Excess risk in infant mortality among populations living in flood-prone areas in Bangladesh: A cluster-matched cohort study over three decades, 1988 to 2017.

The Ganges-Brahmaputra-Meghna river basin, running through Tibet, Nepal, Bhutan, Bangladesh, and northern India, is home to more than 618 million people. Annual monsoons bring extensive flooding to the basin, with floods predicted to be more frequent and extreme due to climate change. Yet, evidence regarding the long-term impacts of floods on children's health is lacking. In this analysis, we used high-resolution maps of recent large floods in Bangladesh to identify flood-prone areas over the country. We then used propensity score techniques to identify, among 58,945 mothers interviewed in six demographic population-based surveys throughout Bangladesh, matched cohorts of exposed and unexposed mothers and leverage data on 150,081 births to estimate that living in flood-prone areas was associated with an excess risk in infant mortality of 5.3 (95% CI 2.2 to 8.4) additional deaths per 1,000 births compared to living in non-flood-prone areas over the 30-y period between 1988 and 2017, with higher risk for children born during rainy (7.9, 95% CI: 3.3 to 12.5) vs. dry months (3.1, 95% CI: -1.1 to 7.2). Finally, drawing on national-scale, high-resolution estimates of flood risk and population distribution, we estimated an excess of 152,753 (64,120 to 241,386) infant deaths were attributable to living in flood-prone areas in Bangladesh over the past 30 y, with marked heterogeneity in attributable burden by subdistrict. Our approach demonstrates the importance of measuring longer-term health impacts from floods and provides a generalizable example for how to study climate-related exposures and long-term health effects.

Results of a nationally representative seroprevalence survey of chikungunya virus in Bangladesh.

There is an increasing global burden from chikungunya virus (CHIKV). Bangladesh reported a major epidemic in 2017, however, it was unclear if there had been prior widespread transmission. We conducted a nationally representative seroprevalence survey in 70 randomly selected communities immediately prior to the epidemic. We found 69/2,938 (2.4%) of sampled individuals were seropositive to CHIKV. Being seropositive to dengue virus (aOR 3.13 [95% CIs: 1.86-5.27]), male sex (aOR 0.59 [95% CIs: 0.36-0.99]), and community presence of Aedes aegypti mosquitoes (aOR: 1.80, 95% CI: 1.05-3.07) were significantly associated with CHIKV seropositivity. Using a spatial prediction model, we estimated that across the country, 4.99 (95% CI: 4.89 - 5.08) million people had been previously infected. These findings highlight high population susceptibility prior to the major outbreak and that previous outbreaks must have been spatially isolated.

Costs of Digital Adherence Technologies for Tuberculosis Treatment Support, 2018-2021.

Digital adherence technologies are increasingly used to support tuberculosis (TB) treatment adherence. Using microcosting, we estimated healthcare system costs (in 2022 US dollars) of 2 digital adherence technologies, 99DOTS medication sleeves and video-observed therapy (VOT), implemented in demonstration projects during 2018-2021. We also obtained cost estimates for standard directly observed therapy (DOT). Estimated per-person costs of 99DOTS for drug-sensitive TB were $98 in Bangladesh (n = 719), $119 in the Philippines (n = 396), and $174 in Tanzania (n = 976). Estimated per-person costs of VOT were $1,154 in Haiti (87 drug-sensitive), $304 in Moldova (173 drug-sensitive), $452 in Moldova (135 drug-resistant), and $661 in the Philippines (110 drug-resistant). 99DOTS costs may be similar to or less expensive than standard DOT. VOT is more expensive, although in some settings, labor cost offsets or economies of scale may yield savings. 99DOTS and VOT may yield savings to local programs if donors cover infrastructure costs.

Exposure to metal mixtures and telomere length in Bangladeshi children.

Telomere length is associated with chronic diseases and in younger populations, may represent a biomarker of disease susceptibility. As growing evidence suggests that environmental factors, including metals, may impact telomere length, we investigated the association between 17 metals measured in toenail samples and leukocyte relative telomere length (RTL), among 472 five- to seven-year-old children enrolled in the Bangladesh Environmental Research in Children's Health (BiRCH) cohort. In single exposure linear regression models, a doubling of arsenic (As) and mercury (Hg) (µg/g) were associated with a -0.21 (95%CI: -0.032, -0.010; p=0.0005) and -0.017 (95%CI: -0.029, -0.004; p=0.006) difference in RTL, respectively. In Bayesian Kernel Machine Regression (BKMR) mixture models, the overall metal mixture was inversely associated with RTL (P-for-trend <0.001). Negative associations with RTL were observed with both log2-As and log2-Hg, while an inverted U-shaped association was observed for log2-zinc (Zn) with RTL. We found little evidence of interaction among metals. Sex-stratification identified stronger associations of the overall mixture and log2-As with RTL among females, compared to males. Our study suggests that As and Hg may independently influence RTL in mid-childhood. Further studies are needed to investigate potential long-term impacts of metal-associated telomere shortening in childhood on health outcomes in adult life.

