Implementation of Syndromic Surveillance Systems in Two Rural Villages in Senegal.
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SUBMITTER: Abat C
PROVIDER: S-EPMC5167408 | biostudies-literature | 2016 Dec
REPOSITORIES: biostudies-literature
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Implementation of Syndromic Surveillance Systems in Two Rural Villages in Senegal.
Abat Cédric C Colson Philippe P Chaudet Hervé H Rolain Jean-Marc JM Bassene Hubert H Diallo Aldiouma A Mediannikov Oleg O Fenollar Florence F Raoult Didier D Sokhna Cheikh C
PLoS neglected tropical diseases 20161207 12
Infectious diseases still represent a major challenge for humanity. In this context, their surveillance is critical. From 2010 to 2016, two Point-Of-Care (POC) laboratories have been successfully implemented in the rural Saloum region of Senegal. In parallel, a homemade syndromic surveillance system called EPIMIC was implemented to monitor infectious diseases using data produced by the POC laboratory of the Timone hospital in Marseille, France. The aim of this study is to describe the steps nece ...[more]
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Project description:BackgroundSyndromic surveillance provides public health intelligence to aid in early warning and monitoring of public health impacts (e.g. seasonal influenza), or reassurance when an impact has not occurred. Using information collected during routine patient care, syndromic surveillance can be based on signs/symptoms/preliminary diagnoses. This approach makes syndromic surveillance much timelier than surveillance requiring laboratory confirmed diagnoses. The provision of healthcare services and patient access to them varies globally. However, emergency departments (EDs) exist worldwide, providing unscheduled urgent care to people in acute need. This provision of care makes ED syndromic surveillance (EDSyS) a potentially valuable tool for public health surveillance internationally. The objective of this study was to identify and describe the key characteristics of EDSyS systems that have been established and used globally.MethodsWe systematically reviewed studies published in peer review journals and presented at International Society of Infectious Disease Surveillance conferences (up to and including 2017) to identify EDSyS systems which have been created and used for public health purposes. Search criteria developed to identify "emergency department" and "syndromic surveillance" were applied to NICE healthcare, Global Health and Scopus databases.ResultsIn total, 559 studies were identified as eligible for inclusion in the review, comprising 136 journal articles and 423 conference abstracts/papers. From these studies we identified 115 EDSyS systems in 15 different countries/territories across North America, Europe, Asia and Australasia. Systems ranged from local surveillance based on a single ED, to comprehensive national systems. National EDSyS systems were identified in 8 countries/territories: 2 reported inclusion of ≥85% of ED visits nationally (France and Taiwan).ConclusionsEDSyS provides a valuable tool for the identification and monitoring of trends in severe illness. Technological advances, particularly in the emergency care patient record, have enabled the evolution of EDSyS over time. EDSyS reporting has become closer to 'real-time', with automated, secure electronic extraction and analysis possible on a daily, or more frequent basis. The dissemination of methods employed and evidence of successful application to public health practice should be encouraged to support learning from best practice, enabling future improvement, harmonisation and collaboration between systems in future.Prospero numberCRD42017069150 .
| S-EPMC7724621 | biostudies-literature
Project description:ContextHealthcare Electronic Syndromic Surveillance (ESS) is the systematic collection, analysis and interpretation of ongoing clinical data with subsequent dissemination of results, which aid clinical decision-making.ObjectiveTo evaluate, classify and analyze the diagnostic performance, strengths and limitations of existing acute care ESS systems.Data sourcesAll available to us studies in Ovid MEDLINE, Ovid EMBASE, CINAHL and Scopus databases, from as early as January 1972 through the first week of September 2012.Study selectionProspective and retrospective trials, examining the diagnostic performance of inpatient ESS and providing objective diagnostic data including sensitivity, specificity, positive and negative predictive values.Data extractionTwo independent reviewers extracted diagnostic performance data on ESS systems, including clinical area, number of decision points, sensitivity and specificity. Positive and negative likelihood ratios were calculated for each healthcare ESS system. A likelihood matrix summarizing the various ESS systems performance was created.ResultsThe described search strategy yielded 1639 articles. Of these, 1497 were excluded on abstract information. After full text review, abstraction and arbitration with a third reviewer, 33 studies met inclusion criteria, reporting 102,611 ESS decision points. The yielded I2 was high (98.8%), precluding meta-analysis. Performance was variable, with sensitivities ranging from 21% -100% and specificities ranging from 5%-100%.ConclusionsThere is significant heterogeneity in the diagnostic performance of the available ESS implements in acute care, stemming from the wide spectrum of different clinical entities and ESS systems. Based on the results, we introduce a conceptual framework using a likelihood ratio matrix for evaluation and meaningful application of future, frontline clinical decision support systems.
