Establishing an ad hoc COVID-19 mortality surveillance during the first epidemic wave in Belgium, 1 March to 21 June 2020.

BackgroundCOVID-19-related mortality in Belgium has drawn attention for two reasons: its high level, and a good completeness in reporting of deaths. An ad hoc surveillance was established to register COVID-19 death numbers in hospitals, long-term care facilities (LTCF) and the community. Belgium adopted broad inclusion criteria for the COVID-19 death notifications, also including possible cases, resulting in a robust correlation between COVID-19 and all-cause mortality.AimTo document and assess the COVID-19 mortality surveillance in Belgium.MethodsWe described the content and data flows of the registration and we assessed the situation as of 21 June 2020, 103 days after the first death attributable to COVID-19 in Belgium. We calculated the participation rate, the notification delay, the percentage of error detected, and the results of additional investigations.ResultsThe participation rate was 100% for hospitals and 83% for nursing homes. Of all deaths, 85% were recorded within 2 calendar days: 11% within the same day, 41% after 1 day and 33% after 2 days, with a quicker notification in hospitals than in LTCF. Corrections of detected errors reduced the death toll by 5%.ConclusionBelgium implemented a rather complete surveillance of COVID-19 mortality, on account of a rapid investment of the hospitals and LTCF. LTCF could build on past experience of previous surveys and surveillance activities. The adoption of an extended definition of 'COVID-19-related deaths' in a context of limited testing capacity has provided timely information about the severity of the epidemic.

Investigating years of life lost in Belgium, 2004-2019: A comprehensive analysis using a probabilistic redistribution approach.

INTRODUCTION: Information on years of life lost (YLL) due to premature mortality is instrumental to assess the fatal impact of disease and necessary for the calculation of Belgian disability-adjusted life years (DALYs). This study presents a novel method to reallocate causes of death data. MATERIALS AND METHODS: Causes of death data are provided by Statistics Belgium (Statbel). First, the specific ICD-10 codes that define the underlying cause of death are mapped to the GBD cause list. Second, ill-defined deaths (IDDs) are redistributed to specific ICD-10 codes. A four-step probabilistic redistribution was developed to fit the Belgian context: redistribution using predefined ICD codes, redistribution using multiple causes of death data, internal redistribution, and redistribution to all causes. Finally, we used the GBD 2019 reference life table to calculate Standard Expected Years of Life Lost (SEYLL). RESULTS: In Belgium, between 2004 and 2019, IDDs increased from 31 to 34% of all deaths. The majority was redistributed using predefined ICD codes (14-15%), followed by the redistribution using multiple causes of death data (10-12%). The total number of SEYLL decreased from 1.83 to 1.73 million per year. In 2019, the top cause of SEYLL was lung cancer with a share of 8.5%, followed by ischemic heart disease (8.1%) and Alzheimer's disease and other dementias (5.7%). All results are available in an online tool https://burden.sciensano.be/shiny/mortality2019/ . CONCLUSION: The redistribution process assigned a specific cause of death to all deaths in Belgium, making it possible to investigate the full mortality burden for the first time. A large number of estimates were produced to estimate SEYLL by age, sex, and region for a large number of causes of death and every year between 2004 and 2019. These estimates are important stepping stones for future investigations on Disability-Adjusted Life Years (DALYs) in Belgium.

COVID-19 cases, hospitalizations and deaths in Belgian nursing homes: results of a surveillance conducted between April and December 2020.

BACKGROUND: In Belgium, the first COVID-19 death was reported on 10 March 2020. Nursing home (NH) residents are particularly vulnerable for COVID-19, making it essential to follow-up the spread of COVID-19 in this setting. This manuscript describes the methodology of surveillance and epidemiology of COVID-19 cases, hospitalizations and deaths in Belgian NHs. METHODS: A COVID-19 surveillance in all Belgian NHs (n = 1542) was set up by the regional health authorities and Sciensano. Aggregated data on possible/confirmed COVID-19 cases and hospitalizations and case-based data on deaths were reported by NHs at least once a week. The study period covered April-December 2020. Weekly incidence/prevalence data were calculated per 1000 residents or staff members. RESULTS: This surveillance has been launched within 14 days after the first COVID-19 death in Belgium. Automatic data cleaning was installed using different validation rules. More than 99% of NHs participated at least once, with a median weekly participation rate of 95%. The cumulative incidence of possible/confirmed COVID-19 cases among residents was 206/1000 in the first wave and 367/1000 in the second wave. Most NHs (82%) reported cases in both waves and 74% registered ≥10 possible/confirmed cases among residents at one point in time. In 51% of NHs, at least 10% of staff was absent due to COVID-19 at one point. Between 11 March 2020 and 3 January 2021, 11,329 COVID-19 deaths among NH residents were reported, comprising 57% of all COVID-19 deaths in Belgium in that period. CONCLUSIONS: This surveillance was crucial in mapping COVID-19 in this vulnerable setting and guiding public health interventions, despite limitations of aggregated data and necessary changes in protocol over time. Belgian NHs were severely hit by COVID-19 with many fatal cases. The measure of not allowing visitors, implemented in the beginning of the pandemic, could not avoid the spread of SARS-CoV-2 in the NHs during the first wave. The virus was probably often introduced by staff. Once the virus was introduced, it was difficult to prevent healthcare-associated outbreaks. Although, in contrast to the first wave, personal protective equipment was available in the second wave, again a high number of cases were reported.