Geotemporal analysis of Neisseria meningitidis clones in the United States: 2000-2005

Background: The detection of meningococcal outbreaks relies on serogrouping and epidemiologic definitions. Advances in molecular epidemiology have improved the ability to distinguish unique Neisseria meningitidis strains, enabling the classification of isolates into clones. Around 98% of meningococcal cases in the United States are believed to be sporadic. Methods: Meningococcal isolates from 9 Active Bacterial Core surveillance sites throughout the United States from 2000 through 2005 were classified according to serogroup, multilocus sequence typing, and outer membrane protein (porA, porB, and fetA ) genotyping. Clones were defined as isolates that were indistinguishable according to this characterization. Case data were aggregated to the census tract level and all non-singleton clones were assessed for non-random spatial and temporal clustering using retrospective space-time analyses with a discrete Poisson probability model. Results: Among 1,062 geocoded cases with available isolates, 438 unique clones were identified, 78 of which had ≥2 isolates. 702 cases were attributable to non-singleton clones, accounting for 66.0% of all geocoded cases. 32 statistically significant clusters comprised of 107 cases (10.1% of all geocoded cases) were identified. Clusters had the following attributes: included 2 to 11 cases; 1 day to 33 months duration; radius of 0 to 61.7 km; and attack rate of 0.7 to 57.8 cases per 100,000 population. Serogroups represented among the clusters were: B (n = 12 clusters, 45 cases), C (n = 11 clusters, 27 cases), and Y (n = 9 clusters, 35 cases); 20 clusters (62.5%) were caused by serogroups represented in meningococcal vaccines that are commercially available in the United States. Conclusions: Around 10% of meningococcal disease cases in the U.S. could be assigned to a geotemporal cluster. Molecular characterization of isolates, combined with geotemporal analysis, is a useful tool for understanding the spread of virulent meningococcal clones and patterns of transmission in populations

Bias with respect to socioeconomic status: A closer look at zip code matching in a pneumococcal vaccine effectiveness study

In 2010, 13-valent pneumococcal conjugate vaccine (PCV13) was introduced in the US for prevention of invasive pneumococcal disease in children. Individual-level socioeconomic status (SES) is a potential confounder of the estimated effectiveness of PCV13 and is often controlled for in observational studies using zip code as a proxy. We assessed the utility of zip code matching for control of SES in a post-licensure evaluation of the effectiveness of PCV13 (calculated as [1-matched odds ratio]*100). We used a directed acyclic graph to identify subsets of confounders and collected SES variables from birth certificates, geocoding, a parent interview, and follow-up with medical providers. Cases tended to be more affluent than eligible controls (for example, 48.3% of cases had private insurance vs. 44.6% of eligible controls), but less affluent than enrolled controls (52.9% of whom had private insurance). Control of confounding subsets, however, did not result in a meaningful change in estimated vaccine effectiveness (original estimate: 85.1%, 95% CI 74.8–91.9%; adjusted estimate: 82.5%, 95% CI 65.6–91.1%). In the context of a post-licensure vaccine effectiveness study, zip code appears to be an adequate, though not perfect, proxy for individual SES

Guillain-Barré Syndrome Surveillance during National Influenza Vaccination Campaign, New York, USA, 2009

The New York State Department of Health (NYSDOH) collected information about hospitalized patients with Guillain-Barré syndrome (GBS) during October 2009–May 2010, statewide (excluding New York City), to examine a possible relationship with influenza A(H1N1)pdm09 vaccination. NYSDOH established a Clinical Network of neurologists and 150 hospital neurology units. Hospital discharge data from the Statewide Planning and Research Cooperative System (SPARCS) were used to evaluate completeness of reporting from the Clinical Network. A total of 140 confirmed or probable GBS cases were identified: 81 (58%) from both systems, 10 (7%) from Clinical Network only, and 49 (35%) from SPARCS-only. Capture–recapture methods estimated that 6 cases might have been missed by both systems. Clinical Network median reporting time was 12 days versus 131 days for SPARCS. In public health emergencies in New York State, a Clinical Network may provide timely data, but in our study such data were less complete than traditional hospital discharge data

Risk factors for sporadic Shiga toxin-producing Escherichia coli O157 infections in FoodNet sites, 1999–2000

To monitor risk factors for illness, we conducted a case-control study of sporadic Shiga toxin-producing Escherichia coli O157 (STEC O157) infections in 1999–2000. Laboratory-confirmed cases of STEC O157 infection were identified through active laboratory surveillance in all or part of seven states. Patients and age-matched controls were interviewed by telephone using a standard questionnaire. Information was collected on demographics, clinical illness, and exposures to food, water, and animals in the 7 days before the patient's illness onset. During the 12-month study, 283 patients and 534 controls were enrolled. STEC O157 infection was associated with eating pink hamburgers, drinking untreated surface water, and contact with cattle. Eating produce was inversely associated with infection. Direct or indirect contact with cattle waste continues to be a leading identified source of sporadic STEC O157 infections

Utility of Keywords from Chest Radiograph Reports for Pneumonia Surveillance among Hospitalized Patients with Influenza: The CDC Influenza Hospitalization Surveillance Network, 2008–2009

