Syndromic Surveillance System Research Articles

The prevalence and pattern of mask use and its association with COVID-19-related morbidity and mortality in Tabriz, Iran

Background. Using personal protective equipment, including masks, is one of the most important ways to prevent coronavirus disease 2019 (COVID-19). The aim of this study was to estimate the prevalence and pattern of mask use and its association with COVID-19-related morbidity and mortality in different areas of Tabriz, Iran. Methods. In this population-based study, 6,600 pedestrians were selected by multi-stage proportional sampling method in nine areas of Tabriz in 2021. The data was collected using the observation method. For each participant, we recorded gender, approximate age, mask usage, type of mask, and correct or incorrect use. The data of COVID-19-related morbidity and mortality for six months (from 21 March 2021 to 22 September 2021) were obtained from the Integrated Syndromic Surveillance System (ISSS). Results. The overall prevalence of facial mask use was 56.8% (95% CI: 55.56 – 57.95). Out of 3,421 men, 1,599 (46.7%; 95% CI: 45.1-48.4) and out of 3,179 women, 2,147 (67.5%; 95% CI: 65.9-69.2) were used face mask (P<0.001). The correlations between mask use and morbidity (r=0.375, P=0.320) and mortality (r=0.219, P=0.571) rates were not statistically significant. Conclusion. The percentage of using face masks in Tabriz was relatively low, especially among males and young people. Also, there was no significant relationship between COVID-19 morbidity and mortality and mask use. Practical Implications. The results of the present study showed that the percentage of mask use in men and the youth was relatively low. In times of disease epidemics, it is necessary to create the necessary sensitivity in these groups and to carry out the necessary training and interventions to increase the use of masks and protective measures.

Impact of the 7/14/2016 Nice terrorist attack on pediatric emergency department visits thanks to syndromic surveillance: a descriptive study.

Study the impact of 14th July 2016 Nice terrorist attack on Pediatric Emergency Department (PED) visits by youth under 18 years of age. PED visits diagnoses (ICD10) were clustered and analyzed based on retrospective data from the syndromic surveillance system of the Children's university hospital of Nice (Southern France). The studied period ranges from 2013 to 2019, i.e., 3 years before and after the terrorist attack of 14th July 2016. Among 416,191 PED visits, the number of visits for stress in 4-17 years old appeared to increase in the 3 years after the attack compared to the 3 years before, particularly in September 2016 (acute effect) with 11 visits compared to an average of 2.3 visits per month from September 2013 to 2016 (p = 0.001827). In September 2017, we noticed 21 visits compared to an average of 4.8 visits per month during the following period (2013-2019). In 2017, PED visits for stress among 4-17 year olds were higher in comparison to the other years of the study: 107 visits compared to an annual average of 57. To our knowledge, this is the first study of the use of the pediatric care system before and after a terrorist attack involving syndromic surveillance. This suggests acute and long-term effects of the terrorist attack on PED use by youth for mental health issues. Further studies of the pediatric care system involving syndromic surveillance are needed in the context of mass violent events, such as terrorist attacks.

COVID-19 health impact: A use case for syndromic surveillance system monitoring in the Netherlands (Preprint)

COVID-19 health impact: A use case for syndromic surveillance system monitoring in the Netherlands (Preprint)

Emergency Department Syndromic Surveillance to Monitor Tick-Borne Diseases: A 6-Year Small-Area Analysis in Northeastern Italy.

