Comparing Four Approaches for Technical Debt Identification

Background: Software systems accumulate technical debt (TD) when short-term goals in software development are traded for long term goals (e.g., quick-and-dirty implementation to reach a release date vs. a well-refactored implementation that supports the long term health of the project). Some forms of TD accumulate over time in the form of source code that is difficult to work with and exhibits a variety of anomalies. A number of source code analysis techniques and tools have been proposed to potentially identify the code-level debt accumulated in a system. What has not yet been studied is if using multiple tools to detect TD can lead to benefits, i.e. if different tools will flag the same or different source code components. Further, these techniques also lack investigation into the symptoms of TD "interest" that they lead to. To address this latter question, we also investigated whether TD, as identified by the source code analysis techniques, correlates with interest payments in the form of increased defect- and change-proneness. Aims: Comparing the results of different TD identification approaches to understand their commonalities and differences and to evaluate their relationship to indicators of future TD "interest". Method: We selected four different TD identification techniques (code smells, automatic static analysis (ASA) issues, grime buildup, and modularity violations) and applied them to 13 versions of the Apache Hadoop open source software project. We collected and aggregated statistical measures to investigate whether the different techniques identified TD indicators in the same or different classes and whether those classes in turn exhibited high interest (in the form of a large number of defects and higher change proneness). Results: The outputs of the four approaches have very little overlap and are therefore pointing to different problems in the source code. Dispersed coupling and modularity violations were co-located in classes with higher defect proneness. We also observed a strong relationship between modularity violations and change proneness. Conclusions: Our main contribution is an initial overview of the TD landscape, showing that different TD techniques are loosely coupled and therefore indicate problems in different locations of the source code. Moreover, our proxy interest indicators (change- and defect-proneness) correlate with only a small subset of TD indicator

Heterologous prime-boost vaccination using an ASO3B-adjuvanted influenza A(H5N1) vaccine in infants and children <3 years of age

Presented in part: Options for the Control of Influenza VIII Conference, Cape Town, South Africa, 5–10 September 2013BACKGROUND: Protecting young children from pandemic influenza should also reduce transmission to susceptible adults, including pregnant women. METHODS: An open study assessed immunogenicity and reactogenicity of a heterologous booster dose of A/turkey/Turkey/1/2005(H5N1)-AS03B (AS03B is an Adjuvant System containing α-tocopherol and squalene in an oil-in-water emulsion [5.93 mg tocopherol]) in infants and children aged 6 to <36 months that was given 6 months following 2-dose primary vaccination with A/Indonesia/05/2005(H5N1)-AS03B. Vaccines contained 1.9 µg of hemagglutinin antigen and AS03B. Hemagglutinin inhibition (HI) responses, microneutralization titers, and antineuraminidase antibody levels were assessed for 6 months following the booster vaccination. RESULTS: For each age stratum (defined on the basis of the subject's age at first vaccination as 6 to <12 months, 12 to <24 months, and 24 to <36 months) and overall (n=113), European influenza vaccine licensure criteria were fulfilled for responses to A/turkey/Turkey/1/2005(H5N1) 10 days following the booster vaccination. Local pain and fever increased with consecutive doses. Anamnestic immune responses were demonstrated for HI, neutralizing, and antineuraminidase antibodies against vaccine-homologous/heterologous strains. Antibody responses to vaccine-homologous/heterologous strains persisted in all children 6 months following the booster vaccination. CONCLUSIONS: Prevaccination of young children with a clade 2 strain influenza A(H5N1) AS03-adjuvanted vaccine followed by heterologous booster vaccination boosted immune responses to the homologous strain and a related clade, with persistence for at least 6 months. The results support a prime-boost vaccination approach in young children for pandemic influenza preparedness. CLINICAL TRIALS REGISTRATION: NCT01323946.Terry Nolan, Patricia Izurieta, Bee-Wah Lee, Poh Chong Chan, Helen Marshall, Robert Booy, Mamadou Drame, and David W. Vaugh

Seasonal Influenza Vaccine Effectiveness among Children Aged 6 to 59 Months in Southern China

