Rapid establishment of a national surveillance of COVID-19 hospitalizations in Belgium.
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ABSTRACT: Background
In response to the COVID-19 epidemic, caused by a novel coronavirus, it was of great importance to rapidly collect as much accurate information as possible in order to characterize the public health threat and support the health authorities in its management. Hospital-based surveillance is paramount to monitor the severity of a disease in the population.Methods
Two separate surveillance systems, a Surge Capacity survey and a Clinical survey, were set up to collect complementary data on COVID-19 from Belgium's hospitals. The Surge Capacity survey collects aggregated data to monitor the hospital capacity through occupancy rates of beds and medical devices, and to follow a set of key epidemiological indicators over time. Participation is mandatory and the daily data collection includes prevalence and incidence figures on the number of COVID-19 patients in the hospital. The Clinical survey is strongly recommended by health authorities, focusses on specific patient characteristics and relies on individual patient data provided by the hospitals at admission and discharge.Conclusions
This national double-level hospital surveillance was implemented very rapidly after the first COVID-19 patients were hospitalized and revealed to be crucial to monitor hospital capacity over time and to better understand the disease in terms of risk groups and outcomes. The two approaches are complementary and serve different needs.
SUBMITTER: Van Goethem N
PROVIDER: S-EPMC7673251 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:COVID-19 Health Surveillance FVG
| PRJEB46661 | ENA
Project description:ObjectivesHigh-quality data are crucial for guiding decision-making and practising evidence-based healthcare, especially if previous knowledge is lacking. Nevertheless, data quality frailties have been exposed worldwide during the current COVID-19 pandemic. Focusing on a major Portuguese epidemiological surveillance dataset, our study aims to assess COVID-19 data quality issues and suggest possible solutions.SettingsOn 27 April 2020, the Portuguese Directorate-General of Health (DGS) made available a dataset (DGSApril) for researchers, upon request. On 4 August, an updated dataset (DGSAugust) was also obtained.ParticipantsAll COVID-19-confirmed cases notified through the medical component of National System for Epidemiological Surveillance until end of June.Primary and secondary outcome measuresData completeness and consistency.ResultsDGSAugust has not followed the data format and variables as DGSApril and a significant number of missing data and inconsistencies were found (eg, 4075 cases from the DGSApril were apparently not included in DGSAugust). Several variables also showed a low degree of completeness and/or changed their values from one dataset to another (eg, the variable 'underlying conditions' had more than half of cases showing different information between datasets). There were also significant inconsistencies between the number of cases and deaths due to COVID-19 shown in DGSAugust and by the DGS reports publicly provided daily.ConclusionsImportant quality issues of the Portuguese COVID-19 surveillance datasets were described. These issues can limit surveillance data usability to inform good decisions and perform useful research. Major improvements in surveillance datasets are therefore urgently needed-for example, simplification of data entry processes, constant monitoring of data, and increased training and awareness of healthcare providers-as low data quality may lead to a deficient pandemic control.
| S-EPMC8649880 | biostudies-literature
Project description:IntroductionThe surveillance of human salmonellosis in Belgium is dependent on the referral of human Salmonella isolates to the National Reference Center (NRC). Knowledge of current diagnostic practices and the coverage of the national Salmonella surveillance system are important to correctly interpret surveillance data and trends over time, to estimate the true burden of salmonellosis in Belgium, and to evaluate the appropriateness of implementing whole-genome sequencing (WGS) at this central level.MethodsThe coverage of the NRC was defined as the proportion of all diagnosed human Salmonella cases in Belgium reported to the NRC and was assessed for 2019 via a survey among all licensed Belgian medical laboratories in 2019, and for 2016-2020 via a capture-recapture study using the Sentinel Network of Laboratories (SNL) as the external source. In addition, the survey was used to assess the impact of the implementation of culture-independent diagnostic tests (CIDTs) at the level of peripheral laboratory sites, as a potential threat to national public health surveillance programs.ResultsThe coverage of the NRC surveillance system was estimated to be 83% and 85%, based on the results of the survey and on the two-source capture-recapture study, respectively. Further, the results of the survey indicated a limited use of CIDTs by peripheral laboratories in 2019.ConclusionGiven the high coverage and the limited impact of CIDTs on the referral of isolates, we may conclude that the NRC can confidently monitor the epidemiological situation and identify outbreaks throughout the country. These findings may guide the decision to implement WGS at the level of the NRC and may improve estimates of the true burden of salmonellosis in Belgium.
