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1.
Int J Infect Dis ; 122: 337-344, 2022 Jun 07.
Article in English | MEDLINE | ID: covidwho-1882081

ABSTRACT

OBJECTIVE: Northern Syria faces a large burden of influenza-like illness (ILI) and severe acute respiratory illness (SARI). This study aimed to investigate the trends of Early Warning and Response Network (EWARN) reported ILI and SARI in northern Syria between 2016 and 2021 and the potential impact of SARS-CoV-2. METHODS: We extracted weekly EWARN data on ILI/ SARI and aggregated cases and consultations into 4-week intervals to calculate case positivity. We conducted a seasonal-trend decomposition to assess case trends in the presence of seasonal fluctuations. RESULTS: It was observed that 4-week aggregates of ILI cases (n = 5,942,012), SARI cases (n = 114,939), ILI case positivity, and SARI case positivity exhibited seasonal fluctuations with peaks in the winter months. ILI and SARI cases in individuals aged ≥5 years surpassed those in individuals aged <5 years in late 2019. ILI cases clustered primarily in Aleppo and Idlib, whereas SARI cases clustered in Aleppo, Idlib, Deir Ezzor, and Hassakeh. SARI cases increased sharply in 2021, corresponding with a severe SARS-CoV-2 wave, compared with the steady increase in ILI cases over time. CONCLUSION: Respiratory infections cause widespread morbidity and mortality throughout northern Syria, particularly with the emergence of SARS-CoV-2. Strengthened surveillance and access to testing and treatment are critical to manage outbreaks among conflict-affected populations.

2.
Int J Environ Res Public Health ; 19(8)2022 04 13.
Article in English | MEDLINE | ID: covidwho-1809866

ABSTRACT

Syndromic surveillance involves the near-real-time collection of data from a potential multitude of sources to detect outbreaks of disease or adverse health events earlier than traditional forms of public health surveillance. The purpose of the present study is to elucidate the role of syndromic surveillance during mass gathering scenarios. In the present review, the use of syndromic surveillance for mass gathering scenarios is described, including characteristics such as methodologies of data collection and analysis, degree of preparation and collaboration, and the degree to which prior surveillance infrastructure is utilized. Nineteen publications were included for data extraction. The most common data source for the included syndromic surveillance systems was emergency departments, with first aid stations and event-based clinics also present. Data were often collected using custom reporting forms. While syndromic surveillance can potentially serve as a method of informing public health policy regarding specific mass gatherings based on the profile of syndromes ascertained, the present review does not indicate that this form of surveillance is a reliable method of detecting potentially critical public health events during mass gathering scenarios.


Subject(s)
Sentinel Surveillance , Disease Outbreaks , Emergency Service, Hospital , Population Surveillance , Public Health Surveillance/methods
3.
Euro Surveill ; 27(16)2022 04.
Article in English | MEDLINE | ID: covidwho-1809281

ABSTRACT

BackgroundThe COVID-19 pandemic presented new challenges for the existing respiratory surveillance systems, and adaptations were implemented. Systematic assessment of the syndromic and sentinel surveillance platforms during the pandemic is essential for understanding the value of each platform in the context of an emerging pathogen with rapid global spread.AimWe aimed to evaluate systematically the performance of various respiratory syndromic surveillance platforms and the sentinel surveillance system in Israel from 1 January to 31 December 2020.MethodsWe compared the 2020 syndromic surveillance trends to those of the previous 3 years, using Poisson regression adjusted for overdispersion. To assess the performance of the sentinel clinic system as compared with the national SARS-CoV-2 repository, a cubic spline with 7 knots and 95% confidence intervals were applied to the sentinel network's weekly percentage of positive SARS-CoV-2 cases.ResultsSyndromic surveillance trends changed substantially during 2020, with a statistically significant reduction in the rates of visits to physicians and emergency departments to below previous years' levels. Morbidity patterns of the syndromic surveillance platforms were inconsistent with the progress of the pandemic, while the sentinel surveillance platform was found to reflect the national circulation of SARS-CoV-2 in the population.ConclusionOur findings reveal the robustness of the sentinel clinics platform for the surveillance of the main respiratory viruses during the pandemic and possibly beyond. The robustness of the sentinel clinics platform during 2020 supports its use in locations with insufficient resources for widespread testing of respiratory viruses.