In China the protective effect of seasonal influenza vaccine has only been assessed in controlled clinical trials and proven to be highly effective. However, the post-licensure effectiveness of influenza vaccine has not been examined. In our study all influenza cases from the 19 surveillance sites in Guangzhou were laboratory confirmed during 2009 and 2010. Controls were randomly selected from children aged 6 to 59 months in the Children's Expanded Programmed Immunization Administrative Computerized System. 2529 cases and 4539 controls were finally enrolled. After adjusting for gender, age and area of residence, the vaccine effectiveness of full vaccination was 51.79% and 57.78% in the 2009 and 2010 influenza season, respectively. Partial vaccination provided 39.38% and 35.98% protection to children aged 24 to 59 months in 2009 and 2010, respectively, and no protective effect was observed among younger children. Full vaccination is highly protective and partial vaccination is protective for older children. Influenza vaccination in general should be encouraged, and full vaccination should be particularly encouraged because its protective effect is much stronger than that of partial vaccination

Monitoring Influenza Activity in the United States: A Comparison of Traditional Surveillance Systems with Google Flu Trends

Google Flu Trends was developed to estimate US influenza-like illness (ILI) rates from internet searches; however ILI does not necessarily correlate with actual influenza virus infections.Influenza activity data from 2003-04 through 2007-08 were obtained from three US surveillance systems: Google Flu Trends, CDC Outpatient ILI Surveillance Network (CDC ILI Surveillance), and US Influenza Virologic Surveillance System (CDC Virus Surveillance). Pearson's correlation coefficients with 95% confidence intervals (95% CI) were calculated to compare surveillance data. An analysis was performed to investigate outlier observations and determine the extent to which they affected the correlations between surveillance data. Pearson's correlation coefficient describing Google Flu Trends and CDC Virus Surveillance over the study period was 0.72 (95% CI: 0.64, 0.79). The correlation between CDC ILI Surveillance and CDC Virus Surveillance over the same period was 0.85 (95% CI: 0.81, 0.89). Most of the outlier observations in both comparisons were from the 2003-04 influenza season. Exclusion of the outlier observations did not substantially improve the correlation between Google Flu Trends and CDC Virus Surveillance (0.82; 95% CI: 0.76, 0.87) or CDC ILI Surveillance and CDC Virus Surveillance (0.86; 95%CI: 0.82, 0.90).This analysis demonstrates that while Google Flu Trends is highly correlated with rates of ILI, it has a lower correlation with surveillance for laboratory-confirmed influenza. Most of the outlier observations occurred during the 2003-04 influenza season that was characterized by early and intense influenza activity, which potentially altered health care seeking behavior, physician testing practices, and internet search behavior

Accuracy in Copy Number Calling by qPCR and PRT: A Matter of DNA

The possible implication of copy number variation (CNV) in the genetic susceptibility to human disease needs to be assessed using robust methods that can be applied at a population scale. In this report, we analyze the performance of the two major techniques, quantitative PCR (qPCR) and paralog ratio test (PRT), and investigate the influence of input DNA amount and template integrity on the reliability of both methods. Analysis of three genes (PRELID1, SYNPO and DEFB4) in a large sample set showed that both methods are prone to false copy number assignments if sufficient attention is not paid to DNA concentration and quality. Accurate normalization of samples is essential for reproducible qPCR because it avoids the effect of differential amplification efficiencies between target and control assays, whereas PRT is generally more sensitive to template degradation due to the fact that longer amplicons are usually needed to optimize sensitivity and specificity of paralog sequence PCR. The use of normalized, high quality genomic DNA yields comparable results with both methods

Validation of Statistical Models for Estimating Hospitalization Associated with Influenza and Other Respiratory Viruses

