Advancing equity in pandemic preparedness and response: modelling social vulnerability and inequality
1
Universitat de Barcelona, Barcelona, Spain
2
ISGlobal, Barcelona, Spain
3
Institute of Collective Health, Federal University of Bahia, Bahia, Brazil
4
University of the Free State, Bloemfontein, South Africa
5
Molo Songololo, Cape Town, South Africa
6
The Saartjie Baartman Centre for Women and Children, Cape Town, South Africa
7
Karl Bremer Hospital, Western Cape Department of Health and Wellness, Cape Town, South Africa
8
Scalabrini Institute for Human Mobility in Africa, Cape Town, South Africa
9
Callas Foundation, Cape Town, South Africa
10
London School of Hygiene and Tropical Medicine, London, United Kingdom
Popul. Med. 2026;8(Supplement Supplement 1):
ABSTRACT
BACKGROUND:
The COVID-19 pandemic underscored the urgent need for equitable emergency preparedness and response. Mathematical models are useful tools in pandemic planning. However, they often ignore social vulnerability (SV): the structural social, economic, and political inequalities that lead to unjust and unequal health outcomes. Modelling an outbreak of a novel pandemic Influenza in Cape Town, South Africa, we compared disease incidence and mortality when SV conditions deteriorate or improve as a result of policy and programmatic action.
METHODS:
Using a participatory modelling framework, we partnered with community-based organisations throughout the study process. We developed an adaptable, evidence-based 18-compartment mathematical model for a novel pandemic Influenza (“Influenza X”). To incorporate SV, we leveraged a mixed-methods approach. Community experts identified the key intersectional SV and its pathways during a structured focus group. The quantitative epidemiological measure of population attributable fraction was then used to adjust the relevant model parameters and dynamics.
RESULTS:
Community experts selected extreme poverty as the central intersectional driver of SV during a pandemic. As a result, reducing extreme poverty from the community’s baseline of 35% to 20% with income support measures (e.g., cash transfers or grants) one month into the pandemic prevented half of cases (48%) and deaths (52%). However, delays in implementation dampened these gains. Introducing income support three months into the pandemic reduced cases and deaths by a third (28% and 32%, respectively).
CONCLUSIONS:
Pandemic management tends to focus on the biomedical aspects of transmission and neglects the social conditions that allow disease to proliferate. Our results demonstrate that social protection can meaningfully mitigate disease burden and supports global commitments to Sustainable Development Goals 1 (No Poverty), 3 (Good Health and Well-Being), and 10 (Reduced Inequalities). Poverty alleviation should be considered a key pandemic control strategy.
The COVID-19 pandemic underscored the urgent need for equitable emergency preparedness and response. Mathematical models are useful tools in pandemic planning. However, they often ignore social vulnerability (SV): the structural social, economic, and political inequalities that lead to unjust and unequal health outcomes. Modelling an outbreak of a novel pandemic Influenza in Cape Town, South Africa, we compared disease incidence and mortality when SV conditions deteriorate or improve as a result of policy and programmatic action.
METHODS:
Using a participatory modelling framework, we partnered with community-based organisations throughout the study process. We developed an adaptable, evidence-based 18-compartment mathematical model for a novel pandemic Influenza (“Influenza X”). To incorporate SV, we leveraged a mixed-methods approach. Community experts identified the key intersectional SV and its pathways during a structured focus group. The quantitative epidemiological measure of population attributable fraction was then used to adjust the relevant model parameters and dynamics.
RESULTS:
Community experts selected extreme poverty as the central intersectional driver of SV during a pandemic. As a result, reducing extreme poverty from the community’s baseline of 35% to 20% with income support measures (e.g., cash transfers or grants) one month into the pandemic prevented half of cases (48%) and deaths (52%). However, delays in implementation dampened these gains. Introducing income support three months into the pandemic reduced cases and deaths by a third (28% and 32%, respectively).
CONCLUSIONS:
Pandemic management tends to focus on the biomedical aspects of transmission and neglects the social conditions that allow disease to proliferate. Our results demonstrate that social protection can meaningfully mitigate disease burden and supports global commitments to Sustainable Development Goals 1 (No Poverty), 3 (Good Health and Well-Being), and 10 (Reduced Inequalities). Poverty alleviation should be considered a key pandemic control strategy.
| eISSN: | 2654-1459 |
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