Genome sequence of a dengue virus serotype 2 strain identified during the 2019 outbreak in Bangladesh

A nearly complete genome sequence of a dengue virus serotype 2 strain detected in the serum of a patient in 2019 during the largest outbreak of dengue fever in Bangladesh is reported

Unbiased Metagenomic Sequencing for Pediatric Meningitis in Bangladesh Reveals Neuroinvasive Chikungunya Virus Outbreak and Other Unrealized Pathogens.

The burden of meningitis in low-and-middle-income countries remains significant, but the infectious causes remain largely unknown, impeding institution of evidence-based treatment and prevention decisions. We conducted a validation and application study of unbiased metagenomic next-generation sequencing (mNGS) to elucidate etiologies of meningitis in Bangladesh. This RNA mNGS study was performed on cerebrospinal fluid (CSF) specimens from patients admitted in the largest pediatric hospital, a World Health Organization sentinel site, with known neurologic infections (n = 36), with idiopathic meningitis (n = 25), and with no infection (n = 30), and six environmental samples, collected between 2012 and 2018. We used the IDseq bioinformatics pipeline and machine learning to identify potentially pathogenic microbes, which we then confirmed orthogonally and followed up through phone/home visits. In samples with known etiology and without infections, there was 83% concordance between mNGS and conventional testing. In idiopathic cases, mNGS identified a potential bacterial or viral etiology in 40%. There were three instances of neuroinvasive Chikungunya virus (CHIKV), whose genomes were >99% identical to each other and to a Bangladeshi strain only previously recognized to cause febrile illness in 2017. CHIKV-specific qPCR of all remaining stored CSF samples from children who presented with idiopathic meningitis in 2017 (n = 472) revealed 17 additional CHIKV meningitis cases, exposing an unrecognized meningitis outbreak. Orthogonal molecular confirmation, case-based clinical data, and patient follow-up substantiated the findings. Case-control CSF mNGS surveys can complement conventional diagnostic methods to identify etiologies of meningitis, conduct surveillance, and predict outbreaks. The improved patient- and population-level data can inform evidence-based policy decisions.IMPORTANCE Globally, there are an estimated 10.6 million cases of meningitis and 288,000 deaths every year, with the vast majority occurring in low- and middle-income countries. In addition, many survivors suffer from long-term neurological sequelae. Most laboratories assay only for common bacterial etiologies using culture and directed PCR, and the majority of meningitis cases lack microbiological diagnoses, impeding institution of evidence-based treatment and prevention strategies. We report here the results of a validation and application study of using unbiased metagenomic sequencing to determine etiologies of idiopathic (of unknown cause) cases. This included CSF from patients with known neurologic infections, with idiopathic meningitis, and without infection admitted in the largest children's hospital of Bangladesh and environmental samples. Using mNGS and machine learning, we identified and confirmed an etiology (viral or bacterial) in 40% of idiopathic cases. We detected three instances of Chikungunya virus (CHIKV) that were >99% identical to each other and to a strain previously recognized to cause systemic illness only in 2017. CHIKV qPCR of all remaining stored 472 CSF samples from children who presented with idiopathic meningitis in 2017 at the same hospital uncovered an unrecognized CHIKV meningitis outbreak. CSF mNGS can complement conventional diagnostic methods to identify etiologies of meningitis, and the improved patient- and population-level data can inform better policy decisions

The direct and indirect impact of SARS-CoV-2 infections on neonates: a series of 26 cases in Bangladesh

Background: The impact of SARS-CoV-2 on neonates remains largely unknown in low- and middle-income countries (LMICs). We provide an epidemiologic and clinical report of SARS-CoV-2 infections in neonates hospitalized in Bangladesh. Methods: Outborn neonates admitted to Dhaka Shishu Hospital, a tertiary-care referral hospital, between 29 March and 1 July were screened for SARS-CoV-2. We reviewed clinical data, including chest radiograph and laboratory reports, and conducted SARS-CoV-2 genome sequencing. Patients were followed-up for 27–75 days. A subset of caregivers was also tested. Results: Of 83 neonates tested, 26 were positive (median age 8 days). Most neonates were admitted with diagnosis unrelated to SARS-CoV-2: 11 presented with serious non-communicable diseases, 7 with early-onset sepsis, 5 with late-onset sepsis and 2 with pneumonia. In 3 of 5 chest radiograph, infiltrates and ground-glass or patchy opacities were noted. Two neonates developed metabolic acidosis, one developed disseminated intravascular coagulation. Most SARS-CoV-2 positive neonates were referred to government-designated COVID-19 hospitals, leading to gaps in treatment. Twenty-three neonates could be followed-up: 12 were healthy, 8 died and 3 were still seeking medical care. Of 9 caregivers tested, 8 were positive. Conclusions: SARS-CoV-2 may have serious adverse effects on children born in LMICs. The virus likely contributed directly to two deaths, but the remaining 6 neonates who died had serious comorbidities. Positive SARS-CoV-2 test results led to gaps in immediate clinical care for other morbidities, which likely contributed to adverse outcomes. This case series emphasizes the need to understand COVID-19 in neonates in LMICs and its indirect impacts