Subject(s)
COVID-19 , SARS-CoV-2 , COVID-19/epidemiology , Humans , Israel/epidemiology , Pandemics , Sentinel Surveillance
4.
5th International Workshop on Health Intelligence, W3PHAI 2021 held in conjection with 35th AAAI Conference on Artificial Intelligence, AAAI 2021 ; 1013:101-111, 2022.
Article in English | Scopus | ID: covidwho-1777636

ABSTRACT

Surveillance of open-source media, such as social media, has become an essential complement to traditional surveillance data for quickly detecting changes in the occurrence of diseases in time and space. We present our method for classifying Tweets into narratives about COVID-19 symptoms to produce a dataset for downstream surveillance applications. A dataset of 10,405 tweets has been manually classified as relevant or not to self-reported symptoms of COVID-19. Five machine learning classification algorithms, with different tokenization methods, were trained on the dataset and tested. The Support vector machine (SVM) algorithm, with a term frequency-inverse document frequency (TF-IDF) 3-4 n-grams on character as the tokenization method, was the classification algorithm with the highest F1-score of 0.70. However, the training dataset showed an imbalanced classification problem. To reduce the bias of the imbalance classes, the crowdsourcing website Mechanical Turk was used to add 133 relevant tweets. This addition improved the F1-score from 0.70 to 0.77. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

5.
Informatics in Medicine Unlocked ; : 100931, 2022.
Article in English | ScienceDirect | ID: covidwho-1757426

ABSTRACT

Introduction Epidemiological data collection is often challenged by low response and, in the case of cohorts, poor long-term compliance, i.e. a high drop-out. For the correct recording of incident or recurring health events, that are subject to recall difficulties, gathering of data during the event and immediate response of the participants is crucial. This is especially true when biosampling that catches a transient biological situation like COVID-19 is involved. In addition, emerging research topics (e.g. pandemics like the current SARS-CoV-2) demand a flexible approach regarding content while allowing for complex and varying study designs. To meet these needs, we developed an eResearch system for prospective monitoring and management of incident health events (PIA). Methods Programming PIA focusses on IT security and data protection as well as aiming for a user-friendly and motivating design e.g. through feedback for study participants. The main building blocks of the infrastructure are identical functionalities in web-based, iOS and Android compatible application to strengthen the user acceptance of the participants. The backend consists of services and databases, which are all containerised using Docker containers. All programming is based on the JavaScript ecosystem as this is widely used and well supported. Results PIA offers complete management of observational epidemiological studies with six different roles: PIA administrator, researcher, participant manager, study nurse, consent manager and participant. Each role has a specific interface, so that different functions e.g. implementation of new questionnaires, administration of biosamples or management of participant contacts can be performed by different personae. PIA can be integrated in the IT system of ongoing studies like the German National Cohort but also used as stand-alone system. The software is open source (AGPL3.0): https://github.com/hzi-braunschweig/pia-system. Discussion Despite the abundance of existing Electronic Data Capture Systems (EDC systems), we developed our own generic tool that combines monitoring and management in order to use it for specific applications e.g. in certain pre-existing epidemiological studies or for syndromic surveillance in the current pandemic. Hence, PIA is continuously adapted to emerging requirements. Currently, systematic feedback from users is collected. We aim to improve the user experience of PIA as well as provide further feedback and additional elements like gamification in the future.

6.
International Optical Design Conference 2021 ; 12078, 2021.
Article in English | Scopus | ID: covidwho-1642786

ABSTRACT

The optical design of a reflective objective system of a thermal camera for a syndromic surveillance system that captures bio-clinical signals, like temperature, directly related to the physical symptoms of the COVID-19 disease through thermal images is presented. The design is based on an off-axis four mirror system that allows for correcting spherical, coma, astigmatism, and field curvature aberrations. The OFOS design works on wavelengths of 7.5 µm - 14 µm, with an f-number less than 5, and a field of view (FOV) greater than 10 degrees. © COPYRIGHT SPIE. Downloading of the is permitted for personal use only.

