Active surveillance for rheumatic heart disease in endemic regions: a systematic review and meta-analysis of prevalence among children and adolescents

BACKGROUND Rheumatic heart disease accounts for up to 250 000 premature deaths every year worldwide and can be regarded as a physical manifestation of poverty and social inequality. We aimed to estimate the prevalence of rheumatic heart disease in endemic countries as assessed by different screening modalities and as a function of age. METHODS We searched Medline, Embase, the Latin American and Caribbean System on Health Sciences Information, African Journals Online, and the Cochrane Database of Systematic Reviews for population-based studies published between Jan 1, 1993, and June 30, 2014, that reported on prevalence of rheumatic heart disease among children and adolescents (≥5 years to <18 years). We assessed prevalence of clinically silent and clinically manifest rheumatic heart disease in random effects meta-analyses according to screening modality and geographical region. We assessed the association between social inequality and rheumatic heart disease with the Gini coefficient. We used Poisson regression to analyse the effect of age on prevalence of rheumatic heart disease and estimated the incidence of rheumatic heart disease from prevalence data. FINDINGS We included 37 populations in the systematic review and meta-analysis. The pooled prevalence of rheumatic heart disease detected by cardiac auscultation was 2·9 per 1000 people (95% CI 1·7-5·0) and by echocardiography it was 12·9 per 1000 people (8·9-18·6), with substantial heterogeneity between individual reports for both screening modalities (I(2)=99·0% and 94·9%, respectively). We noted an association between social inequality expressed by the Gini coefficient and prevalence of rheumatic heart disease (p=0·0002). The prevalence of clinically silent rheumatic heart disease (21·1 per 1000 people, 95% CI 14·1-31·4) was about seven to eight times higher than that of clinically manifest disease (2·7 per 1000 people, 1·6-4·4). Prevalence progressively increased with advancing age, from 4·7 per 1000 people (95% CI 0·0-11·2) at age 5 years to 21·0 per 1000 people (6·8-35·1) at 16 years. The estimated incidence was 1·6 per 1000 people (0·8-2·3) and remained constant across age categories (range 2·5, 95% CI 1·3-3·7 in 5-year-old children to 1·7, 0·0-5·1 in 15-year-old adolescents). We noted no sex-related differences in prevalence (p=0·829). INTERPRETATION We found a high prevalence of rheumatic heart disease in endemic countries. Although a reduction in social inequalities represents the cornerstone of community-based prevention, the importance of early detection of silent rheumatic heart disease remains to be further assessed. FUNDING UBS Optimus Foundation.

A pilot study for targeted surveillance of bovine spongiform encephalopathy in Nigeria.

Bovine spongiform encephalopathy (BSE), popularly known as 'mad cow disease', led to an epidemic in Europe that peaked in the mid-1990s. Its impact on developing countries, such as Nigeria, has not been fully established as information on livestock and surveillance has eluded those in charge of this task. The BSE risk to Nigeria's cattle population currently remains undetermined, which has resulted in international trade restrictions on commodities from the cattle population. This is mainly because of a lack of updated BSE risk assessments and disease surveillance data. To evaluate the feasibility of BSE surveillance in Nigeria, we carried out a pilot study targeting cattle that were presented for emergency or casualty slaughter. In total, 1551 cattle of local breeds, aged 24 months and above were clinically examined. Ataxia, recumbency and other neurological signs were topmost on our list of criteria. A total of 96 cattle, which correspond to 6.2%, presented clinical signs that supported a suspect of BSE. The caudal brainstem tissues of these animals were collected post-mortem and analysed for the disease-specific form of the prion protein using a rapid test approved by the International Animal Health Organization (OIE). None of the samples were positive for BSE. Although our findings do not exclude the presence of BSE in Nigeria, they do demonstrate that targeted sampling of clinically suspected cases of BSE is feasible in developing countries. In addition, these findings point to the possibility of implementing clinical monitoring schemes for BSE and potentially other diseases with grave economic and public health consequences.

