Web-based Surveillance System Research Articles

Knowledge and practices of private healthcare providers regarding tuberculosis case notification in Rural Maharashtra

India carries the highest share of active and missing tuberculosis (TB) cases globally. The Government of India is prioritizing private sector engagement (PSE) in TB elimination activities, as most healthcare-seeking in the country happens in this sector. This study aimed to understand the knowledge and practices of private healthcare providers (PHP) on various aspects of TB case notification through the National TB Elimination Programme (NTEP). This cross-sectional study was carried out between Oct 2020 to April 2021 amongst PHPs in the Junnar Tuberculosis Unit (TU), Pune District, Maharashtra. Junnar Block has 299 PHPs who assess, diagnose, and/or treat TB cases. A total of 97 participants were enrolled in the study. About 89 (91.8%) PHPs are aware that TB case notifications are mandatory by law. However, 80.4% are unaware of the Ni-kshay portal (web-based case surveillance system) by NTEP. Similarly, 74 (76.3%) must be aware of incentives for PHPs to collaborate with the government healthcare delivery system. 82.8% of total Ayurveda, Unani, Naturopathy, Siddha, and Homeopathy (AYUSH) practitioners and 46.2% of Allopathic practitioners have poor knowledge about TB case notification, with a Chi-square value of 14.36 (p<0.01). Our study shows that the active engagement of private providers (PPs), especially AYUSH practitioners in rural areas, is a need of the hour in achieving TB elimination.

Decreased Seasonal Influenza Rates Detected in a Crowdsourced Influenza-Like Illness Surveillance System During the COVID-19 Pandemic: Prospective Cohort Study.

Seasonal respiratory viruses had lower incidence during their 2019-2020 and 2020-2021 seasons, which overlapped with the COVID-19 pandemic. The widespread implementation of precautionary measures to prevent transmission of SARS-CoV-2 has been seen to also mitigate transmission of seasonal influenza. The COVID-19 pandemic also led to changes in care seeking and access. Participatory surveillance systems have historically captured mild illnesses that are often missed by surveillance systems that rely on encounters with a health care provider for detection. This study aimed to assess if a crowdsourced syndromic surveillance system capable of detecting mild influenza-like illness (ILI) also captured the globally observed decrease in ILI in the 2019-2020 and 2020-2021 influenza seasons, concurrent with the COVID-19 pandemic. Flu Near You (FNY) is a web-based participatory syndromic surveillance system that allows participants in the United States to report their health information using a brief weekly survey. Reminder emails are sent to registered FNY participants to report on their symptoms and the symptoms of household members. Guest participants may also report. ILI was defined as fever and sore throat or fever and cough. ILI rates were determined as the number of ILI reports over the total number of reports and assessed for the 2016-2017, 2017-2018, 2018-2019, 2019-2020, and 2020-2021 influenza seasons. Baseline season (2016-2017, 2017-2018, and 2018-2019) rates were compared to the 2019-2020 and 2020-2021 influenza seasons. Self-reported influenza diagnosis and vaccination status were captured and assessed as the total number of reported events over the total number of reports submitted. CIs for all proportions were calculated via a 1-sample test of proportions. ILI was detected in 3.8% (32,239/848,878) of participants in the baseline seasons (2016-2019), 2.58% (7418/287,909) in the 2019-2020 season, and 0.27% (546/201,079) in the 2020-2021 season. Both influenza seasons that overlapped with the COVID-19 pandemic had lower ILI rates than the baseline seasons. ILI decline was observed during the months with widespread implementation of COVID-19 precautions, starting in February 2020. Self-reported influenza diagnoses decreased from early 2020 through the influenza season. Self-reported influenza positivity among ILI cases varied over the observed time period. Self-reported influenza vaccination rates in FNY were high across all observed seasons. A decrease in ILI was detected in the crowdsourced FNY surveillance system during the 2019-2020 and 2020-2021 influenza seasons, mirroring trends observed in other influenza surveillance systems. Specifically, the months within seasons that overlapped with widespread pandemic precautions showed decreases in ILI and confirmed influenza. Concerns persist regarding respiratory pathogens re-emerging with changes to COVID-19 guidelines. Traditional surveillance is subject to changes in health care behaviors. Systems like FNY are uniquely situated to detect disease across disease severity and care seeking, providing key insights during public health emergencies.

