From risk factors to disease situations: A socio-spatial analysis of COVID-19 experiences in Lima, Peru.

Publication date: Dec 01, 2024

The goal of this qualitative research study, part of an interdisciplinary project, was to understand the overlapping geographical distribution of COVID-19 and tuberculosis burden in Lima. Using an ethnographic approach, we applied the concept of disease situations to explore how inhabitants’ social and spatial situatedness affected their capacity to respond to the pandemic. Our results show that for some populations in Lima, the risk to develop COVID-19 did not emerge suddenly; it could be traced back to situations of living under subsistence models, relying on unstable sources of income, facing food insecurity, depending on certain mechanisms of social protection, residing in precarious living environments and lacking access to quality health care. These populations did not only have less resources to adjust to changes in daily life induced by the pandemic; they were also forced to constantly weigh the risk of COVID-19 against other pressing needs and potentially face increased risks when control measures were actually followed. Pre-existing social networks played fundamental roles as sources of emotional and material support. The lens of disease situations can help to identify and explain spatial and social configurations that enhance vulnerability, as well as resilience mechanisms that are in place to deal with crises. This perspective could inform the design of contextualised prevention and response strategies around health risks in cities as diverse as Lima, whilst building on existing resources at local levels.

Concepts Keywords
Daily Adult
Emotional Anthropology, Cultural
Models Assemblage
Peru COVID-19
Tuberculosis COVID-19
Disease situations
Female
Food Insecurity
Health Services Accessibility
Humans
Interdisciplinary study
Lima
Male
Middle Aged
Pandemics
Peru
Qualitative data
Qualitative Research
Risk Factors
SARS-CoV-2
Socio-spatial variation
Socioeconomic Factors
Spatial Analysis
Tuberculosis
Tuberculosis

Semantics

Type Source Name
disease MESH COVID-19
disease MESH tuberculosis
pathway KEGG Tuberculosis
disease IDO quality
disease MESH Health Services Accessibility

Original Article

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