Capability of a space-based space surveillance system to detect and track objects in GEO, MEO and LEO orbits

In this paper we present the results from the coverage and the orbit determination accuracy simulations performed within the recently completed ESA study “Assessment Study for Space Based Space Surveillance (SBSS) Demonstration System” (Airbus Defence and Space consortium). This study consisted in investigating the capability of a space based optical sensor (SBSS) orbiting in low Earth orbit (LEO) to detect and track objects in GEO (geosynchronous orbit), MEO (medium Earth orbit) and LEO and to determinate and improve initial orbits from such observations. Space based systems may achieve better observation conditions than ground based sensors in terms of astrometric accuracy, detection coverage, and timeliness. The primary observation mode of the proposed SBSS demonstrator is GEO surveillance, i.e. the systematic search and detection of unknown and known objects. GEO orbits are specific and unique orbits from dynamical point of view. A space-based sensor may scan the whole GEO ring within one sidereal day if the orbit and pointing directions are chosen properly. For an efficient survey, our goal was to develop a leak-proof GEO fence strategy. Collaterally, we show that also MEO, LEO and other (GTO,Molniya, etc.) objects would be possible to observe by the system and for a considerable number of LEO objects to down to size of 1 cm we can obtain meaningful statistical data for improvement and validation of space debris environment models

A system design for space-based space surveillance

This paper presents the capabilities of a Space-Based Space Surveillance (SBSS) demonstration mission for Space Surveillance and Tracking (SST) based on a micro- satellite platform. The results have been produced in the frame of ESA’s "As sessment Study for Space Based Space Surveillance Demonstration Mission (Phase A) " performed by the Airbus DS consortium. Space Surveillance and Tracking is part of Space Situational Awareness (SSA) and covers the detection, tracking and cataloguing of spa ce debris and satellites. Derived SST services comprise a catalogue of these man-made objects, collision warning, detection and characterisation of in-orbit fragmentations, sub-catalogue debris characterisation, etc. The assessment of SBSS in an SST system architecture has shown that both an operational SBSS and also already a well - designed space-based demonstrator can provide substantial performance in terms of surveillance and tracking of beyond - LEO objects. Especially the early deployment of a demonstrator, possible by using standard equipment, could boost initial operating capability and create a self-maintained object catalogue. Unlike classical technology demonstration missions, the primary goal is the demonstration and optimisation of the functional elements in a complex end-to-end chain (mission planning, observation strategies, data acquisition, processing and fusion, etc.) until the final products can be offered to the users. The presented SBSS system concept takes the ESA SST System Requirements (derived within the ESA SSA Preparatory Program) into account and aims at fulfilling some of the SST core requirements in a stand-alone manner. The evaluation of the concept has shown that an according solution can be implemented with low technological effort and risk. The paper presents details of the system concept, candidate micro - satellite platforms, the observation strategy and the results of performance simulations for GEO coverage and cataloguing accuracy

Space-based space surveillance and tracking demonstrator: mission and system design

This paper presents the capabilities of a Space-Based Space Surveillance (SBSS) demonstration mission for Space Surveillance and Tracking (SST) based on a micro-satellite platform. The results have been produced in the frame of ESA’s "Assessment Study for Space Based Space Surveillance Demonstration Mission" performed by the Airbus Defence and Space consortium. The assessment of SBSS in an SST system architecture has shown that both an operational SBSS and also already a well- designed space-based demonstrator can provide substantial performance in terms of surveillance and tracking of beyond-LEO objects. Especially the early deployment of a demonstrator, possible by using standard equipment, could boost initial operating capability and create a self-maintained object catalogue. Furthermore, unique statistical information about small-size LEO debris (mm size) can be collected in-situ. Unlike classical technology demonstration missions, the primary goal is the demonstration and optimisation of the functional elements in a complex end-to-end chain (mission planning, observation strategies, data acquisition, processing, etc.) until the final products can be offered to the users and with low technological effort and risk. The SBSS system concept takes the ESA SST System Requirements into account and aims at fulfilling SST core requirements in a stand-alone manner. Additionally, requirements for detection and characterisation of small-sizedLEO debris are considered. The paper presents details of the system concept, candidate micro-satellite platforms, the instrument design and the operational modes. Note that the detailed results of performance simulations for space debris coverage and cataloguing accuracy are presented in a separate paper “Capability of a Space-based Space Surveillance System to Detect and Track Objects in GEO, MEO and LEO Orbits” by J. Silha (AIUB) et al., IAC-14, A6, 1.1x25640.