Molecular investigation of Blastocystis in children and calves in Bangladesh.

BACKGROUND: Blastocystis, a widely distributed zoonotic protozoan infecting both humans and numerous animals, remains poorly understood with its potential medical and veterinary significance. This study examined the molecular occurrence and genetic variation of Blastocystis in children and calves in Bangladesh to explore cross-species transmission and disease burden. METHODS: In total, 998 DNA samples were investigated, comprising 299 stool DNA from children and 699 fecal DNA from calves, using polymerase chain reaction and sequencing of the small subunit ribosomal RNA (SSU rRNA) gene. RESULTS: This study detected Blastocystis in 5.35% of the children and 14.74% of the calves. While slight variations in occurrence rates were observed across different study variables, none were statistically significant. The occurrence was highest among children under 5 years and calves aged 1-3 months. Regarding breed, the Holstein Friesian cross and the Jersey cross exhibited higher rates of infection. Conversely, occurrences were lower among children and calves in Gazipur district. The remaining parameters displayed nearly equivalent percentages of Blastocystis. The subtypes identified in children included ST1, ST3, and ST4, with ST1 comprising 50% of them. ST3 and ST4 were also found in calves, alongside ST10 (55.34%) being the most prevalent. Other subtypes found in calves were ST14, ST21, and ST24-ST26. CONCLUSIONS: This study found that Blastocystis is more common in calves than in children in Bangladesh, with genetic diversity of nine subtypes. The common occurrence of identical variants of two subtypes in both populations suggests potential zoonotic transmission, highlighting the necessity for further molecular investigations and comprehensive measures within the One Health framework to mitigate public health risks.

Rotavirus trends and distribution of genotypes before and during COVID-19 pandemic era: Bangladesh, 2017-2021.

Rotavirus gastroenteritis is accountable for an estimated 128 500 deaths among children younger than 5 years worldwide, and the majority occur in low-income countries. Although the clinical trials of rotavirus vaccines in Bangladesh revealed a significant reduction of severe rotavirus disease by around 50%, the vaccines are not yet included in the routine immunization program. The present study was designed to provide data on rotavirus diarrhea with clinical profiles and genotypes before (2017-2019) and during the COVID-19 pandemic period (2020-2021). Fecal samples were collected from 2% of the diarrheal patients at icddr,b Dhaka hospital of all ages between January 2017 and December 2021 and were tested for VP6 rotavirus antigen using ELISA. The clinical manifestations such as fever, duration of diarrhea and hospitalization, number of stools, and dehydration and so on were collected from the surveillance database (n = 3127). Of the positive samples, 10% were randomly selected for genotyping using Sanger sequencing method. A total of 12 705 fecal samples were screened for rotavirus A antigen by enzyme immunoassay. Overall, 3369 (27%) were rotavirus antigen-positive, of whom children <2 years had the highest prevalence (88.6%). The risk of rotavirus A infection was 4.2 times higher in winter than in summer. Overall, G3P[8] was the most prominent genotype (45.3%), followed by G1P[8] (32.1%), G9P[8] (6.8%), and G2P[4] (6.1%). The other unusual combinations, such as G1P[4], G1P[6], G2P[6], G3P[4], G3P[6], and G9P[6], were also present. Genetic analysis on Bangladeshi strains revealed that the selection pressure (dN/dS) was estimated as <1. The number of hospital visits showed a 37% drop during the COVID-19 pandemic relative to the years before the pandemic. Conversely, there was a notable increase in the rate of rotavirus positivity during the pandemic (34%, p < 0.00) compared to the period before COVID-19 (23%). Among the various clinical symptoms, only the occurrence of watery stool significantly increased during the pandemic. The G2P[4] strain showed a sudden rise (19%) in 2020, which then declined in 2021. In the same year, G1P[8] was more prevalent than G3P[8] (40% vs. 38%, respectively). The remaining genotypes were negligible and did not exhibit much fluctuation. This study reveals that the rotavirus burden remained high during the COVID-19 prepandemic and pandemic in Bangladesh. Considering the lack of antigenic variations between the circulating and vaccine-targeted strains, integrating the vaccine into the national immunization program could reduce the prevalence of the disease, the number of hospitalizations, and the severity of cases.