7.
BMC Public Health ; 21(1): 2307, 2021 12 20.
Article in English | MEDLINE | ID: covidwho-1633730

ABSTRACT

BACKGROUND: Effective syndromic surveillance alongside COVID-19 testing behaviours in the population including in higher risk and hard to reach subgroups is vital to detect re-emergence of COVID-19 transmission in the community. The aim of this paper was to identify the prevalence of acute respiratory infection symptoms and coronavirus testing behaviour among South Australians using data from a population based survey. METHODS: We used cross-sectional data from the 2020 state-wide population level health survey on 6857 respondents aged 18 years and above. Descriptive statistics were used to explore the risk factors and multivariable logistic regression models were used to assess the factors associated with the acute respiratory infection symptoms and coronavirus testing behaviour after adjusting for gender, age, household size, household income, Aboriginal and/or Torres Strait Islander status, SEIFA, Country of birth, number of chronic diseases, wellbeing, psychological distress, and mental health. RESULTS: We found that 19.3% of respondents reported having symptoms of acute respiratory infection and the most commonly reported symptoms were a runny nose (11.2%), coughing (9.9%) and sore throat (6.2%). Fever and cough were reported by 0.8% of participants. Of the symptomatic respondents, 32.6% reported seeking health advice from a nurse, doctor or healthcare provider. Around 18% (n = 130) of symptomatic respondents had sought testing and a further 4.3% (n = 31) reported they intended to get tested. The regression results suggest that older age, larger household size, a higher number of chronic disease, mental health condition, poor wellbeing, and psychological distress were associated with higher odds of ARI symptoms. Higher household income was associated with lower odds of being tested or intending to be tested for coronavirus after adjusting for other explanatory variables. CONCLUSIONS: There were relatively high rates of self-reported acute respiratory infection during a period of very low COVID-19 prevalence and low rate of coronavirus testing among symptomatic respondents. Ongoing monitoring of testing uptake, including in higher-risk groups, and possible interventions to improve testing uptake is key to early detection of disease.


Subject(s)
COVID-19 Testing , COVID-19 , Aged , Australia/epidemiology , Cross-Sectional Studies , Health Surveys , Humans , SARS-CoV-2 , South Australia/epidemiology
8.
Asia Pac J Public Health ; 34(2-3): 191-198, 2022 03.
Article in English | MEDLINE | ID: covidwho-1571671

ABSTRACT

Although multilayered strategies including preventive behaviors should be adopted to mitigate coronavirus disease 2019 (COVID-19) transmission, evidence on the effectiveness of preventive behaviors against COVID-19 remains limited. This Internet-based prospective cohort study collected baseline data in November 2020 and follow-up data in February 2021, during the third wave of the epidemic in Japan. Among the 19 941 included participants, the percentages reporting that they always used a face mask, practiced hand washing/disinfection, gargling, and ensuring proper room ventilation were 85.4%, 36.0%, 51.1%, and 44.6%, respectively. Multiple logistic regression analyses revealed that less frequently practicing hand washing/disinfection (odds ratio [OR] = 1.20), gargling (OR = 1.20), and ensuring proper room ventilation (OR = 1.38) were significantly associated with self-reported COVID-19-like illness (CLI). These results suggest that personal preventive behaviors may be effective in reducing CLI, even when universal masking is practiced.


Subject(s)
COVID-19 , COVID-19/epidemiology , COVID-19/prevention & control , Cohort Studies , Cross-Sectional Studies , Follow-Up Studies , Humans , Japan/epidemiology , Prospective Studies , SARS-CoV-2 , Surveys and Questionnaires
9.
Emerg Infect Dis ; 28(1): 214-218, 2022 Jan.
Article in English | MEDLINE | ID: covidwho-1547205

ABSTRACT

We examined respiratory disease short-term disability claims submitted to the Mexican Social Security Institute during 2020. A total of 1,631,587 claims were submitted by 19.1 million insured workers. Cumulative incidence (8.5%) was 3.6 times higher than that for January 2015‒December-2019. Workers in healthcare, social assistance, self-service, and retail stores were disproportionately affected.


