The University of Oxford has highlighted the importance of age and demographic science in explaining the differences in fatalities from Covid-19.
The University is among the first to do so.
Research conducted by Jennifer Beam Dowd, Melinda Mills and their colleagues at the Leverhulme Centre for Demographic Science, Nuffield College and the University of Oxford, highlight the potential of exponentially higher fatalities from Covid-19 in countries and regions with older populations.
As widely reported, Covid-19 mortality rates are particularly high in those aged over 80.
Research into a country’s age demographics can help predict the burden of critical cases and aid in more precise planning of availability of hospital beds, staff and other resources.
Lead author, Jennifer Dowd, Associate Professor of Demography and Population Health said:
‘Until more nuanced data on comorbidities becomes available, the concentration of mortality risk in the oldest ages is one of the best tools we have to understand and deal with Covid-19 at local and national levels.’
The study was motivated by the surprising early severity and number of deaths from Covid-19 in Italy.
Compared to South Korea, which also had an early surge in cases, Italy has one of the oldest populations in the world with 23.3% over age 65, compared to 14% in South Korea.
Using the current age-specific case fatality rate in Italy, the researchers illustrate how population age structure interacts with high Covid-19 mortality rates at older ages to generate large differences in numbers of deaths.
In Italy, the predicted number of fatalities was 1.7 times greater than for South Korea.
Melinda Mills, Nuffield Professor and Director of the Leverhulme Centre for Demographic Science said:
‘In addition to age demographics, intergenerational interactions are also important to understand the spread of Covid-19.’
‘Italy is a country characterised by extensive intergenerational contacts and residential proximity between adult children and their parents.’
‘Covid-19 mitigation policies need to consider this interaction between household living situations and the concentration of vulnerable populations.’
Demographic projections can also be used to understand how population age structure could influence fatalities in different countries around the world.
To demonstrate how population age structure might affect countries yet to experience a large surge in the virus, the authors simulated potential mortality rates in two countries with similar population sizes but very different age distributions: Brazil, where 2% of the population is 80+, and Nigeria, where only 0.2% of the population is over 80.
This scenario saw in excess of three times more deaths in Brazil, based on age structure alone – but population density and health system capacity are also important.
Jennifer Dowd went on to say:
‘Our demographic science forecasting approach shows how Covid-19 could play out in different places, and could be an important tool for governments and policy makers.’
‘Holding other factors such as medical capacity constant, a younger age structure should provide protection to a population. But countries and localities with older populations will need to take more aggressive protective measures to stay below the threshold of critical cases that outstrip health system capacity.’
