Search

Background Reliable diagnostics are a key to identifying influenza infections. Objectives Our objectives were to describe the detection of influenza among severe acute respiratory infection (SARI) cases, to compare test results from the Fast Track Diagnostics (FTD) Kit for influenza detection to the Centers for Disease Control (CDC) human influenza virus detection and characterization panel, and to assess seasonality of influenza in Burkina Faso. Methods Nasopharyngeal and oropharyngeal specimens from SARI cases (hospitalized patients with fever, cough, and onset in the previous 10 days) were tested using the FTD‐33 Kit and the CDC rRT‐PCR influenza assays. We assessed sensitivity and specificity of the FTD‐33 Kit for detecting influenza A, influenza B, and the influenza A(H1N1)pdm09 strain using the CDC human influenza rRT‐PCR panel as the gold standard. Results From December 2016 to February 2019, 1706 SARI cases were identified, 1511 specimens were tested, and 211 were positive for influenza A (14.0%) and 100 for influenza B (6.6%) by either assay. Higher influenza circulation occurred between November and April with varying peaks of influenza A and influenza B. Sensitivity of the FTD‐33 assay was 91.9% for influenza A, 95.7% for influenza B, and 93.8% for A(H1N1)pdm09 subtype. Specificity was over 99% for all three tests. Conclusions Our study indicates that Burkina Faso has one peak of influenza each year which is similar to the Northern Hemisphere and differs from other countries in West Africa. We found high concordance of influenza results between the two assays indicating FTD‐33 can be used to reliably detect influenza among SARI cases.

- Label: BACKGROUND NlmCategory: BACKGROUND content: "Sub-Saharan Africa and south Asia contributed 81% of 5\xC2\xB79 million under-5 deaths and 77% of 2\xC2\xB76 million stillbirths worldwide in 2015. Vital registration and verbal autopsy data are mainstays for the estimation of leading causes of death, but both are non-specific and focus on a single underlying cause. We aimed to provide granular data on the contributory causes of death in stillborn fetuses and in deceased neonates and children younger than 5 years, to inform child mortality prevention efforts." - Label: METHODS NlmCategory: METHODS content: "The Child Health and Mortality Prevention Surveillance (CHAMPS) Network was established at sites in seven countries (Baliakandi, Bangladesh; Harar and Kersa, Ethiopia; Siaya and Kisumu, Kenya; Bamako, Mali; Manhi\xC3\xA7a, Mozambique; Bombali, Sierra Leone; and Soweto, South Africa) to collect standardised, population-based, longitudinal data on under-5 mortality and stillbirths in sub-Saharan Africa and south Asia, to improve the accuracy of determining causes of death. Here, we analysed data obtained in the first 2 years after the implementation of CHAMPS at the first five operational sites, during which surveillance and post-mortem diagnostics, including minimally invasive tissue sampling (MITS), were used. Data were abstracted from all available clinical records of deceased children, and relevant maternal health records were also extracted for stillbirths and neonatal deaths, to incorporate reported pregnancy or delivery complications. Expert panels followed standardised procedures to characterise causal chains leading to death, including underlying, intermediate (comorbid or antecedent causes), and immediate causes of death for stillbirths, neonatal deaths, and child (age 1-59 months) deaths." - Label: FINDINGS NlmCategory: RESULTS content: Between Dec 10, 2016, and Dec 31, 2018, MITS procedures were implemented at five sites in Mozambique, South Africa, Kenya, Mali, and Bangladesh. We screened 2385 death notifications for inclusion eligibility, following which 1295 families were approached for consent; consent was provided for MITS by 963 (74%) of 1295 eligible cases approached. At least one cause of death was identified in 912 (98%) of 933 cases (180 stillbirths, 449 neonatal deaths, and 304 child deaths); two or more conditions were identified in the causal chain for 585 (63%) of 933 cases. The most common underlying causes of stillbirth were perinatal asphyxia or hypoxia (130 [72%] of 180 stillbirths) and congenital infection or sepsis (27 [15%]). The most common underlying causes of neonatal death were preterm birth complications (187 [42%] of 449 neonatal deaths), perinatal asphyxia or hypoxia (98 [22%]), and neonatal sepsis (50 [11%]). The most common underlying causes of child deaths were congenital birth defects (39 [13%] of 304 deaths), lower respiratory infection (37 [12%]), and HIV (35 [12%]). In 503 (54%) of 933 cases, at least one contributory pathogen was identified. Cytomegalovirus, Escherichia coli, group B Streptococcus, and other infections contributed to 30 (17%) of 180 stillbirths. Among neonatal deaths with underlying prematurity, 60% were precipitated by other infectious causes. Of the 275 child deaths with infectious causes, the most common contributory pathogens were Klebsiella pneumoniae (86 [31%]), Streptococcus pneumoniae (54 [20%]), HIV (40 [15%]), and cytomegalovirus (34 [12%]), and multiple infections were common. Lower respiratory tract infection contributed to 174 (57%) of 304 child deaths. - Label: INTERPRETATION NlmCategory: CONCLUSIONS content: Cause of death determination using MITS enabled detailed characterisation of contributing conditions. Global estimates of child mortality aetiologies, which are currently based on a single syndromic cause for each death, will be strengthened by findings from CHAMPS. This approach adds specificity and provides a more complete overview of the chain of events leading to death, highlighting multiple potential interventions to prevent under-5 mortality and stillbirths. - Label: FUNDING NlmCategory: BACKGROUND content: Bill & Melinda Gates Foundation.

Background Lower respiratory tract infections are a leading cause of death in young children, but few studies have collected the specimens needed to define the role of specific causes. The Child Health and Mortality Prevention Surveillance (CHAMPS) platform aims to investigate causes of death in children aged Methods We included deaths that occurred between December 2016 and December 2019. Panels determined causes of deaths by reviewing all available data including pathological results from minimally invasive tissue sampling, polymerase chain reaction screening for multiple infectious pathogens in lung tissue, nasopharyngeal swab, blood, and cerebrospinal fluid samples, clinical information from medical records, and verbal autopsies. Results We evaluated 1213 deaths, including 695 in neonates (aged Conclusions RSV is an important cause of child deaths, particularly in young infants. These findings add to the substantial body of literature calling for better treatment and prevention options for RSV in high–mortality rate settings.

Child Health and Mortality Prevention Surveillance (CHAMPS) laboratories are employing a variety of laboratory methods to identify infectious agents contributing to deaths of children 100 real-time polymerase chain reaction (PCR) targets in total (30–45 per card depending on configuration). Multipathogen panels were configured by syndrome and customized to include pathogens of significance in young children within the regions where CHAMPS is conducted, including bacteria (57 targets covering 30 genera), viruses (48 targets covering 40 viruses), parasites (8 targets covering 8 organisms), and fungi (3 targets covering 3 organisms). The development and application of multiplex real-time PCR reactions to the TAC microfluidic platform increased the number of targets in each panel while maintaining assay efficiency and replicates for heightened sensitivity. These advances represent a substantial improvement in the utility of this technology for infectious disease diagnostics and surveillance. We optimized all aspects of the CHAMPS molecular laboratory testing workflow including nucleic acid extraction, quality assurance, and data management to ensure comprehensive molecular testing of specimens and high-quality data. Here we describe the development and implementation of multiplex TACs and associated laboratory protocols for specimen processing, testing, and data management at CHAMPS site laboratories., We developed and implemented custom TaqMan Array Cards for testing postmortem specimens for pathogens of significance in young children. All aspects of the CHAMPS molecular laboratory workflow were optimized to ensure generation and management of comprehensive and high-quality data.

