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Abstract Background Measuring recurrent infections such as diarrhoea or respiratory infections in epidemiological studies is a methodological challenge. Problems in measuring the incidence of recurrent infections include the episode definition, recall error, and the logistics of close follow up. Longitudinal prevalence (LP), the proportion-of-time-ill estimated by repeated prevalence measurements, is an alternative measure to incidence of recurrent infections. In contrast to incidence which usually requires continuous sampling, LP can be measured at intervals. This study explored how many more participants are needed for infrequent sampling to achieve the same study power as frequent sampling. Methods We developed a set of four empirical simulation models representing low and high risk settings with short or long episode durations. The model was used to evaluate different sampling strategies with different assumptions on recall period and recall error. Results The model identified three major factors that influence sampling strategies: (1) the clustering of episodes in individuals; (2) the duration of episodes; (3) the positive correlation between an individual's disease incidence and episode duration. Intermittent sampling (e.g. 12 times per year) often requires only a slightly larger sample size compared to continuous sampling, especially in cluster-randomized trials. The collection of period prevalence data can lead to highly biased effect estimates if the exposure variable is associated with episode duration. To maximize study power, recall periods of 3 to 7 days may be preferable over shorter periods, even if this leads to inaccuracy in the prevalence estimates. Conclusion Choosing the optimal approach to measure recurrent infections in epidemiological studies depends on the setting, the study objectives, study design and budget constraints. Sampling at intervals can contribute to making epidemiological studies and trials more efficient, valid and cost-effective.

A comparative inspection of the rules of cross-border pension taxation across member countries of the Organization of Economic Cooperation and Development (OECD) shows that the existing pattern is extremely diverse and inconsistent and generates unfair outcomes for individuals and for countries. This article argues that this double fairness dilemma cannot be solved within the current network of double taxation treaties. Instead, it proposes a new approach for the taxation of old-age pensions in a world of high and increasing cross-border mobility of workers and pensioners. The article demonstrates that a coordinated move to frontloaded pension taxation would pave the way for an international pension tax order that eliminates the double fairness dilemma. An additional innovative element of frontloaded pension taxation is presented: the separation of individual tax assessment and tax payment, which may help curb political opposition against frontloaded pension taxation and smooth transitional effects after its introduction (JEL codes: H24, H55, H87, and F22). [ABSTRACT FROM AUTHOR]

Abstract Background The number of subjects that can be recruited in immunological studies and the number of immunological parameters that can be measured has increased rapidly over the past decade and is likely to continue to expand. Large and complex immunological datasets can now be used to investigate complex scientific questions, but to make the most of the potential in such data and to get the right answers sophisticated statistical approaches are necessary. Such approaches are used in many other scientific disciplines, but immunological studies on the whole still use simple statistical techniques for data analysis. Results The paper provides an overview of the range of statistical methods that can be used to answer different immunological study questions. We discuss specific aspects of immunological studies and give examples of typical scientific questions related to immunological data. We review classical bivariate and multivariate statistical techniques (factor analysis, cluster analysis, discriminant analysis) and more advanced methods aimed to explore causal relationships (path analysis/structural equation modelling) and illustrate their application to immunological data. We show the main features of each method, the type of study question they can answer, the type of data they can be applied to, the assumptions required for each method and the software that can be used. Conclusion This paper will help the immunologist to choose the correct statistical approach for a particular research question.

Abstract Background There is evidence of higher prevalence of asthma in populations of lower socio-economic status in affluent societies, and the prevalence of asthma is also very high in some Latin American countries, where societies are characterized by a marked inequality in wealth. This study aimed to examine the relationship between estimates of asthma prevalence based on surveys conducted in children in Brazilian cities and health and socioeconomic indicators measured at the population level in the same cities. Methods We searched the literature in the medical databases and in the annals of scientific meeting, retrieving population-based surveys of asthma that were conducted in Brazil using the methodology defined by the International Study of Asthma and Allergies in Childhood. We performed separate analyses for the age groups 6–7 years and 13–14 years. We examined the association between asthma prevalence rates and eleven health and socio-economic indicators by visual inspection and using linear regression models weighed by the inverse of the variance of each survey. Results Six health and socioeconomic variables showed a clear pattern of association with asthma. The prevalence of asthma increased with poorer sanitation and with higher infant mortality at birth and at survey year, GINI index and external mortality. In contrast, asthma prevalence decreased with higher illiteracy rates. Conclusion The prevalence of asthma in urban areas of Brazil, a middle income country, appears to be higher in cities with more marked poverty or inequality.

Abstract Background Asthma and allergic diseases are becoming increasingly frequent in children in urban centres of Latin America although the prevalence of allergic disease is still low in rural areas. Understanding better why the prevalence of asthma is greater in urban migrant populations and the role of risk factors such as life style and environmental exposures, may be key to understand what is behind this trend. Methods/design The Esmeraldas-SCAALA (Social Changes, Asthma and Allergy in Latin America) study consists of cross-sectional and nested case-control studies of school children in rural and urban areas of Esmeraldas Province in Ecuador. The cross-sectional study will investigate risk factors for atopy and allergic disease in rural and migrant urban Afro-Ecuadorian school children and the nested case-control study will examine environmental, biologic and social risk factors for asthma among asthma cases and non-asthmatic controls from the cross-sectional study. Data will be collected through standardised questionnaires, skin prick testing to relevant aeroallergen extracts, stool examinations for parasites, blood sampling (for measurement of IgE, interleukins and other immunological parameters), anthropometric measurements for assessment of nutritional status, exercise testing for assessment of exercise-induced bronchospasm and dust sampling for measurement of household endotoxin and allergen levels. Discussion The information will be used to identify the factors associated with an increased risk of asthma and allergies in migrant and urbanizing populations, to improve the understanding of the causes of the increase in asthma prevalence and to identify potentially modifiable factors to inform the design of prevention programmes to reduce the risk of allergy in urban populations in Latin America.

Abstract Background The prevalence of asthma and allergic diseases has increased in industrialised countries, and it is known that rates vary according whether the area is urban or rural and to socio-economic status. Surveys conducted in some urban settings in Latin America found high prevalence rates, only exceeded by the rates observed in industrialised English-speaking countries. It is likely that the marked changes in the environment, life style and living conditions in Latin America are responsible for these observations. The understanding of the epidemiological and immunological changes that underlie the increase in asthma and allergic diseases in Latin America aimed by SCAALA studies in Brazil and Ecuador will be crucial for the identification of novel preventive interventions. Methods/Design The Salvador-SCAALA project described here is a longitudinal study involving children aged 4–11 years living in the city of Salvador, Northeastern Brazil. Data on asthma and allergic diseases (rhinitis and eczema) and potential risk factors will be collected in successive surveys using standardised questionnaire. This will be completed with data on dust collection (to dust mite and endotoxin), skin test to most common allergens, stool examinations to helminth and parasites, blood samples (to infection, total and specific IgE, and immunological makers), formaldehyde, physical inspection to diagnoses of eczema, and anthropometric measures. Data on earlier exposures when these children were 0–3 years old are available from a different project. Discussion It is expected that knowledge generated may help identify public health interventions that may enable countries in LA to enjoy the benefits of a "modern" lifestyle while avoiding – or minimising – increases in morbidity caused by asthma and allergies.