Using Bayes' rule to define the value of evidence from syndromic surveillance

In this work we propose the adoption of a statistical framework used in the evaluation of forensic evidence as a tool for evaluating and presenting circumstantial "evidence" of a disease outbreak from syndromic surveillance. The basic idea is to exploit the predicted distributions of reported cases to calculate the ratio of the likelihood of observing n cases given an ongoing outbreak over the likelihood of observing n cases given no outbreak. The likelihood ratio defines the Value of Evidence (V). Using Bayes' rule, the prior odds for an ongoing outbreak are multiplied by V to obtain the posterior odds. This approach was applied to time series on the number of horses showing clinical respiratory symptoms or neurological symptoms. The separation between prior beliefs about the probability of an outbreak and the strength of evidence from syndromic surveillance offers a transparent reasoning process suitable for supporting decision makers. The value of evidence can be translated into a verbal statement, as often done in forensics or used for the production of risk maps. Furthermore, a Bayesian approach offers seamless integration of data from syndromic surveillance with results from predictive modeling and with information from other sources such as disease introduction risk assessments.

A practical approach to designing syndromic surveillance systems for livestock and poultry

The field of animal syndromic surveillance (SyS) is growing, with many systems being developed worldwide. Now is an appropriate time to share ideas and lessons learned from early SyS design and implementation. Based on our practical experience in animal health SyS, with additions from the public health and animal health SyS literature, we put forward for discussion a 6-step approach to designing SyS systems for livestock and poultry. The first step is to formalise policy and surveillance goals which are considerate of stakeholder expectations and reflect priority issues (1). Next, it is important to find consensus on national priority diseases and identify current surveillance gaps. The geographic, demographic, and temporal coverage of the system must be carefully assessed (2). A minimum dataset for SyS that includes the essential data to achieve all surveillance objectives while minimizing the amount of data collected should be defined. One can then compile an inventory of the data sources available and evaluate each using the criteria developed (3). A list of syndromes should then be produced for all data sources. Cases can be classified into syndrome classes and the data can be converted into time series (4). Based on the characteristics of the syndrome-time series, the length of historic data available and the type of outbreaks the system must detect, different aberration detection algorithms can be tested (5). Finally, it is essential to develop a minimally acceptable response protocol for each statistical signal produced (6). Important outcomes of this pre-operational phase should be building of a national network of experts and collective action and evaluation plans. While some of the more applied steps (4 and 5) are currently receiving consideration, more emphasis should be put on earlier conceptual steps by decision makers and surveillance developers (1-3).

Evaluation of Swiss slaughterhouse data for integration in a syndromic surveillance system

