Optimal resource allocation with spatiotemporal transmission discovery for effective disease control.

ABSTRACT:

Background

The new waves of COVID-19 outbreaks caused by the SARS-CoV-2 Omicron variant are developing rapidly and getting out of control around the world, especially in highly populated regions. The healthcare capacity (especially the testing resources, vaccination coverage, and hospital capacity) is becoming extremely insufficient as the demand will far exceed the supply. To address this time-critical issue, we need to answer a key question: How can we effectively infer the daily transmission risks in different districts using machine learning methods and thus lay out the corresponding resource prioritization strategies, so as to alleviate the impact of the Omicron outbreaks?

Methods

We propose a computational method for future risk mapping and optimal resource allocation

SUBMITTER: Ren J 

PROVIDER: S-EPMC8947954 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature