The diagnosis of paediatric pulmonary tuberculosis is difficult, especially in young infants who cannot expectorate sputum spontaneously. Breath testing has shown promise in diagnosing respiratory tract infections, but data on paediatric tuberculosis are limited. We performed a prospective cross-sectional study in Kenya in children younger than five years with symptoms of tuberculosis. We analysed exhaled breath with a hand-held battery-powered nose device. For data analysis, machine learning was applied using samples classified as positive (microbiologically confirmed) or negative (unlikely tuberculosis) to assess diagnostic accuracy. Breath analysis was performed in 118 children. The area under the curve of the optimal model was 0.73. At a sensitivity of 86 % (CI 62-96 %), this resulted in a specificity of 42 % (95 % CI 30-55 %). Exhaled breath analysis shows promise as a triage test for TB in young children, although the WHO target product characteristics were not met.

For microbiological confirmation of pediatric pulmonary tuberculosis (PTB), gastric aspirates (GA) are often operationally unfeasible without hospitalization, and the encapsulated orogastric string test is not easily swallowed in young children. The Combined-NasoGastric-Tube-and-String-Test (CNGTST) enables dual collection of GA and string specimens. In a prospective cohort study in Kenya, we examined its feasibility in children under five with presumptive PTB and compared the bacteriological yield of string to GA. Paired GA and string samples were successfully collected in 95.6 % (281/294) of children. Mycobacterium tuberculosis was isolated from 7.0 % (38/541) of GA and 4.3 % (23/541) of string samples, diagnosing 8.2 % (23/281) of children using GA and 5.3 % (15/281) using string. The CNGTST was feasible in nearly all children. Yield from string was two-thirds that of GA despite a half-hour median dwelling time. In settings where the feasibility of hospitalisation for GA is uncertain, the string component can be used to confirm PTB.

Listeria monocytogenes can cause severe foodborne illness, including miscarriage during pregnancy or death in newborn infants. When outbreaks of L. monocytogenes illness occur, it may be possible to determine the food source of the outbreak. However, most reported L. monocytogenes illnesses do not occur as part of a recognized outbreak and most of the time the food source of sporadic L. monocytogenes illness in people cannot be determined. In the United States, L. monocytogenes isolates from patients, foods, and environments are routinely sequenced and analyzed by whole genome multilocus sequence typing (wgMLST) for outbreak detection by PulseNet, the national molecular surveillance system for foodborne illnesses. We investigated whether machine learning approaches applied to wgMLST allele call data could assist in attribution analysis of food source of L. monocytogenes isolates. We compiled isolates with a known source from five food categories (dairy, fruit, meat, seafood, and vegetable) using the metadata of L. monocytogenes isolates in PulseNet, deduplicated closely genetically related isolates, and developed random forest models to predict the food sources of isolates. Prediction accuracy of the final model varied across the food categories; it was highest for meat (65%), followed by fruit (45%), vegetable (45%), dairy (44%), and seafood (37%); overall accuracy was 49%, compared with the naive prediction accuracy of 28%. Our results show that random forest can be used to capture genetically complex features of high-resolution wgMLST for attribution of isolates to their sources.

Introduction. Combining genomic and geospatial data can be useful for understanding Mycobacterium tuberculosis (Mtb) transmission in high tuberculosis burden settings. Methods. We performed whole genome sequencing (WGS) on Mtb DNA extracted from sputum cultures from a population-based tuberculosis study conducted in 2012-2016 in Gaborone, Botswana. We used kernel density estimation, spatial K-functions, and created spatial distributions of phylogenetic trees. WGS-based clusters of isolates <5 single nucleotide polymorphisms were considered recent transmission, and large WGS-based clusters (>10 members) were considered outbreaks. Results. We analyzed data from 1449 participants with culture-confirmed TB. Among these, 946 (65%) participants had both molecular and geospatial data. A total of 62 belonged to five large outbreaks (10-19 participants each). Geospatial clustering was detected in two of the five large outbreaks, suggesting heterogeneous spatial patterns within the community. Conclusions. Integration of genomic and geospatial data identified distinct patterns of tuberculosis transmission in a high-tuberculosis burden setting. Targeted interventions in these smaller geographies may interrupt on-going transmission. Copyright The copyright holder for this preprint is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.

Diagnosis of tuberculosis (TB) among young children (<5 years) is challenging due to the paucibacillary nature of clinical disease and clinical similarities to other childhood diseases. We used machine learning to develop accurate prediction models of microbial confirmation with simply defined and easily obtainable clinical, demographic, and radiologic factors. We evaluated eleven supervised machine learning models (using stepwise regression, regularized regression, decision tree, and support vector machine approaches) to predict microbial confirmation in young children (<5 years) using samples from invasive (reference-standard) or noninvasive procedure. Models were trained and tested using data from a large prospective cohort of young children with symptoms suggestive of TB in Kenya. Model performance was evaluated using areas under the receiver operating curve (AUROC) and precision-recall curve (AUPRC), accuracy metrics. (i.e., sensitivity, specificity), F-beta scores, Cohen's Kappa, and Matthew's Correlation Coefficient. Among 262 included children, 29 (11%) were microbially confirmed using any sampling technique. Models were accurate at predicting microbial confirmation in samples obtained from invasive procedures (AUROC range: 0.84-0.90) and from noninvasive procedures (AUROC range: 0.83-0.89). History of household contact with a confirmed case of TB, immunological evidence of TB infection, and a chest x-ray consistent with TB disease were consistently influential across models. Our results suggest machine learning can accurately predict microbial confirmation of M. tuberculosis in young children using simply defined features and increase the bacteriologic yield in diagnostic cohorts. These findings may facilitate clinical decision making and guide clinical research into novel biomarkers of TB disease in young children.