| S-EPMC8389443 | biostudies-literature
Project description:COVID-19 Health Surveillance FVG-0
| PRJEB46741 | ENA
Project description:Hybrid immunity, acquired through vaccination followed or preceded by a COVID-19 infection, elicits robust antibody augmentation. We hypothesize that maternal hybrid immunity will provide greater infant protection than other forms of COVID-19 immunity in the first 6 months of life. We conducted a case-control study in Israel, enrolling 661 infants up to 6 months of age, hospitalized with COVID-19 (cases) and 59,460 age-matched non-hospitalized infants (controls) between August 24, 2021, and March 15, 2022. Infants were grouped by maternal immunity status at delivery: Naïve (never vaccinated or tested positive, reference group), Hybrid-immunity (vaccinated and tested positive), Natural-immunity (tested positive before or during the study period), Full-vaccination (two-shot regimen plus 1 booster), and Partial-vaccination (less than full three shot regimen). Applying Cox proportional hazards models to estimate the hazard ratios, which was then converted to percent vaccine effectiveness, and using the Naïve group as the reference, maternal hybrid-immunity provided the highest protection (84% [95% CI 75-90]), followed by full-vaccination (66% [95% CI 56-74]), natural-immunity (56% [95% CI 39-68]), and partial-vaccination (29% [95% CI 15-41]). Maternal hybrid-immunity was associated with a reduced risk of infant hospitalization for Covid-19, as compared to natural-immunity, regardless of exposure timing or sequence. These findings emphasize the benefits of vaccinating previously infected individuals during pregnancy to reduce COVID-19 hospitalizations in early infancy.
| S-EPMC10987618 | biostudies-literature
Project description:On February 27, 2020, the Santa Clara County Public Health Department (SCCPHD) identified its first case of coronavirus disease 2019 (COVID-19) associated with probable community transmission (i.e., infection among persons without a known exposure by travel or close contact with a patient with confirmed COVID-19). At the time the investigation began, testing guidance recommended focusing on persons with clinical findings of lower respiratory illness and travel to an affected area or an epidemiologic link to a laboratory-confirmed COVID-19 case, or on persons hospitalized for severe respiratory disease and no alternative diagnosis (1). To rapidly understand the extent of COVID-19 in the community, SCCPHD, the California Department of Public Health (CDPH), and CDC began sentinel surveillance in Santa Clara County. During March 5-14, 2020, four urgent care centers in Santa Clara County participated as sentinel sites. For this investigation, county residents evaluated for respiratory symptoms (e.g., fever, cough, or shortness of breath) who had no known risk for COVID-19 were identified at participating urgent care centers. A convenience sample of specimens that tested negative for influenza virus was tested for SARS-CoV-2 RNA. Among 226 patients who met the inclusion criteria, 23% had positive test results for influenza. Among patients who had negative test results for influenza, 79 specimens were tested for SARS-CoV-2, and 11% had evidence of infection. This sentinel surveillance system helped confirm community transmission of SARS-CoV-2 in Santa Clara County. As a result of these data and an increasing number of cases with no known source of transmission, the county initiated a series of community mitigation strategies. Detection of community transmission is critical for informing response activities, including testing criteria, quarantine guidance, investigation protocols, and community mitigation measures (2). Sentinel surveillance in outpatient settings and emergency departments, implemented together with hospital-based surveillance, mortality surveillance, and serologic surveys, can provide a robust approach to monitor the epidemiology of COVID-19.