BACKGROUND: We evaluated Swiss slaughterhouse data for integration in a national syndromic surveillance system for the early detection of emerging diseases in production animals. We analysed meat inspection data for cattle, pigs and small ruminants slaughtered between 2007 and 2012 (including emergency slaughters of sick/injured animals); investigating patterns in the number of animals slaughtered and condemned; the reasons invoked for whole carcass condemnations; reporting biases and regional effects. RESULTS: Whole carcass condemnation rates were fairly uniform (1-2‰) over time and between the different types of production animals. Condemnation rates were much higher and less uniform following emergency slaughters. The number of condemnations peaked in December for both cattle and pigs, a time when individuals of lower quality are sent to slaughter when hay and food are limited and when certain diseases are more prevalent. Each type of production animal was associated with a different profile of condemnation reasons. The most commonly reported one was "severe lesions" for cattle, "abscesses" for pigs and "pronounced weight loss" for small ruminants. These reasons could constitute valuable syndromic indicators as they are unspecific clinical manifestations of a large range of animal diseases (as well as potential indicators of animal welfare). Differences were detected in the rate of carcass condemnation between cantons and between large and small slaughterhouses. A large percentage (>60% for all three animal categories) of slaughterhouses operating never reported a condemnation between 2007 and 2012, a potential indicator of widespread non-reporting bias in our database. CONCLUSIONS: The current system offers simultaneous coverage of cattle, pigs and small ruminants for the whole of Switzerland; and traceability of each condemnation to its farm of origin. The number of condemnations was significantly linked to the number of slaughters, meaning that the former should be always be offset by the later in analyses. Because this denominator is only communicated at the end of the month, condemnations may currently only be monitored on a monthly basis. Coupled with the lack of timeliness (30-60 days delay between condemnation and notification), this limits the use of the data for early-detection.

Mining free-text medical records for companion animal enteric syndrome surveillance.

Large amounts of animal health care data are present in veterinary electronic medical records (EMR) and they present an opportunity for companion animal disease surveillance. Veterinary patient records are largely in free-text without clinical coding or fixed vocabulary. Text-mining, a computer and information technology application, is needed to identify cases of interest and to add structure to the otherwise unstructured data. In this study EMR's were extracted from veterinary management programs of 12 participating veterinary practices and stored in a data warehouse. Using commercially available text-mining software (WordStat™), we developed a categorization dictionary that could be used to automatically classify and extract enteric syndrome cases from the warehoused electronic medical records. The diagnostic accuracy of the text-miner for retrieving cases of enteric syndrome was measured against human reviewers who independently categorized a random sample of 2500 cases as enteric syndrome positive or negative. Compared to the reviewers, the text-miner retrieved cases with enteric signs with a sensitivity of 87.6% (95%CI, 80.4-92.9%) and a specificity of 99.3% (95%CI, 98.9-99.6%). Automatic and accurate detection of enteric syndrome cases provides an opportunity for community surveillance of enteric pathogens in companion animals.

Estimating HIV Incidence, Time to Diagnosis, and the Undiagnosed HIV Epidemic Using Routine Surveillance Data.

BACKGROUND Estimates of the size of the undiagnosed HIV-infected population are important to understand the HIV epidemic and to plan interventions, including "test-and-treat" strategies. METHODS We developed a multi-state back-calculation model to estimate HIV incidence, time between infection and diagnosis, and the undiagnosed population by CD4 count strata, using surveillance data on new HIV and AIDS diagnoses. The HIV incidence curve was modelled using cubic splines. The model was tested on simulated data and applied to surveillance data on men who have sex with men in The Netherlands. RESULTS The number of HIV infections could be estimated accurately using simulated data, with most values within the 95% confidence intervals of model predictions. When applying the model to Dutch surveillance data, 15,400 (95% confidence interval [CI] = 15,000, 16,000) men who have sex with men were estimated to have been infected between 1980 and 2011. HIV incidence showed a bimodal distribution, with peaks around 1985 and 2005 and a decline in recent years. Mean time to diagnosis was 6.1 (95% CI = 5.8, 6.4) years between 1984 and 1995 and decreased to 2.6 (2.3, 3.0) years in 2011. By the end of 2011, 11,500 (11,000, 12,000) men who have sex with men in The Netherlands were estimated to be living with HIV, of whom 1,750 (1,450, 2,200) were still undiagnosed. Of the undiagnosed men who have sex with men, 29% (22, 37) were infected for less than 1 year, and 16% (13, 20) for more than 5 years. CONCLUSIONS This multi-state back-calculation model will be useful to estimate HIV incidence, time to diagnosis, and the undiagnosed HIV epidemic based on routine surveillance data.