Combining genomic and geospatial data can be useful for understanding Mycobacterium tuberculosis transmission in high-burden tuberculosis (TB) settings. We performed whole-genome sequencing on M. tuberculosis DNA extracted from sputum cultures from a population-based TB study conducted in Gaborone, Botswana, during 2012-2016. We determined spatial distribution of cases on the basis of shared genotypes among isolates. We considered clusters of isolates with ≤5 single-nucleotide polymorphisms identified by whole-genome sequencing to indicate recent transmission and clusters of ≥10 persons to be outbreaks. We obtained both molecular and geospatial data for 946/1,449 (65%) participants with culture-confirmed TB; 62 persons belonged to 5 outbreaks of 10-19 persons each. We detected geospatial clustering in just 2 of those 5 outbreaks, suggesting heterogeneous spatial patterns. Our findings indicate that targeted interventions applied in smaller geographic areas of high-burden TB identified using integrated genomic and geospatial data might help interrupt TB transmission during outbreaks.

BACKGROUND: Many children with pulmonary tuberculosis remain undiagnosed and untreated with related high morbidity and mortality. Recent advances in childhood tuberculosis algorithm development have incorporated prediction modelling, but studies so far have been small and localised, with limited generalisability. We aimed to evaluate the performance of currently used diagnostic algorithms and to use prediction modelling to develop evidence-based algorithms to assist in tuberculosis treatment decision making for children presenting to primary health-care centres. METHODS: For this meta-analysis, we identified individual participant data from a WHO public call for data on the management of tuberculosis in children and adolescents and referral from childhood tuberculosis experts. We included studies that prospectively recruited consecutive participants younger than 10 years attending health-care centres in countries with a high tuberculosis incidence for clinical evaluation of pulmonary tuberculosis. We collated individual participant data including clinical, bacteriological, and radiological information and a standardised reference classification of pulmonary tuberculosis. Using this dataset, we first retrospectively evaluated the performance of several existing treatment-decision algorithms. We then used the data to develop two multivariable prediction models that included features used in clinical evaluation of pulmonary tuberculosis-one with chest x-ray features and one without-and we investigated each model's generalisability using internal-external cross-validation. The parameter coefficient estimates of the two models were scaled into two scoring systems to classify tuberculosis with a prespecified sensitivity target. The two scoring systems were used to develop two pragmatic, treatment-decision algorithms for use in primary health-care settings. FINDINGS: Of 4718 children from 13 studies from 12 countries, 1811 (38·4%) were classified as having pulmonary tuberculosis: 541 (29·9%) bacteriologically confirmed and 1270 (70·1%) unconfirmed. Existing treatment-decision algorithms had highly variable diagnostic performance. The scoring system derived from the prediction model that included clinical features and features from chest x-ray had a combined sensitivity of 0·86 [95% CI 0·68-0·94] and specificity of 0·37 [0·15-0·66] against a composite reference standard. The scoring system derived from the model that included only clinical features had a combined sensitivity of 0·84 [95% CI 0·66-0·93] and specificity of 0·30 [0·13-0·56] against a composite reference standard. The scoring system from each model was placed after triage steps, including assessment of illness acuity and risk of poor tuberculosis-related outcomes, to develop treatment-decision algorithms. INTERPRETATION: We adopted an evidence-based approach to develop pragmatic algorithms to guide tuberculosis treatment decisions in children, irrespective of the resources locally available. This approach will empower health workers in primary health-care settings with high tuberculosis incidence and limited resources to initiate tuberculosis treatment in children to improve access to care and reduce tuberculosis-related mortality. These algorithms have been included in the operational handbook accompanying the latest WHO guidelines on the management of tuberculosis in children and adolescents. Future prospective evaluation of algorithms, including those developed in this work, is necessary to investigate clinical performance. FUNDING: WHO, US National Institutes of Health.

Ongoing symptoms might follow acute COVID-19. Using electronic health information, we compared pre‒ and post‒COVID-19 diagnostic codes to identify symptoms that had higher encounter incidence in the post‒COVID-19 period as sequelae. This method can be used for hypothesis generation and ongoing monitoring of sequelae of COVID-19 and future emerging diseases.

BACKGROUND: Pediatric tuberculosis (TB) remains a critical public health concern, yet bacteriologic confirmation of TB in children is challenging. Clinical, demographic, and radiological factors associated with a positive Mycobacterium tuberculosis specimen in young children (5years) are poorly understood. METHODS: We conducted a prospective cohort study of young children with presumptive TB and examined clinical, demographic, and radiologic factors associated with invasive and noninvasive specimen collection techniques (gastric aspirate, induced sputum, nasopharyngeal aspirate, stool, and string test); up to 2 samples were taken per child, per technique. We estimated associations between these factors and a positive specimen for each technique using generalized estimating equations (GEEs) and logistic regression. RESULTS: A median (range) of 544 (507-566) samples were obtained for each specimen collection technique from 300 enrolled children; bacteriologic yield was low across all collection techniques (range, 1%-7% from Xpert MTB/RIF or culture), except for lymph node fine needle aspiration (29%) taken for children with cervical lymphadenopathy. Factors associated with positive M. tuberculosis samples across all techniques included prolonged lethargy (median [range] adjusted odds ratio [aOR], 8.1 [3.9-10.1]), history of exposure with a TB case (median [range] aOR, 6.1 [2.9-9.0]), immunologic evidence of M. tuberculosis infection (median [range] aOR, 4.6 [3.7-9.2]), large airway compression (median [range] aOR, 6.7 [4.7-9.5]), and hilar/mediastinal density (median [range] aOR, 2.9 [1.7-3.2]). CONCLUSIONS: Identifying factors that lead to a positive M. tuberculosis specimen in very young children can inform clinical management and increase the efficiency of diagnostic testing in children being assessed for TB.

