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Estimating household contact matrices structure from easily collectable metadata.
Dall'Amico, Lorenzo; Kleynhans, Jackie; Gauvin, Laetitia; Tizzoni, Michele; Ozella, Laura; Makhasi, Mvuyo; Wolter, Nicole; Language, Brigitte; Wagner, Ryan G; Cohen, Cheryl; Tempia, Stefano; Cattuto, Ciro.
Afiliação
  • Dall'Amico L; ISI Foundation, Turin, Italy.
  • Kleynhans J; National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa.
  • Gauvin L; School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
  • Tizzoni M; ISI Foundation, Turin, Italy.
  • Ozella L; Institute for Research on sustainable Development, UMR215 PRODIG, Aubervilliers, France.
  • Makhasi M; ISI Foundation, Turin, Italy.
  • Wolter N; Department of Sociology and Social Research, University of Trento, Trento, Italy.
  • Language B; ISI Foundation, Turin, Italy.
  • Wagner RG; National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa.
  • Cohen C; National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa.
  • Tempia S; School of Pathology, University of the Witwatersrand, Johannesburg, South Africa.
  • Cattuto C; Unit for Environmental Science and Management, Climatology Research Group, North-West University, Potchefstroom, South Africa.
PLoS One ; 19(3): e0296810, 2024.
Article em En | MEDLINE | ID: mdl-38483886
ABSTRACT
Contact matrices are a commonly adopted data representation, used to develop compartmental models for epidemic spreading, accounting for the contact heterogeneities across age groups. Their estimation, however, is generally time and effort consuming and model-driven strategies to quantify the contacts are often needed. In this article we focus on household contact matrices, describing the contacts among the members of a family and develop a parametric model to describe them. This model combines demographic and easily quantifiable survey-based data and is tested on high resolution proximity data collected in two sites in South Africa. Given its simplicity and interpretability, we expect our method to be easily applied to other contexts as well and we identify relevant questions that need to be addressed during the data collection procedure.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Epidemias / Metadados País/Região como assunto: Africa Idioma: En Revista: PLoS One Assunto da revista: CIENCIA / MEDICINA Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Itália

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Epidemias / Metadados País/Região como assunto: Africa Idioma: En Revista: PLoS One Assunto da revista: CIENCIA / MEDICINA Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Itália