Residents in long-term care facilities (LTCF) are a vulnerable population group. Coronavirus disease (COVID-19)-related deaths in LTCF residents represent 30–60% of all COVID-19 deaths in many European countries. This situation demands that countries implement local and national testing, infection prevention and control, and monitoring programmes for COVID-19 in LTCF in order to identify clusters early, decrease the spread within and between facilities and reduce the size and severity of outbreaks.

In white, European children, sunscreen use appears to be associated with development of nevi, probably because it allows longer sun exposures. Wearing clothes may be an effective way to prevent proliferation of nevi. Since a high nevus count is a strong predictor of melanoma, sunscreen use may be involved in melanoma occurrence because it may encourage recreational sun exposure.

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The number and size of melanocytic naevi are the main predictors of cutaneous melanoma. Naevus development per unit of skin surface is greatest during childhood. We assessed the body distribution of naevi 2-4.9 mm and > or = 5 mm in 649 European children aged 6-7 years old from Brussels (Belgium), Bochum (Germany), Lyon (France) and Rome (Italy). The numbers of naevi 2-4.9 mm and naevi > or = 5 mm were strongly correlated, especially on the trunk. For naevi 2-4.9 mm, the highest relative densities were found on the face, back, shoulders and the external surface of the arms. The lowest relative densities were found on the hands, legs, feet and abdomen. The relative density of naevi > or = 5 mm was higher on the trunk than on any other body site. Similar body distributions were observed in both sexes and at each centre. The body site distribution of naevi 2-4.9 mm seemed to parallel the usual sun exposure patterns of young European children. It is suggested that the development of naevi > or = 5 mm might be a marker of the vulnerability of melanocytes to the harmful effects of solar radiation. Vulnerability would be maximal on the back, and would decrease from proximal to distal skin areas, with melanocytes of the hands and feet having the lowest vulnerability. The number of naevi acquired on a specific area of skin would result from the combined effects of local vulnerability to solar radiation and local sun exposure history. The origin of acquired body site differences in the susceptibility of melanocytes to ultraviolet radiation is unknown, although it seems to parallel the body site density of sensory innervation.

Objective. Scrutiny of COVID-19 mortality in Belgium over the period 8 March-9 May 2020 (Weeks 11-19), using number of deaths per million, infection fatality rates, and the relation between COVID-19 mortality and excess death rates. Data. Publicly available COVID-19 mortality (2020); overall mortality (2009-2020) data in Belgium and demographic data on the Belgian population; data on the nursing home population; results of repeated sero-prevalence surveys in March-April 2020. Statistical methods. Reweighing, missing-data handling, rate estimation, visualization. Results. Belgium has virtually no discrepancy between COVID-19 reported mortality (confirmed and possible cases) and excess mortality. There is a sharp excess death peak over the study period; the total number of excess deaths makes April 2020 the deadliest month of April since WWII, with excess deaths far larger than in early 2017 or 2018, even though influenza-induced January 1951 and February 1960 number of excess deaths were similar in magnitude. Using various sero-prevalence estimates, infection fatality rates (IFRs; fraction of deaths among infected cases) are estimated at 0.38-0.73% for males and 0.20-0.39% for females in the non-nursing home population (non-NHP), and at 0.79-1.52% for males and 0.88-1.31% for females in the entire population. Estimates for the NHP range from 38 to 73% for males and over 22 to 37% for females. The IFRs rise from nearly 0% under 45 years, to 4.3% and 13.2% for males in the non-NHP and the general population, respectively, and to 1.5% and 11.1% for females in the non-NHP and general population, respectively. The IFR and number of deaths per million is strongly influenced by extensive reporting and the fact that 66.0% of the deaths concerned NH residents. At 764 (our re-estimation of the figure 735, presented by "Our World in Data"), the number of COVID-19 deaths per million led the international ranking on May 9, 2020, but drops to 262 in the non-NHP. The NHP is very specific: age-related increased risk; highly prevalent comorbidities that, while non-fatal in themselves, exacerbate COVID-19; larger collective households that share inadvertent vectors such as caregivers and favor clustered outbreaks; initial lack of protective equipment, etc. High-quality health care countries have a relatively older but also more frail population [1], which is likely to contribute to this result.