As of October 21, 2022, a total of 27,884 monkeypox cases (confirmed and probable) have been reported in the United States.(§) Gay, bisexual, and other men who have sex with men have constituted a majority of cases, and persons with HIV infection and those from racial and ethnic minority groups have been disproportionately affected (1,2). During previous monkeypox outbreaks, severe manifestations of disease and poor outcomes have been reported among persons with HIV infection, particularly those with AIDS (3-5). This report summarizes findings from CDC clinical consultations provided for 57 patients aged ≥18 years who were hospitalized with severe manifestations of monkeypox(¶) during August 10-October 10, 2022, and highlights three clinically representative cases. Overall, 47 (82%) patients had HIV infection, four (9%) of whom were receiving antiretroviral therapy (ART) before monkeypox diagnosis. Most patients were male (95%) and 68% were non-Hispanic Black (Black). Overall, 17 (30%) patients received intensive care unit (ICU)-level care, and 12 (21%) have died. As of this report, monkeypox was a cause of death or contributing factor in five of these deaths; six deaths remain under investigation to determine whether monkeypox was a causal or contributing factor; and in one death, monkeypox was not a cause or contributing factor.** Health care providers and public health professionals should be aware that severe morbidity and mortality associated with monkeypox have been observed during the current outbreak in the United States (6,7), particularly among highly immunocompromised persons. Providers should test all sexually active patients with suspected monkeypox for HIV at the time of monkeypox testing unless a patient is already known to have HIV infection. Providers should consider early commencement and extended duration of monkeypox-directed therapy(††) in highly immunocompromised patients with suspected or laboratory-diagnosed monkeypox.(§§) Engaging all persons with HIV in sustained care remains a critical public health priority.

Since May 2022, approximately 20,000 cases of monkeypox have been identified in the United States, part of a global outbreak occurring in approximately 90 countries and currently affecting primarily gay, bisexual, and other men who have sex with men (MSM) (1). Monkeypox virus (MPXV) spreads from person to person through close, prolonged contact; a small number of cases have occurred in populations who are not MSM (e.g., women and children), and testing is recommended for persons who meet the suspected case definition* (1). CDC previously developed five real-time polymerase chain reaction (PCR) assays for detection of orthopoxviruses from lesion specimens (2,3). CDC was granted 510(k) clearance for the nonvariola-orthopoxvirus (NVO)-specific PCR assay by the Food and Drug Administration. This assay was implemented within the Laboratory Response Network (LRN) in the early 2000s and became critical for early detection of MPXV and implementation of public health action in previous travel-associated cases as well as during the current outbreak (4-7). PCR assays (NVO and other Orthopoxvirus laboratory developed tests [LDT]) represent the primary tool for monkeypox diagnosis. These tests are highly sensitive, and cross-contamination from other MPXV specimens being processed, tested, or both alongside negative specimens can occasionally lead to false-positive results. This report describes three patients who had atypical rashes and no epidemiologic link to a monkeypox case or known risk factors; these persons received diagnoses of monkeypox based on late cycle threshold (Ct) values ≥34, which were false-positive test results. The initial diagnoses were followed by administration of antiviral treatment (i.e., tecovirimat) and JYNNEOS vaccine postexposure prophylaxis (PEP) to patients' close contacts. After receiving subsequent testing, none of the three patients was confirmed to have monkeypox. Knowledge gained from these and other cases resulted in changes to CDC guidance. When testing for monkeypox in specimens from patients without an epidemiologic link or risk factors or who do not meet clinical criteria (or where these are unknown), laboratory scientists should reextract and retest specimens with late Ct values (based on this report, Ct ≥34 is recommended) (8). CDC can be consulted for complex cases including those that appear atypical or questionable cases and can perform additional viral species- and clade-specific PCR testing and antiorthopoxvirus serologic testing.

BACKGROUND: Tuberculosis (TB) is a leading cause of illness and death in children globally. Improved bacteriologic and clinical diagnostic approaches in children are urgently needed. METHODS: In a prospective cohort study, a consecutive series of young (<5 years) children presenting with symptoms suggestive of TB and parenchymal abnormality on chest radiograph in inpatient and outpatient settings in Kisumu County, Kenya from October 2013 to August 2015 were evaluated at baseline and over 6 months. Up to 14 specimens per child were tested for the Mycobacterium tuberculosis complex by fluorescence microscopy, Xpert MTB/RIF and mycobacterial culture. Using detailed clinical characterization, cases were retrospectively classified according to standardized research case definitions and the sensitivity and specificity of microbiological tests on different specimen types were determined. RESULTS: Among 300 young children enrolled, 266 had sufficient information to be classified according to the research clinical case definition. Of these, 36% (96/266) had TB disease; 32% (31/96) with bacteriologically confirmed intrathoracic TB. Compared to culture, the sensitivity of a single Xpert test ranged from 60 to 67% and specificity from 97.5 to 100% for different specimen types. CONCLUSIONS: Despite extensive specimen collection and laboratory testing, TB could not be bacteriologically confirmed in almost two-thirds of children with intrathoracic TB classified by research clinical case definitions. Improved diagnostic tests are needed to identify children with TB and to exclude other potential causes of illness.

