Dengue disease surveillance: an updated systematic literature review

Objectives To review the evidence for the application of tools for dengue outbreak prediction/detection and trend monitoring in passive and active disease surveillance systems in order to develop recommendations for endemic countries and identify important research needs. Methods This systematic literature review followed the protocol of a review from 2008, extending the systematic search from January 2007 to February 2013 on PubMed, EMBASE, CDSR, WHOLIS and Lilacs. Data reporting followed the PRISMA statement. The eligibility criteria comprised (i) population at risk of dengue, (ii) dengue disease surveillance, (iii) outcome of surveillance described and (iv) empirical data evaluated. The analysis classified studies based on the purpose of the surveillance programme. The main limitation of the review was expected publication bias. Results A total of 1116 papers were identified of which 36 articles were included in the review. Four cohort-based prospective studies calculated expansion factors demonstrating remarkable levels of underreporting in the surveillance systems. Several studies demonstrated that enhancement methods such as laboratory support, sentinel-based reporting and staff motivation contributed to improvements in dengue reporting. Additional improvements for passive surveillance systems are possible by incorporating simple data forms/entry/electronic-based reporting; defining clear system objectives; performing data analysis at the lowest possible level (e.g. district); seeking regular data feedback. Six studies showed that serotype changes were positively correlated with the number of reported cases or with dengue incidence, with lag times of up to 6 months. Three studies found that data on internet searches and event-based surveillance correlated well with the epidemic curve derived from surveillance data. Conclusions Passive surveillance providing the baseline for outbreak alert should be strengthened and appropriate threshold levels for outbreak alerts investigated. Additional enhancement tools such as syndromic surveillance, laboratory support and motivation strategies can be added. Appropriate alert signals need to be identified and integrated into a risk assessment tool. Shifts in dengue serotypes/genotype or electronic event-based surveillance have also considerable potential as indicator in dengue surveillance. Further research on evidence-based response strategies and cost-effectiveness is needed

Success Factors of European Syndromic Surveillance Systems: A Worked Example of Applying Qualitative Comparative Analysis

Introduction: Syndromic surveillance aims at augmenting traditional public health surveillance with timely information. To gain a head start, it mainly analyses existing data such as from web searches or patient records. Despite the setup of many syndromic surveillance systems, there is still much doubt about the benefit of the approach. There are diverse interactions between performance indicators such as timeliness and various system characteristics. This makes the performance assessment of syndromic surveillance systems a complex endeavour. We assessed if the comparison of several syndromic surveillance systems through Qualitative Comparative Analysis helps to evaluate performance and identify key success factors. Materials and Methods: We compiled case-based, mixed data on performance and characteristics of 19 syndromic surveillance systems in Europe from scientific and grey literature and from site visits. We identified success factors by applying crisp-set Qualitative Comparative Analysis. We focused on two main areas of syndromic surveillance application: seasonal influenza surveillance and situational awareness during different types of potentially health threatening events. Results: We found that syndromic surveillance systems might detect the onset or peak of seasonal influenza earlier if they analyse non-clinical data sources. Timely situational awareness during different types of events is supported by an automated syndromic surveillance system capable of analysing multiple syndromes. To our surprise, the analysis of multiple data sources was no key success factor for situational awareness. Conclusions: We suggest to consider these key success factors when designing or further developing syndromic surveillance systems. Qualitative Comparative Analysis helped interpreting complex, mixed data on small-N cases and resulted in concrete and practically relevant findings

Challenges in defining an optimal approach to formula-based allocations of public health funds in the United States

BACKGROUND: Controversy and debate can arise whenever public health agencies determine how program funds should be allocated among constituent jurisdictions. Two common strategies for making such allocations are expert review of competitive applications and the use of funding formulas. Despite widespread use of funding formulas by public health agencies in the United States, formula allocation strategies in public health have been subject to relatively little formal scrutiny, with the notable exception of the attention focused on formula funding of HIV care programs. To inform debates and deliberations in the selection of a formula-based approach, we summarize key challenges to formula-based funding, based on prior reviews of federal programs in the United States. DISCUSSION: The primary challenge lies in identifying data sources and formula calculation methods that both reflect and serve program objectives, with or without adjustments for variations in the cost of delivering services, the availability of local resources, capacity, or performance. Simplicity and transparency are major advantages of formula-based allocations, but these advantages can be offset if formula-based allocations are perceived to under- or over-fund some jurisdictions, which may result from how guaranteed minimum funding levels are set or from "hold-harmless" provisions intended to blunt the effects of changes in formula design or random variations in source data. While fairness is considered an advantage of formula-based allocations, the design of a formula may implicitly reflect unquestioned values concerning equity versus equivalence in setting funding policies. Whether or how past or projected trends are taken into account can also have substantial impacts on allocations. SUMMARY: Insufficient attention has been focused on how the approach to designing funding formulas in public health should differ for treatment or service versus prevention programs. Further evaluations of formula-based versus competitive allocation methods are needed to promote the optimal use of public health funds. In the meantime, those who use formula-based strategies to allocate funds should be familiar with the nuances of this approach

