Abstract

The COVID-19 pandemic caused an unexpected impact on society, the derivative condition of the pandemic impact applied to people’s mental health. In this study, we propose to make a comparison of mental health disorder statistical results between the pre-pandemic period and during the pandemic period. We aim to investigate the change of mental health disorder statistical results in pre-pandemic and during the pandemic period. Discuss the social facts that caused the condition.

Keywords: COVID-19, Data Analyze, Mental health disorders

Introduction

The COVID-19 pandemic and the resulting economic recession have negatively affected the mental health of many people. Since the first confirmed case of COVID-19 was reported in the United States in January 2020, the disease has had a massive impact on all aspects of United States society. Like many other countries worldwide, the number of cases and deaths caused by COVID-19 has risen sharply. The travel ban began in mid-March 2020. The different epidemic prevention measures and policies of various states and governments have widely appealed to everyone to wear masks and social distancing. Although these measures may reduce the spread of Severe Acute Respiratory Syndrome Coronavirus 2, they may also have a negative impact on the economy, employment, and public health.

Mental health disorders are health conditions affected by different features, including emotion, behavior, and the environment (or a combination of these). [7] The COVID-19 infection is sudden, widely disseminated, lacks specific drugs, and life-threatening if it is not treated in time. Besides, the information overload of the epidemic has caused a significant impact on the public's psychology, causing them to feel panic, anxiety, worry, and depression. For people, staying at home for a long time must reduce going out and being unable to study, work, and participate in social activities normally, which exacerbates anxiety and depression. Based on the future uncertainty, people are increasingly concerned about the mental health sequelae of the COVID-19 crisis. According to probability samples [3], it is reported that among the United States adults, psychological distress in April 2020 has increased compared to 2018-19.

Literature Review

We reference the processes of the longitudinal study of Dutch case-control cohorts [1]. In this paper, the author made a comparison between two periods (pre-pandemic and during the pandemic) with the survey results come from people with (n = 1181) or without (n = 336) mental health disorder symptoms.

We think there are some limitations in this study; the first one is that this paper’s study is a regional study that only focused on Dutch people, which means the number of samples could be small. The second is the data that the study used comes from the survey result provided by unprompted people. Some conditions happen during the process of collecting respond from these people. Moreover, the paper [1] indicated that some people did not respond after the first response or even never respond. These conditions reduce the number of samples, and we think these conditions caused bias to the study’s conclusion. Furthermore, due to the general data protection regulation, we can not access the actual data. The data content is challenging to quantify because the responses are all in text form. Therefore, we propose using the Anxiety and Depression Household Pulse Survey data that comes from Census Bureau which is clean and quantifiable.

Method

Purpose of Survey

The Household Pulse Survey aimed to show the level of anxiety and depression of United States people under the impacts of the COVID-19 pandemic in society and economy. [2]

Data Source

The data of the Household Pulse Survey come from the U.S. Census Bureau and five other federal agencies. The basic process to collect the data is to send an innovative email or text message to a randomly selected person. The contact information comes from Census Bureau Master Address File Data. Each email address or phone number was linked with one housing unit’s address[2].

Survey Questions

The questionnaire questions for every seven days asked the participants to make a self-evaluation based on the level of anxiety and depression that adapted to Patient Health Questionnaire-2 (PHQ-2) [5] and Generalized Anxiety Disorder 2-item (GAD-2) [6] standard. All the questionnaire questions are multiple-choice questions, and the participant needs to choose each question in the questionnaire. The response to each question from the participant will be considered as a numerical value.

Scoring and Estimation

The choices for each question in the questionnaire are the same, and all the choices are assigned a numerical value from 0 to 3. The greater numerical value indicates the severity of the symptoms. If the sum of the response under the PHQ-2 standard equals three or greater than three, the participant will be considered as associated with diagnoses of major depressive disorder[2]. If the sum of the response under the GAD-2 standard equals three or greater than three, the participant will be considered associated with generalized anxiety disorder diagnoses[2].

Comparison between infection/death ratio and level of anxiety and depression

We want to find out how the level of the COVID-19 pandemic in the region and the intensity of restriction measures that affect the level of anxiety and depression live in that region.

Data Processing

The Household Pulse Survey dataset included information about the open survey period, the percentage of participants with symptoms of anxiety disorder or depressive disorder in different groups. Those diverse groups are age, gender, state, education level, and race/Hispanic ethnicity. We divided those groups into the corresponding subgroup. Grouped by age are as follows: 18 - 29 years, 30 - 39 years, 40 - 49 years, 50 - 59 years, 60 - 69 years, 70 - 79 years, 80 years and above. Grouped by education levels are as follows: Less than a high school diploma, High school diploma or GED, Some college/Associate's degree, Bachelor's degree or higher. Grouped by race/Hispanic ethnicity is Hispanic or Latino, Non-Hispanic white, single race, Non-Hispanic black, single race, Non-Hispanic Asian, single race, Non-Hispanic, other races and multiple races. We use the R language to process our data and then generate corresponding time series plots based on these groups and subgroups. [3]

1. The Structure of Dataset

The time-series COVID-19 confirmed case dataset includes observation date, province or state of the observation, country of observation, and the cumulative number of confirmed cases till that date. The time-series COVID-19 deaths dataset includes observation date, province or state of the observation, country of observation, and observation province/state population. And the cumulative number of death cases till that date.