MC-YOLO-Based Lightweight Detection Method for Nighttime Vehicle Images in a Semantic Web-Based Video Surveillance System

Semantic web-based video surveillance systems can provide strong decision-making support for managers, and they have high requirements for real-time and precision of vehicle detection models in complex night scenes. To address this issue, a lightweight nighttime vehicle detection method (MC-YOLO) integrating MobileNetV2 and YOLOV3 is proposed. Firstly, in the preprocessing stage, image enhancement is performed on nighttime images to facilitate model feature extraction. Then, the lightweight network MobileNetV2 is used to extract feature by replacing the backbone network DarkNet53 in YOLOv3, thus accelerating the speed of target detection. Finally, after the convolution operation of the backbone network, a convolution block attention module is added to enhance the important feature information and suppress the secondary features, thereby improving the detection precision. The experimental results on the BDD100K dataset show that the proposed MC-YOLO model has a precision of up to 92.75%, which is superior to several other advanced comparative models.

Imported malaria from land bordering countries in China: A challenge in preventing the reestablishment of malaria transmission

ObjectiveNo indigenous malaria cases have been reported since 2017 in China, but a large number of imported cases are still reported every year, including those from the land bordering countries. To characterize their epidemiological profiles will provide evidence for the development of appropriate strategies to effectively address the challenges of border malaria in the post-elimination phase. MethodsIndividual-level data of imported malaria cases from the land bordering countries were collected from 2017 to 2021 in China via the web-based surveillance systems, and analyzed by SPSS, ArcGIS and WPS software, to explore their epidemiological profiles. ResultsA total of 1170 malaria cases imported into China from six of the fourteen land bordering countries were reported between 2017 and 2021 with a decline trend. Overall, cases were widely distributed in 31–97 counties from 11 to 21 provinces but mainly in Yunnan. Moreover, these imported cases were mainly infected with P. vivax (94.8%), and a total of 68 recurrent cases were reported in 6–14 counties from 4 to 8 provinces. In addition, nearly 57.1% of the total reported cases could seek healthcare within 2 days of getting sick, and 71.3% of the reported cases could be confirmed as malaria on the day they sought medical care. ConclusionsChina still needs to attach great importance to the risk and challenge of the imported malaria from bordering countries particularly from Myanmar in preventing reestablishment of malaria transmission in the post-elimination phase. It is necessary not only to strengthen collaboration and cooperation with the bordering countries, but also coordinate multiple departments at home to improve malaria surveillance and response system and prevent the reestablishment of malaria transmission in China.

Overview of web-based public health surveillance system in Uttarakhand: Integrated health information platform under integrated disease surveillance programme

Overview of web-based public health surveillance system in Uttarakhand: Integrated health information platform under integrated disease surveillance programme - IJFCM- Print ISSN No: - 2394-6768 Online ISSN No:- 2394-6776 Article DOI No:- 10.18231/j.ijfcm.2023.001, Indian Journal of Forensic and Community Medicine-Indi

A digital health solution for parasitological surveillance at Anti-Malaria Campaign, Sri Lanka

The Anti Malaria Campaign in Sri Lanka is a public health initiative aimed at preventing and controlling the spread of malaria in the country. The outcome of the malaria control program is improved by effective surveillance. The National Malaria Strategic Plan highlights the lack of a web-based surveillance system for malaria as a weakness in the central-level availability of malaria parasitological surveillance data. DHIS2 (District Health Information Software 2) is a global-good, health management information system recommended by WHO. Creating a malaria information system based on DHIS2 and incorporating an interactive dashboard are employed to enhance the prompt accessibility of data at the national level.