Tick-borne diseases (TBD) are endemic in Europe. However, surveillance is currently incomplete. Alternative strategies need to be considered. The aim of this study was to test an Emergency Department Syndromic Surveillance (EDSyS) system as a complementary data source to describe the impact of tick bites and TBD using a small-area analysis approach and to monitor the risk of TBD to target prevention. ED databases in the Local Health Authority 8 District (Veneto, Italy) were queried for tick-bite and TBD-related visits between January 2017 and December 2022. Hospitalisations were also collected. Events involving the resident population were used to calculate incidence rates. A total of 4187 ED visits for tick-bite and 143 for TBD were recorded; in addition, 62 TBD-related hospitalisations (of which 72.6% in over 50 s and 22.6% in over 65 s). ED visits peaked in spring and in autumn, followed by a 4-week lag in the increase in hospital admissions. The small-area analysis identified two areas at higher risk of bites and TBD. The use of a EDSyS system allowed two natural foci to be identified. This approach proved useful in predicting temporal and geographic risk of TBD and in identifying local endemic areas, thus enabling an effective multidisciplinary prevention strategy.

Recent Advances in the Use of the Mortality Syndromic Surveillance System-New York City, 2015-2020.

New York City's automated mortality syndromic surveillance system monitors temporal and spatial patterns in mortality. To describe the use of the syndromic surveillance system, we used the system to find mortality patterns for the 15 leading causes of death and for deaths from rare and reportable diseases in New York City from February 2015 through June 2020. We used results to find aberrations that indicate threats to public health. We used unobserved components models to analyze time series of mortality counts for leading causes of death, historical limits methods for rare and reportable diseases, and SaTScan for temporal-spatial cluster analysis. We obtained data on the number of deaths from the electronic death registry system maintained by the city's Bureau of Vital Statistics. The mortality syndromic surveillance system detected an increase in the number of deaths from heart disease by April 1, 2020, when 75.0 deaths occurred on March 24, 2020, instead of an expected 45.8 deaths (95% upper prediction limit of 61.0) and an increase in the number of deaths from all causes on March 20, 2020, when 194.0 deaths were observed while 150.1 deaths were expected (95% upper prediction limit of 178.0). The number of deaths from all causes returned to normal the week beginning June 14, 2020, when 990.0 deaths were observed and 998.8 deaths were expected. When compared with efforts from New York City to provide yearly vital statistics, the automated mortality syndromic surveillance system can provide timely mortality data with fewer resources and raise the capacity to detect anomalous increases in mortality.

Comparison of statistical methods for the early detection of disease outbreaks in small population settings

ObjectivesThis study examines the performance of 6 aberration detection algorithms for the early detection of disease outbreaks in small population settings using syndrome-based early warning surveillance data collected by the Pacific Syndromic Surveillance System (PSSS). Although previous studies have proposed statistical methods for detecting aberrations in larger datasets, there is limited knowledge about how these perform in the presence of small numbers of background cases. MethodsTo address this gap a simulation model was developed to test and compare the performance of the 6 algorithms in detecting outbreaks of different magnitudes, durations, and case distributions. ResultsThe study found that while the Early Aberration Reporting System–C1 algorithm developed by Hutwagner et al. outperformed others, no single approach provided reliable monitoring across all outbreak types. Furthermore, aberration detection approaches could only detect very large and acute outbreaks with any reliability. ConclusionThe findings of this study suggest that algorithm-based approaches to outbreak signal detection perform poorly when applied to settings with small numbers of background cases and should not be relied upon in these contexts. This highlights the need for alternative approaches for accurate and timely outbreak detection in small population settings, particularly those that are resource-constrained.

Pregnancy and Emergency Department Utilization in North Carolina, 2016–2021: A Population-Based Surveillance Study