Arsenic exposure is associated with alterations to multiple red blood cell parameters among adults in rural Bangladesh.

Chronic arsenic exposures are associated with multiple hematologic disturbances, including anemia. The goal of this study was to evaluate associations between arsenic exposures and hematological parameters among men and women who are chronically exposed to elevated levels of arsenic from drinking water. Hematologic analyses were performed on blood collected from 755 participants (45% male and 54% female) in the Health Effects of Arsenic Longitudinal Study (HEALS) cohort, Bangladesh. Herein, we used linear regression models to estimate associations between red blood cell (RBC) parameters (i.e., RBC counts, hematocrit (HCT), hemoglobin (Hgb), mean corpuscular volume (MCV), mean corpuscular hemoglobin (MCH), and mean corpuscular hemoglobin concentration (MCHC)) and measurements of arsenic exposure (urinary arsenic and urinary arsenic metabolites). Arsenic exposures showed trending associations with decreased RBC counts in both men and women, a positive association with MCV in males, and an inverse association with MCHC among males, but not among non-smoking females. Among men, those who smoked had stronger associations between arsenic exposures and MCHC than non-smoking males. Collectively, our results show that arsenic exposures affect multiple RBC parameters and highlight potentially important sex differences in arsenic-induced hematotoxicity.

Cervical cancer risk in association with TNF-alpha gene polymorphisms in Bangladeshi women.

BACKGROUND: Tumor necrosis factor-alpha (TNF-α) is among the vital pro-inflammatory cytokines that potentially exerts a significant influence on the immune response, hence potentially regulating the advancement of cervical lesions. OBJECTIVE: Our study objective was to examine the relationship between two single nucleotide polymorphisms (SNPs) (rs1799724 and rs1800629) of TNF-α and the risk of cervical cancer in women from Bangladesh. METHODS: We recruited 133 patients with cervical cancer and 126 healthy individuals for this study. Genotyping was performed using real-time PCR SNP genotyping assay. Multivariate logistic regression analysis was used to determine the odds ratio (OR) along with 95% confidence intervals (CI) and p-values. RESULTS: For rs1799724 (C > T) polymorphism, TT mutant homozygous genotype carried 3.26 times increased risk of developing cervical cancer (OR = 3.26, 95% CI = 1.15-9.28, p = 0.027). Polymorphism of rs1800629 (G > A) was also related to an elevated risk of cervical cancer. Individuals with the AG heterozygous genotype (OR = 2.85, 95% CI = 1.20-6.74, p = 0.017) and AA mutant homozygous genotype (OR = 4.55, 95% CI = 1.24-16.60, p = 0.022) also had a higher likelihood of having cervical cancer. Moreover, we found that injectable contraceptives increase the risk of cervical cancer. Individuals who smoked and/or had first-degree relatives with cancer were more likely to carry the risk allele, which increases the likelihood of developing cervical cancer. CONCLUSION: TNF-α polymorphisms in rs1799724 and rs1800629 increase the susceptibility of developing cervical cancer in women from Bangladesh.

An Egg Intervention Improves Ponderal But Not Linear Growth Among Infants 6-12 mo of Age in Rural Bangladesh.

