Reliability of medical students' vaccination histories for immunisable diseases

<p>Abstract</p> <p>Background</p> <p>Medical students come into contact with infectious diseases early on their career. Immunity against vaccine-preventable diseases is therefore vital for both medical students and the patients with whom they come into contact.</p> <p>Methods</p> <p>The purpose of this study was to compare the medical history and serological status of selected vaccine-preventable diseases of medical students in Germany.</p> <p>Results</p> <p>The overall correlation between self-reported medical history statements and serological findings among the 150 students studied was 86.7 %, 66.7 %, 78 % and 93.3 % for measles, mumps, rubella and varicella, conditional on sufficient immunity being achieved after one vaccination. Although 81.2 % of the students' medical history data correlated with serological findings, significant gaps in immunity were found.</p> <p>Conclusion</p> <p>Our findings indicate that medical history alone is not a reliable screening tool for immunity against the vaccine-preventable diseases studied.</p

Seroepidemiology of pandemic influenza A (H1N1) 2009 virus infections in Pune, India

<p>Abstract</p> <p>Background</p> <p>In India, Pune was one of the badly affected cities during the influenza A (H1N1) 2009 pandemic. We undertook serosurveys among the risk groups and general population to determine the extent of pandemic influenza A (H1N1) 2009 virus infections.</p> <p>Methods</p> <p>Pre-pandemic sera from the archives, collected during January 2005 to March 2009, were assayed for the determination of baseline seropositivity. Serosurveys were undertaken among the risk groups such as hospital staff, general practitioners, school children and staff and general population between 15^thAugust and 11^thDecember 2009. In addition, the PCR-confirmed pandemic influenza A (H1N1) 2009 cases and their household contacts were also investigated. Haemagglutination-inhibition (HI) assays were performed using turkey red blood cells employing standard protocols. A titre of ≥1:40 was considered seropositive.</p> <p>Results</p> <p>Only 2 (0.9%) of the 222 pre-pandemic sera were positive. The test-retest reliability of HI assay in 101 sera was 98% for pandemic H1N1, 93.1% for seasonal H1N1 and 94% for seasonal H3N2. The sera from 48 (73.8%) of 65 PCR-confirmed pandemic H1N1 cases in 2009 were positive. Seropositivity among general practitioners increased from 4.9% in August to 9.4% in November and 15.1% in December. Among hospital staff, seropositivity increased from 2.8% in August to 12% in November. Seropositivity among the schools increased from 2% in August to 10.7% in September. The seropositivity among students (25%) was higher than the school staff in September. In a general population survey in October 2009, seropositivity was higher in children (9.1%) than adults (4.3%). The 15-19 years age group showed the highest seropositivity of 20.3%. Seropositivity of seasonal H3N2 (55.3%) and H1N1 (26.4%) was higher than pandemic H1N1 (5.7%) (n = 2328). In households of 74 PCR-confirmed pandemic H1N1 cases, 25.6% contacts were seropositive. Almost 90% pandemic H1N1 infections were asymptomatic or mild. Considering a titre cut off of 1:10, seropositivity was 1.5-3 times as compared to 1:40.</p> <p>Conclusions</p> <p>Pandemic influenza A (H1N1) 2009 virus infection was widespread in all sections of community. However, infection was significantly higher in school children and general practitioners. Hospital staff had the lowest infections suggesting the efficacy of infection-control measures.</p

Seroprevalence and Severity of 2009 Pandemic Influenza A H1N1 in Taiwan

BACKGROUND: This study is to determine the seroprevalence of the pandemic influenza A H1N1 virus (pH1N1) in Taiwan before and after the 2009 pandemic, and to estimate the relative severity of pH1N1 infections among different age groups. METHODOLOGY/PRINCIPAL FINDINGS: A total of 1544 and 1558 random serum samples were collected from the general population in Taiwan in 2007 and 2010, respectively. Seropositivity was defined by a hemagglutination inhibition titer to pH1N1 (A/Taiwan/126/09) ≥1:40. The seropositivity rate of pH1N1 among the unvaccinated subjects and national surveillance data were used to compare the proportion of infections that led to severe diseases and fatalities among different age groups. The overall seroprevalence of pH1N1 was 0.91% (95% confidence interval [CI] 0.43-1.38) in 2007 and significantly increased to 29.9% (95% CI 27.6-32.2) in 2010 (p<0.0001), with the peak attack rate (55.4%) in 10-17 year-old adolescents, the lowest in elderly ≥65 years (14.1%). The overall attack rates were 20.6% (188/912) in unvaccinated subjects. Among the unvaccinated but infected populations, the estimated attack rates of severe cases per 100,000 infections were significantly higher in children aged 0-5 years (54.9 cases, odds ratio [OR] 4.23, 95% CI 3.04-5.90) and elderly ≥ 65 years (22.4 cases, OR 2.76, 95% CI 1.99-3.83) compared to adolescents aged 10-17 years (13.0 cases). The overall case-fatality rate was 0.98 per 100,000 infections without a significant difference in different age groups. CONCLUSIONS/SIGNIFICANCE: Pre-existing immunity against pH1N1 was rarely identified in Taiwanese at any age in 2007. Young children and elderly--the two most lower seroprotection groups showed the greatest vulnerability to clinical severity after the pH1N1 infections. These results imply that both age groups should have higher priority for immunization in the coming flu season

