Genomic surveillance reveals dynamic shifts in the connectivity of COVID-19 epidemics

Abstract

The maturation of genomic surveillance in the past decade has enabled tracking of the emergence and spread of epidemics at an unprecedented level. During the COVID-19 pandemic, for example, genomic data revealed that local epidemics varied considerably in the frequency of SARS-CoV-2 lineage importation and persistence, likely due to a combination of COVID-19 restrictions and changing connectivity. Here, we show that local COVID-19 epidemics are driven by regional transmission, including across international boundaries, but can become increasingly connected to distant locations following the relaxation of public health interventions. By integrating genomic, mobility, and epidemiological data, we find abundant transmission occurring between both adjacent and distant locations, supported by dynamic mobility patterns. We find that changing connectivity significantly influences local COVID-19 incidence. Our findings demonstrate a complex meaning of 'local' when investigating connected epidemics and emphasize the importance of collaborative interventions for pandemic prevention and mitigation.

A Lightweight Security Model using Delta Probabilistic Hashing Technique for Secured Data Transmission in IoT Systems

“…These results confirm the value of our simple security architecture for securing data storage and transmission in IoT applications. In summary, the suggested methodology addresses the drawbacks of current approaches and ensures increased security and effectiveness while introducing a revolutionary lightweight security model for IoT data transfer [40]. For safe data processing in IoT contexts, the of Delta Probabilistic Hashing (DPH) [39] and Double-String Data Cryptographic (DSDC) encryption techniques offers a special and efficient solution.…”