Item request has been placed! ×
Item request cannot be made. ×
loading  Processing Request

Comparing the COVID-19 pandemic in space and over time in Europe, using numbers of deaths, crude rates and adjusted mortality trend ratios

Item request has been placed! ×
Item request cannot be made. ×
loading   Processing Request
  • معلومة اضافية
    • Contributors:
      Gallo, V.; Chiodini, P.; Bruzzese, D.; Kondilis, E.; Howdon, D.; Mierau, J.; Bhopal, R.; Value, Affordability and Sustainability (VALUE); Research programme EEF
    • بيانات النشر:
      Nature Publishing Group, 2021.
    • الموضوع:
      2021
    • نبذة مختصرة :
      BackgroundSince COVID-19 was declared a pandemic, attempts have been made to monitor trends over time and to compare countries and regions. Insufficient testing for COVID-19 underestimates the incidence and inflates the case-fatality proportion. Given the age- and sex- distribution of morbidity and mortality from COVID-19, the underlying sex- and age-distribution of a population needs to be accounted for. The aim of this paper is to present a method for monitoring trends of COVID-19 using adjusted mortality trend ratios (AMTR).MethodsAge- and sex-mortality distribution of a reference population composed of the first 14,086 fatalities which occurred before the end of March and were reported in Europe by some countries were used to calculate age- and sex-specific mortality rates per 1,000,000 population. These were applied to each country population to calculate the expected deaths. Adjusted Mortality Trend Ratios (AMTRs) with 95% confidence intervals (C.I.) were calculated for selected European countries from 17/03/2020 to 22/06/2020 by dividing observed cumulative mortality, by expected mortality times the crude mortality of the reference population. These estimated the sex- and age-adjusted mortality for COVID-19 per million population in each country.ResultsThe cumulative mortality from COVID-19, the crude mortality rates, and the AMTRs were calculated for each country and compared. United Kingdom, Italy, France and Spain registered the highest mortality in Europe. On 22/06/2020 in Europe the total mortality rate from COVID-19 was 352 per 1,000,000 inhabitants; and it was highest in Belgium (850 per 1,000,000 inhabitants) followed by Spain, UK, Italy, Sweden and France. When accounting for the underlying age and sex structure of each country, Belgium remained the single country experiencing the highest AMTR of 929 per million inhabitants on 22/06/2020; however Ireland – which had a CMR in line with the total European population – emerged as having experienced a much more important impact of COVID-19 mortality with an AMTR of 550/million on 22/06/2020, higher than Sweden and Italy.ConclusionsIn understanding and managing the pandemic of COVID-19, comparable international data is a priority. Our methods allow a fair comparison of mortality in space and over time. The authors urge the WHO, given the absence of age and sex-specific mortality data for direct standardisation, to adopt this method to estimate the comparative mortality from COVID-19 pandemic worldwide.Key messageComparing trends of the COVID-19 pandemic over time and in space is essential to monitor the disease and compare different local policiesUsing the concept of indirect standardisation we propose a method to effectively compare age- and sex-adjusted mortality rates trends interpretable as deaths for COVID-19 per million inhabitantsApplying this methods, interesting features of the infection in Europe emerged; e.g. by 22/06/2020 Belgium is the most severely affected country with an AMTR of 929 per million inhabitants, followed by the UK; Ireland and Sweden rank fourth and fifth most affected country in EuropeThe WHO should consider using this method for monitoring the spread of COVID-19, which only requires recording the total number of death from COVID-19 from each country/region
    • File Description:
      application/pdf
    • ISSN:
      2045-2322
    • Rights:
      OPEN
    • الرقم المعرف:
      edsair.doi.dedup.....8b9c986fdb3c660d61e4453c9496348a