OBJECTIVES: To describe COVID-19-related pediatric hospitalizations during a period of B.1.617.2 (Delta) variant predominance and to determine age-specific factors associated with severe illness. PATIENTS AND METHODS: We abstracted data from medical charts to conduct a cross-sectional study of patients aged <21 years hospitalized at 6 US children's hospitals during July-August 2021 for COVID-19 or with an incidental positive SARS-CoV-2 test. Among patients with COVID-19, we assessed factors associated with severe illness by calculating age-stratified prevalence ratios (PR). We defined severe illness as receiving high-flow nasal cannula, positive airway pressure, or invasive mechanical ventilation. RESULTS: Of 947 hospitalized patients, 759 (80.1%) had COVID-19, of whom 287 (37.8%) had severe illness. Factors associated with severe illness included coinfection with RSV (PR 3.64) and bacteria (PR 1.88) in infants; RSV coinfection in patients aged 1-4 years (PR 1.96); and obesity in patients aged 5-11 (PR 2.20) and 12-17 years (PR 2.48). Having ≥2 underlying medical conditions was associated with severe illness in patients aged <1 (PR 1.82), 5-11 (PR 3.72), and 12-17 years (PR 3.19). CONCLUSIONS: Among patients hospitalized for COVID-19, factors associated with severe illness included RSV coinfection in those aged <5 years, obesity in those aged 5-17 years, and other underlying conditions for all age groups <18 years. These findings can inform pediatric practice, risk communication, and prevention strategies, including vaccination against COVID-19.

BACKGROUND: Case-control studies are commonly used to explore factors associated with enteric bacterial diseases. Control of confounding is challenging due to the large number of exposures of interest and the low frequencies of many of them. METHODS: We evaluated nearest-neighbors matching in a case-control study (originally 1:1 matched, published in 2004) of sporadic Campylobacter infections that included information on 433 exposures in 2,632 subjects during 1998-1999. We performed multiple imputation of missing data (m=100) and calculated Gower distances between cases and controls using all possible confounders for each exposure in each dataset. We matched each case with ≤20 controls within a data-determined distance. We calculated odds ratios and population attributable fractions (PAFs). RESULTS: Examination of pairwise correlation between exposures found very strong associations for 1,046 pairs of exposures. More than 100 exposures were associated with campylobacteriosis, including nearly all risk factors identified using the previously published approach that included only 16 exposures and some less studied, rare exposures such as consumption of chicken liver and raw clams. Consumption of chicken and non-poultry meat had the highest PAFs (62% and 59%, respectively). CONCLUSIONS: Nearest-neighbors matching appears to provide an improved ability to examine rare exposures and better control for numerous highly associated confounders.

Mycobacterium tuberculosis transmission dynamics in high-burden settings are poorly understood. Growing evidence suggests transmission may be characterized by extensive individual heterogeneity in secondary cases (i.e., superspreading), yet the degree and influence of such heterogeneity is largely unknown and unmeasured in high burden-settings. We conducted a prospective, population-based molecular epidemiology study of TB transmission in both an urban and rural setting of Botswana, one of the highest TB burden countries in the world. We used these empirical data to fit two mathematical models (urban and rural) that jointly quantified both the effective reproductive number, [Formula: see text], and the propensity for superspreading in each population. We found both urban and rural populations were characterized by a high degree of individual heterogeneity, however such heterogeneity disproportionately impacted the rural population: 99% of secondary transmission was attributed to only 19% of infectious cases in the rural population compared to 60% in the urban population and the median number of incident cases until the first outbreak of 30 cases was only 32 for the rural model compared to 791 in the urban model. These findings suggest individual heterogeneity plays a critical role shaping local TB epidemiology within subpopulations.

OBJECTIVE: Healthcare facilities are a well-known high-risk environment for transmission of M. tuberculosis, the etiologic agent of tuberculosis (TB) disease. However, the link between M. tuberculosis transmission in healthcare facilities and its role in the general TB epidemic is unknown. We estimated the proportion of overall TB transmission in the general population attributable to healthcare facilities. METHODS: We combined data from a prospective, population-based molecular epidemiologic study with a universal electronic medical record (EMR) covering all healthcare facilities in Botswana to identify biologically plausible transmission events occurring at the healthcare facility. Patients with M. tuberculosis isolates of the same genotype visiting the same facility concurrently were considered an overlapping event. We then used TB diagnosis and treatment data to categorize overlapping events into biologically plausible definitions. We calculated the proportion of overall TB cases in the cohort that could be attributable to healthcare facilities. RESULTS: In total, 1,881 participants had TB genotypic and EMR data suitable for analysis, resulting in 46,853 clinical encounters at 338 healthcare facilities. We identified 326 unique overlapping events involving 370 individual patients; 91 (5%) had biologic plausibility for transmission occurring at a healthcare facility. A sensitivity analysis estimated that 3%-8% of transmission may be attributable to healthcare facilities. CONCLUSIONS: Although effective interventions are critical in reducing individual risk for healthcare workers and patients at healthcare facilities, our findings suggest that development of targeted interventions aimed at community transmission may have a larger impact in reducing TB.

