Incorporating social contact data in spatio-temporal models for infectious disease spread

Abstract

Routine public health surveillance of notifiable infectious diseases gives rise to weekly counts of reported cases -- possibly stratified by region and/or age group. We investigate how an age-structured social contact matrix can be incorporated into a spatio-temporal endemic-epidemic model for infectious disease counts. To illustrate the approach, we analyze the spread of norovirus gastroenteritis over 6 age groups within the 12 districts of Berlin, 2011-2015, using contact data from the POLYMOD study. The proposed age-structured model outperforms alternative scenarios with homogeneous or no mixing between age groups. An extended contact model suggests a power transformation of the survey-based contact matrix towards more within-group transmission.

accepted manuscript; 14 pages, including 4 figures and 1 table

References in corpus (3)

• The scaling laws of human travel
• Power-law models for infectious disease spread
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• A zero-inflated endemic-epidemic model with an application to measles time series in Germany
• Periodically stationary multivariate autoregressive models
• Inference under Superspreading: Determinants of SARS-CoV-2 Transmission in Germany
• Impact of Indirect Contacts in Emerging Infectious Disease on Social Networks