| S-EPMC3716308 | biostudies-literature
Project description:BackgroundSyndromic surveillance has been widely adopted as a real-time monitoring tool for timely response to disease outbreaks. During the second wave of the pH1N1 pandemic in Fall 2009, two major universities in Washington, DC collected data that were potentially indicative of influenza-like illness (ILI) cases in students and staff. In this study, our objectives were three-fold. The primary goal of this study was to characterize the impact of pH1N1 on the campuses as clearly as possible given the data available and their likely biases. In addition, we sought to evaluate the strengths and weaknesses of the data series themselves, in order to inform these two universities and other institutions of higher education (IHEs) about real-time surveillance systems that are likely to provide the most utility in future outbreaks (at least to the extent that it is possible to generalize from this analysis).MethodsWe collected a wide variety of data that covered both student ILI cases reported to medical and non-medical staff, employee absenteeism, and hygiene supply distribution records (from University A only). Communication data were retrieved from university broadcasts, university preparedness websites, and H1N1-related on campus media reports. Regional data based on the Centers for Disease Control and Prevention Outpatient Influenza-like Illness Surveillance Network (CDC ILINet) surveillance network, American College Health Association (ACHA) pandemic influenza surveillance data, and local Google Flu Trends were used as external data sets. We employed a "triangulation" approach for data analysis in which multiple contemporary data sources are compared to identify time patterns that are likely to reflect biases as well as those that are more likely to be indicative of actual infection rates.ResultsMedical personnel observed an early peak at both universities immediately after school began in early September and a second peak in early November; only the second peak corresponded to patterns in the community at large. Self-reported illness to university deans' offices was also relatively increased during mid-term exam weeks. The overall volume of pH1N1-related communication messages similarly peaked twice, corresponding to the two peaks of student ILI cases.ConclusionsDuring the 2009 H1N1 pandemic, both University A and B experienced a peak number of ILI cases at the beginning of the Fall term. This pattern, seen in surveillance systems at these universities and to a lesser extent in data from other IHEs, most likely resulted from students bringing the virus back to campus from their home states coupled with a sudden increase in population density in dormitories and lecture halls. Through comparison of data from different syndromic surveillance data streams, paying attention to the likely biases in each over time, we have determined, at least in the case of the pH1N1 pandemic, that student health center data more accurately depicted disease transmission on campus at both universities during the Fall 2009 pandemic than other available data sources.
| S-EPMC3151236 | biostudies-literature
Project description:BackgroundSince the end of January 2020, the coronavirus (COVID-19) pandemic has been responsible for a global health crisis. In England a number of non-pharmaceutical interventions have been introduced throughout the pandemic, including guidelines on healthcare attendance (for example, promoting remote consultations), increased handwashing and social distancing. These interventions are likely to have impacted the incidence of non-COVID-19 conditions as well as healthcare seeking behaviour. Syndromic Surveillance Systems offer the ability to monitor trends in healthcare usage over time.MethodsThis study describes the indirect impact of COVID-19 on healthcare utilisation using a range of syndromic indicators including eye conditions, mumps, fractures, herpes zoster and cardiac conditions. Data from the syndromic surveillance systems monitored by Public Health England were used to describe the number of contacts with NHS 111, general practitioner (GP) In Hours (GPIH) and Out-of-Hours (GPOOH), Ambulance and Emergency Department (ED) services over comparable periods before and during the pandemic.ResultsThe peak pandemic period in 2020 (weeks 13-20), compared to the same period in 2019, displayed on average a 12% increase in NHS 111 calls, an 11% decrease in GPOOH consultations, and a 49% decrease in ED attendances. In the GP In Hours system, conjunctivitis consultations decreased by 64% and mumps consultations by 31%. There was a 49% reduction in attendance at EDs for fractures, and there was no longer any weekend increase in ED fracture attendances, with similar attendance patterns observed across each day of the week. There was a decrease in the number of ED attendances with diagnoses of myocardial ischaemia.ConclusionThe COVID-19 pandemic drastically impacted healthcare utilisation for non-COVID-19 conditions, due to a combination of a probable decrease in incidence of certain conditions and changes in healthcare seeking behaviour. Syndromic surveillance has a valuable role in describing and understanding these trends.