Pregnancy-associated complaints are a common reason for emergency department visits for women of reproductive age. Emergency department utilization during pregnancy is associated with worse birth outcomes for both mothers and infants. We used statewide North Carolina emergency department surveillance data between 2016 and 2021 to describe the sociodemographic factors associated with the use of emergency department for pregnancy-associated problems and subsequent hospital admission. North Carolina Disease Event Tracking and Epidemiologic Collection Tool is a syndromic surveillance system that includes all emergency department encounters at civilian acute-care facilities in North Carolina. We analyzed all emergency department visits between January 1, 2016 and December 31, 2021 for female patients aged 15-44 years residing in North Carolina with at least 1 ICD-10-CM code (analysis occurred in July 2021-October 2022). Each emergency department visit was categorized as pregnancy-associated if assigned ICD-10-CM code(s) indicated pregnancy. We stratified visits by age, race, ethnicity, county of residence, and insurance and compared them with estimated pregnant population proportions using 1-sample t-tests. We used multivariable logistic regression to determine whether pregnancy-associated visits were more likely to be associated with hospital admission and then to determine sociodemographic predictors of admission among pregnancy-associated emergency department visits. More than 6.4 million emergency department visits were included (N=6,471,197); 10.1% (n=655,476) were pregnancy-associated, significantly higher than the proportion of women estimated to be pregnant at any given time in North Carolina (4.6%, p<0.0001) and increased over time (8.6% in 2016 vs 11.1% in 2021, p<0.0001). Pregnancy-associated visits were lower than expected for ages 25-44 years and higher than expected for those aged 15-24 years, for those of Black race, and for patients residing in rural or suburban areas. The proportion admitted was higher for pregnancy-associated emergency department visits than for nonpregnancy associated (15.6% vs 7.0%, AOR=3.06 [95% CI=3.03, 3.09]). Pregnancy-associated emergency department visits for patients of Black race had 0.58 times (95% CI=0.57, 0.59) the odds of admission compared with White patients. Emergency department utilization during pregnancy is common. The proportion of pregnancy-associated emergency department visits among reproductive-age women is increasing, as are inpatient admissions from the emergency department for pregnancy-associated diagnoses. Use of public health surveillance databases such as the North Carolina Disease Event Tracking and Epidemiologic Collection Tool may help identify opportunities for improving disparities in maternal health care, especially related to access to care.

Communicable Disease Surveillance in Lebanon during the Syrian Humanitarian Crisis, 2013-2019.

Lebanon has been one of the most affected countries by the Syrian humanitarian crisis. The national communicable disease surveillance was enhanced to detect outbreaks among Syrians. In this study, we aim to describe the findings of the communicable disease surveillance among Syrians in Lebanon, compare it to residents' data, and describe the implemented surveillance activities between 2013 and 2019. During the study period, data on communicable diseases was mainly collected through the routine national surveillance system and an enhanced syndromic surveillance system. Predefined case definitions and standard operating procedures were in place. Data collection included both case-based and disease-specific reporting forms. Descriptive data and incidence rates were generated. Information was disseminated through weekly reports. Activities were conducted in close collaboration with different partners. The most commonly reported diseases were: viral hepatitis A, cutaneous leishmaniasis, mumps, and measles. Hepatitis A incidence increased in 2013 and 2014 among Syrians as well as residents. For leishmaniasis, the incidence increased only among Syrians in 2013 and decreased after that. An outbreak of mumps was reported among Syrians between 2014 and 2016, with a peak in 2015 concomitant with a national outbreak. Outbreaks of measles were reported among Syrians and residents in 2013, 2018, and 2019. The infrastructure of the well-implemented surveillance system in Lebanon has been utilized to monitor the health status of Syrians in Lebanon, early detect communicable diseases among this population, and guide needed preventive and control measures. This highlights the importance of having a flexible surveillance system that can be adapted to emergencies and the importance of sharing results with involved partners.

New developments and expansion of the GP in-hours syndromic surveillance system: collaboration between UKHSA and the Oxford-Royal College of General Practitioners Clinical Informatics Digital Hub.