BACKGROUND: In 2019, the United States experienced a nationwide outbreak of e-cigarette, or vaping, product use-associated lung injury (EVALI). More than half of these patients required admission to an intensive care unit (ICU). METHODS: To synthesize information critical to pulmonary/critical care specialists in the care of patients with EVALI, we examined data available from patients hospitalized with EVALI between August 2019 and January 2020; reviewed the clinical course and critical care experience with those patients admitted to the ICU; and compiled opinion of national experts. RESULTS: Of the 2,708 confirmed or probable EVALI patients requiring hospitalization as of January 21, 2020, 1,604 (59.2%) had data available on ICU admission; of these, 705 (44.0%) were admitted to the ICU and are included in this analysis. The majority of ICU patients required respiratory support (88.5%), and in severe cases required intubation (36.1%), or extracorporeal membrane oxygenation (ECMO) (6.7%). The majority (93.0%) of these ICU patients survived to discharge. Review of the clinical course and expert opinion provided insight into: imaging; considerations for bronchoscopy; medical treatment, including use of empiric antibiotics, antivirals, and corticosteroids; respiratory support, including considerations for intubation, positioning maneuvers, and ECMO; and patient outcomes. CONCLUSIONS: Review of the clinical course of EVALI patients requiring ICU admission and compilation of expert opinion provided critical insight into pulmonary/critical care-specific considerations for this patient population. As a large proportion of patients hospitalized with EVALI required ICU admission, it is important to remain prepared to care for patients with EVALI.

During June 2021, the highly transmissible(†) B.1.617.2 (Delta) variant of SARS-CoV-2, the virus that causes COVID-19, became the predominant circulating strain in the United States. U.S. pediatric COVID-19-related hospitalizations increased during July-August 2021 following emergence of the Delta variant and peaked in September 2021.(§) As of May 12, 2021, CDC recommended COVID-19 vaccinations for persons aged ≥12 years,(¶) and on November 2, 2021, COVID-19 vaccinations were recommended for persons aged 5-11 years.** To date, clinical signs and symptoms, illness course, and factors contributing to hospitalizations during the period of Delta predominance have not been well described in pediatric patients. CDC partnered with six children's hospitals to review medical record data for patients aged <18 years with COVID-19-related hospitalizations during July-August 2021.(††) Among 915 patients identified, 713 (77.9%) were hospitalized for COVID-19 (acute COVID-19 as the primary or contributing reason for hospitalization), 177 (19.3%) had incidental positive SARS-CoV-2 test results (asymptomatic or mild infection unrelated to the reason for hospitalization), and 25 (2.7%) had multisystem inflammatory syndrome in children (MIS-C), a rare but serious inflammatory condition associated with COVID-19.(§§) Among the 713 patients hospitalized for COVID-19, 24.7% were aged <1 year, 17.1% were aged 1-4 years, 20.1% were aged 5-11 years, and 38.1% were aged 12-17 years. Approximately two thirds of patients (67.5%) had one or more underlying medical conditions, with obesity being the most common (32.4%); among patients aged 12-17 years, 61.4% had obesity. Among patients hospitalized for COVID-19, 15.8% had a viral coinfection(¶¶) (66.4% of whom had respiratory syncytial virus [RSV] infection). Approximately one third (33.9%) of patients aged <5 years hospitalized for COVID-19 had a viral coinfection. Among 272 vaccine-eligible (aged 12-17 years) patients hospitalized for COVID-19, one (0.4%) was fully vaccinated.*** Approximately one half (54.0%) of patients hospitalized for COVID-19 received oxygen support, 29.5% were admitted to the intensive care unit (ICU), and 1.5% died; of those requiring respiratory support, 14.5% required invasive mechanical ventilation (IMV). Among pediatric patients with COVID-19-related hospitalizations, many had severe illness and viral coinfections, and few vaccine-eligible patients hospitalized for COVID-19 were vaccinated, highlighting the importance of vaccination for those aged ≥5 years and other prevention strategies to protect children and adolescents from COVID-19, particularly those with underlying medical conditions.

BACKGROUND: Recommended by the World Health Organization as an initial diagnostic test for TB in children, Xpert(®) MTB/RIF is widely implemented in many countries, including Kenya.METHODS: Three hundred HIV-positive and negative children (<5 years) were enrolled in Kisumu County, Kenya, from October 2013 to August 2015. Multiple specimen types were collected from each child and tested using Xpert, liquid culture, and phenotypic drug susceptibility testing (DST). Samples positive for rifampin (RIF) resistance on Xpert were tested using line-probe assay and sequencing.RESULTS: Of 32 children with bacteriologically confirmed TB, 27 had positive Xpert results. Of these, 3/27 (11%, 95% CI 4-28) had RIF resistance detected on Xpert, but not by phenotypic DST, line-probe assay, or sequencing. For these three children, five Xpert tests showed RIF resistance; all five tests had semi-quantitative "very low" results and delay or absence of probe D signal, whereas no Xpert results with higher semi-quantitative results showed RIF resistance. All three children responded well to standard TB treatment.CONCLUSIONS: False RIF resistance may be detected in pediatric specimens. Further study is needed to determine if false RIF resistance is associated with low bacterial load.