Background The Coronavirus Disease 2019 (COVID-19) pandemic, caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), evolved rapidly in the United States. This report describes the demographic, clinical, and epidemiologic characteristics of 544 U.S. persons under investigation (PUI) for COVID-19 with complete SARS-CoV-2 testing in the beginning stages of the pandemic from January 17 through February 29, 2020. Methods In this surveillance cohort, the U.S. Centers for Disease Control and Prevention (CDC) provided consultation to public health and healthcare professionals to identify PUI for SARS-CoV-2 testing by quantitative real-time reverse-transcription PCR. Demographic, clinical, and epidemiologic characteristics of PUI were reported by public health and healthcare professionals during consultation with on-call CDC clinicians and subsequent submission of a CDC PUI Report Form. Characteristics of laboratory-negative and laboratory-positive persons were summarized as proportions for the period of January 17−February 29, and characteristics of all PUI were compared before and after February 12 using prevalence ratios. Results A total of 36 PUI tested positive for SARS-CoV-2 and were classified as confirmed cases. Confirmed cases and PUI testing negative for SARS-CoV-2 had similar demographic, clinical, and epidemiologic characteristics. Consistent with changes in PUI evaluation criteria, 88% (13/15) of confirmed cases detected before February 12, 2020, reported travel from China. After February 12, 57% (12/21) of confirmed cases reported no known travel- or contact-related exposures. Conclusions These findings can inform preparedness for future pandemics, including capacity for rapid expansion of novel diagnostic tests to accommodate broad surveillance strategies to assess community transmission, including potential contributions from asymptomatic and presymptomatic infections.

Respiratory diphtheria, characterized by a firmly adherent pseudomembrane, is caused by toxin-producing strains of Corynebacterium diphtheriae, with similar illness produced occasionally by toxigenic Corynebacterium ulcerans or, rarely, Corynebacterium pseudotuberculosis. While diphtheria laboratory confirmation requires culture methods to determine toxigenicity, real-time PCR (RT-PCR) provides a faster method to detect the toxin gene (tox). Nontoxigenic tox-bearing (NTTB) Corynebacterium isolates have been described, but impact of these isolates on the accuracy of molecular diagnostics is not well characterized. Here, we describe a new triplex RT-PCR assay to detect tox and distinguish C. diphtheriae from the closely related species C. ulcerans and C. pseudotuberculosis. Analytical sensitivity and specificity of the assay were assessed in comparison to culture using 690 previously characterized microbial isolates. The new triplex assay characterized Corynebacterium isolates accurately, with 100% analytical sensitivity for all targets. Analytical specificity with isolates was 94.1%, 100%, and 99.5% for tox, Diph_rpoB, and CUP_rpoB targets, respectively. Twenty-nine NTTB Corynebacterium isolates, representing 5.9% of 494 nontoxigenic isolates tested, were detected by RT-PCR. Whole-genome sequencing of NTTB isolates revealed varied mutations putatively underlying their lack of toxin production, as well as eight isolates with no mutation in tox or the promoter region. This new Corynebacterium RT-PCR method provides a rapid tool to screen isolates and identify probable diphtheria cases directly from specimens. However, the sporadic occurrence of NTTB isolates reinforces the viewpoint that diphtheria culture diagnostics continue to provide the most accurate case confirmation.

Background Reliable diagnostics are key to identifying influenza infections. Our objectives were to describe detection of influenza among severe acute respiratory infection (SARI) cases, to compare test results from the FTD-33 kit for influenza detection to the Centers for Disease Control (CDC) human influenza virus detection and characterization panel, and to assess seasonality of influenza in Burkina Faso. Methods: Nasopharyngeal and oropharyngeal specimens from SARI cases (hospitalized patients with fever, cough, and onset in the previous 10 days) were tested using the FTD-33 kit and the CDC rRT-PCR influenza assays. We assessed sensitivity and specificity of the FTD-33 kit for detecting Influenza A, Influenza B, and the influenza A(H1N1)pdm09 strain using the CDC human influenza rRT-PCR panel as the gold standard. Results: From December 2016 to February 2019, 1706 SARI cases were identified, 1,511 specimens were tested, and 211 were positive for influenza A (14.0%) and 100 for influenza B (6.6%) by either assay. Higher influenza circulation occurred between November and April with varying peaks of influenza A and B. Sensitivity of the FTD-33 assay was 91.9% for influenza A, 95.7% for influenza B, and 93.8% for A(H1N1)pdm09 subtype. Specificity was over 99% for all three tests. Conclusions: Our study indicates that Burkina Faso has one peak of influenza each year which is similar to the Northern Hemisphere and differs from other countries in West Africa. We found high concordance of influenza results between the two assays indicating FTD-33 can be used to reliably detect influenza among SARI cases.

