Timely Reporting and Interactive Visualization of Animal Health and Slaughterhouse Surveillance Data in Switzerland

The reporting of outputs from health surveillance systems should be done in a near real-time and interactive manner in order to provide decision makers with powerful means to identify, assess, and manage health hazards as early and efficiently as possible. While this is currently rarely the case in veterinary public health surveillance, reporting tools do exist for the visual exploration and interactive interrogation of health data. In this work, we used tools freely available from the Google Maps and Charts library to develop a web application reporting health-related data derived from slaughterhouse surveillance and from a newly established web-based equine surveillance system in Switzerland. Both sets of tools allowed entry-level usage without or with minimal programing skills while being flexible enough to cater for more complex scenarios for users with greater programing skills. In particular, interfaces linking statistical softwares and Google tools provide additional analytical functionality (such as algorithms for the detection of unusually high case occurrences) for inclusion in the reporting process. We show that such powerful approaches could improve timely dissemination and communication of technical information to decision makers and other stakeholders and could foster the early-warning capacity of animal health surveillance systems.

Data-driven healthcare: from patterns to actions

The era of big data opens up new opportunities in personalised medicine, preventive care, chronic disease management and in telemonitoring and managing of patients with implanted devices. The rich data accumulating within online services and internet companies provide a microscope to study human behaviour at scale, and to ask completely new questions about the interplay between behavioural patterns and health. In this paper, we shed light on a particular aspect of data-driven healthcare: autonomous decision-making. We first look at three examples where we can expect data-driven decisions to be taken autonomously by technology, with no or limited human intervention. We then discuss some of the technical and practical challenges that can be expected, and sketch the research agenda to address them.

Mycoplasma bovis infections in Swiss dairy cattle: a clinical investigation

Mycoplasma bovis causes mastitis in dairy cows and is associated with pneumonia and polyarthritis in cattle. The present investigation included a retrospective case–control study to identify potential herd-level risk factors for M. bovis associated disease, and a prospective cohort study to evaluate the course of clinical disease in M. bovis infected dairy cattle herds in Switzerland. Eighteen herds with confirmed M. bovis cases were visited twice within an average interval of 75 d. One control herd with no history of clinical mycoplasmosis, matched for herd size, was randomly selected within a 10 km range for each case herd. Animal health data, production data, information on milking and feeding-management, housing and presence of potential stress- factors were collected. Composite quarter milk samples were aseptically collected from all lactating cows and 5% of all animals within each herd were sampled by nasal swabs. Organ samples of culled diseased cows were collected when logistically possible. All samples were analyzed by real-time polymerase chain reaction (PCR). In case herds, incidence risk of pneumonia, arthritis and clinical mastitis prior to the first visit and incidence rates of clinical mastitis and clinical pneumonia between the two visits was estimated. Logistic regression was used to identify potential herd-level risk factors for M. bovis infection. In case herds, incidence risk of M. bovis mastitis prior to the first visit ranged from 2 to 15%, whereas 2 to 35% of the cows suffered from clinical pneumonia within the 12 months prior to the first herd visit. The incidence rates of mycoplasmal mastitis and clinical pneumonia between the two herd visits were low in case herds (0–0.1 per animal year at risk and 0.1-0.6 per animal year at risk, respectively). In the retrospective-case-control study high mean milk production, appropriate stimulation until milk-let-down, fore-stripping, animal movements (cattle shows and trade), presence of stress-factors, and use of a specific brand of milking equipment, were identified as potential herd-level risk factors. The prospective cohort study revealed a decreased incidence of clinical disease within three months and prolonged colonization of the nasal cavity by M. bovis in young stock.

Life-span development of self-esteem and its effects on important life outcomes

We examined the life-span development of self-esteem and tested whether self-esteem influences the development of important life outcomes, including relationship satisfaction, job satisfaction, occupational status, salary, positive and negative affect, depression, and physical health. Data came from the Longitudinal Study of Generations. Analyses were based on 5 assessments across a 12-year period of a sample of 1,824 individuals ages 16 to 97 years. First, growth curve analyses indicated that self-esteem increases from adolescence to middle adulthood, reaches a peak at about age 50 years, and then decreases in old age. Second, cross-lagged regression analyses indicated that self-esteem is best modeled as a cause rather than a consequence of life outcomes. Third, growth curve analyses, with self-esteem as a time-varying covariate, suggested that self-esteem has medium-sized effects on life-span trajectories of affect and depression, small to medium-sized effects on trajectories of relationship and job satisfaction, a very small effect on the trajectory of health, and no effect on the trajectory of occupational status. These findings replicated across 4 generations of participants— children, parents, grandparents, and their great-grandparents. Together, the results suggest that self-esteem has a significant prospective impact on real-world life experiences and that high and low self-esteem are not mere epiphenomena of success and failure in important life domains.