BACKGROUND: Animal source foods are rich in multiple nutrients. Regular egg consumption may improve infant growth in low- and middle-income countries. OBJECTIVES: To assess the impact of daily egg consumption on linear growth among 6-12-mo olds in rural Bangladesh. METHODS: We conducted a 2 × 4 factorial cluster-randomized controlled trial allocating clusters (n = 566) to treatment for enteric pathogens or placebo and a daily egg, protein supplement, isocaloric supplement, or control. All arms received nutrition education. Here, we compare the effect of the egg intervention versus control on linear growth, a prespecified aim of the trial. Infants were enrolled at 3 mo. We measured length and weight at 6 and 12 mo and visited households weekly to distribute eggs and monitor compliance. We used linear regression models to compare 12-mo mean length, weight, and z-scores for length-for-age (LAZ), weight-for-length, and weight-for-age (WAZ), and log-binomial or robust Poisson regression to compare prevalence of stunting, wasting, and underweight between arms. We used generalized estimating equations to account for clustering and adjusted models for baseline measures of outcomes. RESULTS: We enrolled 3051 infants (n = 283 clusters) across arms, with complete 6 and 12 mo anthropometry data from 1228 infants (n = 142 clusters) in the egg arm and 1109 infants (n = 141 clusters) in the control. At baseline, 18.5%, 6.0%, and 16.4% were stunted, wasted, and underweight, respectively. The intervention did not have a statistically significant effect on mean LAZ (ß: 0.05, 95% confidence interval [CI]: -0.01, 0.10) or stunting prevalence (ß: 0.98, 95% CI: 0.89, 1.13) at 12 mo. Mean weight (ß: 0.07 kg, 95% CI: 0.02, 0.11) and WAZ (ß: 0.06, 95% CI: 0.02, 0.11) were significantly higher in the egg compared with control arms. CONCLUSIONS: Provision of a daily egg for 6 mo to infants in rural Bangladesh improved ponderal but not linear growth. TRIAL REGISTRATION NUMBER: NCT03683667, https://clinicaltrials.gov/ct2/show/NCT03683667.

Diabetes distress and depression are independently associated with gastrointestinal symptoms in type 2 diabetes in Bangladesh.

BACKGROUND AND AIMS: Gastrointestinal (GI) symptoms, common in type 2 diabetes (T2D), are typically bothersome, socially embarrassing, and impact negatively on quality of life. They may also contribute to diabetes distress (DD), but this has never been formally evaluated. We aimed to investigate the relationships between GI symptoms, DD and depressive symptoms in a large cohort of individuals with T2D in Bangladesh. MATERIALS AND METHODS: 1406 unselected T2D individuals (female 58.8%; mean age 51.0 ± 12.5 years) from four diabetes clinics in Bangladesh completed validated questionnaires evaluating GI symptoms (PAGI-SYM), DD (DDS-17) and depressive symptoms (PHQ-9). RESULTS: 31.1% of participants reported GI symptoms (36.2% females, 23.7% males), while 51.1% had elevated DD and 37.8% depressive symptoms. GI symptoms exhibited independent relationships with both DD and depressive symptoms, and their likelihood was higher among those with DD (OR: 3.6 [2.2-5.6] and with depressive symptoms (OR: 5.9 [3.5-9.9]). CONCLUSIONS: GI symptoms are independently associated with both DD and depressive symptoms in people with T2D in Bangladesh.

Molecular characterization to study the genetic diversity of begomoviruses occurring in the major chilli growing areas of Tamil Nadu state of India.

Chilli leaf curl disease (ChiLCD), which is a significant problem in chilli cultivation, is caused by begomoviruses that are transmitted by the whitefly Bemisia tabaci. This disease leads to severe impacts on crop yields. To determine the incidence of begomovirus in the chilli crop, infected chilli leaf samples exhibiting symptoms such as curling, yellowing, reduced leaf size, and overall stunted growth were collected from various districts of Tamil Nadu, namely, Coimbatore, Dharmapuri, Kancheepuram, Karur, Salem, Krishnagiri, Thoothukudi, Thiruvallur, Tiruchirappalli, Virudhunagar, Tiruvannamalai, Tenkasi, and Vellore, during the years 2018-2022. To determine the complete genome sequence of the begomoviruses, the rolling circle amplification (RCA) method was used to clone and sequence the begomovirus genomes from the chilli samples collected from various districts of Tamil Nadu. Here we characterized 17 DNA A genome sequences and 12 betasatellite sequences. BLAST results of the DNA A genome sequences revealed nucleotide identities ranging from 94.2 to 99.7% with five distinct begomovirus species of chilli, namely, chilli leaf curl Salem virus (HM007119), chilli leaf curl virus Bhavanisagar (NC_055130), chilli leaf curl Ahmedabad virus (MW795666), chilli leaf curl virus (NC_055131), and chilli leaf curl Sri Lanka virus (JN555600). BLAST results of the betasatellite sequences showed nucleotide identities of 96 to 98.8% with the tomato leaf curl Bangladesh betasatellite (MZ151286). In the present study, five distinct begomovirus species and one associated betasatellite were found to infect chilli crops in Tamil Nadu. This finding indicates a changing pattern of begomovirus occurrence in the different districts of Tamil Nadu. This study highlights the prevalence of chilli-infecting begomoviruses in the major chilli growing districts of Tamil Nadu, the identification of begomovirus species, and the significance of understanding and managing these viruses to safeguard chilli cultivation in the region.