The UK Health Security Agency have established a partnership with the Oxford-Royal College of General Practitioners (RCGP) Clinical Informatics Digital Hub (ORCHID) to provide a new source of primary care data to enhance an existing GP in-hours syndromic surveillance system. To provide better coverage of the English population and more comprehensive information to inform public health action. We produced indicators using SNOMED CT codes grouped into syndromes and validated the outputs against the existing GP in-hours data. A daily data feed from the ORCHID system at Oxford to the GP in-hours syndromic surveillance system was established for routine surveillance. Population coverage increased from 6.8 to 18.8 million patients, representative of the English population. More granular data are available at postcode district and lower layer super output level (LSOA), providing better geographical and sociodemographic coverage, and enabling the investigation of social inequalities on conditions diagnosed in primary care. New indicators can be implemented rapidly in response to new public health threats. For decades the RCGP has run sentinel surveillance with integrated virology and now RCGP data are being used for syndromic surveillance. The addition of ORCHID data to the GP in-hours syndromic surveillance system has improved the utility of the system. There is better population coverage, additional syndromic indicators, and greater ability to interrogate the data. The new system will provide enhanced information to support public health in England and highlights the value of GP records for use in protecting the health security of the nation.

Benefits of Using a Transdisciplinary Approach for the Design and Operationalization of a Surveillance System

Abstract During the preparatory phase of a surveillance project in Western Kenya, it was noted that several animal health activities, including meat inspection, were recorded using paper-based forms. Through discussions with the meat inspectors and other slaughterhouse actors, an electronic meat inspection form was developed, tested, and used in two slaughterhouses in Bungoma County. The meat inspectors completed and submitted a form for every animal slaughtered at their facility over a 2.75-year period. In a feedback meeting with the meat inspectors and other stakeholders, areas for improvement were highlighted, such as the timely provision of feedback to the data providers, and the inclusion of data fields that allow for more detailed animal movement information. The meat inspectors remarked that the form made them feel appreciated and added value to their work as the data could be used to educate farmers on prevailing livestock conditions and provide economic incentives for disease control interventions. The data submitted via the electronic forms were of sufficient quality to be summarized and identify trends in the animal slaughterhouse throughput, as well as frequent reasons for meat condemnation and associated costs. These data could therefore set the foundation for a syndromic surveillance system based on slaughterhouse data. Other non-traditional data sources, such as livestock and meat transport certificates, could also be leveraged to create a post-farm animal health information system. Information © The Authors 2023

Development and application syndromic surveillance and early warning system in border area in Yunnan Province

Objective: To establish a dynamic syndromic surveillance system in the border areas of Yunnan Province based on information technology, evaluate its effectiveness and timeliness in the response to common communicable disease epidemics and improve the communicable disease prevention and control in border areas. Methods: Three border counties were selected for full coverage as study areas, and dynamic surveillance for 14 symptoms and 6 syndromes were conducted in medical institutions, the daily collection of information about students' school absence in primary schools and febrile illness in inbound people at border ports were conducted in these counties from January 2016 to February 2018 to establish an early warning system based on mobile phone and computer platform for a field experimental study. Results: With syndromes of rash, influenza-like illness and the numbers of primary school absence, the most common communicable disease events, such as hand foot and mouth disease, influenza and chickenpox, can be identified 1-5 days in advance by using EARS-3C and Kulldorff time-space scanning models with high sensitivity and specificity. The system is easy to use with strong security and feasibility. All the information and the warning alerts are released in the form of interactive charts and visual maps, which can facilitate the timely response. Conclusions: This system is highly effective and easy to operate in the detection of possible outbreaks of common communicable diseases in border areas in real time, so the timely and effective intervention can be conducted to reduce the risk of local and cross-border communicable disease outbreaks. It has practical application value.