| S-EPMC8571013 | biostudies-literature
Project description:BACKGROUND:After the introduction of an artemisinin-based combination therapy, the reduction of prevalence of malaria infections has shown a remarkable progress during the last decade. However due to the lack of a consistent malaria control programme and socioeconomic inequalities, Plasmodium infection is still one of the major cause of disease in Equatorial Guinea, namely in the rural communities. This study explored the associated risk factors of malaria transmission at the microeconomic level (households) in two rural villages of mainland Equatorial Guinea. METHODS:This survey involved 232 individuals living in 69 households located in two rural villages, Ngonamanga and Miyobo, of coastal and interior of Equatorial Guinea, respectively. Malaria prevalence was measured by PCR and parasitaemia level by optical microscopy; household socioeconomic status (SES) was measured based on house characteristics using a 2-step cluster analysis. Logistic regression analysis was performed to investigate the relationship of a diverse set of independent variables on being diagnosed with malaria and on showing high levels of parasitaemia. RESULTS:The prevalence of Plasmodium spp. infection was 69%, with 80% of households having at least one parasitaemic member. The majority of houses have eaves (80%), walls of clay/wood (90%) and zinc roof (99%) and only 10% of them have basic sanitation facilities. The studied areas showed reduced rates of indoor residual spraying coverage (9%), and long-lasting insecticide-treated net ownership (35%), with none of these preventive tools showing any significant effects on malaria risk in these areas. Neither the risk of malaria infection (PCR positive result) or the development of high parasitaemia did show association with SES. CONCLUSIONS:This study has contributed to reinforce the importance of living conditions associated to a high risk of malaria infection and vulnerability to develop high parasitaemia. This study also contributes to future malaria control interventions to be implemented in mainland Equatorial Guinea or in other countries with similar environmental conditions.
| S-EPMC5960103 | biostudies-literature
Project description:BackgroundHepatocellular carcinoma (HCC), one of the most fatal types of malignancy, is increasing worldwide, and particularly in Egypt where there is a confluence of its contributing factors, including high prevalence of hepatitis C virus (HCV) infection, widespread use of pesticides, and diets that are contaminated by aflatoxin B1 (AFB1) in rural areas. We investigated knowledge, attitudes, and prevention practices related to HCV infection and pesticides use in rural Egypt, where over half of the population resides and agriculture is the predominant occupation.MethodsFrom two rural villages we recruited 67 residents aged 18-80 years, who completed a 40-item survey that included questions about demographics, knowledge of and protective measures relevant to pesticides use in the home and in agriculture, awareness and perceptions of HCV infection and its treatment and prevention.ResultsAmong the 67 study participants, gender distribution was equal, the mean age was 47.2, and one third never attended school. More than 50% reported using pesticides at home, but fewer reported having some knowledge about its health effects. Twelve participants were agricultural workers, and 11 of them applied pesticides in the field and knew about their toxicity; however only one person was correctly using the appropriate protective equipment. Among all the participants, 52 did not know what causes HCV infection, and 42 of those who knew it was a virus mentioned incorrect modes of transmission; and 30 did not know the disease manifestations.ConclusionIn rural Egypt, there is a significant lack of knowledge of HCV infection and its transmission mode and limited use of protective measures against pesticides despite familiarity with these chemicals.
| S-EPMC4050414 | biostudies-literature
Project description:IntroductionSyndromic 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 methodsWe 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.ResultsWe 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.ConclusionsWe 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.
| S-EPMC4868285 | biostudies-literature
Project description:BackgroundSyndromic surveillance complements traditional public health surveillance by collecting and analysing health indicators in near real time. The rationale of syndromic surveillance is that it may detect health threats faster than traditional surveillance systems permitting more timely, and hence potentially more effective public health action. The effectiveness of syndromic surveillance largely relies on the methods used to detect aberrations. Very few studies have evaluated the performance of syndromic surveillance systems and consequently little is known about the types of events that such systems can and cannot detect.MethodsWe introduce a framework for the evaluation of syndromic surveillance systems that can be used in any setting based upon the use of simulated scenarios. For a range of scenarios this allows the time and probability of detection to be determined and uncertainty is fully incorporated. In addition, we demonstrate how such a framework can model the benefits of increases in the number of centres reporting syndromic data and also determine the minimum size of outbreaks that can or cannot be detected. Here, we demonstrate its utility using simulations of national influenza outbreaks and localised outbreaks of cryptosporidiosis.ResultsInfluenza outbreaks are consistently detected with larger outbreaks being detected in a more timely manner. Small cryptosporidiosis outbreaks (<1000 symptomatic individuals) are unlikely to be detected. We also demonstrate the advantages of having multiple syndromic data streams (e.g. emergency attendance data, telephone helpline data, general practice consultation data) as different streams are able to detect different outbreak types with different efficacy (e.g. emergency attendance data are useful for the detection of pandemic influenza but not for outbreaks of cryptosporidiosis). We also highlight that for any one disease, the utility of data streams may vary geographically, and that the detection ability of syndromic surveillance varies seasonally (e.g. an influenza outbreak starting in July is detected sooner than one starting later in the year). We argue that our framework constitutes a useful tool for public health emergency preparedness in multiple settings.ConclusionsThe proposed framework allows the exhaustive evaluation of any syndromic surveillance system and constitutes a useful tool for emergency preparedness and response.
