The purpose of this study was to apply a novel statistical method for variable selection and a model-based approach for filling data gaps in mortality rates associated with foodborne diseases using the WHO Vital Registration mortality dataset. Correlation analysis and elastic net regularization methods were applied to drop redundant variables and to select the most meaningful subset of predictors. Whenever predictor data were missing, multiple imputation was used to fill in plausible values. Cluster analysis was applied to identify similar groups of countries based on the values of the predictors. Finally, a Bayesian hierarchical regression model was fit to the final dataset for predicting mortality rates. From 113 potential predictors, 32 were retained after correlation analysis. Out of these 32 predictors, eight with non-zero coefficients were selected using the elastic net regularization method. Based on the values of these variables, four clusters of countries were identified. The uncertainty of predictions was large for countries within clusters lacking mortality rates, and it was low for a cluster that had mortality rate information. Our results demonstrated that, using Bayesian hierarchical regression models, a data-driven clustering of countries and a meaningful subset of predictors can be used to fill data gaps in foodborne disease mortality.

ST131 Escherichia coli is an emergent clonal group that has achieved successful worldwide spread through a combination of virulence and antimicrobial resistance. Our aim was to develop a mathematical model, based on current knowledge of the epidemiology of ESBL-producing and non-ESBL-producing ST131 E. coli, to provide a framework enabling a better understanding of its spread within the community, in hospitals and long-term care facilities, and the potential impact of specific interventions on the rates of infection. A model belonging to the SEIS (Susceptible–Exposed–Infected–Susceptible) class of compartmental models, with specific modifications, was developed. Quantification of the model is based on the law of mass preservation, which helps determine the relationships between flows of individuals and different compartments. Quantification is deterministic or probabilistic depending on subpopulation size. The assumptions for the model are based on several developed epidemiological studies. Based on the assumptions of the model, an intervention capable of sustaining a 25% reduction in person-to-person transmission shows a significant reduction in the rate of infections caused by ST131; the impact is higher for non-ESBL-producing ST131 isolates than for ESBL producers. On the other hand, an isolated intervention reducing exposure to antimicrobial agents has much more limited impact on the rate of ST131 infection. Our results suggest that interventions achieving a continuous reduction in the transmission of ST131 in households, nursing homes and hospitals offer the best chance of reducing the burden of the infections caused by these isolates.

A challenge to the development of foodborne illness prevention measures is determining the sources of enteric illness. Microbial subtyping source-attribution models attribute illnesses to various sources, requiring data characterizing bacterial isolate subtypes collected from human and food sources. We evaluated the use of antimicrobial resistance data on isolates of Salmonella enterica serotype Hadar, collected from ill humans, food animals, and from retail meats, in two microbial subtyping attribution models. We also compared model results when either antimicrobial resistance or pulsed-field gel electrophoresis (PFGE) patterns were used to subtype isolates. Depending on the subtyping model used, 68–96% of the human infections were attributed to meat and poultry food products. All models yielded similar outcomes, with 86% [95% confidence interval (CI) 80–91] to 91% (95% CI 88–96) of the attributable infections attributed to turkey, and 6% (95% CI 2–10) to 14% (95% CI 8–20) to chicken. Few illnesses (<3%) were attributed to cattle or swine. Results were similar whether the isolates were obtained from food animals during processing or from retail meat products. Our results support the view that microbial subtyping models are a flexible and robust approach for attributing Salmonella Hadar.

Impetigo is common in remote Indigenous children of northern Australia, with the primary driver in this context being Streptococcus pyogenes [or group A Streptococcus (GAS)]. To reduce the high burden of impetigo, the transmission dynamics of GAS must be more clearly elucidated. We performed whole genome sequencing on 31 GAS isolates collected in a single community from children in 11 households with ⩾2 GAS-infected children. We aimed to determine whether transmission was occurring principally within households or across the community. The 31 isolates were represented by nine multilocus sequence types and isolates within each sequence type differed from one another by only 0–3 single nucleotide polymorphisms. There was evidence of extensive transmission both within households and across the community. Our findings suggest that strategies to reduce the burden of impetigo in this setting will need to extend beyond individual households, and incorporate multi-faceted, community-wide approaches.