Subject(s)
COVID-19 , SARS-CoV-2 , Humans , Mexico/epidemiology , Private Sector , Workforce
10.
Euro Surveill ; 26(43)2021 10.
Article in English | MEDLINE | ID: covidwho-1533602

ABSTRACT

We report a large-scale outbreak of hand, foot and mouth disease (HFMD) in France. As at 28 September 2021, 3,403 cases have been reported (47% higher than in 2018-19). We prospectively analysed 210 clinical samples; 190 (90.5%) were enterovirus-positive. Most children presented with atypical HFMD. Coxsackievirus (CV)A6 (49.5%; 94/190) was predominant; no enterovirus A71 was detected. Dermatological and neurological complications of HFMD justify prospective syndromic and virological surveillance for early detection of HFMD outbreaks and identification of associated types.


Subject(s)
Enterovirus Infections , Enterovirus , Hand, Foot and Mouth Disease , Child , Disease Outbreaks , Enterovirus Infections/epidemiology , Hand, Foot and Mouth Disease/diagnosis , Hand, Foot and Mouth Disease/epidemiology , Humans , Infant , Prospective Studies
11.
Epidemiol Infect ; 149: e248, 2021 11 09.
Article in English | MEDLINE | ID: covidwho-1506270

ABSTRACT

This study describes the development of a pilot sentinel school absence syndromic surveillance system. Using data from a sample of schools in England the capability of this system to monitor the impact of disease on school absences in school-aged children is shown, using the coronavirus disease 2019 (COVID-19) pandemic period as an example. Data were obtained from an online app service used by schools and parents to report their children absent, including reasons/symptoms relating to absence. For 2019 and 2020, data were aggregated into daily counts of 'total' and 'cough' absence reports. There was a large increase in the number of absence reports in March 2020 compared to March 2019, corresponding to the first wave of the COVID-19 pandemic in England. Absence numbers then fell rapidly and remained low from late March 2020 until August 2020, while lockdown was in place in England. Compared to 2019, there was a large increase in the number of absence reports in September 2020 when schools re-opened in England, although the peak number of absences was smaller than in March 2020. This information can help provide context around the absence levels in schools associated with COVID-19. Also, the system has the potential for further development to monitor the impact of other conditions on school absence, e.g. gastrointestinal infections.


Subject(s)
Absenteeism , COVID-19/epidemiology , Disease Outbreaks/prevention & control , Epidemiological Monitoring , Sentinel Surveillance , Child , Communicable Disease Control , England/epidemiology , Humans , Male , Pandemics , SARS-CoV-2 , Schools , Students/statistics & numerical data
12.
BMC Public Health ; 21(1): 2019, 2021 11 05.
Article in English | MEDLINE | ID: covidwho-1503931

ABSTRACT

BACKGROUND: Since 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. METHODS: This 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. RESULTS: The 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. CONCLUSION: The 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.


Subject(s)
COVID-19 , Pandemics , Emergency Service, Hospital , Humans , Patient Acceptance of Health Care , SARS-CoV-2 , Sentinel Surveillance
13.
Public Health Rep ; 136(1_suppl): 72S-79S, 2021.
Article in English | MEDLINE | ID: covidwho-1495836