Point and Lifetime Prevalence of Sexually Transmitted Diseases Based on the Definitions of the Iranian Syndrome Surveillance System: A Hospital-Based Survey

Background: Sexually transmitted infections (STIs) are among the most common infectious diseases and a globally concerning public health issue, especially in developing countries. Objectives: This study aimed to evaluate the syndrome-based point and lifetime prevalence of sexually transmitted infections in a big Iranian city. Methods: This cross-sectional study was conducted in 2019 on a hospital-based random sample of 2107 people (men and women aged 15 - 50) at Marvdasht Central Hospital (Iran). Results: The lifetime prevalence of Sexually Transmitted Diseases (STDs) was significantly higher in women than in men (81.56% vs. 33.60%, P-value &lt; 0.0001). Also, about 20.7% of men and 48.26% of women had at least one of the STIs-associated syndromes at the time of the interview (instantaneous prevalence) (P-value = 0.001). Conclusions: The estimated prevalence of syndromes associated with sexually transmitted infections is alarmingly high. The results emphasize the need for further studies on effective health care and health promotion services to reduce STIs (including early detection and treatment of infections and public education).

The Association of Acute Watery Diarrhea in Iranian Pilgrims of Iraq with Cholera Cases in Iranians.

Despite the advances in the control of infectious diseases like cholera, they can potentially cause epidemics, especially in mass gathering events. One of the most important countries on the walking way of the Arbaeen religious event is Iran, which requires health system preparedness. The aim of this study was to predict the cholera epidemic in Iran by using the syndromic surveillance system of Iranian pilgrims in Iraq. The data of the Iranian pilgrims with acute watery diarrhea in Iraq during the Arbaeen religious event and the confirmed cholera cases of pilgrims after returning to Iran were analyzed. We used the Poisson regression model of the relationship between the numbers of cases to evaluate acute watery diarrhea and cholera. Spatial statistics and hot spot analysis were used to identify the provinces with the highest incidence. SPSS software Version 24 was used for statistical analysis. The frequency of acute watery diarrhea cases was 2232 and the frequency of cholera in pilgrims after returning to Iran was 641. The results of spatial analysis for acute watery diarrhea cases showed a high number of acute watery diarrhea cases in the Khuzestan and Isfahan provinces, located in hot spots. Using Poisson regression, the relationship between the number of acute watery diarrhea reported in the syndromic surveillance system and the number of cholera cases was confirmed. The syndromic surveillance system is useful to predict the outbreak of infectious diseases in large religious mass gatherings.

Interrupted time series segmented regression analysis for detecting waterborne disease outbreaks by syndromic surveillance.

Pathogens can enter the drinking water supply and cause gastroenteritis outbreaks. Such events can affect many people in a short time, making them a high risk for public health. In Australia, the Victoria State Government Department of Health is deploying a syndromic surveillance system for drinking water contamination events. We assessed the utility of segmented regression models for detecting such events and determined the number of excess presentations needed for such methods to signal a detection. The study involved an interrupted time series study of a past lapse in water treatment. The baseline period comprised the four weeks before the minimum incubation period of suspected pathogens, set at two days post-event. The surveillance period comprised the week after. We used segmented linear regression to compare the count of gastroenteritis presentations to public hospital emergency departments (EDs) between the surveillance and baseline periods. We then simulated events resulting in varying excess presentations. These were superimposed onto the ED data over fifty different dates across 2020. Using the same regression, we calculated the detection probability at p < 0.05 for each outbreak size. In the retrospective analysis, there was strong evidence for an increase in presentations shortly after the event. In the simulations, with no excess presentations (i.e., with the ED data as is) the models signalled 8% probability of detection. The models returned 50% probability of detection with 28 excess presentations and 100% probability of detection with 78 excess presentations. The transient increase in presentations after the event may be attributed to microbiological hazards or increased health-seeking behaviour following the issuing of boil water advisories. The simulations demonstrated the ability for segmented regressions to signal a detection, even without a large excess in presentations. The approach also demonstrated high specificity and should be considered for informing Victoria's syndromic surveillance system.