Adverse events of the Pfizer-BioNTech COVID-19 vaccine in Korean children and adolescents aged 5 to 17 years

This study aimed to identify potential safety signals and adverse events following the primary Pfizer-BioNTech coronavirus disease 2019 (COVID-19) vaccination series among children and adolescents aged 5 to 17 years in the Republic of Korea. Adverse events reported through the COVID-19 vaccination management system (CVMS, a web-based passive vaccine safety surveillance system) and adverse events and health conditions collected from a text message-based survey were analyzed. A total of 14,786 adverse events among 5 to 17-year-old children and adolescents were reported in the CVMS; 14,334 (96.9%) were non-serious and 452 (3.1%) were serious, including 125 suspected cases of acute cardiovascular injury and 101 suspected cases of anaphylaxis. The overall reporting rate was lower in 5 to 11-year-old children (64.5 per 100,000 doses) than in 12 to 17-year-old adolescents (300.5 per 100,000 doses). The text message survey identified that local and systemic adverse events after either dose were reported less frequently in 5 to 11-year-old children than in 12 to 17-year-old adolescents (p<0.001). The most commonly reported adverse events were pain at the injection site, myalgia, headache, and fatigue/tiredness. The overall results are consistent with the results of controlled trials; serious adverse events were extremely rare among 5 to 17-year-old children and adolescents following Pfizer-BioNTech COVID-19 vaccination. Adverse events were less frequent in children aged 5 to 11 years than in adolescents aged 12 to 17 years.

Mechanisms of Sports Concussion in Taekwondo: A Systematic Video Analysis of Seven Cases.

Sports-related traumatic brain injuries are the most common injury in adolescents and young adults due to recurrent concussion experiences and head shock. Therefore, this study was designed to describe player characteristics and situational factors associated with concussions in the World Taekwondo Championships using systematic video analysis. Athlete injury data were collected using a web-based injury surveillance system at the World Taekwondo Championships organized by World Taekwondo from 2017 to 2019. Seven video footage were independently analyzed by four analysts using a modified Heads-Up Checklist. Descriptive statistical analysis was used. The incidence of concussion was 3.21 per 1000 games. Most players with concussions were shorter than their opponents, and most concussions were caused by a roundhouse kick on the front of the face. Regarding the acceleration direction of the head after the impact, transverse and multiplane directions were the most common. Most players with a concussion have used a closed stance and did not use blocking techniques during the defense. The rate of concussions caused by penalties was 42.9%. Based on our findings, no other injury mechanisms, except for direct blows to the head, were observed. Therefore, education on the risk and symptoms of concussion, the appropriate management and blocking techniques should be emphasized in TKD-S to reduce incidence of concussion.

Evaluasi Sistem Kewaspadaan Dini dan Respon Penyakit (SKDR) Provinsi Daerah Istimewa Yogyakarta tahun 2022

Indonesia is a country with high population movements as well as urbanization, this causes new emerging and re-emerging diseases such as malaria, diarrhea, cholera, diphtheria, anthrax, rabies, measles, pertussis, and Covid 19. Which can cause infectious diseases and outbreaks. The Early Warning and Response System (EWARS) is a web-based syndrome surveillance system used to detect any abnormal phenomenon that will trigger prompt public health intervention. This study aims to describe performance of the reporting system and management of EWARS implementation in the Province of Yogyakarta in 2022. This research was descriptive qualitative research by using evaluating approach. Qualitative descriptive research design using an evaluation approach. The informant selection technique was carried out using purposive sampling technique through in-depth interviews, observation and document review related to the research topic. The data analysis was content analysis. Validity test used was sources triangulation, methods and data. The results showed that Province of Yogyakarta had a timeliness of reports was 96.32%, completeness of reports was 99.43%, and 100% alerts responded. Meanwhile most of the data on the number of diseases in the EWARS did not match the report manual reports. EWARS has been carried out well in Province of Yogyakarta which can be seen from Timeliness, completeness, and alert responded, but needs to be improved in terms of data validation on the number of disease reports.

Strengthening the Surveillance of Antimicrobial Resistance in India Using Integrative Technologies.

