Household transmission and immunity to SARS-CoV-2 among paediatric clients of a primary care centre in a low-resource community in Rio de Janeiro
- Funded by Department of Health and Social Care / National Institute for Health and Care Research (DHSC-NIHR), UK Research and Innovation (UKRI)
- Total publications:0 publications
Grant number: unknown
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Key facts
Disease
COVID-19Funder
Department of Health and Social Care / National Institute for Health and Care Research (DHSC-NIHR), UK Research and Innovation (UKRI)Principal Investigator
N/A
Research Location
BrazilLead Research Institution
Oswaldo Cruz Foundation, London School of Hygiene & Tropical Medicine, University of ExeterResearch Priority Alignment
N/A
Research Category
Epidemiological studies
Research Subcategory
Disease transmission dynamics
Special Interest Tags
N/A
Study Type
Clinical
Clinical Trial Details
Not applicable
Broad Policy Alignment
Pending
Age Group
Children (1 year to 12 years)
Vulnerable Population
Unspecified
Occupations of Interest
Unspecified
Abstract
Understanding SARS-CoV-2 in children is important for their health, as well as for their families and communities, particularly in crowded living conditions such as slums, where households are very small and it is almost impossible to keep children within their homes.The aim of this project is to study the household transmission dynamics of the COVID-19 in a favela in Rio de Janeiro, Brazil. The researchers will examine and test for COVID-19 in a sample of children and their families from one of the poorest neighborhoods of the city, with regular follow-up visits over two years. The study expects to bring more evidence to the role of children in disease transmission, answering questions such as whether adults catch the virus at work, then transmit it to their children or do children catch the virus from neighbours, then bring it back to their families. "The risk of catching SARS-CoV-2 comes down to a variety of factors, from genetics, to behaviour, to the environment in the home. We're hoping to tease variables apart with statistical models and figure out which ones are the most important." Leonard Bastos, Associate Researcher, FIOCRUZ, Brazil