A vulnerability index for COVID-19: spatial analysis to inform equitable response in Kenya

Abstract

Background: Response to the COVID-19 pandemic calls for precision public health reflecting our improved understanding of who is the most vulnerable and their geographical location. We created three vulnerability indices to identify areas and people who require greater support while elucidating health inequities to inform emergency response in Kenya. Methods: Geospatial indicators were assembled to create three vulnerability indices; social (SVI), epidemiological (EVI) and a composite of the two (SEVI) resolved at 295 sub-counties in Kenya. SVI included nineteen indicators that affect the spread of disease; socio-economic inequities, access to services and population dynamics while EVI comprised five indicators describing comorbidities associated with COVID-19 severe disease progression. The indicators were scaled to a common measurement scale, spatially overlaid via arithmetic mean and equally weighted. The indices were classified into seven classes, 1-2 denoted low-vulnerability and 6-7 high-vulnerability. The population within vulnerabilities classes was quantified. Results: The spatial variation of each index was heterogeneous across Kenya. Forty-nine north-western and partly eastern sub-counties (6.9 m people) were highly vulnerable while 58 sub-counties (9.7 m people) in western and central Kenya were the least vulnerable for SVI. For EVI, 48 sub-counties (7.2 m people) in central and the adjacent areas and 81 sub-counties (13.2 m people) in northern Kenya were the most and least vulnerable respectively. Overall (SEVI), 46 sub-counties (7.0 m people) around central and south-eastern were more vulnerable while 81 sub-counties (14.4 m people) that were least vulnerable. Conclusion: The vulnerability indices created are tools relevant to the county, national government and stakeholders for prioritization and improved planning especially in highly vulnerable sub-counties where cases have not been confirmed. The heterogeneous nature of the vulnerability highlights the need to address social determinants of health disparities, strengthen the health system and establish programmes to cushion against the negative effects of the pandemic.

Assessing Socioeconomic Vulnerabilities Related to COVID-19 Risk in India: A State-Level Analysis

“…Table1 provides a detailed list of demographic, socioeconomic and health system-related indicators, data sources, and description of the indicators. We reviewed different frameworks, ranging from the infectious disease vulnerability index, socioeconomic vulnerability indicator framework, and recent COVID-19 vulnerability assessment tools (focussed on socioeconomic inequalities, population characteristics, access to services, and epidemiological factors), to investigate the sub-national vulnerability assessment of COVID-19 risk in India 33,44,45 . The infectious disease vulnerability framework identified seven domains (demographic, health care, public health, disease dynamics, political-domestic, political-international, and economic), which show a nation's/region's ability to prevent or contain a disease outbreak.…”

A rapid and reproducible picture of open access health facility data in Africa to support the COVID-19 response

“…By combining open health facility data with other open datasets such as demographic data, it is possible to determine where additional testing facilities might be required, where hospitals may be overwhelmed, and where to send additional health care workers. In Kenya, open facility databases, travel times, bed capacity and health system surge capacity have been combined to aid in COVID-19 response ( Barasa et al , 2020 ; Macharia et al , 2020 ). COVID-19 is not a problem that will be solved by governments alone, but needs a concerted effort with NGOs, private enterprises, start-ups, and citizens.…”

Community vulnerability to epidemics in Nepal: A high-resolution spatial assessment amidst COVID-19 pandemic

“…The findings could also be useful to fight against other epidemics. Index based vulnerability assessment has been used in a number of diseases including COVID-19 (Dickin et al 2013, DeCapprio et al 2020, Macharia et al 2020, KC et al 2020. The high vulnerability score can be described as a location that could be strongly impacted by the epidemic with severe outcomes such as hospitalization or death as compared to a locality with a low vulnerability score irrespective of current number of reported cases (Acharya & Porwal 2020).…”

“…We constructed three vulnerability indices: SVI, EVI and a composite of the two, the SEVI, following the approach of (Macharia et al 2020). We chose equally weighted arithmetic mean (Sullivan & Meigh 2006) for overlaying these indicators.…”

“…Geographic information system (GIS) is an essential tool to examine the spatial distribution of infectious diseases (Acharya et al 2018, Kang et al 2020. However, a limited number of GIS-based studies have been published since the initial outbreak of COVID-19 (Kamel Boulos & Geraghty 2020, Kang et al 2020, Macharia et al 2020, Mollalo et al 2020, Sarwar et al 2020. Assessment of the disease risk level is important for preparedness and response.…”