Evaluating the surveillance for swine dysentery and progressive atrophic Rhinitis in closed multiplier herds using Scenario tree modelling

Background: The Swiss pig population enjoys a favourable health situation. To further promote this, the Pig Health Service (PHS) conducts a surveillance program in affiliated herds: closed multiplier herds with the highest PHS-health and hygiene status have to be free from swine dysentery and progressive atrophic rhinitis and are clinically examined four times a year, including laboratory testing. Besides, four batches of pigs per year are fattened together with pigs from other herds and checked for typical symptoms (monitored fattening groups (MF)). While costly and laborious, little was known about the effectiveness of the surveillance to detect an infection in a herd. Therefore, the sensitivity of the surveillance for progressive atrophic rhinitis and swine dysentery at herd level was assessed using scenario tree modelling, a method well established at national level. Furthermore, its costs and the time until an infection would be detected were estimated, with the final aim of yielding suggestions how to optimize surveillance. Results: For swine dysentery, the median annual surveillance sensitivity was 96.7 %, mean time to detection 4.4 months, and total annual costs 1022.20 Euro/herd. The median component sensitivity of active sampling was between 62.5 and 77.0 %, that of a MF between 7.2 and 12.7 %. For progressive atrophic rhinitis, the median surveillance sensitivity was 99.4 %, mean time to detection 3.1 months and total annual costs 842.20 Euro. The median component sensitivity of active sampling was 81.7 %, that of a MF between 19.4 and 38.6 %. Conclusions: Results indicate that total sensitivity for both diseases is high, while time to detection could be a risk in herds with frequent pig trade. From all components, active sampling had the highest contribution to the surveillance sensitivity, whereas that of MF was very low. To increase efficiency, active sampling should be intensified (more animals sampled) and MF abandoned. This would significantly improve sensitivity and time to detection at comparable or lower costs. The method of scenario tree modelling proved useful to assess the efficiency of surveillance at herd level. Its versatility allows adjustment to all kinds of surveillance scenarios to optimize sensitivity, time to detection and/or costs.

Outcomes of Active Surveillance for Ductal Carcinoma in Situ: A Computational Risk Analysis.

BACKGROUND Ductal carcinoma in situ (DCIS) is a noninvasive breast lesion with uncertain risk for invasive progression. Usual care (UC) for DCIS consists of treatment upon diagnosis, thus potentially overtreating patients with low propensity for progression. One strategy to reduce overtreatment is active surveillance (AS), whereby DCIS is treated only upon detection of invasive disease. Our goal was to perform a quantitative evaluation of outcomes following an AS strategy for DCIS. METHODS Age-stratified, 10-year disease-specific cumulative mortality (DSCM) for AS was calculated using a computational risk projection model based upon published estimates for natural history parameters, and Surveillance, Epidemiology, and End Results data for outcomes. AS projections were compared with the DSCM for patients who received UC. To quantify the propagation of parameter uncertainty, a 95% projection range (PR) was computed, and sensitivity analyses were performed. RESULTS Under the assumption that AS cannot outperform UC, the projected median differences in 10-year DSCM between AS and UC when diagnosed at ages 40, 55, and 70 years were 2.6% (PR = 1.4%-5.1%), 1.5% (PR = 0.5%-3.5%), and 0.6% (PR = 0.0%-2.4), respectively. Corresponding median numbers of patients needed to treat to avert one breast cancer death were 38.3 (PR = 19.7-69.9), 67.3 (PR = 28.7-211.4), and 157.2 (PR = 41.1-3872.8), respectively. Sensitivity analyses showed that the parameter with greatest impact on DSCM was the probability of understaging invasive cancer at diagnosis. CONCLUSION AS could be a viable management strategy for carefully selected DCIS patients, particularly among older age groups and those with substantial competing mortality risks. The effectiveness of AS could be markedly improved by reducing the rate of understaging.