BACKGROUND: Reliable estimates of disease burden associated with respiratory viruses are keys to deployment of preventive strategies such as vaccination and resource allocation. Such estimates are particularly needed in tropical and subtropical regions where some methods commonly used in temperate regions are not applicable. While a number of alternative approaches to assess the influenza associated disease burden have been recently reported, none of these models have been validated with virologically confirmed data. Even fewer methods have been developed for other common respiratory viruses such as respiratory syncytial virus (RSV), parainfluenza and adenovirus. METHODS AND FINDINGS: We had recently conducted a prospective population-based study of virologically confirmed hospitalization for acute respiratory illnesses in persons <18 years residing in Hong Kong Island. Here we used this dataset to validate two commonly used models for estimation of influenza disease burden, namely the rate difference model and Poisson regression model, and also explored the applicability of these models to estimate the disease burden of other respiratory viruses. The Poisson regression models with different link functions all yielded estimates well correlated with the virologically confirmed influenza associated hospitalization, especially in children older than two years. The disease burden estimates for RSV, parainfluenza and adenovirus were less reliable with wide confidence intervals. The rate difference model was not applicable to RSV, parainfluenza and adenovirus and grossly underestimated the true burden of influenza associated hospitalization. CONCLUSION: The Poisson regression model generally produced satisfactory estimates in calculating the disease burden of respiratory viruses in a subtropical region such as Hong Kong

Model Selection in Time Series Studies of Influenza-Associated Mortality

Background: Poisson regression modeling has been widely used to estimate influenza-associated disease burden, as it has the advantage of adjusting for multiple seasonal confounders. However, few studies have discussed how to judge the adequacy of confounding adjustment. This study aims to compare the performance of commonly adopted model selection criteria in terms of providing a reliable and valid estimate for the health impact of influenza. Methods: We assessed four model selection criteria: quasi Akaike information criterion (QAIC), quasi Bayesian information criterion (QBIC), partial autocorrelation functions of residuals (PACF), and generalized cross-validation (GCV), by separately applying them to select the Poisson model best fitted to the mortality datasets that were simulated under the different assumptions of seasonal confounding. The performance of these criteria was evaluated by the bias and root-mean-square error (RMSE) of estimates from the pre-determined coefficients of influenza proxy variable. These four criteria were subsequently applied to an empirical hospitalization dataset to confirm the findings of simulation study. Results: GCV consistently provided smaller biases and RMSEs for the influenza coefficient estimates than QAIC, QBIC and PACF, under the different simulation scenarios. Sensitivity analysis of different pre-determined influenza coefficients, study periods and lag weeks showed that GCV consistently outperformed the other criteria. Similar results were found in applying these selection criteria to estimate influenza-associated hospitalization. Conclusions: GCV criterion is recommended for selection of Poisson models to estimate influenza-associated mortality and morbidity burden with proper adjustment for confounding. These findings shall help standardize the Poisson modeling approach for influenza disease burden studies. © 2012 Wang et al.published_or_final_versio

Clinical and socioeconomic impact of different types and subtypes of seasonal influenza viruses in children during influenza seasons 2007/2008 and 2008/2009

<p>Abstract</p> <p>Background</p> <p>There are few and debated data regarding possible differences in the clinical presentations of influenza A/H1N1, A/H3N2 and B viruses in children. This study evaluates the clinical presentation and socio-economic impact of laboratory-confirmed influenza A/H1N1, A/H3N2 or B infection in children attending an Emergency Room because of influenza-like illness.</p> <p>Methods</p> <p>Among the 4,726 children involved, 662 had influenza A (143 A/H1N1 and 519 A/H3N2) and 239 influenza B infection detected by means of real-time polymerase chain reaction. Upon enrolment, systematic recordings were made of the patients' demographic characteristics and medical history using standardised written questionnaires. The medical history of the children was re-evaluated 5-7 days after enrolment and until the resolution of their illness by means of interviews and a clinical examination by trained investigators using standardised questionnaires. During this evaluation, information was also obtained regarding illnesses and related morbidity among households.</p> <p>Results</p> <p>Children infected with influenza A/H1N1 were significantly younger (mean age, 2.3 yrs) than children infected with influenza A/H3N2 (mean age, 4.7 yrs; p < 0.05)) or with influenza B (mean age, 5.2 yrs; p < 0.05). Adjusted for age and sex, children with influenza A/H3N2 in comparison with those infected by either A/H1N1 or with B influenza virus were more frequently affected by fever (p < 0.05) and lower respiratory tract involvement (p < 0.05), showed a worse clinical outcome (p < 0.05), required greater drug use (p < 0.05), and suffered a worse socio-economic impact (p < 0.05). Adjusted for age and sex, children with influenza B in comparison with those infected by A/H1N1 influenza virus had significantly higher hospitalization rates (p < 0.05), the households with a disease similar to that of the infected child (p < 0.05) and the need for additional household medical visits (p < 0.05).</p> <p>Conclusions</p> <p>Disease due to influenza A/H3N2 viral subtype is significantly more severe than that due to influenza A/H1N1 subtype and influenza B virus, which indicates that the characteristics of the different viral types and subtypes should be adequately considered by health authorities when planning preventive and therapeutic measures.</p