Summary of data reported to CDC's national automated biosurveillance system, 2008

<p>Abstract</p> <p>Background</p> <p>BioSense is the US national automated biosurveillance system. Data regarding chief complaints and diagnoses are automatically pre-processed into 11 broader syndromes (e.g., respiratory) and 78 narrower sub-syndromes (e.g., asthma). The objectives of this report are to present the types of illness and injury that can be studied using these data and the frequency of visits for the syndromes and sub-syndromes in the various data types; this information will facilitate use of the system and comparison with other systems.</p> <p>Methods</p> <p>For each major data source, we summarized information on the facilities, timeliness, patient demographics, and rates of visits for each syndrome and sub-syndrome.</p> <p>Results</p> <p>In 2008, the primary data sources were the 333 US Department of Defense, 770 US Veterans Affairs, and 532 civilian hospital emergency department facilities. Median times from patient visit to record receipt at CDC were 2.2 days, 2.0 days, and 4 hours for these sources respectively. Among sub-syndromes, we summarize mean 2008 visit rates in 45 infectious disease categories, 11 injury categories, 7 chronic disease categories, and 15 other categories.</p> <p>Conclusions</p> <p>We present a systematic summary of data that is automatically available to public health departments for monitoring and responding to emergencies.</p

Approaches to the evaluation of outbreak detection methods

BACKGROUND: An increasing number of methods are being developed for the early detection of infectious disease outbreaks which could be naturally occurring or as a result of bioterrorism; however, no standardised framework for examining the usefulness of various outbreak detection methods exists. To promote comparability between studies, it is essential that standardised methods are developed for the evaluation of outbreak detection methods. METHODS: This analysis aims to review approaches used to evaluate outbreak detection methods and provide a conceptual framework upon which recommendations for standardised evaluation methods can be based. We reviewed the recently published literature for reports which evaluated methods for the detection of infectious disease outbreaks in public health surveillance data. Evaluation methods identified in the recent literature were categorised according to the presence of common features to provide a conceptual basis within which to understand current approaches to evaluation. RESULTS: There was considerable variation in the approaches used for the evaluation of methods for the detection of outbreaks in public health surveillance data, and appeared to be no single approach of choice. Four main approaches were used to evaluate performance, and these were labelled the Descriptive, Derived, Epidemiological and Simulation approaches. Based on the approaches identified, we propose a basic framework for evaluation and recommend the use of multiple approaches to evaluation to enable a comprehensive and contextualised description of outbreak detection performance. CONCLUSION: The varied nature of performance evaluation demonstrated in this review supports the need for further development of evaluation methods to improve comparability between studies. Our findings indicate that no single approach can fulfil all evaluation requirements. We propose that the cornerstone approaches to evaluation identified provide key contributions to support internal and external validity and comparability of study findings, and suggest these be incorporated into future recommendations for performance assessment

Sentinel surveillance system for early outbreak detection in Madagascar

<p>Abstract</p> <p>Background</p> <p>Following the outbreak of chikungunya in the Indian Ocean, the Ministry of Health directed the necessary development of an early outbreak detection system. A disease surveillance team including the Institut Pasteur in Madagascar (IPM) was organized to establish a sentinel syndromic-based surveillance system. The system, which was set up in March 2007, transmits patient data on a daily basis from the various voluntary general practitioners throughout the six provinces of the country to the IPM. We describe the challenges and steps involved in developing a sentinel surveillance system and the well-timed information it provides for improving public health decision-making.</p> <p>Methods</p> <p>Surveillance was based on data collected from sentinel general practitioners (SGP). The SGPs report the sex, age, visit date and time, and symptoms of each new patient weekly, using forms addressed to the management team. However, the system is original in that SGPs also report data at least once a day, from Monday to Friday (number of fever cases, rapid test confirmed malaria, influenza, arboviral syndromes or diarrhoeal disease), by cellular telephone (encrypted message SMS). Information can also be validated by the management team, by mobile phone. This data transmission costs 120 ariary per day, less than US$1 per month.</p> <p>Results</p> <p>In 2008, the sentinel surveillance system included 13 health centers, and identified 5 outbreaks. Of the 218,849 visits to SGPs, 12.2% were related to fever syndromes. Of these 26,669 fever cases, 12.3% were related to Dengue-like fever, 11.1% to Influenza-like illness and 9.7% to malaria cases confirmed by a specific rapid diagnostic test.</p> <p>Conclusion</p> <p>The sentinel surveillance system represents the first nationwide real-time-like surveillance system ever established in Madagascar. Our findings should encourage other African countries to develop their own syndromic surveillance systems.</p> <p>Prompt detection of an outbreak of infectious disease may lead to control measures that limit its impact and help prevent future outbreaks.</p