| S-EPMC5921418 | biostudies-literature
Project description:We visited 1519 villages across 19 Indian states in 2009 to (a) count all health care providers and (b) elicit their quality as measured through tests of medical knowledge. We document three main findings. First, 75% of villages have at least one health care provider and 64% of care is sought in villages with 3 or more providers. Most providers are in the private sector (86%) and, within the private sector, the majority are 'informal providers' without any formal medical training. Our estimates suggest that such informal providers account for 68% of the total provider population in rural India. Second, there is considerable variation in quality across states and formal qualifications are a poor predictor of quality. For instance, the medical knowledge of informal providers in Tamil Nadu and Karnataka is higher than that of fully trained doctors in Bihar and Uttar Pradesh. Surprisingly, the share of informal providers does not decline with socioeconomic status. Instead, their quality, along with the quality of doctors in the private and public sector, increases sharply. Third, India is divided into two nations not just by quality of health care providers, but also by costs: Better performing states provide higher quality at lower per-visit costs, suggesting that they are on a different production possibility frontier. These patterns are consistent with significant variation across states in the availability and quality of medical education. Our results highlight the complex structure of health care markets, the large share of private informal providers, and the substantial variation in the quality and cost of care across and within markets in rural India. Measuring and accounting for this complexity is essential for health care policy in India.
| S-EPMC9188269 | biostudies-literature
Project description:BackgroundInfluenza is a major cause of morbidity and mortality in Africa. However, a lack of epidemiological data remains for this pathology, and the performances of the influenza-like illness (ILI) case definitions used for sentinel surveillance have never been evaluated in Senegal. This study aimed to i) assess the performance of three different ILI case definitions, adopted by the WHO, USA-CDC (CDC) and European-CDC (ECDC) and ii) identify clinical factors associated with a positive diagnosis for Influenza in order to develop an algorithm fitted for the Senegalese context.MethodsAll 657 patients with a febrile pathological episode (FPE) between January 2013 and December 2016 were followed in a cohort study in two rural villages in Senegal, accounting for 1653 FPE observations with nasopharyngeal sampling and influenza virus screening by rRT-PCR. For each FPE, general characteristics and clinical signs presented by patients were collected. Sensitivity, Specificity, Positive Predictive Value (PPV) and Negative Predictive Value (NPV) for the three ILI case definitions were assessed using PCR result as the reference test. Associations between clinical signs and influenza infection were analyzed using logistic regression with generalized estimating equations. Sore throat, arthralgia or myalgia were missing for children under 5 years.ResultsWHO, CDC and ECDC case definitions had similar sensitivity (81.0%; 95%CI: 77.0-85.0) and NPV (91.0%; 95%CI: 89.0-93.1) while the WHO and CDC ILI case definitions had the highest specificity (52.0%; 95%CI: 49.1-54.5) and PPV (32.0%; 95%CI: 30.0-35.0). These performances varied by age groups. In children < 5 years, the significant predictors of influenza virus infection were cough and nasal discharge. In patients from 5 years, cough, nasal discharge, sore throat and asthenia grade 3 best predicted influenza infection. The addition of "nasal discharge" as a symptom to the WHO case definition decreased sensitivity but increased specificity, particularly in the pediatric population.ConclusionIn summary, all three definitions studies (WHO, ECDC & CDC) have similar performance, even by age group. The revised WHO ILI definition could be chosen for surveillance purposes for its simplicity. Symptomatic predictors of influenza virus infection vary according the age group.
| S-EPMC7790019 | biostudies-literature