ObjectiveTranscripts from admission chest radiographs could aid in identification of pneumonia cases for public health surveillance. We assessed the reliability of radiographic data abstraction and performance of radiographic key terms to identify pneumonia in patients hospitalized with laboratory-confirmed influenza virus infection.MethodsWe used data on patients hospitalized with laboratory-confirmed influenza virus infection from October 2008 through December 2009 from 10 geographically diverse U.S. study sites participating in the Influenza Hospitalization Surveillance Network (FluSurv-NET). Radiographic key terms (i.e., bronchopneumonia, consolidation, infiltrate, airspace density, and pleural effusion) were abstracted from final impressions of chest radiograph reports. We assessed the reliability of radiographic data abstraction by examining the percent agreement and Cohen's k statistic between clinicians and surveillance staff members. Using a composite reference standard for presence or absence of pneumonia based on International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes and discharge summary data, we calculated sensitivity, specificity, positive predictive value (PPV), and percent agreement for individual and combined radiographic key terms.ResultsFor each radiographic key term, the percent agreement between clinicians and surveillance staff members ranged from 89.4% to 98.6% and Cohen's k ranged from 0.46 (moderate) to 0.84 (almost perfect). The combination of bronchopneumonia or consolidation or infiltrate or airspace density terms had sensitivity of 66.5%, specificity of 89.2%, PPV of 80.4%, and percent agreement of 80.1%. Adding pleural effusion did not result in significant changes in sensitivity, specificity, PPV, or percent agreement.ConclusionRadiographic key terms abstracted by surveillance staff members from final impressions of chest radiograph reports had moderate to almost perfect reliability and could be used to identify pneumonia among patients hospitalized with laboratory-confirmed influenza virus infection. This method can inform pneumonia surveillance and aid in public health response

Does Influenza Vaccination Modify Influenza Severity? Data on Older Adults Hospitalized With Influenza During the 2012−2013 Season in the United States

Background. Some studies suggest that influenza vaccination might be protective against severe influenza outcomes in vaccinated persons who become infected. We used data from a large surveillance network to further investigate the effect of influenza vaccination on influenza severity in adults aged ≥50 years who were hospitalized with laboratory-confirmed influenza. Methods. We analyzed influenza vaccination and influenza severity using Influenza Hospitalization Surveillance Network (FluSurv-NET) data for the 2012−2013 influenza season. Intensive care unit (ICU) admission, death, diagnosis of pneumonia, and hospital and ICU lengths of stay served as measures of disease severity. Data were analyzed by multivariable logistic regression, parametric survival models, and propensity score matching (PSM). Results. Overall, no differences in severity were observed in the multivariable logistic regression model. Using PSM, adults aged 50−64 years (but not other age groups) who were vaccinated against influenza had a shorter length of ICU stay than those who were unvaccinated (hazard ratio for discharge, 1.84; 95% confidence interval, 1.12−3.01). Conclusions. Our findings show a modest effect of influenza vaccination on disease severity. Analysis of data from seasons with different predominant strains and higher estimates of vaccine effectiveness are needed

Investigation into the seasonal salmonellosis in lactating dairy cattle

Sporadic salmonellosis has been reported in mature lactating dairy cattle in the southwestern United States and is an intriguing problem in that Salmonella can be cultured from faecal samples of these cattle throughout the year. However, it is pathogenic only during late summer/early autumn and in certain years. We sampled apparently healthy (n=10) and diarrhoeic (n=10) cattle during an outbreak on a 2000 head dairy in 2003. The following year, monthly faecal (from the same 30 head), total mixed ration, water, and pen soil samples were collected for Salmonella culture. No serogroup, serotype, genetic, or antimicrobial susceptibility differences were observed in comparison of isolates from healthy and sick cattle. During year 2 of the study, Salmonella was routinely cultured (although highly variable from month to month) from the cattle and the environment, although no outbreak of salmonellosis was observed

Does Influenza Vaccination Modify Influenza Severity? Data on Older Adults Hospitalized With Influenza During the 2012−2013 Season in the United States

BackgroundSome studies suggest that influenza vaccination might be protective against severe influenza outcomes in vaccinated persons who become infected. We used data from a large surveillance network to further investigate the effect of influenza vaccination on influenza severity in adults aged ≥50 years who were hospitalized with laboratory-confirmed influenza.MethodsWe analyzed influenza vaccination and influenza severity using Influenza Hospitalization Surveillance Network (FluSurv-NET) data for the 2012-2013 influenza season. Intensive care unit (ICU) admission, death, diagnosis of pneumonia, and hospital and ICU lengths of stay served as measures of disease severity. Data were analyzed by multivariable logistic regression, parametric survival models, and propensity score matching (PSM).ResultsOverall, no differences in severity were observed in the multivariable logistic regression model. Using PSM, adults aged 50-64 years (but not other age groups) who were vaccinated against influenza had a shorter length of ICU stay than those who were unvaccinated (hazard ratio for discharge, 1.84; 95% confidence interval, 1.12-3.01).ConclusionsOur findings show a modest effect of influenza vaccination on disease severity. Analysis of data from seasons with different predominant strains and higher estimates of vaccine effectiveness are needed