Vulnerability in the context of COVID-19 is not distributed evenly across all people and households. Globally, a range of factors – including race and social and economic status – have already been shown to shape vulnerability.
In the South African context, household composition and structure are already known to be linked to socio-economic vulnerability. They are likely to be relevant in the context of COVID-19 too. In particular, female-headed households and multigenerational households are likely to be at risk.
To explore these relationships, we created a series of interactive visualisations. They consider various household characteristics and exposure to factors which might increase the risk of contracting COVID-19, or of suffering economic and health impacts as a result of the pandemic.
Our analysis draws on Gauteng City Region Observatory’s Quality of Life V (2017/18) survey data. This defines the household as those people living in the same dwelling and eating together for four or more nights a week.
We focus on the following household characteristics: size; children; multiple generations; headship; and dwelling conditions. We also look at levels of vulnerability in households where respondents are over 60 years old, primary caregivers or migrants.
We have previously developed a set of indices to capture multiple forms of risk during the COVID-19 pandemic. Our current analysis shows how risks shift and overlap for different household characteristics.
We found that vulnerability in the context of COVID-19 is complex. Responses to the pandemic need to consider variations in forms and distribution of risk. For example, households in informal dwellings are more likely to have poor access to water and sanitation but they are less likely to have members with pre-existing health conditions. Female-headed households, larger households, and those where respondents are females with primary care-giving responsibilities have higher levels of risk for both transmission and the impacts of the lockdown. Women are more likely to live in larger households, so these patterns seem likely to place them at greater risk of transmission within the household.
Understanding how vulnerability shifts alongside household structure and attributes is crucial to delivering targeted support.
Estimating risk
Our work follows the analysis established in the Gauteng City-Region Observatory’s March 2020 Map of the Month. This outlined two indices of factors that were expected to increase vulnerability related to the COVID-19 pandemic.
The first index considers factors which might increase the difficulty of preventing COVID-19 transmission. This includes, for example, maintaining high levels of personal hygiene and practising social distancing. These risk factors include living in a crowded dwelling, absence of piped water, shared or inadequate toilet facilities, dependence on public health care services, limited access to communication tools, and reliance on public transport.