| S-EPMC7147906 | biostudies-literature
Project description:BackgroundIn the United States, COVID-19 is a nationally notifiable disease, meaning cases and hospitalizations are reported by states to the Centers for Disease Control and Prevention (CDC). Identifying and reporting every case from every facility in the United States may not be feasible in the long term. Creating sustainable methods for estimating the burden of COVID-19 from established sentinel surveillance systems is becoming more important.ObjectiveWe aimed to provide a method leveraging surveillance data to create a long-term solution to estimate monthly rates of hospitalizations for COVID-19.MethodsWe estimated monthly hospitalization rates for COVID-19 from May 2020 through April 2021 for the 50 states using surveillance data from the COVID-19-Associated Hospitalization Surveillance Network (COVID-NET) and a Bayesian hierarchical model for extrapolation. Hospitalization rates were calculated from patients hospitalized with a lab-confirmed SARS-CoV-2 test during or within 14 days before admission. We created a model for 6 age groups (0-17, 18-49, 50-64, 65-74, 75-84, and ≥85 years) separately. We identified covariates from multiple data sources that varied by age, state, and month and performed covariate selection for each age group based on 2 methods, Least Absolute Shrinkage and Selection Operator (LASSO) and spike and slab selection methods. We validated our method by checking the sensitivity of model estimates to covariate selection and model extrapolation as well as comparing our results to external data.ResultsWe estimated 3,583,100 (90% credible interval [CrI] 3,250,500-3,945,400) hospitalizations for a cumulative incidence of 1093.9 (992.4-1204.6) hospitalizations per 100,000 population with COVID-19 in the United States from May 2020 through April 2021. Cumulative incidence varied from 359 to 1856 per 100,000 between states. The age group with the highest cumulative incidence was those aged ≥85 years (5575.6; 90% CrI 5066.4-6133.7). The monthly hospitalization rate was highest in December (183.7; 90% CrI 154.3-217.4). Our monthly estimates by state showed variations in magnitudes of peak rates, number of peaks, and timing of peaks between states.ConclusionsOur novel approach to estimate hospitalizations for COVID-19 has potential to provide sustainable estimates for monitoring COVID-19 burden as well as a flexible framework leveraging surveillance data.
| S-EPMC9169704 | biostudies-literature
Project description:Purpose: COVID-19 reached Belgium in February and quickly became a major public health challenge. It is of importance to evaluate the actual impact of COVID-19 on patients and staff in Belgian radiotherapy departments (RTDs). This was evaluated through a weekly national survey sent to departments measuring key factors that were affected by the pandemic. Materials and Methods: The Belgian SocieTy for Radiation Oncology (BeSTRO) together with the Belgian College for physicians in Radiation Oncology invited all 26 RTD to participate in a survey that started on March 2nd and was re- submitted weekly for 4 months to assess variations in time. The survey focused on: (1) the COVID-19 status of patients and staff; (2) the management of clinically suspected COVID patients and COVID positive patients; (3) the impact of COVID-19 on RTD activities; (4) its impact in radiotherapy indications and fractionation schemes. Results: Seventy-three percent of 26 RTDs completed the first survey and 57% responded to all weekly surveys. In the RTD staff, 24 members were COVID-positive of whom 67% were RTTs. Over the study period, the number of patients treated dropped by a maximum of 18.8% when compared to March 2nd. In 32.3% of COVID-positive and 54% of COVID suspected patients, treatment was continued without any interruptions. Radiotherapy indications were adapted within the 1st weeks of the survey in 47.4% of RTD, especially for urological and breast tumors. Fractionation schemes were changed in 68.4% of RTD, mainly for urological, breast, gastro-intestinal, and lung tumors. Conclusions: Between March and June 2020, the COVID-19 pandemic resulted in an important decrease in treatment activity in RTD in Belgium (18.8%). The COVID-19 infection status of patients influenced the continuity of the radiotherapy schedule. Changes in indications and fractionation schedules of radiotherapy were rapidly incorporated in the different RTD.
