Nanopore sequencing using the amplicon sequencing approach developed by the ARTIC Network.

Funder: Bill and Melinda Gates Foundation (Bill & Melinda Gates Foundation); doi: https://doi.org/10.13039/100000865, Genomics, combined with population mobility data, used to map importation and spatial spread of SARS-CoV-2 in high-income countries has enabled the implementation of local control measures. Here, to track the spread of SARS-CoV-2 lineages in Bangladesh at the national level, we analysed outbreak trajectory and variant emergence using genomics, Facebook ‘Data for Good’ and data from three mobile phone operators. We sequenced the complete genomes of 67 SARS-CoV-2 samples (collected by the IEDCR in Bangladesh between March and July 2020) and combined these data with 324 publicly available Global Initiative on Sharing All Influenza Data (GISAID) SARS-CoV-2 genomes from Bangladesh at that time. We found that most (85%) of the sequenced isolates were Pango lineage B.1.1.25 (58%), B.1.1 (19%) or B.1.36 (8%) in early-mid 2020. Bayesian time-scaled phylogenetic analysis predicted that SARS-CoV-2 first emerged during mid-February in Bangladesh, from abroad, with the first case of coronavirus disease 2019 (COVID-19) reported on 8 March 2020. At the end of March 2020, three discrete lineages expanded and spread clonally across Bangladesh. The shifting pattern of viral diversity in Bangladesh, combined with the mobility data, revealed that the mass migration of people from cities to rural areas at the end of March, followed by frequent travel between Dhaka (the capital of Bangladesh) and the rest of the country, disseminated three dominant viral lineages. Further analysis of an additional 85 genomes (November 2020 to April 2021) found that importation of variant of concern Beta (B.1.351) had occurred and that Beta had become dominant in Dhaka. Our interpretation that population mobility out of Dhaka, and travel from urban hotspots to rural areas, disseminated lineages in Bangladesh in the first wave continues to inform government policies to control national case numbers by limiting within-country travel.

We report the coding-complete genome sequences of 15 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sublineage B.1.617.2 strains that were obtained from Bangladeshi individuals with a history of recent travel to India and from the Bangladeshi community. Genomic data were generated by Nanopore sequencing using the amplicon sequencing approach developed by the ARTIC Network.

BackgroundNew data streams are being used to track the pandemic of SARS-CoV-2, including genomic data which provides insights into patterns of importation and spatial spread of the virus, as well as population mobility data obtained from mobile phones. Here, we analyse the emergence and outbreak trajectory of SARS-CoV-2 in Bangladesh using these new data streams, and identify mass population movements as a key early event driving the ongoing epidemic.MethodsWe sequenced complete genomes of 67 SARS-CoV-2 samples (March-July 2020) and combined this dataset with 324 genomes from Bangladesh. For phylogenetic context, we also used 68,000 GISAID genomes collected globally. We paired this genomic data with population mobility information from Facebook and three mobile phone operators.FindingsThe majority (85%) of the Bangladeshi sequenced isolates fall into either pangolin lineage B.1.36 (8%), B.1.1 (19%) or B.1.1.25 (58%). Bayesian time-scaled phylogenetic analysis predicted SARS-COV-2 first appeared in mid-February, through international introductions. The first case was reported on March 8th. This pattern of repeated international introduction changed at the end of March when three discrete lineages expanded and spread clonally across Bangladesh. The shifting pattern of viral diversity across Bangladesh is reflected in the mobility data which shows the mass migration of people from cities to rural areas at the end of March, followed by frequent travel between Dhaka and the rest of the country during the following months.InterpretationIn Bangladesh, population mobility out of Dhaka as well as frequent travel from urban hotspots to rural areas resulted in rapid country-wide dissemination of SARS-CoV-2. The strains in Bangladesh reflect the local expansion of global lineages introduced early from international travellers to and from major international travel hubs. Importantly, the Bangladeshi context is consistent with epidemiologic and phylogenetic findings globally. Bangladesh is one of the few countries in the world with a rich history of conducting mass vaccination campaigns under complex circumstances. Combining genomics and these new data streams should allow population movements to be modelled and anticipated rendering Bangladesh extremely well prepared to immunize citizens rapidly. Based on our genomics data and the country’s successful immunization history, vaccines becoming available globally will be suitable for implementation in Bangladesh while ongoing genomic surveillance is conducted to monitor for new variants of the virus.FundingGovernment of Bangladesh, Bill and Melinda Gates Foundation, Wellcome Trust.Research in contextEvidence before this studyThe emergence of SARS-CoV-2, leading to the COVID-19 pandemic, has motivated all countries in the world to obtain high resolution data on the virus. Globally over 300,000 strains have been sequenced and information made available in GISAID. Within the first 100 days of the emergence of SARS-CoV-2, genomic analysis from different countries led to the development of vaccines which have now reached market. Information on the prevailing genotypes of SARS-CoV-2 since introduction is needed in low and middle-income countries (LMICs), including Bangladesh, in order to determine the suitability of therapeutics and vaccines in the pipeline and help vaccine deployment.Added value of this studyWe sequenced SARS-CoV-2 genomes from strains that were prospectively collected during the height of the pandemic and combined these genomic data with mobility data to comprehensively describe i) how repeated international importations of SARS-CoV-2 were ultimately linked to nationwide spread, ii) 85% of strains belonged to the Pangolin lineages B.1.1, B.1.1.25 and B.1.36 and that similar mutation rates were observed as seen globally iii) the switch in genomic dynamics of SARS-CoV-2 coincided with mass migration out of cities to the rest of the country. We have assessed the contributions of population mobility on the maintenance and spread of clonal lineages of SARS-CoV-2. This is the first time these data types have been combined to look at the spread of this virus nationally.Implications of all the available evidenceSARS-CoV-2 genomic diversity and mutation rate in Bangladesh is comparable to strains circulating globally. Notably, the data on the genomic changes of SARS-CoV-2 in Bangladesh is reassuring, suggesting that immunotherapeutic and vaccines being developed globally should also be suitable for this population. Since Bangladesh already has extensive experience of conducting mass vaccination campaigns, such as the rollout of the oral Cholera vaccine, experience of developing and using new data streams will enable efficient and targeted immunization of the population in 2021 with COVID-19 vaccine(s).