Background:The antimicrobial resistance (AMR) situation in India is alarming. In the absence of newer antibiotics, the best possible approach is to efficiently use the existing antimicrobials through surveillance of resistance. The data generated by AMR surveillance across the country has immense potential to drive policy decisions. However, this data is available in a variety of sources. It is imperative to have tools to integrate the data generated across the country into a single data repository.MethodsAn ensemble of tools (i-AMRSS, i-DIA, and i-AMRIT) have been designed and developed by the data management team at the Indian Council of Medical Research (ICMR) to strengthen surveillance of antimicrobial resistance in India.ResultsThe i-AMRSS is a web-based ICMR's AMR surveillance system, collecting data from tertiary care centers across the country and sending it to the one-stop data repository. The i-DIA is a web-based API that simplifies the AMR data interoperability by seamlessly importing most of the LIS / HIS data from CSV files into a central, one-stop data repository. The i-AMRIT is a standalone ICMR's AMR surveillance system using integrative technologies, collecting data from all the labs across the country and sending the lab-specific cumulative data to the one-stop data repository.DiscussionThe tools are being used in ICMR's AMR Network and have collected over 0.4 million patient records to date. The complete system is presently being used to capture human susceptibility testing data and can be extended for capturing data using the ‘One Health' approach. The authors plan to make the system compliant with FHIR standards to enable interoperability with other countries.

Assessment of electronic surveillance and knowledge, attitudes, and practice (KAP) survey toward imported malaria surveillance system acceptance in France.

ObjectiveAn electronic surveillance system was released to monitor morbidity and mortality incidence of imported malaria cases, investigate autochthonous cases, and assess chemosensitivity of Plasmodium isolates among travelers to and from endemic areas. The aim of this study is to evaluate the use of an electronic surveillance system for imported malaria in France.Materials and MethodsThree main indicators were used to assess the online malaria web-based surveillance system: (1) the quality of the surveillance system; (2) the capacity of the online system to early warning in case of particular events of public health; (3) the knowledge, attitude, and practice of online electronic system by practitioners of malaria network in France.ResultsOverall, the median time onset a case is reported to the system decrease by 99%, ranging from 227 days (144–309) to 2 days (1–6) in 2006 and 2020, respectively.ConclusionThe online malaria surveillance system in France has demonstrated its effectiveness and can therefore be extended to carry out numerous investigations linked to research on malaria.

COVID-19 Surveiller: toward a robust and effective pandemic surveillance system basedon social media mining.

The outbreak of the novel coronavirus, COVID-19, has become one of the most severe pandemics in human history. In this paper, we propose to leverage social media users as social sensors to simultaneously predict the pandemic trends and suggest potential risk factors for public health experts to understand spread situations and recommend proper interventions. More precisely, we develop novel deep learning models to recognize important entities and their relations over time, thereby establishing dynamic heterogeneous graphs to describe the observations of social media users. A dynamic graph neural network model can then forecast the trends (e.g. newly diagnosed cases and death rates) and identify high-risk events from social media. Based on the proposed computational method, we also develop a web-based system for domain experts without any computer science background to easily interact with. We conduct extensive experiments on large-scale datasets of COVID-19 related tweets provided by Twitter, which show that our method can precisely predict the new cases and death rates. We also demonstrate the robustness of our web-based pandemic surveillance system and its ability to retrieve essential knowledge and derive accurate predictions across a variety of circumstances. Our system is also available at http://scaiweb.cs.ucla.edu/covidsurveiller/.This article is part of the theme issue ‘Data science approachs to infectious disease surveillance’.

SARS-CoV-2 Seroprevalence in Florida Department of Health in Palm Beach County Obstetric Clinics: A Cross-Sectional Study during the First Pandemic Surge.

Estimating severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) seroprevalence is an important part of the public health approach to coronavirus disease 2019 (COVID-19) understanding and containment. This is particularly relevant to an obstetric population because of implications in the management of the pregnant host, care of the newborn, and disease progression within the community. A cross-sectional seroprevalence study was performed in four Department of Health Palm Beach County clinics from June 29, 2020, to August 5, 2020. Samples were collected from asymptomatic antepartum and postpartum participants. A web-based surveillance system was used to identify subsequent antibody or polymerase chain reaction (PCR) testing encounters. A total of 163 of 618 subjects were seropositive (26.4%). Racial makeup was white 2.5%, black 19.0%, and Hispanic 78.5%. Positive serology was seen in 16.0, 35.6, and 30.1% of first, second, and third trimesters, respectively; 18.4% were positive postpartum. Only four patients voluntarily reported PCR positivity prior to antibody testing. Six home zip codes accounted for the majority (68.1%) of positive results. Thirty-two patients had repeat serology (65.6% positive and 34.4% negative). Of the 163 subjects, 65 underwent later PCR testing with 92% negative for SAR-CoV-2. Almost one in four subjects had serologic evidence of previous SARS-CoV-2 infection. These very high seroprevalence rates have not been previously reported and highlight the concern for health disparities in the United States. Most were asymptomatic and without a history for SARS-CoV-2 exposure. There was a loss of seropositivity in a significant number of subjects, raising concern for risk of reinfection, inadequate transplacental antibody transfer, and subsequent limited passive protection to the newborn. These seroprevalence data will also allow for better newborn follow-up of unanticipated consequences of COVID-19 infection in pregnancy. · SAR-CoV-2 seroprevalence is disproportionately high in this obstetric population. · The majority of subjects who tested positive for SAR-CoV-2 were asymptomatic for COVID-19 infection. · Estimating seroprevalence is an important public health approach to disease surveillance and understanding.