Syndromic surveillance system during mass gathering of Panchkroshi Yatra festival, Ujjain, Madhya Pradesh, India

BackgroundThe health implications surrounding a mass gathering pose significant challenges to public health officials. The use of syndromic surveillance provides an ideal method for achieving the public health goals and objectives at such events. In the absence of published reports of systematic documentation of public health preparedness in mass gatherings in the local context, we describe the public health preparedness and demonstrate the operational feasibility of a tablet-based participatory syndromic surveillance among pilgrims during the annual ritual circumambulation- Panchkroshi Yatra. MethodsA real-time surveillance system was established from 2017-2019 to capture all the health consultations done at the designated points (medical camps) in the Panchkroshi yatra area of the city Ujjain in Madhya Pradesh. We also surveyed a subset of pilgrims in 2017 to gauge satisfaction with the public health measures such as sanitation, water, safety, food, and cleanliness. ResultsIn 2019, injuries were reported in the highest proportion (16.7%; 794/4744); most numbers of fever cases (10.6%; 598/5600) were reported in 2018, while 2017 saw the highest number of patient presentations of abdominal pain (7.73%; 498/6435). ConclusionPublic health and safety measures were satisfactory except for the need for setting up urinals along the fixed route of the circumambulation. A systematic data collection of selected symptoms among yatris and their surveillance through tablet could be established during the panchkroshi yatra, which can complement the existing surveillance for detecting early warning signals. We recommend the implementation of such tablet-based surveillance during such mass gathering events.

Syndromic surveillance in early detection of outbreaks of infectious diseases

Aim: Motivated by the threat of infectious diseases and bioterrorism, syndromic surveillance systems are being developed and implemented around the world. The aim of the study was to describe the early warning surveillance system in Albania. Methods: Syndromic surveillance is a primary health care-facility- and emergency room (ER)-based syndromic surveillance system aiming at detecting outbreaks and undertaking public health actions. It is based on weekly notifications of nine syndromes by over 1,600 General Practitioners (GPs) in the 36 districts of Albania. Data is aggregated by district epidemiologists (DE) and centralized by the national Institute of Public Health. Results: A syndrome is “a set of symptoms or conditions that occur together and suggest the presence of a certain disease or an increased chance of developing the disease.” In the context of syndromic surveillance, a syndrome is a set of non-specific pre-diagnosis medical and other information that may indicate the release of a bioterrorism agent or natural disease outbreak. Since its inception, syndromic surveillance has mainly focused on early event detection: gathering and analysing data in advance of diagnostic case confirmation to give early warning of a possible outbreak. Conclusion: The system is useful for detecting and responding to natural disease outbreaks such as seasonal and pandemic flu, and thus they have the potential to significantly advance and modernize the practice of public health surveillance.

DiD IT?: a differences-in-differences investigation tool to quantify the impact of local incidents on public health using real-time syndromic surveillance health data.

Syndromic surveillance was originally developed to provide early warning compared to laboratory surveillance, but it is increasing used for real-time situational awareness. When a potential threat to public health is identified, a rapid assessment of its impact is required for public health management. When threats are localised, analysis is more complex as local trends need to be separated from national trends and differences compared to unaffected areas may be due to confounding factors such as deprivation or age distributions. Accounting for confounding factors usually requires an in-depth study, which takes time. Therefore, a tool is required which can provide a rapid estimate of local incidents using syndromic surveillance data.Here, we present 'DiD IT?', a new investigation tool designed to measure the impact of local threats to public health. 'DiD IT?' uses a difference-in-differences statistical approach to account for temporal and spatial confounding and provide a direct estimate of impact due to incidents. Temporal confounding differences are estimated by comparing unaffected locations during and outside of exposure periods. Whilst spatial confounding differences are estimated by comparing unaffected and exposed locations outside of the exposure period. Any remaining differences can be considered to be the direct effect of the local incident.We illustrate the potential utility of the tool through four examples of localised health protection incidents in England. The examples cover a range of data sources including general practitioner (GP) consultations, emergency department (ED) attendances and a telehealth call and online health symptom checker; and different types of incidents including, infectious disease outbreak, mass-gathering, extreme weather and an industrial fire. The examples use the UK Health Security Agency's ongoing real-time syndromic surveillance systems to show how results can be obtained in near real-time.The tool identified 700 additional online difficulty breathing assessments associated with a severe thunderstorm, 53 additional GP consultations during a mumps outbreak, 2-3 telehealth line calls following an industrial fire and that there was no significant increase in ED attendances during the G7 summit in 2021.DiD IT? can provide estimates for the direct impact of localised events in real-time as part of a syndromic surveillance system. Thus, it has the potential for enhancing surveillance and can be used to evaluate the effectiveness of extending national surveillance to a more granular local surveillance.

