Laboratory tests in adult outpatients with longer lasting coughs to identify a potential causal pathogen are rarely performed, and there is no gold standard for these diagnostic tests. While the diagnostic validity of serological tests for pertussis is well established their potential contribution for diagnosing adenovirus and influenza virus A and B infections is unclear. A sentinel study into the population-based incidence of longer lasting coughs in adults was done in Rostock (former East Germany) and Krefeld (former West Germany). A total of 971 outpatients who consulted general practitioners or internists were included. Inclusion criteria were coughing for ⩾1 week and no chronic respiratory diseases. We evaluated the performance of polymerase chain reaction (PCR) as well as IgG and IgA serology, applying a latent class model for diagnosing infections with adenovirus, B. pertussis, and influenza virus A and B. The adult outpatients first sought medical attention when they had been coughing for a median of 3 weeks. In this situation, direct detection of infectious agents by PCR had a low sensitivity. Modelling showed that additional serological tests equally improved sensitivity and specificity for diagnosis for adenovirus, B. pertussis and influenza virus A and B infections. The combination of serology and PCR may improve the overall performance of diagnostic tests for B. pertussis and also for adenovirus, and influenza virus A and B infections.

The increase in pertussis cases in Minnesota in the last decade has been mainly attributed to the switch from whole cell to acellular pertussis [as part of the diphtheria, tetanus and acellular pertussis vaccine (DTaP)]. It is unclear, however, to what degree community-level risk factors also contribute. Understanding these factors can help inform public health policy-makers about where else to target resources. We performed an ecological analysis within Minnesota to identify risk factors at the county level using a Bayesian Poisson generalized linear areal model to account for spatial dependence. Univariate analyses suggested an association between increased pertussis rates at the county level and white maternal ethnicity, being US born, urban counties and average household size. In the multivariable analysis, the rate of pertussis was 1·79 times greater for urban vs. rural counties and 4·75 times greater for counties with a one-person larger average household size. Pertussis rates in counties with higher (i.e. 4+DTaP) receipt in children were 0·97 times lower. Examining county-level factors associated with varying levels of pertussis may help identify those counties that would most benefit from targeted interventions and increased resource allocation.

Multidrug-resistant Pseudomonas aeruginosa (MDRPA) infections are major threats to healthcare-associated infection control and the intrinsic molecular mechanisms of MDRPA are also unclear. We examined 348 isolates of P. aeruginosa, including 188 MDRPA and 160 non-MDRPA, obtained from five tertiary-care hospitals in Guangzhou, China. Significant correlations were found between gene/enzyme carriage and increased rates of antimicrobial resistance (P < 0·01). gyrA mutation, OprD loss and metallo-β-lactamase (MBL) presence were identified as crucial molecular risk factors for MDRPA acquisition by a combination of univariate logistic regression and a multifactor dimensionality reduction approach. The MDRPA rate was also elevated with the increase in positive numbers of those three determinants (P < 0·001). Thus, gyrA mutation, OprD loss and MBL presence may serve as predictors for early screening of MDRPA infections in clinical settings.

Group A Streptococcus (GAS) are globally distributed bacterial pathogens. We examined the emm genotypes, which are important indicators of virulence, of 349 clinical GAS isolates collected using two surveillance systems, i.e. Invasive Bacterial Infection Surveillance (IBIS) from 2010 to 2011 (234 isolates) and routine surveillance of clinically isolated bacteria from various hospitals during 1996–2011 (115 isolates) in Thailand. The major emm genotypes in IBIS samples were emm44 (12·0%), emm104 (6·8%), emm22 (5·6%), and emm81 (5·6%), whereas only one isolate (0·4%) had the emm1 genotype, which is significantly more common in invasive cases in the Western world. In samples collected during routine surveillance, emm238 (10·4%), emm44 (8·7%), and emm165 (7·0%) were dominant. The major superantigen gene profiles were similar between the groups, and 30·1% of isolates did not possess the phage-encoded superantigens (speA, speC, speH, speI, speK, speL, speM, ssa). Although most isolates exhibited limited gene profiles, emm44 isolates had highly variable gene profiles (15 patterns). We conclude that emm44 is the predominant GAS genotype in Thailand, and isolates varied in superantigen gene profiles.

Uptake rates for the combined measles, mumps and rubella (MMR) vaccine have been below the required 95% in the UK since a retracted and discredited article linking the MMR vaccine with autism and inflammatory bowel disease was released in 1998. This study undertook semi-structured telephone interviews among parents or carers of 47 unvaccinated measles cases who were aged between 13 months and 9 years, during a large measles outbreak in Merseyside. Results showed that concerns over the specific links with autism remain an important cause of refusal to vaccinate, with over half of respondents stating this as a reason. A quarter stated child illness during scheduled vaccination time, while other reasons included general safety concerns and access issues. Over half of respondents felt that more information or a discussion with a health professional would help the decision-making process, while a third stated improved access. There was clear support for vaccination among respondents when asked about current opinions regarding MMR vaccine. The findings support the hypothesis that safety concerns remain a major barrier to MMR vaccination, and also support previous evidence that experience of measles is an important determinant in the decision to vaccinate.

Immunoglobulin A (IgA)-based tests have been evaluated in different studies for their utility in diagnosing dengue infections. In most of the studies, the results were inconclusive because of a small sample size. Hence, a meta-analysis involving nine studies with 2096 samples was performed to assess the diagnostic accuracy of IgA-based tests in diagnosing dengue infections. The analysis was conducted using Meta-Disc software. The results revealed that IgA-based tests had an overall sensitivity, specificity, diagnostic odds ratio, and positive and negative likelihood ratios of 73·9%, 95·2%, 66·7, 22·0 and 0·25, respectively. Significant heterogeneity was observed between the studies. The type of test, infection status and day of sample collection influenced the diagnostic accuracy. The IgA-based diagnostic tests showed a greater accuracy when the samples were collected 4 days after onset of symptoms and for secondary infections. The results suggested that IgA-based tests had a moderate level of accuracy and are diagnostic of the disease. However, negative results cannot be used alone for dengue diagnosis. More prospective studies comparing the diagnostic accuracy of combinations of antigen-based tests with either IgA or IgM are needed and might be useful for suggesting the best strategy for dengue diagnosis.

Population seroprevalence can be estimated from serosurveys by classifying quantitative measurements into positives (past infection/vaccinated) or negatives (susceptible) according to a fixed assay cut-off. The choice of assay cut-offs has a direct impact on seroprevalence estimates. A time-resolved fluorescence immunoassay (TRFIA) was used to test exposure to human parvovirus 4 (HP4). Seroprevalence estimates were obtained after applying the diagnostic assay cut-off under different scenarios using simulations. Alternative methods for estimating assay cut-offs were proposed based on mixture modelling with component distributions for the past infection/vaccinated and susceptible populations. Seroprevalence estimates were compared to those obtained directly from the data using mixture models. Simulation results showed that when there was good distinction between the underlying populations all methods gave seroprevalence estimates close to the true one. For high overlap between the underlying components, the diagnostic assay cut-off generally gave the most biased estimates. However, the mixture model methods also gave biased estimates which were a result of poor model fit. In conclusion, fixed cut-offs often produce biased estimates but they also have advantages compared to other methods such as mixture models. The bias can be reduced by using assay cut-offs estimated specifically for seroprevalence studies.