Among 146 nasopharyngeal (NP) and oropharyngeal (OP) swab pairs collected ≤7 days after illness onset, Real-Time Reverse Transcriptase Polymerase Chain Reaction assay for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2 RT-PCR) diagnostic results were 95.2% concordant. However, NP swab cycle threshold values were lower (indicating more virus) in 66.7% of concordant-positive pairs, suggesting NP swabs may more accurately detect the amount of SARS-CoV-2.

Summary Background On April 25, 2017, a cluster of unexplained illnesses and deaths associated with a funeral was reported in Sinoe County, Liberia. Molecular testing identified Neisseria meningitidis serogroup C (NmC) in specimens from patients. We describe the epidemiological investigation of this cluster and metagenomic characterisation of the outbreak strain. Methods We collected epidemiological data from the field investigation and medical records review. Confirmed, probable, and suspected cases were defined on the basis of molecular testing and signs or symptoms of meningococcal disease. Metagenomic sequences from patient specimens were compared with 141 meningococcal isolate genomes to determine strain lineage. Findings 28 meningococcal disease cases were identified, with dates of symptom onset from April 21 to April 30, 2017: 13 confirmed, three probable, and 12 suspected. 13 patients died. Six (21%) patients reported fever and 23 (82%) reported gastrointestinal symptoms. The attack rate for confirmed and probable cases among funeral attendees was 10%. Metagenomic sequences from six patient specimens were similar to a sequence type (ST) 10217 (clonal complex [CC] 10217) isolate genome from Niger, 2015. Multilocus sequencing identified five of seven alleles from one specimen that matched ST-9367, which is represented in the PubMLST database by one carriage isolate from Burkina Faso, in 2011, and belongs to CC10217. Interpretation This outbreak featured high attack and case fatality rates. Clinical presentation was broadly consistent with previous meningococcal disease outbreaks, but predominance of gastrointestinal symptoms was unusual compared with previous African meningitis epidemics. The outbreak strain was genetically similar to NmC CC10217, which caused meningococcal disease outbreaks in Niger and Nigeria. CC10217 had previously been identified only in the African meningitis belt. Funding US Global Health Security.

On April 25, 2017, a cluster of unexplained illness and deaths among persons who had attended a funeral during April 21-22 was reported in Sinoe County, Liberia (1). Using a broad initial case definition, 31 cases were identified, including 13 (42%) deaths. Twenty-seven cases were from Sinoe County (1), and two cases each were from Grand Bassa and Monsterrado counties, respectively. On May 5, 2017, initial multipathogen testing of specimens from four fatal cases using the Taqman Array Card (TAC) assay identified Neisseria meningitidis in all specimens. Subsequent testing using direct real-time polymerase chain reaction (PCR) confirmed N. meningitidis in 14 (58%) of 24 patients with available specimens and identified N. meningitidis serogroup C (NmC) in 13 (54%) patients. N. meningitidis was detected in specimens from 11 of the 13 patients who died; no specimens were available from the other two fatal cases. On May 16, 2017, the National Public Health Institute of Liberia and the Ministry of Health of Liberia issued a press release confirming serogroup C meningococcal disease as the cause of this outbreak in Liberia.