BACKGROUND: Late sequelae of COVID-19 have been reported; however, few studies have investigated the time-course or incidence of late new COVID-19-related health conditions (post-COVID conditions) after COVID-19 diagnosis. Studies distinguishing post-COVID conditions from late conditions caused by other etiologies are lacking. Using data from a large administrative all-payer database, we assessed the type, association, and timing of post-COVID conditions following COVID-19 diagnosis. METHODS: Using the Premier Healthcare Database Special COVID-19 Release (PHD-SR) (release date, October 20, 2020) data, during March-June 2020, 27,589 inpatients and 46,857 outpatients diagnosed with COVID-19 (case-patients) were 1:1 matched with patients without COVID-19 through the 4-month follow-up period (control-patients) by using propensity score matching. In this matched-cohort study, adjusted odds ratios were calculated to assess for late conditions that were more common in case-patients compared with control-patients. Incidence proportion was calculated for conditions that were more common in case-patients than control-patients during 31-120 days following a COVID-19 encounter. RESULTS: During 31-120 days after an initial COVID-19 inpatient hospitalization, 7.0% of adults experienced at least one of five post-COVID conditions. Among adult outpatients with COVID-19, 7.7% experienced at least one of ten post-COVID conditions. During 31-60 days after an initial outpatient encounter, adults with COVID-19 were 2.8 times as likely to experience acute pulmonary embolism as outpatient control-patients and were also more likely to experience a range of conditions affecting multiple body systems (e.g. nonspecific chest pain, fatigue, headache, and respiratory, nervous, circulatory, and gastrointestinal system symptoms) than outpatient control-patients. Children with COVID-19 were not more likely to experience late conditions than children without COVID-19. CONCLUSIONS: These findings add to the evidence of late health conditions possibly related to COVID-19 in adults following COVID-19 diagnosis and can inform health care practice and resource planning for follow-up COVID-19 care.

IMPORTANCE: Criterion-standard specimens for tuberculosis diagnosis in young children, gastric aspirate (GA) and induced sputum, are invasive and rarely collected in resource-limited settings. A far less invasive approach to tuberculosis diagnostic testing in children younger than 5 years as sensitive as current reference standards is important to identify. OBJECTIVE: To characterize the sensitivity of preferably minimally invasive specimen and assay combinations relative to maximum observed yield from all specimens and assays combined. DESIGN, SETTING, AND PARTICIPANTS: In this prospective cross-sectional diagnostic study, the reference standard was a panel of up to 2 samples of each of 6 specimen types tested for Mycobacterium tuberculosis complex by Xpert MTB/RIF assay and mycobacteria growth indicator tube culture. Multiple different combinations of specimens and tests were evaluated as index tests. A consecutive series of children was recruited from inpatient and outpatient settings in Kisumu County, Kenya, between October 2013 and August 2015. Participants were children younger than 5 years who had symptoms of tuberculosis (unexplained cough, fever, malnutrition) and parenchymal abnormality on chest radiography or who had cervical lymphadenopathy. Children with 1 or more evaluable specimen for 4 or more primary study specimen types were included in the analysis. Data were analyzed from February 2015 to October 2020. MAIN OUTCOMES AND MEASURES: Cumulative and incremental diagnostic yield of combinations of specimen types and tests relative to the maximum observed yield. RESULTS: Of the 300 enrolled children, the median (interquartile range) age was 2.0 (1.0-3.6) years, and 151 (50.3%) were female. A total of 294 met criteria for analysis. Of 31 participants with confirmed tuberculosis (maximum observed yield), 24 (sensitivity, 77%; interdecile range, 68%-87%) had positive results on up to 2 GA samples and 20 (sensitivity, 64%; interdecile range, 53%-76%) had positive test results on up to 2 induced sputum samples. The yields of 2 nasopharyngeal aspirate (NPA) samples (23 of 31 [sensitivity, 74%; interdecile range, 64%-84%]), of 1 NPA sample and 1 stool sample (22 of 31 [sensitivity, 71%; interdecile range, 60%-81%]), or of 1 NPA sample and 1 urine sample (21.5 of 31 [sensitivity, 69%; interdecile range, 58%-80%]) were similar to reference-standard specimens. Combining up to 2 each of GA and NPA samples had an average yield of 90% (28 of 31). CONCLUSIONS AND RELEVANCE: NPA, in duplicate or in combination with stool or urine specimens, was readily obtainable and had diagnostic yield comparable with reference-standard specimens. This combination could improve tuberculosis diagnosis among children in resource-limited settings. Combining GA and NPA had greater yield than that of the current reference standards and may be useful in certain clinical and research settings.

Coronavirus disease 2019 (COVID-19) is a complex clinical illness with potential complications that might require ongoing clinical care (1-3). Few studies have investigated discharge patterns and hospital readmissions among large groups of patients after an initial COVID-19 hospitalization (4-7). Using electronic health record and administrative data from the Premier Healthcare Database,* CDC assessed patterns of hospital discharge, readmission, and demographic and clinical characteristics associated with hospital readmission after a patient's initial COVID-19 hospitalization (index hospitalization). Among 126,137 unique patients with an index COVID-19 admission during March-July 2020, 15% died during the index hospitalization. Among the 106,543 (85%) surviving patients, 9% (9,504) were readmitted to the same hospital within 2 months of discharge through August 2020. More than a single readmission occurred among 1.6% of patients discharged after the index hospitalization. Readmissions occurred more often among patients discharged to a skilled nursing facility (SNF) (15%) or those needing home health care (12%) than among patients discharged to home or self-care (7%). The odds of hospital readmission increased with age among persons aged ≥65 years, presence of certain chronic conditions, hospitalization within the 3 months preceding the index hospitalization, and if discharge from the index hospitalization was to a SNF or to home with health care assistance. These results support recent analyses that found chronic conditions to be significantly associated with hospital readmission (6,7) and could be explained by the complications of underlying conditions in the presence of COVID-19 (8), COVID-19 sequelae (3), or indirect effects of the COVID-19 pandemic (9). Understanding the frequency of, and risk factors for, readmission can inform clinical practice, discharge disposition decisions, and public health priorities such as health care planning to ensure availability of resources needed for acute and follow-up care of COVID-19 patients. With the recent increases in cases nationwide, hospital planning can account for these increasing numbers along with the potential for at least 9% of patients to be readmitted, requiring additional beds and resources.

