23Surveillance of drug-resistant bacteria is essential for healthcare providers to deliver effective 24 empiric antibiotic therapy. However, traditional molecular epidemiology does not typically occur 25 on a timescale that could impact patient treatment and outcomes. Here we present a method 26 called 'genomic neighbor typing' for inferring the phenotype of a bacterial sample by identifying 27 its closest relatives in a database of genomes with metadata. We show that this technique can 28 infer antibiotic susceptibility and resistance for both S. pneumoniae and N. gonorrhoeae. We 29 implemented this with rapid k-mer matching, which, when used on Oxford Nanopore MinION 30 data, can run in real time. This resulted in determination of resistance within ten minutes 31 (sens/spec 91%/100% for S. pneumoniae and 81%/100% N. gonorrhoeae from isolates with a 32 representative database) of sequencing starting, and for clinical metagenomic sputum samples 33 (75%/100% for S. pneumoniae), within four hours of sample collection. This flexible approach has 34 wide application to pathogen surveillance and may be used to greatly accelerate appropriate 35 empirical antibiotic treatment. 36 45The molecular epidemiology of infectious disease allows us to identify high-risk pathogens and 46 determine their patterns of spread, on the basis of their genetics or (increasingly) genomics. 47Conventionally such studies, including outbreak investigations and characterization of novel 48 resistant strains, have been conducted in retrospect, but this has been changing with the 49 availability of new and increasingly inexpensive sequencing technologies 2,3 . The wealth of data 50 generated by genomics is promising but introduces a new challenge: while many features of a 51 sequence are correlated with the phenotype of interest, few are causative. 52 53 Prescription, however, has long been informed by correlative features when causative ones are 54 difficult to measure, for example whether the same syndrome or pathogen occurring in other 55 patients from the same clinical environment have responded to a particular antibiotic. This has 56 also been observed at the genetic level as well, as a result of genetic linkage between resistance 57 elements and the rest of the genome. An example is given by the pneumococcus (Streptococcus 58 pneumoniae). The Centers for Disease Control have rated the threat level of drug-resistant 59 pneumococcus as 'serious' 4 . While resistance arises in pneumococci through a variety of 60 mechanisms, approximately 90% of the variance in the minimal inhibitory concentration (MIC) 61 for antibiotics of different classes can be explained by the loci determining the strain type 5 , even 62 though none of these loci themselves causes resistance. Thus, in the overwhelming majority of 63 cases, resistance and susceptibility can be inferred from coarse strain typing based on population Results 81 82 Resistance is associated with clones in S. pneumoniae and N. gonorrhoeae 83 84 To quantify the association of clones with antibi...

Background: There is limited information on the relation between antibiotic use and antibiotic resistance in the US.Methods: We used multivariable logistic regression to relate state-specific rates of outpatient prescribing overall for fluoroquinolones, penicillins, macrolides, and cephalosporins between 2011-2014 to state-specific prevalence of resistance for select combinations of antibiotics/bacteria among catheter-associated urinary tract infections (CAUTIs) in the CDC Patient Safety Atlas data between 2011-2014 for adults aged 65+y and 19-64y, adjusting for potential confounders.Results: Rates of fluoroquinolone prescribing were positively associated with prevalence of fluoroquinolone resistance in Escherichia coli and Pseudomonas aeruginosa (both age groups), resistance to extended-spectrum (ES) cephalosporins in E. coli (aged 19-64y), and resistance to methicillin in Staphylococcus aureus (aged 19-64y). Rates of penicillin prescribing were positively associated with prevalence of resistance to fluoroquinolones in E. coli (aged 65+) and P. aeruginosa (both age groups), and resistance to ES cephalosporins in Klebsiella spp. (both age groups). Rates of cephalosporin prescribing were negatively associated with prevalence of resistance to fluoroquinolones in E. coli and resistance to ES cephalosporins in Klebsiella spp. (both age groups). Average annual temperature was positively associated with prevalence of resistance to ES cephalosporins in E. coli and P. aeruginosa, and resistance to fluoroquinolones in E. coli.Conclusions: Our results suggest that prescribing of fluoroquinolones and penicillins to US adults is associated with prevalence of antibiotic resistance, including ESBLs and MRSA.

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