Detection of multiple respiratory pathogens during primary respiratory infection: nasal swab versus nasopharyngeal aspirate using real-time polymerase chain reaction

In this study, we present the multiple detection of respiratory viruses in infants during primary respiratory illness, investigate the sensitivity of nasal swabs and nasopharyngeal aspirates, and assess whether patient characteristics and viral load played a role in the sensitivity. Healthy infants were included at signs of first respiratory tract infection. Paired nasopharyngeal aspirates and nasal swabs were collected. Real-time polymerase chain reaction (PCR) was carried out for 11 respiratory pathogens. Paired nasopharyngeal aspirates and nasal swabs were collected in 98 infants. Rhinovirus (n = 67) and respiratory syncytial virus (n = 39) were the most frequently detected. Co-infection occurred in 48% (n = 45) of the infants. The sensitivity of the nasal swab was lower than the nasopharyngeal aspirate, in particular, for respiratory syncytial virus (51% vs. 100%) and rhinovirus (75% vs. 97%). The sensitivity of the nasal swab was strongly determined by the cycle threshold (CT) value (p < 0.001). The sensitivity of the swab for respiratory syncytial virus, but not rhinovirus, was 100% in children with severe symptoms (score ≥11). It is concluded that, for community-based studies and surveillance purposes, the nasal swab can be used, though the sensitivity is lower than the aspirate, in particular, for the detection of mild cases of respiratory syncytial virus (RSV) infection

The Population Impact of a Large School-Based Influenza Vaccination Campaign

The optimal vaccination strategy to mitigate the impact of influenza epidemics is unclear. In 2005, a countywide school-based influenza vaccination campaign was launched in Knox County, Tennessee (population 385,899). Approximately 41% and 48% of eligible county children aged 5-17 years were immunized with live attenuated influenza vaccine before the 2005-2006 and 2006-2007 influenza seasons, respectively. We sought to determine the population impact of this campaign.Laboratory-confirmed influenza data defined influenza seasons. We calculated the incidence of medically attended acute respiratory illness attributable to influenza in Knox and Knox-surrounding counties (concurrent controls) during consecutive seasons (5 precampaign and 2 campaign seasons) using negative binomial regression and rate difference methods. Age-stratified analyses compared the incidence of emergency department (ED) visits and hospitalizations attributable to influenza.During precampaign seasons, estimated ED visit rates attributable to influenza were 12.39 (95% CI: 10.34-14.44) per 1000 Knox children aged 5-17 years and similar in Knox-surrounding counties. During the campaign seasons, annual Knox influenza-associated ED visit rates declined relative to rates in Knox-surrounding counties: rate ratios 0.55 (95% CI: 0.27-0.83) and 0.70 (95% CI: 0.56-0.84) for the first and second campaign seasons, respectively. Overall, there were about 35% or 4.86 per 1000 fewer influenza-associated ED visits among Knox County children aged 5-17 years attributable to the campaign. No significant declines in Knox compared to surrounding counties were detected for influenza associated ED visits in children aged <5 years, all adults combined or selected adult age subgroups, although power for these analyses was limited. Alternate rate-difference analyses yielded consistent results.Vaccination of approximately 45% of Knox school-aged children with influenza vaccine was associated with a 35% annual reduction (4.86 per 1000) in ED visit rates attributable to influenza. Higher vaccination coverage and/or larger studies would be needed to determine whether similar interventions have indirect benefits in other age groups