Socioexposomics of covid-19 across new jersey: a comparison of geostatistical and machine learning approaches

HIGHLIGHTS

• who: Xiang Ren from the (UNIVERSITY) have published the research: Socioexposomics of COVID-19 across New Jersey: a comparison of geostatistical and machine learning approaches, in the Journal: (JOURNAL) of 17/05/2022
• what: This study implemented a unified framework (Fig 1) applying and comparing eight representative ML and geostatistical models with structure hierarchy, for health impact assessment and prediction of COVID-19 adverse health outcomes at municipality level across New Jersey. The authors focused on the first wave of the pandemic (March to September 2020) to exclude effects from factors such as vaccination and . . .
  

   

  

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