Complete Genome Sequence of a Novel Coronavirus (SARS-CoV-2) Isolate from Bangladesh.

The complete genome sequence of a novel coronavirus (severe acute respiratory syndrome coronavirus 2 [SARS-CoV-2]) isolate obtained from a nasopharyngeal swab from a patient with COVID-19 in Bangladesh is reported

Complete Genome Sequence of a Novel Coronavirus (SARS-CoV-2) Isolate from Bangladesh.

The complete genome sequence of a novel coronavirus (severe acute respiratory syndrome coronavirus 2 [SARS-CoV-2]) isolate obtained from a nasopharyngeal swab from a patient with COVID-19 in Bangladesh is reported

Unbiased Metagenomic Sequencing for Pediatric Meningitis in Bangladesh Reveals Neuroinvasive Chikungunya Virus Outbreak and Other Unrealized Pathogens

Globally, there are an estimated 10.6 million cases of meningitis and 288,000 deaths every year, with the vast majority occurring in low- and middle-income countries. In addition, many survivors suffer from long-term neurological sequelae. Most laboratories assay only for common bacterial etiologies using culture and directed PCR, and the majority of meningitis cases lack microbiological diagnoses, impeding institution of evidence-based treatment and prevention strategies. We report here the results of a validation and application study of using unbiased metagenomic sequencing to determine etiologies of idiopathic (of unknown cause) cases. This included CSF from patients with known neurologic infections, with idiopathic meningitis, and without infection admitted in the largest children’s hospital of Bangladesh and environmental samples. Using mNGS and machine learning, we identified and confirmed an etiology (viral or bacterial) in 40% of idiopathic cases. We detected three instances of Chikungunya virus (CHIKV) that were >99% identical to each other and to a strain previously recognized to cause systemic illness only in 2017. CHIKV qPCR of all remaining stored 472 CSF samples from children who presented with idiopathic meningitis in 2017 at the same hospital uncovered an unrecognized CHIKV meningitis outbreak. CSF mNGS can complement conventional diagnostic methods to identify etiologies of meningitis, and the improved patient- and population-level data can inform better policy decisions.The burden of meningitis in low-and-middle-income countries remains significant, but the infectious causes remain largely unknown, impeding institution of evidence-based treatment and prevention decisions. We conducted a validation and application study of unbiased metagenomic next-generation sequencing (mNGS) to elucidate etiologies of meningitis in Bangladesh. This RNA mNGS study was performed on cerebrospinal fluid (CSF) specimens from patients admitted in the largest pediatric hospital, a World Health Organization sentinel site, with known neurologic infections (n = 36), with idiopathic meningitis (n = 25), and with no infection (n = 30), and six environmental samples, collected between 2012 and 2018. We used the IDseq bioinformatics pipeline and machine learning to identify potentially pathogenic microbes, which we then confirmed orthogonally and followed up through phone/home visits. In samples with known etiology and without infections, there was 83% concordance between mNGS and conventional testing. In idiopathic cases, mNGS identified a potential bacterial or viral etiology in 40%. There were three instances of neuroinvasive Chikungunya virus (CHIKV), whose genomes were >99% identical to each other and to a Bangladeshi strain only previously recognized to cause febrile illness in 2017. CHIKV-specific qPCR of all remaining stored CSF samples from children who presented with idiopathic meningitis in 2017 (n = 472) revealed 17 additional CHIKV meningitis cases, exposing an unrecognized meningitis outbreak. Orthogonal molecular confirmation, case-based clinical data, and patient follow-up substantiated the findings. Case-control CSF mNGS surveys can complement conventional diagnostic methods to identify etiologies of meningitis, conduct surveillance, and predict outbreaks. The improved patient- and population-level data can inform evidence-based policy decisions