The Charlson comorbidity index (CCI) is widely used for control of confounding from comorbidities in epidemiological studies. International Classification of Diseases (ICD)-coded diagnoses from administrative hospital databases is potentially an efficient way of deriving CCI. However, no studies have evaluated its validity in infectious disease research. We aim to compare CCI derived from administrative data and medical record review in predicting mortality in patients with infections. We conducted a cross-sectional study on 199 inpatients. Correlation analyses were used to compare comorbidity scores from ICD-coded administrative databases and medical record review. Multivariable regression models were constructed and compared for discriminatory power for 30-day in-hospital mortality. Overall agreement was fair [weighted kappa 0·33, 95% confidence interval (CI) 0·23–0·43]. Kappa coefficient ranged from 0·17 (95% CI 0·01–0·36) for myocardial infarction to 0·85 (95% CI 0·59–1·00) for connective tissue disease. Administrative data-derived CCI was predictive of CCI ⩾5 from medical record review, controlling for age, gender, resident status, ward class, clinical speciality, illness severity, and infection source (C = 0·773). Using the multivariable model comprising age, gender, resident status, ward class, clinical speciality, illness severity, and infection source to predict 30-day in-hospital mortality, administrative data-derived CCI (C = 0·729) provided a similar C statistic as medical record review (C = 0·717, P = 0·8548). In conclusion, administrative data-derived CCI can be used for assessing comorbidities and confounding control in infectious disease research.

Legionnaires’ disease (LD) is a globally distributed systemic infectious disease. The burden of LD in many regions is still unclear, especially in Asian countries including China. A survey of Legionella infection using real-time PCR and nested sequence-based typing (SBT) was performed in two hospitals in Shanghai, China. A total of 265 bronchoalveolar lavage fluid (BALF) specimens were collected from hospital A between January 2012 and December 2013, and 359 sputum specimens were collected from hospital B throughout 2012. A total of 71 specimens were positive for Legionella according to real-time PCR focusing on the 5S rRNA gene. Seventy of these specimens were identified as Legionella pneumophila as a result of real-time PCR amplification of the dotA gene. Results of nested SBT revealed high genetic polymorphism in these L. pneumophila and ST1 was the predominant sequence type. These data revealed that the burden of LD in China is much greater than that recognized previously, and real-time PCR may be a suitable monitoring technology for LD in large sample surveys in regions lacking the economic and technical resources to perform other methods, such as urinary antigen tests and culture methods.

The objective of this study was to assess the effectiveness of a catheter-related bloodstream infection (CR BSI) reduction programme and healthcare workers' compliance with recommendations. A 3-year surveillance programme of CR BSIs in all hospital settings was implemented. As part of the programme, there was a direct observation of insertion and maintenance of central venous catheters (CVCs) to determine performance. A total of 38 education courses were held over the study period and feedback reports with the results of surveillance and recommendations were delivered to healthcare workers every 6 months. A total of 6722 short-term CVCs were inserted in 4982 patients for 58 763 catheter-days. Improvements of compliance with hand hygiene was verified at the insertion (87·1–100%, P < 0·001) and maintenance (51·1–72·1%, P = 0·029) of CVCs; and the use of chlorhexidine for skin disinfection was implemented at insertion (35·7–65·4%, P < 0·001) and maintenance (33·3–45·9%, P < 0·197) of CVCs. There were 266 CR BSI incidents recorded with an annual incidence density of 5·75/1000 catheter-days in the first year, 4·38 in the second year [rate ratio (RR) 0·76, 95% confidence interval (CI) 0·57–1·01] and 3·46 in the third year (RR 0·60, 95% CI 0·44–0·81). The education programme clearly improved compliance with recommendations for CVC handling, and was effective in reducing the burden of CR BSIs.

A cross-sectional study was conducted from June 2013 to August 2015 to determine the seroprevalence and possible risk factors for human Toxoplasma gondii infection in Korean, Manchu, Mongol and Han ethnic groups in eastern and northeastern China. A total of 1842 serum samples, including Han (n = 802), Korean (n = 520), Manchu (n = 303) and Mongol (n = 217) groups, were analysed using enzyme-linked immunoassays to detect IgG and IgM T. gondii antibodies. The overall T. gondii IgG and IgM seroprevalences were 13·79% and 1·25%, respectively. Of these groups, Mongol ethnicity had the highest T. gondii seroprevalence (20·74%, 45/217), followed by Korean ethnicity (16·54%, 86/520), Manchu ethnicity (13·86%, 42/303) and Han ethnicity (11·35%, 98/802). Multiple analysis showed that the consumption of raw vegetables and fruits, the consumption of raw/undercooked meat and the source of drinking water were significantly associated with T. gondii infection in the Han group. Likewise, having a cat at home was identified as being associated with T. gondii infection in the Korean, Manchu and Mongol groups. Moreover, the consumption of raw/undercooked meat was identified as another predictor of T. gondii seropositivity in the Mongol group. The results of this survey indicate that T. gondii infection is prevalent in Korean, Manchu, Mongol and Han ethnic groups in the study region. Therefore, it is essential to implement integrated strategies with efficient management measures to prevent and control T. gondii infection in this region of China. Moreover, this is the first report of T. gondii infection in Korean, Manchu, and Mongol ethnic groups in eastern and northeastern China.