ABSTRACT

OBJECTIVE: Traditional public health surveillance of nonfatal opioid overdose relies on emergency department (ED) billing data, which can be delayed substantially. We compared the timeliness of 2 new data sources for rapid drug overdose surveillance-emergency medical services (EMS) and syndromic surveillance-with ED billing data. METHODS: We used data on nonfatal opioid overdoses in Kentucky captured in EMS, syndromic surveillance, and ED billing systems during 2018-2019. We evaluated the time-series relationships between EMS and ED billing data and syndromic surveillance and ED billing data by calculating cross-correlation functions, controlling for influences of autocorrelations. A case example demonstrates the usefulness of EMS and syndromic surveillance data to monitor rapid changes in opioid overdose encounters in Kentucky during the COVID-19 epidemic. RESULTS: EMS and syndromic surveillance data showed moderate-to-strong correlation with ED billing data on a lag of 0 (r = 0.694; 95% CI, 0.579-0.782; t = 9.73; df = 101; P < .001; and r = 0.656; 95% CI, 0.530-0.754; t = 8.73; df = 101; P < .001; respectively) at the week-aggregated level. After the COVID-19 emergency declaration, EMS and syndromic surveillance time series had steep increases in April and May 2020, followed by declines from June through September 2020. The ED billing data were available for analysis 3 months after the end of a calendar quarter but closely followed the trends identified by the EMS and syndromic surveillance data. CONCLUSION: Data from EMS and syndromic surveillance systems can be reliably used to monitor nonfatal opioid overdose trends in Kentucky in near-real time to inform timely public health response.


Subject(s)
Analgesics, Opioid/poisoning , Drug Overdose/epidemiology , Emergency Medical Services/statistics & numerical data , Opioid-Related Disorders/epidemiology , Population Surveillance/methods , Public Health Surveillance/methods , Sentinel Surveillance , Analgesics, Opioid/administration & dosage , COVID-19/epidemiology , Drug Overdose/prevention & control , Emergencies/epidemiology , Emergency Medical Services/trends , Humans , Kentucky/epidemiology , Pandemics , Public Health , SARS-CoV-2
14.
Int J Health Plann Manage ; 37(1): 30-39, 2022 Jan.
Article in English | MEDLINE | ID: covidwho-1469456

ABSTRACT

BACKGROUND: Indonesia faces a continuous threat from communicable disease outbreaks. The current COVID-19 outbreak, the previous one of SARS, and many other infectious outbreaks encountered in the country warn of the need to develop comprehensive early warning systems to enable timely health responses in the long run. In this article, we argue that over the counter medication sales data at community pharmacies in Indonesia can potentially augment and increase the detection power of the current syndromic surveillance system, particularly in dealing with COVID-19 and other future infectious disease outbreaks in the country. MAIN BODY: This article discusses the experience of other countries in employing pharmacy medication sales data to serve as potential syndromic surveillance platform and contribute to pandemic responses. We argue why it is worth considering utilising medication sales data from pharmacies in Indonesia to support the current surveillance system which enables the provision of early warnings of disease outbreaks. We then discuss the potential challenges of operationalising these data and suggest a way forward for the development and implementation of the syndromic surveillance system at community pharmacy settings in Indonesia. CONCLUSION: While there are several challenges in developing a workable system in Indonesia that need to be addressed, introducing a syndromic surveillance system using pharmacy-setting medication sales data is worth investigating in the country.


Subject(s)
COVID-19 , Pharmacies , Pharmacy , Disease Outbreaks , Humans , Indonesia/epidemiology , SARS-CoV-2 , Sentinel Surveillance
15.
Drug Alcohol Depend ; 228: 108977, 2021 11 01.
Article in English | MEDLINE | ID: covidwho-1372960

ABSTRACT

BACKGROUND: Although national syndromic surveillance data reported declines in emergency department (ED) visits after the declaration of the national stay-at-home order for COVID-19, little is known whether these declines were observed for suspected opioid overdose. METHODS: This interrupted time series study used syndromic surveillance data from four states participating in the HEALing Communities Study: Kentucky, Massachusetts, New York, and Ohio. All ED encounters for suspected opioid overdose (n = 48,301) occurring during the first 31 weeks of 2020 were included. We examined the impact of the national public health emergency for COVID-19 (declared on March 14, 2020) on trends in ED encounters for suspected opioid overdose. RESULTS: Three of four states (Massachusetts, New York and Ohio) experienced a statistically significant immediate decline in the rate of ED encounters for suspected opioid overdose (per 100,000) after the nationwide public health emergency declaration (MA: -0.99; 95 % CI: -1.75, -0.24; NY: -0.10; 95 % CI, -0.20, 0.0; OH: -0.33, 95 % CI: -0.58, -0.07). After this date, Ohio and Kentucky experienced a sustained rate of increase for a 13-week period. New York experienced a decrease in the rate of ED encounters for a 10-week period, after which the rate began to increase. In Massachusetts after a significant immediate decline in the rate of ED encounters, there was no significant difference in the rate of change for a 6-week period, followed by an immediate increase in the ED rate to higher than pre-COVID levels. CONCLUSIONS: The heterogeneity in the trends in ED encounters between the four sites show that the national stay-at-home order had a differential impact on opioid overdose ED presentation in each state.