Understanding the impact of the COVID-19 pandemic response on GI infection surveillance trends in England, January 2020-April 2022.

Stepwise non-pharmaceutical interventions and health system changes implemented as part of the COVID-19 response have had implications on the incidence, diagnosis, and reporting of other communicable diseases. Here, we established the impact of the COVID-19 outbreak response on gastrointestinal (GI) infection trends using routinely collected surveillance data from six national English laboratory, outbreak, and syndromic surveillance systems using key dates of governmental policy to assign phases for comparison between pandemic and historic data. Following decreases across all indicators during the first lockdown (March-May 2020), bacterial and parasitic pathogens associated with foodborne or environmental transmission routes recovered rapidly between June and September 2020, while those associated with travel and/or person-to-person transmission remained lower than expected for 2021. High out-of-season norovirus activity was observed with the easing of lockdown measures between June and October 2021, with this trend reflected in laboratory and outbreak systems and syndromic surveillance indicators. Above expected increases in emergency department (ED) attendances may have reflected changes in health-seeking behaviour and provision. Differential reductions across specific GI pathogens are indicative of the underlying routes of transmission. These results provide further insight into the drivers for transmission, which can help inform control measures for GI infections.

Syndromic surveillance in early detection of outbreaks of infectious diseases

Aim: Motivated by the threat of infectious diseases and bioterrorism, syndromic surveillance systems are being developed and implemented around the world. The aim of the study was to describe the early warning surveillance system in Albania.Methods: Syndromic surveillance is a primary health care-facility- and emergency room (ER)-based syndromic surveillance system aiming at detecting outbreaks and undertaking public health actions. It is based on weekly notifications of nine syndromes by over 1,600 General Practitioners (GPs) in the 36 districts of Albania. Data is aggregated by district epidemiologists (DE) and centralized by the national Institute of Public Health.Results: A syndrome is “a set of symptoms or conditions that occur together and suggest the presence of a certain disease or an increased chance of developing the disease.” In the context of syndromic surveillance, a syndrome is a set of non-specific pre-diagnosis medical and other information that may indicate the release of a bioterrorism agent or natural disease outbreak.Since its inception, syndromic surveillance has mainly focused on early event detection: gathering and analysing data in advance of diagnostic case confirmation to give early warning of a possible outbreak.Conclusion: The system is useful for detecting and responding to natural disease outbreaks such as seasonal and pandemic flu, and thus they have the potential to significantly advance and modernize the practice of public health surveillance.

Longitudinal Participatory Surveillance Highlights Association Between Mask-Wearing and Lower COVID-19 Risk - United States, 2020.

Numerous ecological and laboratory studies suggest face masks are an effective non-pharmaceutical intervention for reducing the spread of coronavirus disease 2019 (COVID-19), but cannot otherwise assess individual-level effects. Using a prospective cohort of individuals enrolled in a participatory, syndromic surveillance tool prior to the first case of COVID-19 in the United States, we present a novel longitudinal assessment of the effectiveness of face masks. Our analysis demonstrates an association between self-reported mask-wearing behavior and lower individual risk of syndromic COVID-19-like illness while adjusting for confounders at the individual level. Our results also highlight the dual utility of participatory syndromic surveillance systems as both disease trend monitors and tools that can aid in understanding the effectiveness of personal protective measures.