Experiences with a voluntary surveillance system for early detection of equine diseases in Switzerland

Clinical observations made by practitioners and reported using web- and mobile-based technologies may benefit disease surveillance by improving the timeliness of outbreak detection. Equinella is a voluntary electronic reporting and information system established for the early detection of infectious equine diseases in Switzerland. Sentinel veterinary practitioners have been able to report cases of non-notifiable diseases and clinical symptoms to an internet-based platform since November 2013. Telephone interviews were carried out during the first year to understand the motivating and constraining factors affecting voluntary reporting and the use of mobile devices in a sentinel network. We found that non-monetary incentives attract sentinel practitioners; however, insufficient understanding of the reporting system and of its relevance, as well as concerns over the electronic dissemination of health data were identified as potential challenges to sustainable reporting. Many practitioners are not yet aware of the advantages of mobile-based surveillance and may require some time to become accustomed to novel reporting methods. Finally, our study highlights the need for continued information feedback loops within voluntary sentinel networks.

Prognosis of Atrial Fibrillation in Patients with Symptomatic Peripheral Arterial Disease: Data from the REduction of Atherothrombosis for Continued Health (REACH) Registry

BACKGROUND: Atrial fibrillation (AF) is a significant risk factor for cardiovascular (CV) mortality. This study aims to evaluate the prognostic implication of AF in patients with peripheral arterial disease (PAD). METHODS: The International Reduction of Atherothrombosis for Continued Health (REACH) Registry included 23,542 outpatients in Europe with established coronary artery disease, cerebrovascular disease (CVD), PAD and/or >/=3 risk factors. Of these, 3753 patients had symptomatic PAD. CV risk factors were determined at baseline. Study end point was a combination of cardiac death, non-fatal myocardial infarction (MI) and stroke (CV events) during 2 years of follow-up. Cox regression analysis adjusted for age, gender and other risk factors (i.e., congestive heart failure, coronary artery re-vascularisation, coronary artery bypass grafting (CABG), MI, hypertension, stroke, current smoking and diabetes) was used. RESULTS: Of 3753 PAD patients, 392 (10%) were known to have AF. Patients with AF were older and had a higher prevalence of CVD, diabetes and hypertension. Long-term CV mortality occurred in 5.6% of patients with AF and in 1.6% of those without AF (p<0.001). Multivariable analyses showed that AF was an independent predictor of late CV events (hazard ratio (HR): 1.5; 95% confidence interval (CI): 1.09-2.0). CONCLUSION: AF is common in European patients with symptomatic PAD and is independently associated with a worse 2-year CV outcome.

Data quality of animal health records on Swiss dairy farms

High-quality data are essential for veterinary surveillance systems, and their quality can be affected by the source and the method of collection. Data recorded on farms could provide detailed information about the health of a population of animals, but the accuracy of the data recorded by farmers is uncertain. The aims of this study were to evaluate the quality of the data on animal health recorded on 97 Swiss dairy farms, to compare the quality of the data obtained by different recording systems, and to obtain baseline data on the health of the animals on the 97 farms. Data on animal health were collected from the farms for a year. Their quality was evaluated by assessing the completeness and accuracy of the recorded information, and by comparing farmers' and veterinarians' records. The quality of the data provided by the farmers was satisfactory, although electronic recording systems made it easier to trace the animals treated. The farmers tended to record more health-related events than the veterinarians, although this varied with the event considered, and some events were recorded only by the veterinarians. The farmers' attitude towards data collection was positive. Factors such as motivation, feedback, training, and simplicity and standardisation of data collection were important because they influenced the quality of the data.

No sports – no mental health? Analysis of longitudinal effects in SHP data.