An outbreak at a university in Georgia was identified after 83 cases of probable pneumonia were reported among students. Respiratory specimens were obtained from 21 students for the outbreak investigation. The TaqMan array card (TAC), a quantitative PCR (qPCR)-based multipathogen detection technology, was used to initially identify Mycoplasma pneumoniae as the causative agent in this outbreak. TAC demonstrated 100% diagnostic specificity and sensitivity compared to those of the multiplex qPCR assay for this agent. All M. pneumoniae specimens ( n = 12) and isolates ( n = 10) were found through genetic analysis to be susceptible to macrolide antibiotics. The strain diversity of M. pneumoniae associated with this outbreak setting was identified using a variety of molecular typing procedures, resulting in two P1 genotypes (types 1 [60%] and 2 [40%]) and seven different multilocus variable-number tandem-repeat analysis (MLVA) profiles. Continued molecular typing of this organism, particularly during outbreaks, may enhance the current understanding of the epidemiology of M. pneumoniae and may ultimately lead to a more effective public health response.

BACKGROUND From January 2014-July 2014, more than 46 000 unaccompanied children (UC) from Central America crossed the US-Mexico border. In June-July, UC aged 9-17 years in 4 shelters and 1 processing center in 4 states were hospitalized with acute respiratory illness. We conducted a multistate investigation to interrupt disease transmission. METHODS Medical charts were abstracted for hospitalized UC. Nonhospitalized UC with influenza-like illness were interviewed, and nasopharyngeal and oropharyngeal swabs were collected to detect respiratory pathogens. Nasopharyngeal swabs were used to assess pneumococcal colonization in symptomatic and asymptomatic UC. Pneumococcal blood isolates from hospitalized UC and nasopharyngeal isolates were characterized by serotyping and whole-genome sequencing. RESULTS Among 15 hospitalized UC, 4 (44%) of 9 tested positive for influenza viruses, and 6 (43%) of 14 with blood cultures grew pneumococcus, all serotype 5. Among 48 nonhospitalized children with influenza-like illness, 1 or more respiratory pathogens were identified in 46 (96%). Among 774 nonhospitalized UC, 185 (24%) yielded pneumococcus, and 70 (38%) were serotype 5. UC transferring through the processing center were more likely to be colonized with serotype 5 (odds ratio, 3.8; 95% confidence interval, 2.1-6.9). Analysis of core pneumococcal genomes detected 2 related, yet independent, clusters. No pneumococcus cases were reported after pneumococcal and influenza immunization campaigns. CONCLUSIONS This respiratory disease outbreak was due to multiple pathogens, including Streptococcus pneumoniae serotype 5 and influenza viruses. Pneumococcal and influenza vaccinations prevented further transmission. Future efforts to prevent similar outbreaks will benefit from use of both vaccines.

Identification of etiology remains a significant challenge in the diagnosis of infectious diseases, particularly in resource-poor settings. Viral, bacterial, and fungal pathogens, as well as parasites, play a role for many syndromes, and optimizing a single diagnostic system to detect a range of pathogens is challenging. The TaqMan Array Card (TAC) is a multiple-pathogen detection method that has previously been identified as a valuable technique for determining etiology of infections and holds promise for expanded use in clinical microbiology laboratories and surveillance studies. We selected TAC for use in the Aetiology of Neonatal Infection in South Asia (ANISA) study for identifying etiologies of severe disease in neonates in Bangladesh, India, and Pakistan. Here we report optimization of TAC to improve pathogen detection and overcome technical challenges associated with use of this technology in a large-scale surveillance study. Specifically, we increased the number of assay replicates, implemented a more robust RT-qPCR enzyme formulation, and adopted a more efficient method for extraction of total nucleic acid from blood specimens. We also report the development and analytical validation of ten new assays for use in the ANISA study. Based on these data, we revised the study-specific TACs for detection of 22 pathogens in NP/OP swabs and 12 pathogens in blood specimens as well as two control reactions (internal positive control and human nucleic acid control) for each specimen type. The cumulative improvements realized through these optimization studies will benefit ANISA and perhaps other studies utilizing multiple-pathogen detection approaches. These lessons may also contribute to the expansion of TAC technology to the clinical setting.