To identify the circulating serotype(s) of dengue viruses in Bangladesh, a retrospective molecular identification was performed on stored serum samples of dengue surveillance during the period of 2013–2016. Real time RT-PCR was performed on serum samples collected from the patients with less than 5 days fever for detection of dengue virus nucleic acid. The samples, positive for dengue PCR were further analyzed for serotypes by real time RT-PCR. The overall prevalence of dengue virus infection was varied among 13–42% in study years with a single peak flanked by April to September. Among the four dengue serotypes DEN1 and DEN2 were in the circulation in three metropolitan cities with sequential emergence of DEN1 where DEN2 was persisted constantly during the study period. Persistence of all four serotypes in the neighboring country makes Bangladesh vulnerable for devastating secondary infection by introduction of new serotype(s) other than currently circulating viruses in the country. Thus continuous virological surveillance is crucial for early warning of emergence of new serotype in the circulation and public health preparedness. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s13337-018-0469-x) contains supplementary material, which is available to authorized users.

In this work, wall driven incompressible viscous fluid flow through a tube in the presence of magnetic field is considered. The mathematical model of the problem is formulated and solved using series solution method and Hermite-Pade approximation method. Flow becomes unstable due to movement of wall and existence of magnetic field where critical Reynolds number and critical Hartmann number indicate the point of flow instability. This critical point for instability in terms of Reynolds number and Hartmann number are determined and described using bifurcation diagrams. The effect of these two dimensionless numbers on flow velocity and their interaction on flow stability are discussed.

Introduction Every year around 150,000 pilgrims from Bangladesh perform Umrah and Hajj. Emergence and continuous reporting of MERS-CoV infection in Saudi Arabia emphasize the need for surveillance of MERS-CoV in returning pilgrims or travelers from the Middle East and capacity building of health care providers for disease containment. The Institute of Epidemiology, Disease Control & Research (IEDCR) under the Bangladesh Ministry of Health and Family welfare (MoHFW), is responsible for MERS-CoV screening of pilgrims/ travelers returning from the Middle East with respiratory illness as part of its outbreak investigation and surveillance activities. Methods Bangladeshi travelers/pilgrims who returned from the Middle East and presented with fever and respiratory symptoms were studied over the period from October 2013 to June 2016. Patients with respiratory symptoms that fulfilled the WHO MERS-CoV case algorithm were tested for MERS-CoV and other respiratory tract viruses. Beside surveillance, case recognition training was conducted at multiple levels of health care facilities across the country in support of early detection and containment of the disease. Results Eighty one suspected cases tested by real time PCR resulted in zero detection of MERS-CoV infection. Viral etiology detected in 29.6% of the cases was predominantly influenza A (H1N1 and H3N2), and influenza B infection (22%). Peak testing occurred mostly following the annual Hajj season. Conclusions Respiratory tract infections in travelers/pilgrims returning to Bangladesh from the Middle East are mainly due to influenza A and influenza B. Though MERS-CoV was not detected in the 81 patients tested, continuous screening and surveillance are essential for early detection of MERS-CoV infection and other respiratory pathogens to prevent transmissions in hospital settings and within communities. Awareness building among healthcare providers will help identify suspected cases.

The study aimed to examine for the first time the spectra of viral and bacterial pathogens along with the antibiotic susceptibility of the isolated bacteria in under-5 children with acute respiratory infections (ARIs) in hospital settings of Dhaka, Bangladesh. Nasal swabs were collected from 200 under-five children hospitalized with clinical signs of ARIs. Nasal swabs from 30 asymptomatic children were also collected. Screening of viral pathogens targeted ten respiratory viruses using RT-qPCR. Bacterial pathogens were identified by bacteriological culture methods and antimicrobial susceptibility of the isolates was determined following CLSI guidelines. About 82.5% (n = 165) of specimens were positive for pathogens. Of 165 infected cases, 3% (n = 6) had only single bacterial pathogens, whereas 43.5% (n = 87) cases had only single viral pathogens. The remaining 36% (n = 72) cases had coinfections. In symptomatic cases, human rhinovirus was detected as the predominant virus (31.5%), followed by RSV (31%), HMPV (13%), HBoV (11%), HPIV-3 (10.5%), and adenovirus (7%). Streptococcus pneumoniae was the most frequently isolated bacterial pathogen (9%), whereas Klebsiella pneumaniae, Streptococcus spp., Enterobacter agglomerans, and Haemophilus influenzae were 5.5%, 5%, 2%, and 1.5%, respectively. Of 15 multidrug-resistant bacteria, a Klebsiella pneumoniae isolate and an Enterobacter agglomerans isolate exhibited resistance against more than 10 different antibiotics. Both ARI incidence and predominant pathogen detection rates were higher during post-monsoon and winter, peaking in September. Pathogen detection rates and coinfection incidence in less than 1-year group were significantly higher (P = 0.0034 and 0.049, respectively) than in 1–5 years age group. Pathogen detection rate (43%) in asymptomatic cases was significantly lower compared to symptomatic group (P