Strategic investment and program effectiveness: a roadmap to ending AIDS in Bangladesh by 2030.

The journey towards ending AIDS epidemic in Bangladesh by 2030 is ambitious yet achievable. Although Bangladesh has always had a low rate of HIV among its general population, it remains one of seven countries in Asia and the Pacific where new HIV cases are rising. This study evaluates the effectiveness of HIV programmatic strategies and investment scenarios using the AIDS Epidemic Model (AEM) from 2023 to 2030, focusing on optimizing resource allocation and interventions. The findings indicate that without improved program effectiveness, new HIV infections will increase to 1,382 by 2030, failing to meet the targets of the Global AIDS Strategy 2021-2026. If Bangladesh improves its HIV program effectiveness according to the Global AIDS Strategy 2021-2026, the NSP and Global AIDS Strategy targets could significantly lower new infections and AIDS-related deaths and increase treatment coverage to meet Ending AIDS targets. The NSP targets could reduce new HIV infections to under 275 annually and achieve treatment goals by 2030. The study reveals that NSP targets are the most cost-effective, offering the highest benefit-cost ratio, highlighting the urgent need to enhance HIV prevention program effectiveness, particularly among key populations, to achieve both public health and economic benefits.

Age and sex-specific disability-free life expectancy in urban and rural settings of Bangladesh.

BACKGROUND: Disability-free life expectancy (DFLE) has been used to gain a better understanding of the population's quality of life. OBJECTIVES: The authors aimed to estimate age and sex-specific disability-free life expectancy (DFLE) for urban and rural areas of Bangladesh, as well as to investigate the differences in DFLE between males and females of urban and rural areas. METHODS: Data from the Bangladesh Sample Vital Statistics-2016 and the Bangladesh Household Income and Expenditure Survey (HIES)-2016 were used to calculate the disability-free life expectancy (DFLE) of urban and rural males and females in Bangladesh in 2016. The DFLE was calculated using the Sullivan method. RESULTS: With only a few exceptions, rural areas have higher mortality and disability rates than urban areas. For both males and females, statistically significant differences in DFLE were reported between urban and rural areas between the ages of birth and 39 years. In comparison to rural males and females, urban males and females had a longer life expectancy (LE), a longer disability-free life expectancy, and a higher share of life without disability. CONCLUSION: This study illuminates stark urban-rural disparities in LE and DFLE, especially among individuals aged < 1-39 years. Gender dynamics reveal longer life expectancy but shorter disability-free life expectancy for Bangladeshi women compared to men, emphasizing the need for targeted interventions to address these pronounced health inequalities.

A protocol for harvesting biodiversity data from Facebook.

The expanding use of community science platforms has led to an exponential increase in biodiversity data in global repositories. Yet, understanding of species distributions remains patchy. Biodiversity data from social media can potentially reduce the global biodiversity knowledge gap. However, practical guidelines and standardized methods for harvesting such data are nonexistent. Following data privacy and protection safeguards, we devised a standardized method for extracting species distribution records from Facebook groups that allow access to their data. It involves 3 steps: group selection, data extraction, and georeferencing the record location. We present how to structure keywords, search for species photographs, and georeference localities for such records. We further highlight some challenges users might face when extracting species distribution data from Facebook and suggest solutions. Following our proposed framework, we present a case study on Bangladesh's biodiversity-a tropical megadiverse South Asian country. We scraped nearly 45,000 unique georeferenced records across 967 species and found a median of 27 records per species. About 12% of the distribution data were for threatened species, representing 27% of all species. We also obtained data for 56 DataDeficient species for Bangladesh. If carefully harvested, social media data can significantly reduce global biodiversity knowledge gaps. Consequently, developing an automated tool to extract and interpret social media biodiversity data is a research priority.