Subject(s)
COVID-19 , Drug Overdose , Opiate Overdose , Analgesics, Opioid , Drug Overdose/epidemiology , Emergency Service, Hospital , Humans , Pandemics , SARS-CoV-2
16.
Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz ; 64(9): 1093-1106, 2021 Sep.
Article in German | MEDLINE | ID: covidwho-1349279

ABSTRACT

The first case of coronavirus SARS-CoV­2 infection in Germany was diagnosed on 27 January 2020. To describe the pandemic course in 2020, we regarded four epidemiologically different periods and used data on COVID-19 cases from the mandatory reporting system as well as hospitalized COVID-19 cases with severe acute respiratory infection from the syndromic hospital surveillance.Period 0 covers weeks 5 to 9 of 2020, where mainly sporadic cases of younger age were observed and few regional outbreaks emerged. In total, 167 cases with mostly mild outcomes were reported. Subsequently, the first COVID-19 wave occurred in period 1 (weeks 10 to 20 of 2020) with a total of 175,013 cases throughout Germany. Increasingly, outbreaks in hospitals and nursing homes were registered. Moreover, elderly cases and severe outcomes were observed more frequently. Period 2 (weeks 21 to 39 of 2020) was an interim period with more mild cases, where many cases were younger and often travel-associated. Additionally, larger trans-regional outbreaks in business settings were reported. Among the 111,790 cases, severe outcomes were less frequent than in period 1. In period 3 (week 40 of 2020 to week 8 of 2021), the second COVID-19 wave started and peaked at the end of 2020. With 2,158,013 reported cases and considerably more severe outcomes in all age groups, the second wave was substantially stronger than the first wave.Irrespective of the different periods, more elderly persons and more men were affected by severe outcomes.


Subject(s)
COVID-19 , Aged , COVID-19/epidemiology , Female , Germany/epidemiology , Humans , Male , Pandemics , Travel
17.
J Clin Med ; 10(15)2021 Jul 21.
Article in English | MEDLINE | ID: covidwho-1325710

ABSTRACT

The objective of this paper is to describe the surveillance system MIDaS and to show how this system has been used for evaluating the consequences of the French COVID-19 lockdown on the bacterial mix of AP-HM and the antibiotic resistance. MIDas is a kind of surveillance activity hub, allowing the automatic construction of surveillance control boards. We investigated the diversity and resistance of bacterial agents from respiratory, blood, and urine samples during the lockdown period (from week 12 to 35 of 2020), using the same period of years from 2017 to 2019 as control. Taking into account the drop in patient recruitment, several species have exhibited significant changes in their relative abundance (either increasing or decreasing) with changes up to 9%. The changes were more important for respiratory and urine samples than for blood samples. The relative abundance in respiratory samples for the whole studied period was higher during the lockdown. A significant increase in the percentage of wild phenotypes during the lockdown was observed for several species. The use of the MIDaS syndromic collection and surveillance system made it possible to efficiently detect, analyze, and follow changes of the microbiological population as during the lockdown period.