| S-EPMC8017334 | biostudies-literature
Project description:BackgroundDue to the Corona Virus Disease 2019 (COVID-19), the Belgian government set out a range of measures to prevent the spread of the virus. One measure included closing all non-food shops, including vape shops.MethodsA retrospective online questionnaire was used to investigate the impact of closing the vape shops on the vaping and/or smoking behavior of current vapers.ResultsThe sample (n = 202) reached consisted of 70% exclusive vapers, 29% dual users and 1% no-product users. Over half (55%, 112/202) of participants needed to buy e-liquid during the lockdown, with a small majority being able to buy e-liquids - mostly with their usual nicotine concentrations, flavor or brand -, but as much as 39% (44/112) of them ran out of e-liquid. Those buying e-liquid mainly did so by making purchases via foreign online webshops. A similar pattern was observed with respect to purchasing hardware, with about half (47%, 95/202) of participants reporting hardware availability and with a small majority (53%, 107/202) reporting hardware unavailability. Of those indicating that hardware was not available, 38% (41/107) ran out of a properly functioning e-cigarette. A non-trivial minority had to consume e-liquids with another nicotine concentration, flavor or brand than usual. One seventh of exclusive vapers before lockdown relapsed partly or completely to smoking during the lockdown. The main reasons for changing vaping and/or smoking behavior included the unavailability of e-liquid with nicotine, the unavailability of hardware, and stress/worries about COVID-19.ConclusionsThe majority of vapers succeeded in maintaining their vaping behavior as usual, highly likely due to (illegally) buying consumables online. Nevertheless, for a minority the lockdown period resulted in unintended consequences and these vapers relapsed (completely) to smoking. Even during periods of lockdown, smokers and vapers should be able to purchase low(er)-risk alternatives to smoking, for example e-cigarettes.
| S-EPMC8414467 | biostudies-literature
Project description:BackgroundCOVID-19 is associated with cardiac complications.ObjectivesThe purpose of this study was to estimate the prevalence, risk factors, and outcomes associated with acute cardiac events during COVID-19-associated hospitalizations among adults.MethodsDuring January 2021 to November 2021, medical chart abstraction was conducted on a probability sample of adults hospitalized with laboratory-confirmed SARS-CoV-2 infection identified from 99 U.S. counties in 14 U.S. states in the COVID-19-Associated Hospitalization Surveillance Network. We calculated the prevalence of acute cardiac events (identified by International Classification of Diseases-10th Revision-Clinical Modification codes) by history of underlying cardiac disease and examined associated risk factors and disease outcomes.ResultsAmong 8,460 adults, 11.4% (95% CI: 10.1%-12.9%) experienced an acute cardiac event during a COVID-19-associated hospitalization. Prevalence was higher among adults who had underlying cardiac disease (23.4%; 95% CI: 20.7%-26.3%) compared with those who did not (6.2%; 95% CI: 5.1%-7.6%). Acute ischemic heart disease (5.5%; 95% CI: 4.5%-6.5%) and acute heart failure (5.4%; 95% CI: 4.4%-6.6%) were the most prevalent events; 0.3% (95% CI: 0.1%-0.5%) experienced acute myocarditis or pericarditis. Risk factors varied by underlying cardiac disease status. Patients with ≥1 acute cardiac event had greater risk of intensive care unit admission (adjusted risk ratio: 1.9; 95% CI: 1.8-2.1) and in-hospital death (adjusted risk ratio: 1.7; 95% CI: 1.3-2.1) compared with those who did not.ConclusionsAcute cardiac events were common during COVID-19-associated hospitalizations, particularly among patients with underlying cardiac disease, and are associated with severe disease outcomes. Persons at greater risk for experiencing acute cardiac events during COVID-19-associated hospitalizations might benefit from more intensive clinical evaluation and monitoring during hospitalization.
| S-EPMC9901494 | biostudies-literature