Un protocolo para recolectar datos sobre biodiversidad en Facebook Resumen El uso creciente de plataformas de ciencia comunitaria ha causado un incremento exponencial de los datos sobre biodiversidad en los repositorios mundiales. Sin embargo, el conocimiento sobre la distribución de las especies todavía está incompleto. Los datos sobre biodiversidad obtenidos de las redes sociales tienen el potencial para disminuir el vacío de conocimiento sobre la biodiversidad mundial. No obstante, no existe una guía práctica o un método estandarizado para recolectar dichos datos. Seguimos los protocolos de privacidad y protección de datos para diseñar un método estandarizado para extraer registros de la distribución de especies de grupos en Facebook que permiten el acceso a sus datos. El método consta de tres pasos: selección del grupo, extracción de datos y georreferenciación de la localidad registrada. También planteamos cómo estructurar las palabras clave, buscar fotografías de especies y georreferenciar las localidades de dichos registros. Además, resaltamos algunos retos que los usuarios pueden enfrentar al extraer los datos de distribución de Facebook y sugerimos algunas soluciones. Aplicamos nuestro marco de trabajo propuesto a un estudio de caso de la biodiversidad en Bangladesh, un país tropical megadiverso en el sureste de Asia. Reunimos casi 45,000 registros georreferenciados únicos para 967 especies y encontramos una media de 27 registros por especie. Casi el 12% de los datos de distribución correspondió a especies amenazadas, que representaban el 27% de todas las especies. También obtuvimos datos para 56 especies deficientes de datos en Bangladesh. Si los datos de las redes sociales se recolectan con cuidado, éstos pueden reducir de forma significativa el vacío de conocimiento para la biodiversidad mundial. Como consecuencia, es una prioridad para la investigación el desarrollo de una herramienta automatizada para extraer e interpretar los datos sobre biodiversidad de las redes sociales.

Using social media records to inform conservation planning.

Citizen science plays a crucial role in helping monitor biodiversity and inform conservation. With the widespread use of smartphones, many people share biodiversity information on social media, but this information is still not widely used in conservation. Focusing on Bangladesh, a tropical megadiverse and mega-populated country, we examined the importance of social media records in conservation decision-making. We collated species distribution records for birds and butterflies from Facebook and Global Biodiversity Information Facility (GBIF), grouped them into GBIF-only and combined GBIF and Facebook data, and investigated the differences in identifying critical conservation areas. Adding Facebook data to GBIF data improved the accuracy of systematic conservation planning assessments by identifying additional important conservation areas in the northwest, southeast, and central parts of Bangladesh, extending priority conservation areas by 4,000-10,000 km2 . Community efforts are needed to drive the implementation of the ambitious Kunming-Montreal Global Biodiversity Framework targets, especially in megadiverse tropical countries with a lack of reliable and up-to-date species distribution data. We highlight that conservation planning can be enhanced by including available data gathered from social media platforms.

Registros de las redes sociales para guiar la planeación de la conservación Resumen La ciencia ciudadana es importante para monitorear la biodiversidad e informar la conservación. Con el creciente uso de los teléfonos inteligentes, muchas personas comparten información de la biodiversidad en redes sociales, pero todavía no se usa ampliamente en la conservación. Analizamos la importancia de los registros de las redes sociales para las decisiones de conservación enfocados en Bangladesh, un país tropical megadiverso y mega poblado. Cotejamos los registros de distribución de especies de aves y mariposas en Facebook y Global Biodiversity Information Facility (GBIF), las agrupamos en datos sólo de GBIF o datos combinados de Facebook y GBIF e investigamos las diferencias en la identificación de las áreas de conservación críticas. La combinación de los datos de Facebook con los de GBIF mejoró la precisión de las evaluaciones de la planeación de la conservación sistemática al identificar otras áreas importantes de conservación en el noroeste, sureste y centro de Bangladesh, extendiendo así las áreas prioritarias de conservación en unos 4,000-10,000 km2 . Se requieren esfuerzos comunitarios para impulsar la implementación de los objetivos ambiciosos del Marco Global de Biodiversidad Kunming-Montreal, especialmente en países tropicales que carecen de datos confiables y actuales sobre la distribución de las especies. Destacamos que la planeación de la conservación puede mejorarse si se incluye información tomada de las redes sociales.

Clinical presentation of post-COVID pain and its impact on quality of life in long COVID patients: a cross-sectional household survey of SARS-CoV-2 cases in Bangladesh.

