AbstractObjectiveTo determine the diagnostic accuracy of serological tests for coronavirus disease-2019 (covid-19).DesignSystematic review and meta-analysis.Data sourcesMedline, bioRxiv, and medRxiv from 1 January to 30 April 2020, using subject headings or subheadings combined with text words for the concepts of covid-19 and serological tests for covid-19.Eligibility criteria and data analysisEligible studies measured sensitivity or specificity, or both of a covid-19 serological test compared with a reference standard of viral culture or reverse transcriptase polymerase chain reaction. Studies were excluded with fewer than five participants or samples. Risk of bias was assessed using quality assessment of diagnostic accuracy studies 2 (QUADAS-2). Pooled sensitivity and specificity were estimated using random effects bivariate meta-analyses.Main outcome measuresThe primary outcome was overall sensitivity and specificity, stratified by method of serological testing (enzyme linked immunosorbent assays (ELISAs), lateral flow immunoassays (LFIAs), or chemiluminescent immunoassays (CLIAs)) and immunoglobulin class (IgG, IgM, or both). Secondary outcomes were stratum specific sensitivity and specificity within subgroups defined by study or participant characteristics, including time since symptom onset.Results5016 references were identified and 40 studies included. 49 risk of bias assessments were carried out (one for each population and method evaluated). High risk of patient selection bias was found in 98% (48/49) of assessments and high or unclear risk of bias from performance or interpretation of the serological test in 73% (36/49). Only 10% (4/40) of studies included outpatients. Only two studies evaluated tests at the point of care. For each method of testing, pooled sensitivity and specificity were not associated with the immunoglobulin class measured. The pooled sensitivity of ELISAs measuring IgG or IgM was 84.3% (95% confidence interval 75.6% to 90.9%), of LFIAs was 66.0% (49.3% to 79.3%), and of CLIAs was 97.8% (46.2% to 100%). In all analyses, pooled sensitivity was lower for LFIAs, the potential point-of-care method. Pooled specificities ranged from 96.6% to 99.7%. Of the samples used for estimating specificity, 83% (10 465/12 547) were from populations tested before the epidemic or not suspected of having covid-19. Among LFIAs, pooled sensitivity of commercial kits (65.0%, 49.0% to 78.2%) was lower than that of non-commercial tests (88.2%, 83.6% to 91.3%). Heterogeneity was seen in all analyses. Sensitivity was higher at least three weeks after symptom onset (ranging from 69.9% to 98.9%) compared with within the first week (from 13.4% to 50.3%).ConclusionHigher quality clinical studies assessing the diagnostic accuracy of serological tests for covid-19 are urgently needed. Currently, available evidence does not support the continued use of existing point-of-care serological tests.Study registrationPROSPERO CRD42020179452.

Through integration of large-scale bacterial whole-genome sequencing and social-network analysis, we show that a socioenvironmental factor--most likely increased crack cocaine use--triggered the simultaneous expansion of two extant lineages of M. tuberculosis that was sustained by key members of a high-risk social network. Genotyping and contact tracing alone did not capture the true dynamics of the outbreak. (Funded by Genome British Columbia and others.).

Mycobacterium tuberculosis is successfully evolving antibiotic resistance, threatening attempts at tuberculosis epidemic control. Mechanisms of resistance, including the genetic changes favored by selection in resistant isolates, are incompletely understood. Using 116 newly and 7 previously sequenced M. tuberculosis genomes, we identified genomewide signatures of positive selection specific to the 47 resistant genomes. By searching for convergent evolution, the independent fixation of mutations at the same nucleotide site or gene, we recovered 100% of a set of known resistance markers. We also found evidence of positive selection in an additional 39 genomic regions in resistant isolates. These regions encode pathways of cell wall biosynthesis, transcriptional regulation and DNA repair. Mutations in these regions could directly confer resistance or compensate for fitness costs associated with resistance. Functional genetic analysis of mutations in one gene, ponA1, demonstrated an in vitro growth advantage in the presence of the drug rifampicin.

Van Orden (1987) reported that false positive errors in a categorization task are elevated for homophonic foils (e.g., HARE for A PART OF THE HUMAN BODY). Two new experiments replicate this finding and extend it to nonword homophone foils (e.g., SUTE FOR AN ARTICLE OF CLOTHING). False positive errors to nonword homophone foils substantially exceed false positive errors to nonhomophonic nonword spelling controls, showing that the phonological characteristics of the nonword foils are critical. Because nonwords are not represented in the lexicon, this new result implicates computed phonological codes as a source of the categorization errors. Additionally, in each of two experiments, matched word and nonword homophones produced virtually identical error rates. If stimulus nonword homophones are viewed as extremely unfamiliar words, compared with the relatively familiar stimulus word homophones, then our failure to observe an effect of stimulus familiarity strengthens the case that phonological coding plays a role in the identification of all printed words. The fact that the results are obtained in a categorization task that requires reading for meaning (rather than a lexical decision task) makes it difficult to avoid the conclusion that phonological mediation plays a role in normal reading of text for meaning.

A critical question in tuberculosis control is why some strains of Mycobacterium tuberculosis are preferentially associated with multiple drug resistances. We demonstrate that M. tuberculosis strains from Lineage 2 (East Asian lineage and Beijing sublineage) acquire drug resistances in vitro more rapidly than M. tuberculosis strains from Lineage 4 (Euro-American lineage) and that this higher rate can be attributed to a higher mutation rate. Moreover, the in vitro mutation rate correlates well with the bacterial mutation rate in humans as determined by whole genome sequencing of clinical isolates. Finally, using a stochastic mathematical model, we demonstrate that the observed differences in mutation rate predict a substantially higher probability that patients infected with a drug susceptible Lineage 2 strain will harbor multidrug resistant bacteria at the time of diagnosis. These data suggest that interventions to prevent the emergence of drug resistant tuberculosis should target bacterial as well as treatment-related risk factors.