Analyzing Symptoms of Anxiety and Depression During the Course of the Covid-19 Pandemic

Motivation

Problem

Since the start of the pandemic almost three years ago, the rise of Covid-19 cases has been accompanied with a decline in mental health throughout the world. In fact, there was a 25% increase in the prevalence of anxiety and depression. This epidemic of mental illness was the product of many factors such as increased social isolation, fear of getting Covid-19, struggling through grief and trauma due to the death of loved ones, and a sense of danger and hopelessness.

Solution

I wanted to do my project on the impact of the pandemic on anxiety and depression on various demographic groups such as age, race, gender identity, sexual orientiation, and more. Through my project, I want to break down the statistics of patients who reported experiencing symptoms of anxiety and depression, to figure out which demographic groups are most suspecptible to experiencing anxiety and depression.

Impact

By noticing trends in which demographic groups are more susceptible to symptoms of anxiety and depression, we will have a better understanding of how America's mental health has been damaged over the course of the Covid-19 pandemic. In addition, we will be more cognizant of people who fall into these demographical categories and ensure that they receive the mental health resources and treatment.

Dataset

I will use the dataset Indicators of Anxiety or Depression Based on Reported Frequency of Symptoms. I will look at the following demographic categories over the course of multiple months from 2022-onwards.

• Age
• Sex
• Gender Identity
• Sexual Orientation
• Race
• Education
• Disability Status
• State of Residence

import pandas as pd

df = pd.read_csv('Indicators_of_Anxiety_or_Depression_Based_on_Reported_Frequency_of_Symptoms_During_Last_7_Days.csv')
df.head()

	Indicator	Group	State	Subgroup	Phase	Time Period	Time Period Label	Time Period Start Date	Time Period End Date	Value	Low CI	High CI	Confidence Interval	Quartile Range
0	Symptoms of Depressive Disorder	National Estimate	United States	United States	1	1	Apr 23 - May 5, 2020	04/23/2020	05/05/2020	23.5	22.7	24.3	22.7 - 24.3	NaN
1	Symptoms of Depressive Disorder	By Age	United States	18 - 29 years	1	1	Apr 23 - May 5, 2020	04/23/2020	05/05/2020	32.7	30.2	35.2	30.2 - 35.2	NaN
2	Symptoms of Depressive Disorder	By Age	United States	30 - 39 years	1	1	Apr 23 - May 5, 2020	04/23/2020	05/05/2020	25.7	24.1	27.3	24.1 - 27.3	NaN
3	Symptoms of Depressive Disorder	By Age	United States	40 - 49 years	1	1	Apr 23 - May 5, 2020	04/23/2020	05/05/2020	24.8	23.3	26.2	23.3 - 26.2	NaN
4	Symptoms of Depressive Disorder	By Age	United States	50 - 59 years	1	1	Apr 23 - May 5, 2020	04/23/2020	05/05/2020	23.2	21.5	25.0	21.5 - 25.0	NaN

Potential Problems

A challenge that I will face with this dataset is that it collects data over multiple months over the course of almost 3 years. In that time, the percentage of people who experience symptoms of anxiety and depression in a specific demographic could change, and I will have to factor that into my model.

Method

I will use the clustering method for my project. I will group together the factors that contribute to similar levels of anxiety and depression symptoms. In addition, I will attempt to use a classification method to predict if someone who falls in certain demographic groups will be susceptible to mental illness.