HCR.20.055 – Dynamic networks and COVID-19 control
The COVID-19 pandemic has demonstrated how closely human contact networks, infectious disease-spread, and control are interrelated. It has also shown how little we know about structure and dynamics of these networks, and about how efficient infection control infection could be implemented while making use of the networks’ structural features. The lockdown caused a severe disruption of a large part of this network, while relaxation of the measures led to its partial restoration. A crucial question for society is, which part of the network can be considered safe to restore, while still keeping control at a high (policy-)level. Presently, this can only be addressed experimentally by lifting restriction measures and subsequently observing the impact on the numbers of cases. Furthermore, contact tracing is viewed as a control measure that explicitly makes use of infected individuals’ contact networks. The effectiveness of contact tracing, however, is presently low and fraught with many logistical problems. Finally, the state of an epidemic strongly influences how people behave: they may change their contact patterns according to their perceived risk of infection. Despite major advances made in behavioural sciences, network sciences, mathematical modelling, and epidemiology in collecting and analysing data, the effectiveness of monitoring and control measures, remains difficult to understand or predict due to the complex and intertwined dynamics of human contact networks, transmission of COVID-19, and control measures. With a multidisciplinary team, we will develop innovative approaches for network-based (digital) surveillance and interventions for the control of emerging infections such as COVID-19. The team will include expertise on human behaviour, epidemiology, sociology, network science, mathematical modelling, and also more practical aspects as implementation science and policy decision making. An important contribution to the control of the current and future epidemics will be the development of digital tools for surveillance and disease control.
complexity, contact patterns, contact tracing, COVID-19, Dynamic networks, epidemic control
CWI, Erasmus Medical Center (EMC), Leiden Universitair Medisch Centrum (LUMC), Rijksinstituut voor Volksgezondheid en Milieu (RIVM), Utrecht University (UU), Vrije Universiteit Amsterdam (VU), Wageningen Universities and Research (WUR)
|Organisation||University Medical Center Utrecht (UMCU)|
|Name||Prof. Dr. Mirjam Kretzschmar|