BackgroundMen having sex with men (MSM) remain the largest high-risk group involved in on-going transmission of sexually transmitted infections (STI), including HIV, in the Netherlands. As risk behaviour may change with age, it is important to explore potential heterogeneity in risks by age. To improve our understanding of this epidemic, we analysed the prevalence of and risk factors for selected STI in MSM attending STI clinics in the Netherlands by age group.MethodsAnalysis of data from the national STI surveillance system for the period 2006–2012. Selected STI were chlamydia, gonorrhoea, infectious syphilis and/or a new HIV infection. Logistic regression was used to identify factors associated with these selected STI and with overall STI positivity. Analyses were done separately for MSM aged younger than 25 years and MSM aged 25 years and older.ResultsIn young MSM a significant increase in positivity rate was seen over time (p < 0.01), mainly driven by increasing gonorrhoea diagnoses, while in MSM aged 25 and older a significant decrease was observed (p < 0.01). In multivariate analyses for young MSM, those who were involved in commercial sex were at higher risk (OR: 1.5, 95% CI: 1.2-1.9). For MSM aged 25 years and older this was not the case. Having a previous negative HIV test was protective among older MSM compared to those not tested for HIV before (OR: 0.8, 95% CI: 0.8-0.8), but not among younger MSM.ConclusionsMSM visiting STI clinics remain a high-risk group for STI infections and transmission, but are not a homogenous group. While in MSM aged older than 25 years, STI positivity rate is decreasing, positivity rate in young MSM increased over time. Therefore specific attention needs to be paid towards targeted counselling and reaching particular MSM sub-groups, taken into account different behavioural profiles.

BackgroundMeasures of household socio-economic position (SEP) are widely used in health research. There exist a number of approaches to their measurement, with Principal Components Analysis (PCA) applied to a basket of household assets being one of the most common. PCA, however, carries a number of assumptions about the distribution of the data which may be untenable, and alternative, non-parametric, approaches may be preferred. Mokken scale analysis is a non-parametric, item response theory approach to scale development which appears never to have been applied to household asset data. A Mokken scale can be used to rank order items (measures of wealth) as well as households. Using data on household asset ownership from a national sample of 4,154 consenting households in the World Health Survey from Vietnam, 2003, we construct two measures of household SEP. Seventeen items asking about assets, and utility and infrastructure use were used. Mokken Scaling and PCA were applied to the data. A single item measure of total household expenditure is used as a point of contrast.ResultsAn 11 item scale, out of the 17 items, was identified that conformed to the assumptions of a Mokken Scale. All the items in the scale were identified as strong items (Hi > .5). Two PCA measures of SEP were developed as a point of contrast. One PCA measure was developed using all 17 available asset items, the other used the reduced set of 11 items identified in the Mokken scale analaysis. The Mokken Scale measure of SEP and the 17 item PCA measure had a very high correlation (r = .98), and they both correlated moderately with total household expenditure: r = .59 and r = .57 respectively. In contrast the 11 item PCA measure correlated moderately with the Mokken scale (r = .68), and weakly with the total household expenditure (r = .18).ConclusionThe Mokken scale measure of household SEP performed at least as well as PCA, and outperformed the PCA measure developed with the 11 items used in the Mokken scale. Unlike PCA, Mokken scaling carries no assumptions about the underlying shape of the distribution of the data, and can be used simultaneous to order household SEP and items. The approach, however, has not been tested with data from other countries and remains an interesting, but under researched approach.

Great progress has been made in mathematical models of cholera transmission dynamics in recent years. However, little impact, if any, has been made by models upon public health decision-making and day-to-day routine of epidemiologists. This paper provides a brief introduction to the basics of ordinary differential equation models of cholera transmission dynamics. We discuss a basic model adapted from Codeço (2001), and how it can be modified to incorporate different hypotheses, including the importance of asymptomatic or inapparent infections, and hyperinfectious V. cholerae and human-to-human transmission. We highlight three important challenges of cholera models: (1) model misspecification and parameter uncertainty, (2) modeling the impact of water, sanitation and hygiene interventions and (3) model structure. We use published models, especially those related to the 2010 Haitian outbreak as examples. We emphasize that the choice of models should be dictated by the research questions in mind. More collaboration is needed between policy-makers, epidemiologists and modelers in public health.

