National age and coresidence patterns shape COVID-19 vulnerability

Abstract

Based on harmonized census data from 81 countries, we estimate how age and coresidence patterns shape the vulnerability of countries’ populations to outbreaks of coronavirus disease 2019 (COVID-19). We estimate variation in deaths arising due to a simulated random infection of 10% of the population living in private households and subsequent within-household transmission of the virus. The age structures of European and North American countries increase their vulnerability to COVID-related deaths in general. The coresidence patterns of elderly persons in Africa and parts of Asia increase these countries’ vulnerability to deaths induced by within-household transmission of COVID-19. Southern European countries, which have aged populations and relatively high levels of intergenerational coresidence, are, all else equal, the most vulnerable to outbreaks of COVID-19. In a second step, we estimate to what extent avoiding primary infections for specific age groups would prevent subsequent deaths due to within-household transmission of the virus. Preventing primary infections among the elderly is the most effective in countries with small households and little intergenerational coresidence, such as France, whereas confining younger age groups can have a greater impact in countries with large and intergenerational households, such as Bangladesh.

The Role of Health Preconditions on COVID-19 Deaths in Portugal: Evidence from Surveillance Data of the First 20293 Infection Cases

“…A retrospective observational study investigating mortality in hospitalized patients with COVID-19 registered the great vulnerability of patients residing in retirement homes, with older age independently associated with mortality when adjusted for other variables of interest [22]. On the opposite residence condition, the shape of COVID-19 vulnerability was estimated based on a random infection of 10% of the population living in private households (excluding individuals living in retirement homes) of 81 countries [27]. In this study, it was estimated that national age and coresidence patterns can alter the vulnerability of a country to COVID-19 outbreaks, with direct effects dependent on a country's age structure and indirect effects dependent on the size and age structure of a country's households [27].…”

“…On the opposite residence condition, the shape of COVID-19 vulnerability was estimated based on a random infection of 10% of the population living in private households (excluding individuals living in retirement homes) of 81 countries [27]. In this study, it was estimated that national age and coresidence patterns can alter the vulnerability of a country to COVID-19 outbreaks, with direct effects dependent on a country's age structure and indirect effects dependent on the size and age structure of a country's households [27].…”

“…From the available information, at least 2973 (14.7%) infected cases were hospitalized (the data include 1623 cases with unknown hospitalization status), at least 261 (1.3%) infected cases were subjected to intensive care, and at least 86 (0.4%) had respiratory support (oxygen or ventilator). Mortality within the hospitalized cases was 11.1% (330), within those subjected to intensive care 10.3% (27). At this point, no deaths were registered among those submitted to respiratory support (Table 1).…”

Modelling COVID-19 mortality at the regional level in Italy

“…In our analysis, these two variables were not significantly associated with COVID-19 mortality, after controlling for other factors. Similarly, the dimension of households has been proposed as a key factor (together with the population age structure) to determine the vulnerability of countries to outbreaks of COVID-19 (Esteve et al, 2020). Conversely, the dimension of households is negatively correlated with COVID-19 mortality in Italian regions during the period analysed, and a similar negative correlation is observable across clusters for the number of nursing homes (see Figure B.2 in Appendix B).…”

Dangerous to claim “no clear association” between intergenerational relationships and COVID-19

“…CFRs can be identical across countries with both very high and low deaths. If used as a proxy for a high proportion of older deaths, it is crude and potentially biased; deaths or excess deaths per population are preferable ( 7 ).…”