BACKGROUND: Pain is one of the prevalent Long COVID Symptoms (LCS). Pain interferes with the quality of life (QoL) and induces disease burden. PURPOSE: The study aimed to elicit the clinical presentation of pain and determine the relationships between QoL and pain in LCS. METHODS: This household cross-sectional study of 12,925 SARS-CoV-2 cases between July and December 2021 was carried out in eight administrative divisions of Bangladesh. Stratified random sampling from the cases retrieved from the Ministry of Health was employed. Symptom screening was performed through COVID-19 Yorkshire Rehabilitation Scale, and long COVID was diagnosed according to World Health Organization (WHO) criteria. The analyses were conducted using IBM SPSS (Version 20.00). RESULTS: The prevalence of pain in long COVID was between 01 and 3.1% in the studied population. The study also found five categories of pain symptoms as LCS in Bangladesh: muscle pain 3.1% (95% CI; 2.4-3.8), chest pain 2.4% (95% CI; 1.8-3.1), joint pain 2.8% (95% CI; 2.2-2.3), headache 3.1% (95% CI; 2.4-3.8), and abdominal pain 0.3% (95% CI; 0.01-0.5). People with LCS as pain, multiple LCS, and longer duration of LCS had significantly lower quality of life across all domains of the WHOQOL-BREF (P < 0.001) compared to asymptomatic cases. CONCLUSION: Three out of ten people with long COVID experience painful symptoms, which can significantly reduce their quality of life. Comprehensive rehabilitation can improve the symptoms and reduce the burden of the disease.

Rural‒urban disparities in household catastrophic health expenditure in Bangladesh: a multivariate decomposition analysis.

BACKGROUND: Rural‒urban disparity in catastrophic healthcare expenditure (CHE) is a well-documented challenge in low- and middle-income countries, including Bangladesh, limiting financial protection and hindering the achievement of the Universal Health Coverage target of the United Nations Sustainable Development Goals. However, the factors driving this divide remain poorly understood. Therefore, this study aims to identify the key determinants of the rural‒urban disparity in CHE incidence in Bangladesh and their changes over time. METHODS: We used nationally representative data from the latest three rounds of the Bangladesh Household Income and Expenditure Survey (2005, 2010, and 2016). CHE incidence among households seeking healthcare was measured using the normative food, housing, and utilities method. To quantify covariate contributions to the rural‒urban CHE gap, we employed the Oaxaca-Blinder multivariate decomposition approach, adapted by Powers et al. for nonlinear response models. RESULTS: CHE incidence among rural households increased persistently during the study period (2005: 24.85%, 2010: 25.74%, 2016: 27.91%) along with a significant (p-value ≤ 0.01) rural‒urban gap (2005: 9.74%-points, 2010: 13.94%-points, 2016: 12.90%-points). Despite declining over time, substantial proportions of CHE disparities (2005: 87.93%, 2010: 60.44%, 2016: 61.33%) are significantly (p-value ≤ 0.01) attributable to endowment differences between rural and urban households. The leading (three) covariate categories consistently contributing significantly (p-value ≤ 0.01) to the CHE gaps were composition disparities in the lowest consumption quintile (2005: 49.82%, 2010: 36.16%, 2016: 33.61%), highest consumption quintile (2005: 32.35%, 2010: 15.32%, 2016: 18.39%), and exclusive reliance on informal healthcare sources (2005: -36.46%, 2010: -10.17%, 2016: -12.58%). Distinctively, the presence of chronic illnesses in households emerged as a significant factor in 2016 (9.14%, p-value ≤ 0.01), superseding the contributions of composition differences in household heads with no education (4.40%, p-value ≤ 0.01) and secondary or higher education (7.44%, p-value ≤ 0.01), which were the fourth and fifth significant contributors in 2005 and 2010. CONCLUSIONS: Rural‒urban differences in household economic status, educational attainment of household heads, and healthcare sources were the key contributors to the rural‒urban CHE disparity between 2005 and 2016 in Bangladesh, with chronic illness emerging as a significant factor in the latest period. Closing the rural‒urban CHE gap necessitates strategies that carefully address rural‒urban variations in the characteristics identified above.

Continuing evolution of H5N1 highly pathogenic avian influenza viruses of clade 2.3.2.1a G2 genotype in domestic poultry of Bangladesh during 2018-2021.

