In many biomedical studies, the event of interest can occur more than once in a participant. These events are termed recurrent events. However, the majority of analyses focus only on time to the first event, ignoring the subsequent events. Several statistical models have been proposed for analysing multiple events. In this paper we explore and illustrate several modelling techniques for analysis of recurrent time-to-event data, including conditional models for multivariate survival data (AG, PWP-TT and PWP-GT), marginal means/rates models, frailty and multi-state models. We also provide a tutorial for analysing such type of data, with three widely used statistical software programmes. Different approaches and software are illustrated using data from a bladder cancer project and from a study on lower respiratory tract infection in children in Brazil. Finally, we make recommendations for modelling strategy selection for analysis of recurrent event data.

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Early heavy infections with T. trichiura may protect against the development of allergen skin test reactivity in later childhood. Novel treatments to program immune-regulation in early childhood in a way that mimics the effects of early infections with T. trichiura may offer new strategies for the prevention of allergic disease.

Purpose: Metabolic syndrome (MS) is a clustering of cardiovascular disease risk factors that identifies individuals with the highest risk for heart disease. Two factors that may influence the MS are physical activity and aerobic fitness. This study determined if adolescent with the MS had low levels of aerobic fitness and physical activity as children.Methods: This longitudinal, exploratory study had 389 participants: 51% girls, 84% Caucasian, 12% African American, 1% Hispanic, and 3% other races, from the State of North Carolina. Habitual physical activity (PA survey), aerobic fitness (VO 2 max), body mass index (BMI), blood pressure, and lipids obtained at 7-10 y of age were compared to their results obtained 7 y later at ages 14-17 y.Results: Eighteen adolescents (4.6%) developed 3 or more characteristics of the MS. Logistic regression, adjusting for BMI percentile, blood pressure, and cholesterol levels, found that adolescents with the MS were 6.08 (95%CI = 1.18-60.08) times more likely to have low aerobic fitness as children and 5.16 (95%CI = 1.06-49.66) times more likely to have low PA levels. Conclusion:Low levels of childhood physical activity and aerobic fitness are associated with the presence of the metabolic syndrome in adolescents. Thus, efforts need to begin early in childhood to increase exercise.

Background: The causation of asthma is poorly understood. Risk factors for atopic and non-atopic asthma may be different. This study aimed to analyze the associations between markers of poverty, dirt and infections and wheezing in atopic and non-atopic children.

Background: Many epidemiologic studies report the odds ratio as a measure of association for cross-sectional studies with common outcomes. In such cases, the prevalence ratios may not be inferred from the estimated odds ratios. This paper overviews the most commonly used procedures to obtain adjusted prevalence ratios and extends the discussion to the analysis of clustered cross-sectional studies.

BackgroundControl of soil-transmitted helminth (STH) infections relies on the periodic and long-term administration of anthelmintic drugs to high-risk groups, particularly school-age children living in endemic areas. There is limited data on the effectiveness of long-term periodic anthelmintic treatment on the prevalence of STHs, particularly from operational programmes. The current study investigated the impact of 15 to 17 years of treatment with the broad-spectrum anthelmintic ivermectin, used for the control of onchocerciasis, on STH prevalence and intensity in school-age and pre-school children.Methods and FindingsA cross-sectional study was conducted in communities that had received annual or twice-annual ivermectin treatments and geographically adjacent communities that had not received treatment in two districts of Esmeraldas Province in Ecuador. Stool samples were collected from school-age children and examined for STH infection using the Kato-Katz and formol-ether concentration methods. Samples were collected also from pre-school children and examined by the formol-ether concentration method. Data on risk factors for STH infection were collected by parental questionnaire. We sampled a total of 3,705 school-age children (6–16 years) from 31 treated and 27 non-treated communities, and 1,701 pre-school children aged 0–5 years from 18 treated and 18 non-treated communities. Among school-age children, ivermectin treatment had significant effects on the prevalence (adjusted OR =  0.06, 95% CI 0.03–0.14) and intensity of Trichuris trichiura infection (adjusted RR = 0.28, 95% CI 0.11–0.70), but appeared to have no impact on Ascaris lumbricoides or hookworm infection. Reduced prevalence and intensities of T. trichiura infection were observed among children not eligible to receive ivermectina, providing some evidence of reduced transmission of T. trichiura infection in communities receiving mass ivermectin treatments.ConclusionAnnual and twice-annual treatments with ivermectin over a period of up to 17 years may have had a significant impact on T. trichiura infection. The present data indicate that the long-term control of onchocerciasis with ivermectin may provide additional health benefits by reducing infections with trichuriasis. The addition of a second anthelmintic drug such as albendazole may be useful for a long-term effect on A. lumbricoides infection.

Data linkage refers to the process of identifying and linking records that refer to the same entity across multiple heterogeneous data sources. This method has been widely utilized across scientific domains, including public health where records from clinical, administrative, and other surveillance databases are aggregated and used for research, decision making, and assessment of public policies. When a common set of unique identifiers does not exist across sources, probabilistic linkage approaches are used to link records using a combination of attributes. These methods require a careful choice of comparison attributes as well as similarity metrics and cutoff values to decide if a given pair of records matches or not and for assessing the accuracy of the results. In large, complex datasets, linking and assessing accuracy can be challenging due to the volume and complexity of the data, the absence of a gold standard, and the challenges associated with manually reviewing a very large number of record matches. In this paper, we present AtyImo, a hybrid probabilistic linkage tool optimized for high accuracy and scalability in massive data sets. We describe the implementation details around anonymization, blocking, deterministic and probabilistic linkage, and accuracy assessment. We present results from linking a large population-based cohort of 114 million individuals in Brazil to public health and administrative databases for research. In controlled and real scenarios, we observed high accuracy of results: 93%-97% true matches. In terms of scalability, we present AtyImo's ability to link the entire cohort in less than nine days using Spark and scaling up to 20 million records in less than 12s over heterogeneous (CPU+GPU) architectures.