Digital and computational epidemiology for pandemic management

Lessons learnt from the current pandemic will be invaluable to tackle a potential second wave, however, gaps remain in our readiness to face future pandemics. At Nature Communications we wish to support further research providing insights into how national and international systems could be shaped for increased preparedness to both local or global epidemics.

In this Perspective, the authors review the different applications for mobile phone data to support COVID-19 pandemic response, the relevance of these applications for infectious disease transmission and control, and potential sources and implications of selection bias in mobile phone data.

New York City is one of the areas most affected by the SARS-CoV-2 pandemic in the United States, and there has been large variation in rates of hospitalisation and death by city borough. Here, the authors show that boroughs with the largest reduction in daily commutes also had the lowest SARS-CoV-2 prevalence.

COVID-19-related travel restrictions were imposed in China around the same time as major annual holiday migrations, with unknown combined impacts on mobility patterns. Here, the authors show that restructuring of the travel network in response to restrictions was temporary, whilst holiday-related travel increased pressure on healthcare services with lower capacity.

Contact tracing is critical to controlling COVID-19, but most protocols only “forward-trace” to notify people who were recently exposed. Using a stochastic branching-process model, the authors show that “bidirectional” tracing to identify infector individuals and their other infectees robustly improves outbreak control.

While Digital contact tracing (DCT) has been argued to be a valuable complement to manual tracing in the containment of COVID-19, no empirical evidence of its effectiveness is available to date. Here, the authors report the results of a 4-week population-based controlled experiment, where they assessed the impact of the Spanish DCT app.

Digital proxies of human mobility can be used to monitor social distancing, and therefore have potential to infer COVID-19 dynamics. Here, the authors integrate travel card data from Hong Kong into a transmission model and show that it can be used to track transmissibility in near real-time.

Digital contact tracing is increasingly considered as one of the tools to control infectious disease outbreaks, in particular the COVID-19 epidemic. Here, the authors present a modeling framework informed by empirical high-resolution contact data to analyze the impact of digital contact tracing apps.

Decision makers must have sufficient confidence in models if they are to influence their decisions. We propose three screening questions to critically evaluate models with respect to their purpose, organization, and evidence. They enable a more transparent, robust, and secure use of model outputs.

Recommendations regarding the use of face masks as a preventive measure for COVID-19 are inconsistent. Here, the authors show that optimal distribution of surgical-standard face masks in the population, or universal coverage of homemade face coverings, could reduce total infections and deaths.

Releasing COVID-19 lockdown measures risks increases in transmission. Here, the authors estimate the increase in transmission rate for different regions in Italy and estimate that isolation of 5.5% exposed and highly infectious individuals would be needed to compensate for a 40% increase in transmission.

An ongoing global debate concerns effective and sustainable lockdown release strategies in the current pandemic. Here, the authors implement a network model at healthcare-relevant spatial scale to show that coordinated local strategies can be effective in containing further resurgence of the disease.

Absent a drug or vaccine, containing epidemic outbreaks is achieved by means of mobility restrictions and lock-downs. Here, the authors propose an alternating quarantine strategy, in which half of the population remains under lockdown while the other half continues to be active, resulting in a dramatic reduction in transmission.

Test, trace, and isolate programmes are central to COVID-19 control. Here, Viola Priesemann and colleagues evaluate how to allocate scarce resources to keep numbers low, and find that if case numbers exceed test, trace and isolate capacity, there will be a self-accelerating spread.

Safely reducing the necessary duration of quarantine for COVID-19 could lessen the economic impacts of the pandemic. Here, the authors demonstrate that testing on exit from quarantine is more effective than testing on entry, and can enable quarantine to be reduced from fourteen to seven days.

Human mobility plays a central role in the spread of infectious diseases and can help in forecasting incidence. Here the authors show a comparison of multiple mobility benchmarks in forecasting influenza, and demonstrate the value of a machine-learned mobility map with global coverage at multiple spatial scales.

The role of children in the spread of COVID-19 is not fully understood, and the circumstances under which schools should be opened are therefore debated. Here, the authors demonstrate protocols by which schools in France can be safely opened without overwhelming the healthcare system.

The COVID-19 pandemic caused many governments to impose policies restricting social interactions. Here, the authors implement an age-specific, individual-based model with data on social contacts for the Belgian population and investigate the effect of non-pharmaceutical interventions.

The role of school-based contacts in the epidemiology of SARS-CoV-2 is incompletely understood. Here, the authors use an age-structured transmission model fitted to age-specific seroprevalence and hospital admission data to assess the effects of school-based measures during the COVID-19 pandemic in the Netherlands.

Massive unemployment during the COVID-19 pandemic could result in an eviction crisis in US cities. Here, the authors model the effect of evictions on SARS-CoV-2 epidemics, simulating viral transmission within and among households in a theoretical and applied urban settings.

Cornelia Betsch (a psychologist, University of Erfurt), Vittoria Colizza (a computational epidemiologist, INSERM), Sara del Valle (a computational epidemiologist, Los Alamos National Laboratory), Chikwe Ihekweazu (a public health epidemiologist, Nigeria Centre for Disease Control) and Carmela Troncoso (a data security specialist, EPFL) talked to Nature Communications about their experience with COVID-19 response and their vision on a new system for disease surveillance and control, providing a view on how this should interact with policy making.

COVID-19 might occur together with other natural disasters but frameworks to quantify collective effects is lacking. Here, the authors investigated the readiness of a healthcare system in the face of wildfire during an epidemic by assuming the COVID-19 pandemic occurred around the same time with the Camp Fire case in Butte Country California 2018/2019.