Inferring high-resolution human mixing patterns for disease modeling

Abstract

Mathematical and computational modeling approaches are increasingly used as quantitative tools in the analysis and forecasting of infectious disease epidemics. The growing need for realism in addressing complex public health questions is, however, calling for accurate models of the human contact patterns that govern the disease transmission processes. Here we present a data-driven approach to generate effective population-level contact matrices by using highly detailed macro (census) and micro (survey) data on key socio-demographic features. We produce age-stratified contact matrices for 35 countries, including 277 sub-national administratvie regions of 8 of those countries, covering approximately 3.5 billion people and reflecting the high degree of cultural and societal diversity of the focus countries. We use the derived contact matrices to model the spread of airborne infectious diseases and show that sub-national heterogeneities in human mixing patterns have a marked impact on epidemic indicators such as the reproduction number and overall attack rate of epidemics of the same etiology. The contact patterns derived here are made publicly available as a modeling tool to study the impact of socio-economic differences and demographic heterogeneities across populations on the epidemiology of infectious diseases.

Estimating the cumulative incidence of COVID-19 in the United States using influenza surveillance, virologic testing, and mortality data: Four complementary approaches

“…As our model considers contact matrices for different settings, namely households, schools, workplaces and community contacts [70,77], we quantify the decrease in contacts that individuals have in each of these environments. To implement school closures in the United States we follow [78] where authors study the effects of school closure in the context of seasonal influenza epidemics.…”

Anatomy of digital contact tracing: Role of age, transmission setting, adoption, and case detection

“…This synthetic population reproduced the location statistics of individuals in different settings, yielding the basis of a multi-setting network of daily face-to-face contacts in household, school, workplace, community and transport (Fig. 1 H) (30)(31)(32). We parametrized the network from a social contact survey providing information on contacts by age and setting (33) (Fig.…”

Controlling the pandemic during the SARS-CoV-2 vaccination rollout: a modeling study

“…The baseline (pre-pandemic) contact matrices for transmission-relevant contacts for Portugal were taken from the recent study by Mistry and colleagues [67]. The contact matrix for Portugal after the introduction of measures to control the first wave of hospitalizations (April 2020) was inferred using the contact matrix for the Netherlands based on a cross-sectional survey carried out in April 2020 (PIENTER Corona study) [68].…”

“…. , n) at time t. The contact rate denotes the number of transmission-relevant contacts per day such as touching or having a conversation with someone [67,68]. Our fitting procedure allows to estimate c kl (t) by assuming that changes due to control measures described in 0)-5) occur as a series of smooth transitions.…”

“…The pre-pandemic matrix b kl for Portugal was taken from [67] (Figure 9 a). The matrix after the first lockdown a kl was inferred using the contact matrix for the Netherlands based on a cross-sectional survey carried out in April 2020 (PIENTER Corona study) [68].…”