Understanding mental health trends during COVID-19 pandemic in the United States using network analysis

Abstract

AbstractThe emergence of COVID-19 in the United States resulted in a series of federal and state-level lock-downs and COVID-19 related health mandates to manage the spread of the virus. These policies may negatively impact the mental health state of the population. This study focused on the trends in mental health indicators following the COVID-19 pandemic amongst four United States geographical regions, and political party preferences. Indicators of interest included feeling anxious, feeling depressed, and worried about finances. Survey data from Delphi Group in Carnegie Mellon University were analyzed using clustering algorithms and dynamic connectome obtained from sliding window analysis. United States maps were generated to observe spatial trends and identify communities with similar mental health and COVID-19 trends. Between March 3rd, 2021 and January 10th, 2022, states in the south geographic region showed similar trends for reported values of feeling anxious and worried about finances. There were no identifiable communities resembling geographical regions or political party affiliation for the feeling depressed indicator. We observed a high degree of correlation among southern states as well as within republican states, where the highest correlation values from the dynamic connectome analysis for feeling anxious and feeling depressed variables seemingly overlapped with an increase in COVID-19 related cases, deaths, hospitalizations, and rapid spread of the COVID-19 Delta variant.