Background <p>Identifying sources of heterogeneity in contact patterns is key to inform disease transmission models. Recent works have investigated how individual-based socio-economic factors, besides age, affect contact behavior, but neglected the individuals’ area of living. Here, we aim at estimating contact matrices stratified by both individual-based and area-based socio-economic factors.</p> Methods <p>We use social contact data from Switzerland collected in 2021, combined with a neighborhood-based index of socio-economic position (SEP). Despite lacking socio-economic information on the contacts, we develop a method to reconstruct contact matrices fully stratified by age, education level, and SEP, with varying assortativity levels.</p> Results <p>We find a positive association between education level and number of contacts in the elderly, and, notably, a negative association between SEP level and number of contacts in adults. Compared to homogeneous mixing, accounting for heterogeneous contact patterns leads to higher attack rates in groups with high education level, especially for adults living in low SEP areas and seniors living in high SEP areas. Adults and young individuals living in high SEP areas are the main contributors to transmission. Including socio-economic factors into model parameterization has limited effect on the basic reproduction number but substantially influences the effectiveness of control strategies. The more assortative contacts are, the higher the control effort required by a targeted strategy to be successful in preventing disease spread.</p> Conclusions <p>Our results shed light on contact behavior in previously neglected socio-economic groups, enable model integration of socio-economic indicators, and provide insights to improve disease control.</p>

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Individual and neighborhood based socioeconomic factors relevant for contact behaviour and epidemic control

  • Laura Di Domenico,
  • Martina L. Reichmuth,
  • Christian L. Althaus

摘要

Background

Identifying sources of heterogeneity in contact patterns is key to inform disease transmission models. Recent works have investigated how individual-based socio-economic factors, besides age, affect contact behavior, but neglected the individuals’ area of living. Here, we aim at estimating contact matrices stratified by both individual-based and area-based socio-economic factors.

Methods

We use social contact data from Switzerland collected in 2021, combined with a neighborhood-based index of socio-economic position (SEP). Despite lacking socio-economic information on the contacts, we develop a method to reconstruct contact matrices fully stratified by age, education level, and SEP, with varying assortativity levels.

Results

We find a positive association between education level and number of contacts in the elderly, and, notably, a negative association between SEP level and number of contacts in adults. Compared to homogeneous mixing, accounting for heterogeneous contact patterns leads to higher attack rates in groups with high education level, especially for adults living in low SEP areas and seniors living in high SEP areas. Adults and young individuals living in high SEP areas are the main contributors to transmission. Including socio-economic factors into model parameterization has limited effect on the basic reproduction number but substantially influences the effectiveness of control strategies. The more assortative contacts are, the higher the control effort required by a targeted strategy to be successful in preventing disease spread.

Conclusions

Our results shed light on contact behavior in previously neglected socio-economic groups, enable model integration of socio-economic indicators, and provide insights to improve disease control.