We characterized 15 H5N1 HPAI viruses from different small- and medium-scale poultry flocks across Bangladesh during 2018-2021 based on their complete genome sequences. The antigenic relatedness of H5N1 HPAI viruses from different timepoints was analysed. During 2020-2021, 42.11% of the flocks tested positive for at least one of the respiratory infections, with 15.79% showing influenza A virus, of which 8.77% tested positive for HPAIV H5N1. Co-infections with two to four pathogens were detected in 15.8% of flocks. Phylogeny and gene constellation analyses based on complete genome sequences of 15 HPAI viruses revealed the continuing circulation of H5 clade 2.3.2.1a genotype G2 viruses. In the HA protein of the study isolates, functionally meaningful mutations caused the loss of an N-linked glycosylation site (T156A), a modified antigenic site A (S141P), and a mutation in the receptor binding pocket (E193R/K). Consequently, antigenic analysis revealed a significant loss of cross-reactivity between viruses from different host species and periods. Most viruses displayed oseltamivir resistance markers at positions V96, I97, S227, and N275 (N1 numbering) of the NA protein. In addition, for the PB2, M1, and NS1 proteins, significant mutations were noticed that have been associated with polymerase activity and increased virulence for mammals in all study isolates. These results highlight the need for intensified genomic surveillance of HPAI circulating in poultry in Bangladesh and for establishing appropriate control measures to decrease the circulation of these viruses in poultry in the country.

Molecular characterization and genetic variability of Toxocara vitulorum from naturally infected buffalo calves for the first time in Bangladesh.

Toxocara vitulorum is one of the deadliest parasite of buffalo calves in Bangladesh. This study was conducted to explore genetic variability within and among the T. vitulorum populations in buffalo calves of Bangladesh. Genomic DNA was extracted, ITS2, COX1 and NAD1 gene were amplified and sequenced. Distinct 29 ITS2, 21 unique NAD1 and 24 COX1 genotypes were detected among the T. vitulorum of different geographic regions. These three gene genotypes similarities ranged from 97 to 99%, when these were compared to best hit scoring T. vitulorum sequences retrieved from GenBank. A total of 12 and 6 unique haplotypes were detected for COX1 and NAD1 gene sequences. The average nucleotide and haplotype diversity for COX1 and NAD1 were 0.0931 & 0.89493 and 0.00658 & 0.77895 respectively and the recorded values were more dispersed than previously published values. The pairwise Nst values ranged from −0.050 to 0.602 and Fst from −0.050 to 0.600 between all the T. vitulorum genotypes indicated huge genetic differentiation which were reportedly higher than other published reports Fst values. This is the first report of T. vitulorum on the basis of COX1 gene in Bangladesh. The study findings will be helpful for further extensive epidemiological studies regarding anthelmintic resistance, control and prevention of T. vitulorum infection in buffalo calves.

Machine learning approach for predicting cardiovascular disease in Bangladesh: evidence from a cross-sectional study in 2023.

BACKGROUND: Cardiovascular disorders (CVDs) are the leading cause of death worldwide. Lower- and middle-income countries (LMICs), such as Bangladesh, are also affected by several types of CVDs, such as heart failure and stroke. The leading cause of death in Bangladesh has recently switched from severe infections and parasitic illnesses to CVDs. MATERIALS AND METHODS: The study dataset comprised a random sample of 391 CVD patients' medical records collected between August 2022 and April 2023 using simple random sampling. Moreover, 260 data points were collected from individuals with no CVD problems for comparison purposes. Crosstabs and chi-square tests were used to determine the association between CVD and the explanatory variables. Logistic regression, Naïve Bayes classifier, Decision Tree, AdaBoost classifier, Random Forest, Bagging Tree, and Ensemble learning classifiers were used to predict CVD. The performance evaluations encompassed accuracy, sensitivity, specificity, and area under the receiver operator characteristic (AU-ROC) curve. RESULTS: Random Forest had the highest precision among the five techniques considered. The precision rates for the mentioned classifiers are as follows: Logistic Regression (93.67%), Naïve Bayes (94.87%), Decision Tree (96.1%), AdaBoost (94.94%), Random Forest (96.15%), and Bagging Tree (94.87%). The Random Forest classifier maintains the highest balance between correct and incorrect predictions. With 98.04% accuracy, the Random Forest classifier achieved the best precision (96.15%), robust recall (100%), and high F1 score (97.7%). In contrast, the Logistic Regression model achieved the lowest accuracy of 95.42%. Remarkably, the Random Forest classifier achieved the highest AUC value (0.989). CONCLUSION: This research mainly focused on identifying factors that are critical in impacting patients with CVD and predicting CVD risk. It is strongly advised that the Random Forest technique be implemented in a system for predicting cardiac diseases. This research may change clinical practice by providing doctors with a new instrument to determine a patient's CVD prognosis.