BackgroundSystems for animal disease mitigation involve both surveillance activities and interventions to control the disease. They are complex organizations that are described by partial or imprecise data, making it difficult to evaluate them or make decisions to improve them. A mathematical method, called loop analysis, can be used to model qualitatively the structure and the behavior of dynamic systems; it relies on the study of the sign of the interactions between the components of the system. This method, currently widely used by ecologists, has to our knowledge never been applied in the context of animal disease mitigation systems. The objective of the study was to assess whether loop analysis could be applied to this new context. We first developed a generic model that restricted the applicability of the method to event-based surveillance systems of endemic diseases, excluding the emergence and eradication phases. Then we chose the mitigation system of highly pathogenic avian influenza (HPAI) H5N1 in Cambodia as an example of such system to study the application of loop analysis to a real disease mitigation system.ResultsBreaking down the generic model, we constructed a 6-variables model to represent the HPAI H5N1 mitigation system in Cambodia. This construction work improved our understanding of this system, highlighting the link between surveillance and control which is unclear in traditional representations of this system. Then we analyzed the effect of the perturbations to this HPAI H5N1 mitigation system that we interpreted in terms of investment in a given compartment. This study suggested that increasing intervention at a local level can optimize the system’s efficiency. Indeed, this perturbation both decreases surveillance and intervention costs and reduces the disease’s occurrence.ConclusionLoop analysis can be applied to disease mitigation systems. Its main strength is that it is easy to design, focusing on the signs of the interactions. It is a simple and flexible tool that could be used as a precursor to large-scale quantitative studies, to support reflection about disease mitigation systems structure and functioning.

Empirical findings show that morbidity and mortality risks of migrants can differ considerably from those of populations in the host countries. However, while several explanatory models have been developed, most migrant studies still do not consider explicitly the situation of migrants before migration. Here, we discuss an extended approach to understand migrant health comprising a life course epidemiology perspective.The incorporation of a life course perspective into a conceptual framework of migrant health enables the consideration of risk factors and disease outcomes over the different life phases of migrants, which is necessary to understand the health situation of migrants and their offspring. Comparison populations need to be carefully selected depending on the study questions under consideration within the life course framework.Migrant health research will benefit from an approach using a life course perspective. A critique of the theoretical foundations of migrant health research is essential for further developing both the theoretical framework of migrant health and related empirical studies.

BackgroundSurvey data are traditionally collected using pen-and-paper, with double data entry, comparison of entries and reconciliation of discrepancies before data cleaning can commence. We used Personal Digital Assistants (PDAs) for data entry at the point of collection, to save time and enhance the quality of data in a survey of over 21,000 scattered rural households in southern Tanzania.MethodsPendragon Forms 4.0 software was used to develop a modular questionnaire designed to record information on household residents, birth histories, child health and health-seeking behaviour. The questionnaire was loaded onto Palm m130 PDAs with 8 Mb RAM. One hundred and twenty interviewers, the vast majority with no more than four years of secondary education and very few with any prior computer experience, were trained to interview using the PDAs. The 13 survey teams, each with a supervisor, laptop and a four-wheel drive vehicle, were supported by two back-up vehicles during the two months of field activities. PDAs and laptop computers were charged using solar and in-car chargers.Logical checks were performed and skip patterns taken care of at the time of data entry. Data records could not be edited after leaving each household, to ensure the integrity of the data from each interview. Data were downloaded to the laptop computers and daily summary reports produced to evaluate the completeness of data collection. Data were backed up at three levels: (i) at the end of every module, data were backed up onto storage cards in the PDA; (ii) at the end of every day, data were downloaded to laptop computers; and (iii) a compact disc (CD) was made of each team's data each day.A small group of interviewees from the community, as well as supervisors and interviewers, were asked about their attitudes to the use of PDAs.ResultsFollowing two weeks of training and piloting, data were collected from 21,600 households (83,346 individuals) over a seven-week period in July-August 2004. No PDA-related problems or data loss were encountered.Fieldwork ended on 26 August 2004, the full dataset was available on a CD within 24 hours and the results of initial analyses were presented to district authorities on 28 August. Data completeness was over 99%.The PDAs were well accepted by both interviewees and interviewers.ConclusionThe use of PDAs eliminated the usual time-consuming and error-prone process of data entry and validation. PDAs are a promising tool for field research in Africa.

A rich and growing body of literature has emerged on ethics in epidemiologic research and public health practice. Recent articles have included conceptual frameworks of public health ethics and overviews of historical developments in the field. Several important topics in public health ethics have also been highlighted. Attention to ethical issues can facilitate the effective planning, implementation, and growth of a variety of public health programs and research activities. Public health ethics is consistent with the prevention orientation of public health. Ethical concerns can be anticipated or identified early and effectively addressed through careful analysis and consultation.