Web-based epidemiological surveillance systems and applications to coffee rust disease

El avance de la tecnología digital ha permitido concebir Sistemas de Vigilancia Epidemiológicos (SVE) automatizados con un enfoque &lt;em&gt;holístico-sistémico&lt;/em&gt; favoreciendo la planeación, operación, gestión y procesamiento de datos fitosanitarios de manera efectiva y oportuna para toma de decisiones en la prevención y manejo regional de plagas. Este tipo de sistemas se enfocan en la salud del cultivo superando la visión reduccionista de plaga en la vigilancia normativa convencional. Un SVE web implica la definición clara del marco regional, objetivos, plaga(s) en su amplia acepción, recursos humanos/financieros, contexto normativo, líneas de investigación de soporte, estructura operativa y modelos de innovación. Estos elementos determinan la precisión, frecuencia y tipo de muestreo y monitoreo, así como las variables de medición relativas a un novel&lt;em&gt; sistema epidemiológico&lt;/em&gt;. A diferencia de la vigilancia normativa, un SVE web &lt;em&gt;holístico-sistémico&lt;/em&gt; tiene capacidad descriptiva y de pronóstico de riesgos, incluyendo alertas tempranas a partir de análisis espaciales y temporales. La interfaz web SVE asegura la generación flexible y dinámica de reportes y/o análisis automatizados. Un SVE operado en plataformas web, con énfasis en lenguajes de programación y herramientas de uso libre puede ser alojado en servidores genéricos o dedicados para almacenamiento de metadatos configurados con tecnologías Linux/Apache y funcionalidad 24/7 (h día-1). Programas de uso libre incluyen MySQL/MariaDB y otros como gestores de bases de datos; PHP / Node.js, y JavaScript, Ajax, HTML5 y CSS, como tecnologías web de maquetado base ‘back-end’ y ‘front-end’, respectivamente. Esta revisión se enfoca en principios, atributos conceptuales, enfoques metodológicos generales y objetivos de SVE base web. Aplicaciones generales se ilustran con un SVE desarrollado en México para el cafeto (&lt;em&gt;Coffea&lt;/em&gt; spp.), el cual permitió operar la vigilancia de 19 plagas, nueve con estatus cuarentenario, mediante la generación, gestión y análisis de 87.4 y 15.7 millones de registros climáticos y epidemiológicos, respectivamente, obtenidos entre 2013-2019.

Geographic Associations Between Social Factors and SARS-CoV-2 Testing Early in the COVID-19 Pandemic, February-June 2020, Massachusetts.

Widespread SARS-CoV-2 testing is critical to identify infected people and implement public health action to interrupt transmission. With SARS-CoV-2 testing supplies and laboratory capacity now widely available in the United States, understanding the spatial heterogeneity of associations between social determinants and the use of SARS-CoV-2 testing is essential to improve testing availability in populations disproportionately affected by SARS-CoV-2. We assessed positive and negative results of SARS-CoV-2 molecular tests conducted from February 1 through June 17, 2020, from the Massachusetts Virtual Epidemiologic Network, an integrated web-based surveillance and case management system in Massachusetts. Using geographically weighted regression and Moran's I spatial autocorrelation tests, we quantified the associations between SARS-CoV-2 testing rates and 11 metrics of the Social Vulnerability Index in all 351 towns in Massachusetts. Median SARS-CoV-2 testing rates decreased with increasing percentages of residents with limited English proficiency (median relative risk [interquartile range] = 0.96 [0.95-0.99]), residents aged ≥65 (0.97 [0.87-0.98]), residents without health insurance (0.96 [0.95-1.04], and people residing in crowded housing conditions (0.89 [0.80-0.94]). These associations differed spatially across Massachusetts, and localized models improved the explainable variation in SARS-CoV-2 testing rates by 8% to 12%. Indicators of social vulnerability are associated with variations in SARS-CoV-2 testing rates. Accounting for the spatial heterogeneity in these associations may improve the ability to explain and address the SARS-CoV-2 pandemic at substate levels.