Results from the Zurich study have shown lasting associations between sport practice and mental health. The effects are pronounced in people with pre-exising mental health problems. This analysis aims to replicate these results with the large Swiss Household Panel data set and to provide more differentiated results. The analysis covered the interviews 1999-2003 and included 3891 stayers, i.e., participants who were interviewed in all years. The outcome variables are depression / blues / anxiety, weakness / weariness, sleeping problems, energy / optimism. Confounding variables include sex, age, education level, citizenship. The analyses were carried out with mixed models (depression, optimism) and GEE models (weakness, sleep). About 60% of the SHP participants practise weekly or daily an individual or a team sport. A similar proportion enjoys a frequent physical activity (for half an hour minimum) which makes oneself slightly breathless. There are slight age-specific differences but also noteworthy regional differences. Practice of sport is clearly interrelated with self-reported depressive symptoms, optimism and weakness. This applies even though some relevant confounders – sex, educational level and citizenship – were introduced into the model. However, no relevant interaction effects with time could be shown. Moreover, direct interrelations commonly led to better fits than models with lagged variables, thus indicating that delayed effects of sport practice on the self-reported psychological complaints are less important. Model variants resulted for specific subgroups, for example, participants with a high vs. low initial activity level. Lack of sport practice is an interesting marker for serious psychological symptoms and mental disorders. The background of this association may differ in different subgroups, and should stimulate further investigations in this area.

Privacy Preserving Probabilistic Record Linkage (P3RL): a novel method for linking existing health-related data and maintaining participant confidentiality.

BACKGROUND Record linkage of existing individual health care data is an efficient way to answer important epidemiological research questions. Reuse of individual health-related data faces several problems: Either a unique personal identifier, like social security number, is not available or non-unique person identifiable information, like names, are privacy protected and cannot be accessed. A solution to protect privacy in probabilistic record linkages is to encrypt these sensitive information. Unfortunately, encrypted hash codes of two names differ completely if the plain names differ only by a single character. Therefore, standard encryption methods cannot be applied. To overcome these challenges, we developed the Privacy Preserving Probabilistic Record Linkage (P3RL) method. METHODS In this Privacy Preserving Probabilistic Record Linkage method we apply a three-party protocol, with two sites collecting individual data and an independent trusted linkage center as the third partner. Our method consists of three main steps: pre-processing, encryption and probabilistic record linkage. Data pre-processing and encryption are done at the sites by local personnel. To guarantee similar quality and format of variables and identical encryption procedure at each site, the linkage center generates semi-automated pre-processing and encryption templates. To retrieve information (i.e. data structure) for the creation of templates without ever accessing plain person identifiable information, we introduced a novel method of data masking. Sensitive string variables are encrypted using Bloom filters, which enables calculation of similarity coefficients. For date variables, we developed special encryption procedures to handle the most common date errors. The linkage center performs probabilistic record linkage with encrypted person identifiable information and plain non-sensitive variables. RESULTS In this paper we describe step by step how to link existing health-related data using encryption methods to preserve privacy of persons in the study. CONCLUSION Privacy Preserving Probabilistic Record linkage expands record linkage facilities in settings where a unique identifier is unavailable and/or regulations restrict access to the non-unique person identifiable information needed to link existing health-related data sets. Automated pre-processing and encryption fully protect sensitive information ensuring participant confidentiality. This method is suitable not just for epidemiological research but also for any setting with similar challenges.

Reporting and handling missing outcome data in mental health: a systematic review of Cochrane systematic reviews and meta-analyses

OBJECTIVES The purpose of the study was to provide empirical evidence about the reporting of methodology to address missing outcome data and the acknowledgement of their impact in Cochrane systematic reviews in the mental health field. METHODS Systematic reviews published in the Cochrane Database of Systematic Reviews after January 1, 2009 by three Cochrane Review Groups relating to mental health were included. RESULTS One hundred ninety systematic reviews were considered. Missing outcome data were present in at least one included study in 175 systematic reviews. Of these 175 systematic reviews, 147 (84%) accounted for missing outcome data by considering a relevant primary or secondary outcome (e.g., dropout). Missing outcome data implications were reported only in 61 (35%) systematic reviews and primarily in the discussion section by commenting on the amount of the missing outcome data. One hundred forty eligible meta-analyses with missing data were scrutinized. Seventy-nine (56%) of them had studies with total dropout rate between 10 and 30%. One hundred nine (78%) meta-analyses reported to have performed intention-to-treat analysis by including trials with imputed outcome data. Sensitivity analysis for incomplete outcome data was implemented in less than 20% of the meta-analyses. CONCLUSIONS Reporting of the techniques for handling missing outcome data and their implications in the findings of the systematic reviews are suboptimal.