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

Natural selection shapes the evolution of SARS-CoV-2 Omicron in Bangladesh

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has evolved to give rise to a highly transmissive and immune-escaping variant of concern, known as Omicron. Many aspects of the evolution of SARS-CoV-2 and the driving forces behind the ongoing Omicron outbreaks remain unclear. Substitution at the receptor-binding domain (RBD) in the spike protein is one of the primary strategies of SARS-CoV-2 Omicron to hinder recognition by the host angiotensin-converting enzyme 2 (ACE2) receptor and avoid antibody-dependent defense activation. Here, we scanned for adaptive evolution within the SARS-CoV-2 Omicron genomes reported from Bangladesh in the public database GISAID (www.gisaid.org; dated 2 April 2023). The ratio of the non-synonymous (Ka) to synonymous (Ks) nucleotide substitution rate, denoted as ω, is an indicator of the selection pressure acting on protein-coding genes. A higher proportion of non-synonymous to synonymous substitutions (Ka/Ks or ω > 1) indicates positive selection, while Ka/Ks or ω near zero indicates purifying selection. An equal amount of non-synonymous and synonymous substitutions (Ka/Ks or ω = 1) refers to neutrally evolving sites. We found evidence of adaptive evolution within the spike (S) gene of SARS-CoV-2 Omicron isolated from Bangladesh. In total, 22 codon sites of the S gene displayed a signature of positive selection. The data also highlighted that the receptor-binding motif within the RBD of the spike glycoprotein is a hotspot of adaptive evolution, where many of the codons had ω > 1. Some of these adaptive sites at the RBD of the spike protein are known to be associated with increased viral fitness. The M gene and ORF6 have also experienced positive selection. These results suggest that although purifying selection is the dominant evolutionary force, positive Darwinian selection also plays a vital role in shaping the evolution of SARS-CoV-2 Omicron in Bangladesh

Genomics, social media and mobile phone data enable mapping of SARS-CoV-2 lineages to inform health policy in Bangladesh.

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

Predicting and Designing Epitope Ensemble Vaccines against HTLV-1

The infection mechanism and pathogenicity of Human T-lymphotropic virus 1 (HTLV-1) are ambiguously known for hundreds of years. Our knowledge about this virus is recently emerging. The purpose of the study is to design a vaccine targeting the envelope glycoprotein, GP62, an outer membrane protein of HTLV-1 that has an increased number of epitope binding sites. Data collection, clustering and multiple sequence alignment of HTLV-1 glycoprotein B, variability analysis of envelope Glycoprotein GP62 of HTLV-1, population protection coverage, HLA-epitope binding prediction, and B-cell epitope prediction were performed to predict an effective vaccine. Among all the predicted peptides, ALQTGITLV and VPSSSTPL epitopes interact with three MHC alleles. The summative population protection coverage worldwide by these epitopes as vaccine candidates was found nearly 70%. The docking analysis revealed that ALQTGITLV and VPSSSTPL epitopes interact strongly with the epitope-binding groove of HLA-A*02:03, and HLA-B*35:01, respectively, as this HLA molecule was found common with which every predicted epitope interacts. Molecular dynamics simulations of the docked complexes show they form stable complexes. So, these potential epitopes might pave the way for vaccine development against HTLV-1

Event based surveillance of Middle East Respiratory Syndrome Coronavirus (MERS- CoV) in Bangladesh among pilgrims and travelers from the Middle East: An update for the period 2013–2016

<div><p>Introduction</p><p>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.</p><p>Methods</p><p>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.</p><p>Results</p><p>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.</p><p>Conclusions</p><p>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.</p></div

Respiratory viral pathogens detected in pilgrims and returning travelers.

<p>Respiratory viral pathogens detected in pilgrims and returning travelers.</p

Testing of respiratory viral pathogens in 2013 to 2016 by month.

<p>Testing of respiratory viral pathogens in 2013 to 2016 by month.</p

Demographic characteristics of 81 patients tested, October 2013 to June 2016.

<p>Demographic characteristics of 81 patients tested, October 2013 to June 2016.</p

Seasonality of influenza and coseasonality with avian influenza in Bangladesh, 2010-19: a retrospective, time-series analysis.

BACKGROUND: Seasonal and avian influenza viruses circulate among human and poultry populations in Bangladesh. However, the epidemiology of influenza is not well defined in this setting. We aimed to characterise influenza seasonality, examine regional heterogeneity in transmission, and evaluate coseasonality between circulating influenza viruses in Bangladesh. METHODS: In this retrospective, time-series study, we used data collected between January, 2010, and December, 2019, from 32 hospital-based influenza surveillance sites across Bangladesh. We estimated influenza peak timing and intensity in ten regions using negative binomial harmonic regression models, and applied meta-analytic methods to determine whether seasonality differed across regions. Using live bird market surveillance data in Dhaka, Bangladesh, we estimated avian influenza seasonality and examined coseasonality between human and avian influenza viruses. FINDINGS: Over the 10-year study period, we included 8790 human influenza cases and identified a distinct influenza season, with an annual peak in June to July each year (peak calendar week 27·6, 95% CI 26·7-28·6). Epidemic timing varied by region (I2=93·9%; p<0·0001), with metropolitan regions peaking earlier and epidemic spread following a spatial diffusion pattern based on geographical proximity. Comparatively, avian influenza displayed weak seasonality, with moderate year-round transmission and a small peak in April (peak calendar week 14·9, 95% CI 13·2-17·0), which was out of phase with influenza peaks in humans. INTERPRETATION: In Bangladesh, influenza prevention and control activities could be timed with annual seasonality, and regional heterogeneity should be considered in health resource planning. Year-round avian influenza transmission poses a risk for viral spillover, and targeted efforts will be crucial for mitigating potential reassortment and future pandemic threats. FUNDING: Canadian Institute of Health Research Vanier Canada Graduate Scholarship

Bacterial and viral pathogen spectra of acute respiratory infections in under-5 children in hospital settings in Dhaka city.

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<0.0001). Human rhinovirus, HPIV-3, adenovirus, Streptococcus pneumonia, and Klebsiella pneumaniae had significant involvement in coinfections with P values of 0.0001, 0.009 and 0.0001, 0.0001 and 0.001 respectively. Further investigations are required to better understand the clinical roles of the isolated pathogens and their seasonality