The National Interscholastic Cycling Association Mountain Biking Injury Surveillance System: 40,000 Student-Athlete-Years of Data.

A web-based injury surveillance system was implemented through a collaboration between University of Utah researchers and the National Interscholastic Cycling Association (NICA) to better understand injury characteristics in mountain biking. Data were collected from NICA leagues during the 2018 and 2019 seasons. Injuries were tracked in 41,327 student-athlete-years, identifying 1750 unique injuries during 1155 injury events. Rider-dependent and rider-independent variables were analyzed. The most commonly reported injuries were concussion (23.6%), injuries to the wrist/hand (22.3%), and shoulder (15.6%). Half of all injury events occurred on downhills. Men and women reported similar yet significantly different injury rates (2.69% and 3.21%, respectively; P = 0.009). Women sustained more lower-limb injuries (37.8% vs 28.3%; P = 0.003). Nearly 50% of crashes resulted in an emergency room visit. Youth mountain bike racing is a rapidly growing sport. Acute traumatic injuries are common. Injury surveillance system data are now being used to inform injury prevention strategies and direct future research.

Sports Injuries and Illnesses After Implementation of the Web-Based Surveillance System in World Taekwondo.

Taekwondo epidemiology studies have been in short supply since the rule changes introduced by World Taekwondo in 2017. To describe injury and illness patterns at the 2017 World Taekwondo Championships (WTC) in Muju, South Korea, after the implementation of the web-based surveillance system by World Taekwondo. Prospective cohort study. All injuries and illnesses were recorded during the 2017 WTC using a web-based system developed by the International Olympic Committee. A total of 971 athletes who participated in the 2017 WTC. Profiles and mechanisms of injury and illness in the 2017 WTC. We analyzed a total of 131 injuries and 26 illnesses, corresponding to an overall clinical incidence of 13.5 (95% CI = 11.2, 15.8) injuries and 2.7 (95% CI = 1.6 3.7) illnesses per 100 athletes and an overall incidence rate of 19.3 (95% CI = 16.0, 22.6) injuries and 3.8 (95% CI = 2.4, 5.3) illnesses per 1000 athlete-days. Most injuries occurred in the lower extremities (n = 61, 46.6%), and knee injuries were most frequent (n = 26, 19.8%). Among head and trunk injuries (n = 39, 29.8%), face injuries (n = 32, 24.4%) were most common, whereas among upper extremity injuries (n = 31, 23.7%), finger injuries (n = 8, 6.1%) were seen most often. Contusions (n = 44, 33.6%) were the most frequent injury type, followed by fractures and ligamentous ruptures or sprains. The most common injury mechanism was contact with another athlete (n = 97, 74.0%), whereas the least common was concussion (n = 5). The major affected system was the respiratory system (n = 11, 42.3%), with major symptoms being pain (n = 11, 42.3%) and fever (n = 7, 26.9%). Environmental factors were the most typical cause of illness (n = 15, 57.7%). The web-based surveillance system used at the 2017 WTC revealed that 13.5 per 100 athletes (77.8/1000 athlete-exposures, 13.9/1000 minute-exposures) had new or recurrent injuries, whereas 2.7 per 100 athletes became ill.