Optimal Design of Intervention Studies to Prevent Influenza in Healthy Cohorts

Background: Influenza cohort studies, in which participants are monitored for infection over an epidemic period, are invaluable in assessing the effectiveness of control measures such as vaccination, antiviral prophylaxis and nonpharmaceutical interventions (NPIs). Influenza infections and illnesses can be identified through a number of approaches with different costs and logistical requirements. Methodology and Principal Findings: In the context of a randomized controlled trial of an NPI with a constrained budget, we used a simulation approach to examine which approaches to measuring outcomes could provide greater statistical power to identify an effective intervention against confirmed influenza. We found that for a short epidemic season, the optimal design was to collect respiratory specimens at biweekly intervals, as well as following report of acute respiratory illness (ARI), for virologic testing by reverse transcription polymerase chain reaction (RT-PCR). Collection of respiratory specimens only from individuals reporting ARI was also an efficient design particularly for studies in settings with longer periods of influenza activity. Collection of specimens only from individuals reporting a febrile ARI was less efficient. Collection and testing of sera before and after influenza activity appeared to be inferior to collection of respiratory specimens for RT-PCR confirmation of acute infections. The performance of RT-PCR was robust to uncertainty in the costs and diagnostic performance of RT-PCR and serological tests

The Age-Specific Cumulative Incidence of Infection with Pandemic Influenza H1N1 2009 Was Similar in Various Countries Prior to Vaccination

Background: During the influenza pandemic of 2009 estimates of symptomatic and asymptomatic infection were needed to guide vaccination policies and inform other control measures. Serological studies are the most reliable way to measure influenza infection independent of symptoms. We reviewed all published serological studies that estimated the cumulative incidence of infection with pandemic influenza H1N1 2009 prior to the initiation of population-based vaccination against the pandemic strain. Methodology and Principal Findings: We searched for studies that estimated the cumulative incidence of pandemic influenza infection in the wider community. We excluded studies that did not include both pre- and post-pandemic serological sampling and studies that included response to vaccination. We identified 47 potentially eligible studies and included 12 of them in the review. Where there had been a significant first wave, the cumulative incidence of pandemic influenza infection was reported in the range 16%-28% in pre-school aged children, 34%-43% in school aged children and 12%-15% in young adults. Only 2%-3% of older adults were infected. The proportion of the entire population infected ranged from 11%-18%. We re-estimated the cumulative incidence to account for the small proportion of infections that may not have been detected by serology, and performed direct age-standardisation to the study population. For those countries where it could be calculated, this suggested a population cumulative incidence in the range 11%-21%. Conclusions and Significance: Around the world, the cumulative incidence of infection (which is higher than the cumulative incidence of clinical disease) was below that anticipated prior to the pandemic. Serological studies need to be routine in order to be sufficiently timely to provide support for decisions about vaccination. © 2011 Kelly et al.published_or_final_versio

Identification of Upper Respiratory Tract Pathogens Using Electrochemical Detection on an Oligonucleotide Microarray

Bacterial and viral upper respiratory infections (URI) produce highly variable clinical symptoms that cannot be used to identify the etiologic agent. Proper treatment, however, depends on correct identification of the pathogen involved as antibiotics provide little or no benefit with viral infections. Here we describe a rapid and sensitive genotyping assay and microarray for URI identification using standard amplification and hybridization techniques, with electrochemical detection (ECD) on a semiconductor-based oligonucleotide microarray. The assay was developed to detect four bacterial pathogens (Bordetella pertussis, Streptococcus pyogenes, Chlamydia pneumoniae and Mycoplasma pneumoniae) and 9 viral pathogens (adenovirus 4, coronavirus OC43, 229E and HK, influenza A and B, parainfluinza types 1, 2, and 3 and respiratory syncytial virus. This new platform forms the basis for a fully automated diagnostics system that is very flexible and can be customized to suit different or additional pathogens. Multiple probes on a flexible platform allow one to test probes empirically and then select highly reactive probes for further iterative evaluation. Because ECD uses an enzymatic reaction to create electrical signals that can be read directly from the array, there is no need for image analysis or for expensive and delicate optical scanning equipment. We show assay sensitivity and specificity that are excellent for a multiplexed format

Real-time numerical forecast of global epidemic spreading: Case study of 2009 A/H1N1pdm

Background Mathematical and computational models for infectious diseases are increasingly used to support public-health decisions; however, their reliability is currently under debate. Real-time forecasts of epidemic spread using data-driven models have been hindered by the technical challenges posed by parameter estimation and validation. Data gathered for the 2009 H1N1 influenza crisis represent an unprecedented opportunity to validate real-time model predictions and define the main success criteria for different approaches. Methods We used the Global Epidemic and Mobility Model to generate stochastic simulations of epidemic spread worldwide, yielding (among other measures) the incidence and seeding events at a daily resolution for 3,362 subpopulations in 220 countries. Using a Monte Carlo Maximum Likelihood analysis, the model provided an estimate of the seasonal transmission potential during the early phase of the H1N1 pandemic and generated ensemble forecasts for the activity peaks in the northern hemisphere in the fall/winter wave. These results were validated against the real-life surveillance data collected in 48 countries, and their robustness assessed by focusing on 1) the peak timing of the pandemic; 2) the level of spatial resolution allowed by the model; and 3) the clinical attack rate and the effectiveness of the vaccine. In addition, we studied the effect of data incompleteness on the prediction reliability. Results Real-time predictions of the peak timing are found to be in good agreement with the empirical data, showing strong robustness to data that may not be accessible in real time (such as pre-exposure immunity and adherence to vaccination campaigns), but that affect the predictions for the attack rates. The timing and spatial unfolding of the pandemic are critically sensitive to the level of mobility data integrated into the model. Conclusions Our results show that large-scale models can be used to provide valuable real-time forecasts of influenza spreading, but they require high-performance computing. The quality of the forecast depends on the level of data integration, thus stressing the need for high-quality data in population-based models, and of progressive updates of validated available empirical knowledge to inform these models

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