Background The COVID-19 mortality rate in Belgium has been ranked among the highest in the world. To assess the appropriateness of the country’s COVID-19 mortality surveillance, that includes long-term care facilities deaths and deaths in possible cases, the number of COVID-19 deaths was compared with the number of deaths from all-cause mortality. Mortality during the COVID-19 pandemic was also compared with historical mortality rates from the last century including those of the Spanish influenza pandemic. Methods Excess mortality predictions and COVID-19 mortality data were analysed for the period March 10th to June 21st 2020. The number of COVID-19 deaths and the COVID-19 mortality rate per million were calculated for hospitals, nursing homes and other places of death, according to diagnostic status (confirmed/possible infection). To evaluate historical mortality, monthly mortality rates were calculated from January 1900 to June 2020. Results Nine thousand five hundred ninety-one COVID-19 deaths and 39,076 deaths from all-causes were recorded, with a correlation of 94% (Spearman’s rho, p < 0,01). During the period with statistically significant excess mortality (March 20th to April 28th; total excess mortality 64.7%), 7917 excess deaths were observed among the 20,159 deaths from all-causes. In the same period, 7576 COVID-19 deaths were notified, indicating that 96% of the excess mortality were likely attributable to COVID-19. The inclusion of deaths in nursing homes doubled the COVID-19 mortality rate, while adding deaths in possible cases increased it by 27%. Deaths in laboratory-confirmed cases accounted for 69% of total COVID-19-related deaths and 43% of in-hospital deaths. Although the number of deaths was historically high, the monthly mortality rate was lower in April 2020 compared to the major fatal events of the last century. Conclusions Trends in all-cause mortality during the first wave of the epidemic was a key indicator to validate the Belgium’s high COVID-19 mortality figures. A COVID-19 mortality surveillance limited to deaths from hospitalised and selected laboratory-confirmed cases would have underestimated the magnitude of the epidemic. Excess mortality, daily and monthly number of deaths in Belgium were historically high classifying undeniably the first wave of the COVID-19 epidemic as a fatal event.

Background COVID-19 mortality, excess mortality, deaths per million population (DPM), infection fatality ratio (IFR) and case fatality ratio (CFR) are reported and compared for many countries globally. These measures may appear objective, however, they should be interpreted with caution. Aim We examined reported COVID-19-related mortality in Belgium from 9 March 2020 to 28 June 2020, placing it against the background of excess mortality and compared the DPM and IFR between countries and within subgroups. Methods The relation between COVID-19-related mortality and excess mortality was evaluated by comparing COVID-19 mortality and the difference between observed and weekly average predictions of all-cause mortality. DPM were evaluated using demographic data of the Belgian population. The number of infections was estimated by a stochastic compartmental model. The IFR was estimated using a delay distribution between infection and death. Results In the study period, 9,621 COVID-19-related deaths were reported, which is close to the excess mortality estimated using weekly averages (8,985 deaths). This translates to 837 DPM and an IFR of 1.5% in the general population. Both DPM and IFR increase with age and are substantially larger in the nursing home population. Discussion During the first pandemic wave, Belgium had no discrepancy between COVID-19-related mortality and excess mortality. In light of this close agreement, it is useful to consider the DPM and IFR, which are both age, sex, and nursing home population-dependent. Comparison of COVID-19 mortality between countries should rather be based on excess mortality than on COVID-19-related mortality.

BackgroundReducing premature mortality is a crucial public health objective. After a long gap in the publication of Belgian mortality statistics, this paper presents the leading causes and the regional disparities in premature mortality in 2008–2009 and the changes since 1993.MethodsAll deaths occurring in the periods 1993–1999 and 2003–2009, in people aged 1–74 residing in Belgium were included.The cause of death and population data for Belgium were provided by Statistics Belgium , while data for international comparisons were extracted from the WHO mortality database.Age-adjusted mortality rates and Person Year of Life Lost (PYLL) were calculated. The Rate Ratios were computed for regional and international comparisons, using the region or country with the lowest rate as reference; statistical significance was tested assuming a Poisson distribution of the number of deaths.ResultsThe burden of premature mortality is much higher in men than in women (respectively 42% and 24% of the total number of deaths). The 2008–9 burden of premature mortality in Belgium reaches 6410 and 3440 PYLL per 100,000, respectively in males and females, ranking 4th and 3rd worst within the EU15. The disparities between Belgian regions are substantial: for overall premature mortality, respective excess of 40% and 20% among males, 30% and 20% among females are observed in Wallonia and Brussels as compared to Flanders. Also in cause specific mortality, Wallonia experiences a clear disadvantage compared to Flanders. Brussels shows an intermediate level for natural causes, but ranks differently for external causes, with less road accidents and suicide and more non-transport accidents than in the other regions.Age-adjusted premature mortality rates decreased by 29% among men and by 22% among women over a period of 15 years. Among men, circulatory diseases death rates decreased the fastest (-43.4%), followed by the neoplasms (-26.6%), the other natural causes (-21.0%) and the external causes (-20.8%). The larger decrease in single cause is observed for stomach cancer (-48.4%), road accident (-44%), genital organs (-40.4%) and lung (-34.6%) cancers. On the opposite, liver cancer death rate increased by 16%.Among female, the most remarkable feature is the 50.2% increase in the lung cancer death rate. For most other causes, the decline is slightly weaker than in men.ConclusionDespite a steady decrease over time, international comparisons of the premature mortality burden highlight the room for improvement in Belgium. The disadvantage in Wallonia and to some extent in Brussels suggest the role of socio-economic factors; well- designed health policies could contribute to reduce the regional disparities. The increase in female lung cancer mortality is worrying.Electronic supplementary materialThe online version of this article (doi:10.1186/2049-3258-72-34) contains supplementary material, which is available to authorized users.