GETTING AHEAD OF THE CURVE

The Covid-19 pandemic has disrupted lives across the globe in just a few months. And yet, there are no effective vaccine or treatment to contain its spread. A very likely scenario for African countries is a continued battle with the disease over the next year at least, with steady spread of infections to larger parts of countries, including into more remote areas. While we are dealing with the immediate and multifaceted effects, we need to also look ahead to bolster preparedness to tackle the crisis in likely future hot spots. An important part of country strategies and readiness in fighting the pandemic is therefore to anticipate where the pandemic is most likely to spread and , more critically, where there is least capacity to absorb the shock if and when it hits. 

Crises like the current one often only bring to the fore the manifestation of long term, chronic vulnerability. Most communities that bear the brunt of the suffering from crises are communities that have been plagued by chronic threats to their livelihoods long before the shocks occur. These pre-existing conditions erode the communities’ absorption capacity and magnify the impact of shocks. Early identification of such communities and a better understanding of the nature of their vulnerability, particularly with respect to specific shocks, in this case the Covid-19 pandemic, make it possible to craft response strategies long before the crisis hits.

In the current work stream of the AKADEMIYA2063 Covid-19 program, we rank communities across regions and countries against a range of key livelihood and threat indicators to determine the ones that are likely to suffer the most, should the pandemic reach them. The findings can help governments, non-state actor organizations and the development community to forge proactive responses to contain the propagation of the disease and mitigate its effects. 

INTRODUCTION

Limited resources will require that responses to the pandemic prioritize the most vulnerable communities where the effects are likely to be particularly devastating. We will use data from our ReSAKSS country eAtlases (https://eatlas.resakss.org) and other sources to pinpoint local communities in countries where chronic vulnerability renders the population uniquely susceptible to the effects of the COVID-19 outbreak. Data layers include indicators on nutrition and food security, disease burden, health infrastructure and access, population density, and poverty. Communities that register at the lower end of all these indicators tend to have high levels of chronic vulnerability and are thus prone to be harder hit by sudden shocks. The overlaying of a number of indicators will provide a more nuanced picture of vulnerability and permit us to identify areas that would be missed if only a few factors were considered. The analysis will allow the team to map potential vulnerability hotspots at the subnational community level.