Enhancing global preparedness during an ongoing pandemic from partial and noisy data

Abstract

As the coronavirus disease 2019 (COVID-19) spread globally, emerging variants such as B.1.1.529 quickly became dominant worldwide. Sustained community transmission favors the proliferation of mutated sub-lineages with pandemic potential, due to cross-national mobility flows, which are responsible for consecutive cases surge worldwide. We show that, in the early stages of an emerging variant, integrating data from national genomic surveillance and global human mobility with large-scale epidemic modeling allows to quantify its pandemic potential, providing quantifiable indicators for pro-active policy interventions. We validate our framework on worldwide spreading variants and gain insights about the pandemic potential of BA.5, BA.2.75 and other sub- and lineages. We combine the different sources of information in a simple estimate of the pandemic delay and show that only in combination, the pandemic potentials of the lineages are correctly assessed relative to each other. Compared to a country-level epidemic intelligence, our scalable integrated approach, i.e. pandemic intelligence, permits to enhance global preparedness to contrast the pandemic of respiratory pathogens such as SARS-CoV-2.

Inferring country-specific import risk of diseases from the world air transportation network

“…In our final comparison, we evaluate the correlation between disease arrival times and the estimated import probability from the outbreak country of the disease. Note that the effective distance, which is the base of the import risk model, already has the clear relation to disease arrival times and the import risk model is developed to extend this qualitative relation to a quantitative number of passengers imported, as done in a recent study on the pandemic potential of SARS-CoV-2 variants [ 11 ]. However, a qualitative comparison to arrival time is of course possible via the negative logarithm of the import probability for each model, which we refer to as effective model distance , which linearly relates [ 16 , 19 ] to the arrival time t A ( i | j ) of a disease with j as the disease outbreak country.…”

“…Already the first plague pandemic that started AD 541 in the Nile Delta of Egypt spread in 8 years across the territories (Mediterranean, Northern Europe and Near East) of 2 affected empires because of the intense commerce in the Roman Empire [6]. Nowadays, the intensified exchange reduces the time until a pandemic reaches all parts of the world to months as for the 2009 H1N1 virus that spread from Mexico in 5 months to all continents [8,9] or the recent COVID-19 pandemic whose variants spread within a few months across the globe [10][11][12][13].…”

Prevalence of long COVID decreases for increasing COVID-19 vaccine uptake

“…Keeping a low infodemic level—i.e., maintaining the circulation of reliable information about the multifaceted aspects of the ongoing pandemic [ 72 – 74 ]—with periodic and adequate communication campaigns, might enhance compliance with public health guidelines [ 75 ]. Additionally, coordination among countries is needed to enhance global preparedness [ 43 , 76 , 77 ] to emerging SARS-CoV-2 variants, as well as to novel pathogens with pandemic potential, as the ones due to zoonotic spillover induced by climate change, that according to a recent study, are not going to be unlikely [ 78 ].…”

Drivers and impact of the early silent invasion of SARS-CoV-2 Alpha

“…Interventions aiming at mitigation or delay may instead have an impact depending on the extent and duration of silent dissemination at the time they are implemented 21,22 . Recent work addressed the minimal sequencing coverage to detect a variant early enough for an effective response, and proposed modeling tools for risk assessment [23][24][25][26][27] . However, the complex interplay of factors determining the duration of silent propagation remains poorly understood.…”