18.
BMC Public Health ; 21(1): 1230, 2021 06 26.
Article in English | MEDLINE | ID: covidwho-1282253

ABSTRACT

BACKGROUND: The COVID-19 pandemic has continued to pose a major global public health risk. The importance of public health surveillance systems to monitor the spread and impact of COVID-19 has been well demonstrated. The purpose of this study was to describe the development and effectiveness of a real-time public health syndromic surveillance system (ACES Pandemic Tracker) as an early warning system and to provide situational awareness in response to the COVID-19 pandemic in Ontario, Canada. METHODS: We used hospital admissions data from the Acute Care Enhanced Surveillance (ACES) system to collect data on pre-defined groupings of symptoms (syndromes of interest; SOI) that may be related to COVID-19 from 131 hospitals across Ontario. To evaluate which SOI for suspected COVID-19 admissions were best correlated with laboratory confirmed admissions, laboratory confirmed COVID-19 hospital admissions data were collected from the Ontario Ministry of Health. Correlations and time-series lag analysis between suspected and confirmed COVID-19 hospital admissions were calculated. Data used for analyses covered the period between March 1, 2020 and September 21, 2020. RESULTS: Between March 1, 2020 and September 21, 2020, ACES Pandemic Tracker identified 22,075 suspected COVID-19 hospital admissions (150 per 100,000 population) in Ontario. After correlation analysis, we found laboratory-confirmed hospital admissions for COVID-19 were strongly and significantly correlated with suspected COVID-19 hospital admissions when SOI were included (Spearman's rho = 0.617) and suspected COVID-19 admissions when SOI were excluded (Spearman's rho = 0.867). Weak to moderate significant correlations were found among individual SOI. Laboratory confirmed COVID-19 hospital admissions lagged in reporting by 3 days compared with suspected COVID-19 admissions when SOI were excluded. CONCLUSIONS: Our results demonstrate the utility of a hospital admissions syndromic surveillance system to monitor and identify potential surges in severe COVID-19 infection within the community in a timely manner and provide situational awareness to inform preventive and preparatory health interventions.


Subject(s)
COVID-19 , Pandemics , Hospitals , Humans , Ontario/epidemiology , SARS-CoV-2 , Sentinel Surveillance
19.
Am J Infect Control ; 49(6): 685-689, 2021 06.
Article in English | MEDLINE | ID: covidwho-1279522

ABSTRACT

OBJECTIVES: Since December 2019, COVID-19 has caused a worldwide pandemic and Singapore has seen escalating cases with community spread. Aggressive contact tracing and identification of suspects has helped to identify local community clusters, surveillance being the key to early intervention. Healthcare workers (HCWs) have contracted COVID-19 infection both at the workplace and community. We aimed to create a prototype staff surveillance system for the detection of acute respiratory infection (ARI) clusters amongst our HCWs and describe its effectiveness. METHODS: A prototypical surveillance system was built on existing electronic health record infrastructure. RESULTS: Over a 10-week period, we investigated 10 ARI clusters amongst 7 departments. One of the ARI clusters was later determined to be related to COVID-19 infection. We demonstrate the feasibility of syndromic surveillance to detect ARI clusters during the COVID-19 outbreak. CONCLUSION: The use of syndromic surveillance to detect ARI clusters amongst HCWs in the COVID-19 pandemic may enable early case detection and prevent onward transmission. It could be an important tool in infection prevention within healthcare institutions.


Subject(s)
COVID-19 , Pandemics , Disease Outbreaks , Electronic Health Records , Health Personnel , Humans , SARS-CoV-2 , Sentinel Surveillance , Singapore/epidemiology
20.
J Am Board Fam Med ; 34(3): 481-488, 2021.
Article in English | MEDLINE | ID: covidwho-1259322

ABSTRACT

As was experienced across the country, the COVID-19 pandemic reached Colorado in early spring 2020. Yet, unlike many of the early hotspots in other states, the initial cases in Colorado surfaced in rural areas. It was evident early on it would be a public health crisis unlike anything Colorado had ever faced. There was an urgent need for rapid dissemination of up-to-date information and practice support provided by a multidisciplinary task force of academic health center and state public health experts working collaboratively to meet these needs. This article provides a roadmap for the development of a similar model, a community-connected Extension for Community Health Outcomes (ECHO) program based at an academic medical center and its ability to facilitate the service rapidly and scale to need.


Subject(s)
COVID-19 , Primary Health Care/organization & administration , Public Health Administration , Telemedicine , Colorado/epidemiology , Health Plan Implementation , Humans , Pandemics , Public Health
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