Beyond traditional surveillance: applying syndromic surveillance to developing settings – opportunities and challenges

<p>Abstract</p> <p>Background</p> <p>All countries need effective disease surveillance systems for early detection of outbreaks. The revised International Health Regulations [IHR], which entered into force for all 194 World Health Organization member states in 2007, have expanded traditional infectious disease notification to include surveillance for public health events of potential international importance, even if the causative agent is not yet known. However, there are no clearly established guidelines for how countries should conduct this surveillance, which types of emerging disease syndromes should be reported, nor any means for enforcement.</p> <p>Discussion</p> <p>The commonly established concept of syndromic surveillance in developed regions encompasses the use of pre-diagnostic information in a near real time fashion for further investigation for public health action. Syndromic surveillance is widely used in North America and Europe, and is typically thought of as a highly complex, technology driven automated tool for early detection of outbreaks. Nonetheless, low technology applications of syndromic surveillance are being used worldwide to augment traditional surveillance.</p> <p>Summary</p> <p>In this paper, we review examples of these novel applications in the detection of vector-borne diseases, foodborne illness, and sexually transmitted infections. We hope to demonstrate that syndromic surveillance in its basic version is a feasible and effective tool for surveillance in developing countries and may facilitate compliance with the new IHR guidelines.</p

Ladies in waiting: the timeliness of first trimester services in New Zealand

<p>Abstract</p> <p>Background</p> <p>Termination of pregnancy (TOP) services are a core service in New Zealand. However, compared to other developed countries, TOP services are accessed significantly later in the first trimester, increasing the risk for complications. The aim of this study is to examine the timeliness of access to first trimester TOP services and establish the length of delay between different points in the care pathway for these services.</p> <p>Methodology</p> <p>Data were collected from all patients attending nine TOP clinics around the country between February and May 2009 (N = 2950). Patient records were audited to determine the timeline between the first point of entry to the health system to the date of termination. In addition, women were invited to fill out a questionnaire to identify personal level factors affecting access to services (N = 1086, response rate = 36.8%).</p> <p>Results</p> <p>Women waited an average of almost 25 days between the date of the first visit with the referring doctor and the date of their termination procedure. There was a delay of 10 days between the first visit with the referring doctor and the date that the appointment for the procedure was booked, and a further 10 days delay between the date the appointment was booked and the first appointment date. Over half of the women in this study had their pregnancy terminated at ten weeks or above.</p> <p>Conclusion</p> <p>Women in New Zealand are subject to a lengthy delay while seeking TOP services. Efforts should be made by TOP clinics as well as referring doctors to reduce the waiting times for this service.</p

Toward unsupervised outbreak detection through visual perception of new patterns

<p>Abstract</p> <p>Background</p> <p>Statistical algorithms are routinely used to detect outbreaks of well-defined syndromes, such as influenza-like illness. These methods cannot be applied to the detection of emerging diseases for which no preexisting information is available.</p> <p>This paper presents a method aimed at facilitating the detection of outbreaks, when there is no a priori knowledge of the clinical presentation of cases.</p> <p>Methods</p> <p>The method uses a visual representation of the symptoms and diseases coded during a patient consultation according to the International Classification of Primary Care 2^ndversion (ICPC-2). The surveillance data are transformed into color-coded cells, ranging from white to red, reflecting the increasing frequency of observed signs. They are placed in a graphic reference frame mimicking body anatomy. Simple visual observation of color-change patterns over time, concerning a single code or a combination of codes, enables detection in the setting of interest.</p> <p>Results</p> <p>The method is demonstrated through retrospective analyses of two data sets: description of the patients referred to the hospital by their general practitioners (GPs) participating in the French Sentinel Network and description of patients directly consulting at a hospital emergency department (HED).</p> <p>Informative image color-change alert patterns emerged in both cases: the health consequences of the August 2003 heat wave were visualized with GPs' data (but passed unnoticed with conventional surveillance systems), and the flu epidemics, which are routinely detected by standard statistical techniques, were recognized visually with HED data.</p> <p>Conclusion</p> <p>Using human visual pattern-recognition capacities to detect the onset of unexpected health events implies a convenient image representation of epidemiological surveillance and well-trained "epidemiology watchers". Once these two conditions are met, one could imagine that the epidemiology watchers could signal epidemiological alerts, based on "image walls" presenting the local, regional and/or national surveillance patterns, with specialized field epidemiologists assigned to validate the signals detected.</p