to characterize the seasonality of the SARS-CoV2 virus is different setting around the world to best support mitigation efforts

Grant number: INV-024911

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Key facts

  • Disease

    COVID-19
  • start year

    2020
  • Known Financial Commitments (USD)

    $476,214
  • Funder

    Gates Foundation
  • Principal Investigator

    N/A

  • Research Location

    United Kingdom
  • Lead Research Institution

    The University of Southampton
  • Research Priority Alignment

    N/A
  • Research Category

    Epidemiological studies

  • Research Subcategory

    Disease surveillance & mapping

  • Special Interest Tags

    N/A

  • Study Type

    Non-Clinical

  • Clinical Trial Details

    N/A

  • Broad Policy Alignment

    Pending

  • Age Group

    Unspecified

  • Vulnerable Population

    Unspecified

  • Occupations of Interest

    Unspecified

Abstract

N/A

Publicationslinked via Europe PMC

Comparing lagged impacts of mobility changes and environmental factors on COVID-19 waves in rural and urban India: A Bayesian spatiotemporal modelling study.

Optimizing the detection of emerging infections using mobility-based spatial sampling.

Spatiotemporal variations of "triple-demic" outbreaks of respiratory infections in the United States in the post-COVID-19 era.

Effects of public-health measures for zeroing out different SARS-CoV-2 variants.

Risk of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Transmission Among Air Passengers in China.

Global holiday datasets for understanding seasonal human mobility and population dynamics.

Mobility in China, 2020: a tale of four phases.

A data driven agent-based model that recommends non-pharmaceutical interventions to suppress Coronavirus disease 2019 resurgence in megacities.