The Centers for Disease Control and Prevention (CDC), the US Food and Drug Administration (FDA), state and local health departments, and public health and clinical stakeholders have investigated a nationwide outbreak of e-cigarette, or vaping, product use-associated lung injury (EVALI). 1 As of February 25, 2020, a total of 2,807 hospitalized cases of EVALI have been reported to the CDC from all 50 states, the District of Columbia, and two US territories (Puerto Rico and US Virgin Islands). Sixty-eight deaths have been confirmed in 29 states and the District of Columbia (as of February 18, 2020).2, 3, 4, 5, 6 Mechanisms for lung injury in this syndrome are still being investigated. Vitamin E acetate (VEA) is strongly linked to the EVALI outbreak. VEA has been found in product samples tested by FDA and state laboratories and patient BAL fluid samples tested by the CDC from geographically diverse states. VEA has not been found in the BAL fluid of people who do not have EVALI. However, evidence is not sufficient to rule out the contribution of other chemicals of concern, including chemicals in either tetrahydrocannabinol (THC) or non-THC products, in some of the reported EVALI cases. The current article summarizes evidence as of February 25, 2020, for potential toxicants and mechanisms of toxicity for EVALI.

Tuberculosis caused by concurrent infection with multiple Mycobacterium tuberculosis strains (i.e., mixed infection) challenges clinical and epidemiologic paradigms. We explored possible transmission mechanisms of mixed infection in a population-based, molecular epidemiology study in Botswana during 2012-2016. We defined mixed infection as multiple repeats of alleles at >2 loci within a discrete mycobacterial interspersed repetitive unit-variable-number tandem-repeat (MIRU-VNTR) result. We compared mixed infection MIRU-VNTR results with all study MIRU-VNTR results by considering all permutations at each multiple allele locus; matched MIRU-VNTR results were considered evidence of recently acquired strains and nonmatched to any other results were considered evidence of remotely acquired strains. Among 2,051 patients, 34 (1.7%) had mixed infection, of which 23 (68%) had recently and remotely acquired strains. This finding might support the mixed infection mechanism of recent transmission and simultaneous remote reactivation. Further exploration is needed to determine proportions of transmission mechanisms in settings where mixed infections are prevalent.

Contact investigation is one public health measure used to prevent tuberculosis by identifying and treating persons exposed to Mycobacterium tuberculosis. Contact investigations are a major tenet of global tuberculosis elimination efforts, but for many reasons remain ineffective. We describe a novel neighbor-based approach to reframe contact investigations.

Importance: To date, limited information is available on the characteristics of adolescents with e-cigarette, or vaping, product use-associated lung injury (EVALI). Objective: To inform public health and clinical practice by describing differences in demographics, substance use behaviors, and clinical characteristics of EVALI among adolescents compared with adults. Design, Setting, and Participants: Surveillance data reported to the Centers for Disease Control and Prevention during the 2019 EVALI outbreak were used to calculate adjusted prevalence ratios (aPRs) with 95% CIs and to test differences between 360 hospitalized or deceased adolescents vs 859 young adults and 936 adults with EVALI (N = 2155). Main Outcomes and Measures: Demographics, substance use behaviors, and clinical characteristics. Results: Included in this cross-sectional study were 360 hospitalized or deceased adolescents (age range, 13-17 years; 67.9% male) vs 859 young adults (age range, 18-24 years; 72.4% male) and 936 adults (age range, 25-49 years; 65.6% male) with EVALI. Adolescents diagnosed as having EVALI reported using any nicotine-containing (62.4%), any tetrahydrocannabinol (THC)-containing (81.7%), and both (50.8%) types of e-cigarette or vaping products. Informal sources for obtaining nicotine-containing and THC-containing e-cigarette or vaping products were more commonly reported by adolescents (50.5% for nicotine and 96.5% for THC) than young adults (19.8% for nicotine [aPR, 2.49; 95% CI, 1.78-3.46] and 86.9% for THC [aPR, 1.11; 95% CI, 1.05-1.18]) or adults (24.3% for nicotine [aPR, 2.06; 95% CI, 1.49-2.84] and 75.1% for THC [aPR, 1.29; 95% CI, 1.19-1.40]). Mental, emotional, or behavioral disorders were commonly reported; a history of attention-deficit/hyperactivity disorder was almost 4 times more likely among adolescents (18.1%) than adults (4.9%) (aPR, 3.74; 95% CI, 1.92-7.26). A history of asthma was more likely to be reported among adolescents (43.6%) than adults (28.3%) (aPR, 1.53; 95% CI, 1.14-2.05). Gastrointestinal and constitutional symptoms were more common in adolescents (90.9% and 97.3%, respectively) than adults (75.3% and 94.5%, respectively) (aPR, 1.20; 95% CI, 1.13-1.28 and aPR, 1.03; 95% CI, 1.00-1.06, respectively). Because of missing data, percentages may not be able to be calculated from data provided. Conclusions and Relevance: Public health and clinical professionals should continue to provide information to adolescents about the association between EVALI and THC-containing e-cigarette or vaping product use, especially those products obtained through informal sources, and that the use of any e-cigarette or vaping product is unsafe. Compared with adults, it appears that adolescents with EVALI more frequently have a history of asthma and mental, emotional, or behavioral disorders, such as attention-deficit/hyperactivity disorder, and report nonspecific problems, including gastrointestinal and constitutional symptoms; therefore, obtaining a confidential substance use history that includes e-cigarette or vaping product use is recommended.

BACKGROUND: Mutations in the genes inhA, katG and rpoB confer resistance to anti-tuberculosis (TB) drugs isoniazid and rifampin. We questioned whether specific mutations in these genes were associated with different clinical and microbiological characteristics. METHODS: In a multi-country prospective cohort study of MDR-TB, we identified inhA, katG and rpoB mutations in sputum isolates using the Hain MTBDRplus line probe assay. For specific mutations, we performed bivariate analysis to determine relative risk of baseline or acquired resistance to other TB drugs. We compared time-to-sputum-culture-conversion (TSCC) using Kaplan-Meier curves and stratified Cox regression. RESULTS: In total, 447 participants enrolled January 2005-December 2008 from seven countries were included. Relative to rpoB S531L, isolates with rpoB D516V had less cross-resistance to rifabutin, increased baseline resistance to other drugs, and increased acquired fluoroquinolone resistance.Relative to mutation of katG only, mutation of inhA promoter and katG was associated with increased acquired fluoroquinolone resistance and slower TSCC (125.5 vs. 89.0 days). CONCLUSIONS: Specific mutations in inhA and katG are associated with differences in resistance to other drugs and TSCC. Molecular testing may make it possible to tailor treatment and assess additional drug resistance risk according to specific mutation profile.

Mycobacterium tuberculosis complex (MTBC) is divided into several major phylogenetic lineages, with differential distribution globally. Using population-based data collected over a three year period, we performed 24-locus Mycobacterial Interspersed Repeat Unit - Variable Number Tandem Repeat (MIRU-VNTR) genotyping on all culture isolates from two districts of the country that differ in tuberculosis (TB) incidence (Gaborone, the capital, and Ghanzi in the Western Kalahari). The study objective was to characterize the molecular epidemiology of TB in these districts. Overall phylogenetic diversity mirrored that reported from neighboring Republic of South Africa, but differences in the two districts were marked. All four major lineages of M. tuberculosis were found in Gaborone, but only three of the four major lineages were found in Ghanzi. Strain diversity was lower in Ghanzi, with a large proportion (38%) of all isolates having an identical MIRU-VNTR result, compared to 6% of all isolates in Gaborone with the same MIRU-VNTR result. This study demonstrates localized differences in strain diversity by two districts in Botswana, and contributes to a growing characterization of MTBC diversity globally.

What is already known on this topic? In a recent examination of rehospitalization and death among previously hospitalized patients with e-cigarette or vaping, product use–associated lung injury (EVALI), at least one quarter of rehospitalizations and deaths occurred within 2 days of discharge; comorbidities were common among patients who were rehospitalized or who died after discharge. What is added by this report? Updated guidance recommends posthospitalization outpatient follow-up, optimally within 48 hours of discharge, and emphasizes the importance of preparation for hospital discharge and postdischarge care coordination to reduce risk of rehospitalization and death among hospitalized EVALI patients. What are the implications for public health practice? Incorporating this updated guidance into the management of hospitalized EVALI patients might reduce EVALI-associated morbidity and mortality. © 2020 Department of Health and Human Services. All rights reserved.

BACKGROUND: HIV is a major driver of the tuberculosis epidemic in sub-Saharan Africa. The population-level impact of antiretroviral therapy (ART) scale-up on tuberculosis rates in this region has not been well studied. We conducted a descriptive analysis to examine evidence of population-level effect of ART on tuberculosis by comparing trends in estimated tuberculosis notification rates, by HIV status, for countries in sub-Saharan Africa. METHODS: We estimated annual tuberculosis notification rates, stratified by HIV status during 2010-2015 using data from WHO, the Joint United Nations Programme on HIV/AIDS, and the United Nations Population Division. Countries were included in this analysis if they had >/=4 years of HIV prevalence estimates and >/= 75% of tuberculosis patients with known HIV status. We compared tuberculosis notification rates among people living with HIV (PLHIV) and people without HIV via Wilcoxon rank sum test. RESULTS: Among 23 included countries, the median annual average change in tuberculosis notification rates among PLHIV during 2010-2015 was -5.7% (IQR -6.9 to -1.7%), compared to a median change of -2.3% (IQR -4.2 to -0.1%) among people without HIV (p-value = 0.0099). Among 11 countries with higher ART coverage, the median annual average change in TB notification rates among PLHIV was -6.8% (IQR -7.6 to -5.7%) compared to a median change of -2.1% (IQR -6.0 to 0.7%) for PLHIV in 12 countries with lower ART coverage (p = 0.0106). CONCLUSION: Tuberculosis notification rates declined more among PLHIV than people without HIV, and have declined more in countries with higher ART coverage. These results are consistent with a population-level effect of ART on decreasing TB incidence among PLHIV. To further reduce TB incidence among PLHIV, additional scale-up of ART as well as greater use of isoniazid preventive therapy and active case-finding will be necessary.