Development of an injury surveillance system (ISS) in judo

Judo is a popular combat sport with a high risk of injury. To date, information on injuries in non-competitive and amateur judo is sparse. Injuries in Swiss judo have not been recorded systematically. The objective of this project was to develop an injury surveillance system for judo. Such a system not only provides a possibility for the systematic monitoring of injuries, but also allows for the planning and assessing of strategies for injury prevention. A survey was conducted to obtain an overview of injuries sustained in Swiss judo. The results served as a basis to develop and implement a database with a web interface, which is called injury surveillance system. Several judo athletes tested the new system in a trial. Amateur judokas provided 34.2 % of the answers of the survey. Upper extremity injuries, especially of the shoulder, were most frequently reported, followed by lower extremity injuries, particularly of the knee. In due consideration of the results and experiences gained from the survey, the SJISS (Swiss Judo Injury Surveillance System) was established. SJISS is a web-based injury surveillance system designed for Swiss judo. This is the first system developed to provide an ongoing and systematic recording of injuries in Swiss judo. The system allows for injury monitoring and may serve as a starting point for developing and evaluating injury prevention programmes.

Risk factors associated with the incidence of self-reported COVID-19-like illness: data from a web-based syndromic surveillance system in the Netherlands.

During the first wave of the severe acute respiratory syndrome-coronavirus-2 epidemic in the Netherlands, notifications consisted mostly of patients with relatively severe disease. To enable real-time monitoring of the incidence of mild coronavirus disease 2019 (COVID-19) - for which medical consultation might not be required - the Infectieradar web-based syndromic surveillance system was launched in mid-March 2020. Our aim was to quantify associations between Infectieradar participant characteristics and the incidence of self-reported COVID-19-like illness. Recruitment for this cohort study was via a web announcement. After registering, participants completed weekly questionnaires, reporting the occurrence of a set of symptoms. The incidence rate of COVID-19-like illness was estimated and multivariable Poisson regression used to estimate the relative risks associated with sociodemographic variables, lifestyle factors and pre-existing medical conditions. Between 17 March and 24 May 2020, 25 663 active participants were identified, who reported 7060 episodes of COVID-19-like illness over 131 404 person-weeks of follow-up. The incidence rate declined over the analysis period, consistent with the decline in notified cases. Male sex, age 65+ years and higher education were associated with a significantly lower COVID-19-like illness incidence rate (adjusted rate ratios (RRs) of 0.80 (95% CI 0.76-0.84), 0.77 (0.70-0.85), 0.84 (0.80-0.88), respectively) and the baseline characteristics ever-smoker, asthma, allergies, diabetes, chronic lung disease, cardiovascular disease and children in the household were associated with a higher incidence (RRs of 1.11 (1.04-1.19) to 1.69 (1.50-1.90)). Web-based syndromic surveillance has proven useful for monitoring the temporal trends in, and risk factors associated with, the incidence of mild disease. Increased relative risks observed for several patient factors could reflect a combination of exposure risk, susceptibility to infection and propensity to report symptoms.

Web-based surveillance system for the trends, risks and preventions of hospital-acquired multidrug resistant organisms (MDRO) infections

Background: Infections caused by multidrug-resistant organisms (MDRO) are associated with high mortality, morbidities and unexpected additional healthcare cost. The emergence of MDRO has become a major global concern as they have compromised our ability to treat infectious diseases. Infection which appear in a patient under medical care in the hospital or other healthcare facility which was absent at the time of admission was defined as hospital acquired infection (HAI). It is the most frequent adverse event in healthcare delivery worldwide, including Malaysia. Using the advancement of information technology, a data analytic system is proposed and developed to monitor epidemiological trends and the spread of MDRO in healthcare settings. Methods and materials: An evidence-based algorithm was used to combine and analyse a variety of structured and unstructured data from the molecular, patients and environmental/practice databases. PFGE were performed to determine the clonal relatedness by using the standard protocol from PulseNet. The banding patterns of PFGE were fragmentised and converted into numerical form. Data retrieved from both patients and hospital environment were inserted into the system and used for risk factor identification as well as infection control decision making. After the analysis, patients’ outcome was matched and a model of transmission pathway was generated to predict the infection risks among patients. Results: Each PFGE banding patterns were converted into numerical data and served as an input data for the specific profile classification. These input data was integrated into a graph for the development comprehensive pathogen transmission features, which were designed based on the linkage and relationship between patient and environmental culture's specific numerical profile; thus, the transmission route could be successfully identified. Conclusion: The system has successfully identified a few episodes of pathogen distribution and transmission. It is expected to be potentially useful and crucial for clinician and infection control unit in clinical settings, especially in terms of real-time surveillance of pathogens dissemination.