2. Calculating numbers

Since the confirmed case and death case numbers in both time series COVID-19 datasets are the cumulative numbers of cases till that date, we set each month as a period and extract the case number on the last day of each month. To calculate the difference of national infection/death case number, sum up all the record numbers vertically and subtract the last month’s case number.

To calculate the infection/death ratio of chosen states, we want to calculate the infection/death ratio of the COVID-19 pandemic in New York state. We select all the New York state records in the dataset, sum up the case number each month and population vertically, finally use the sum of the case number each month to divide by the sum of the population to get the infection/death ratio.

The time series plot about age and anxiety symptoms is shown in figure 1. Obviously, between April 2020 and March 2021, the percentage of people with anxiety symptoms among younger people is higher than the percentage of people with anxiety symptoms among older people. The younger the group, the higher the percentage. 59% of young people in the 18-29 years subgroup reported symptoms of anxiety and/or depression in October 2020. Except for the elderly over the age of 80, the percentage changes in the remaining groups during the epidemic were almost the same.

The time series plot about gender and anxiety symptoms is shown in figure 2. Between April 2020 and March 2021, The percentage of females with anxiety symptoms fluctuates between 37%-47%, and the percentage of males with anxiety symptoms fluctuates between 30%-38%. The percentage of females with anxiety symptoms during the epidemic is higher than that of males, about 10% higher. The percentage changes in the female and male groups during the epidemic were almost the same.

The time series plot about age and anxiety symptoms is shown in figure 1. Obviously, between April 2020 and March 2021, the percentage of people with anxiety symptoms among younger people is higher than the percentage of people with anxiety symptoms among older people. The younger the group, the higher the percentage. 59% of young people in the 18-29 years subgroup reported symptoms of anxiety and/or depression in October 2020. Except for the elderly over the age of 80, the percentage changes in the remaining groups during the epidemic were almost the same.

The time series plot about race and anxiety symptoms is shown in Fig. 4. Between April 2020 and March 2021, the average percentage of people with anxiety symptoms among each subgroup from high to low is: Less than a high school diploma(43.63%), Some college/Associate's degree (38.86%), High school diploma or GED(36.43%), Bachelor's degree or higher (29.33%).

According to Fig. 5, in the early period of the COVID-19 pandemic, the New York state had the highest increase rate of infection ratio between February and April in 2020. The infection ratio of New York state became approached to steady between May and September. However, the infection ratio of New York state increased rapidly after October. Compare to California and Florida. New York state had a lower infection ratio after November in the year 2020.

Florida and California had a similar infection ratio in the early period (between February to June)of the COVID-19 pandemic. Florida’s infection ratio increased rapidly after June, and California’s infection ratio increased rapidly after November. Florida had the highest infection ratio between July and November, and California had the most considerable increased rate after November.

The death ratio of each state shows a strong positive relationship between the infection ratio and death ratio, which had the same increase pattern in the same period. The infection ratio graph and the death ratio graph of these three states show that the New York state had a high level ratio during the COVID-19 pandemic in 2020. However, since the population in these three states are different, New_York_population = 19453561, California_population = 39512223, Florida_population = 21477737, which means the number of confirmed cases in California and Florida after July are greater than the number of confirmed cases in the New York state[4].

Discussion

During the COVID-19 pandemic, the number of responses to the survey indicated people’s anxiety or depression level. According to the Fig. 7 and the table of the number response of survey, there was a rapid increase of confirmed number from June to July, and the table also had a huge increase in response rate in between July 16-21 and August 19-31 from 2.9% to 10.3%. The massive increase in response rate indicated that many people are starting to think more seriously about the COVID-19 pandemic.

According to Fig. 8, with the same period of the huge increase in the response rate, the percentage of symptoms of anxiety disorder and depressive disorder showed a pronounced peak for all three categories of the statistical results. The confirmed number of United States, the response number of the survey, and the percentage of symptoms of anxiety disorder and depression all showed a noticeable growth in the same period compared to the early period of the COVID-19 pandemic. These data reflected a positive relationship between the number of confirmed cases, response number of the survey, and the people’s level of anxiety and depression, which means as the severity of the COVID-19 pandemic increase, the level of anxiety and depression of people in the United States also increases, the severity of the pandemic affected people’s anxiety and depression level directly.

Besides the number of confirmed or death cases, the severity of restriction measures could be a reason that caused the increase in people’s anxiety and depression level. According to the official COVID-19 monitoring website of California, Florida, and the New York state, these three states have different severities of pandemic restriction measures. Florida had the least severity of pandemic restriction measures compared to what California and the New York state had. According to Fig. 11, the percentage of Florida is between 36% to 42% in most of the period. According to Fig. 9, the percentage of California is increased from 34% to 46% as the severity of the COVID-19 pandemic developed in the year 2020. However, According to Fig 10, the percentage of New York state did not reflect an obvious trend but repeat a bounced movement on the graph.

Conclusion

In summary, the severity of symptoms of depression, anxiety, or obsessive-compulsive disorder of people in the United States is systematically increasing with the early development of the epidemic. It is also affected by different quarantine measures by various states and governments with different trends, but the relation of anxiety level and the different groups of quarantine measures are not obvious. Different groups of people have the same changing trend in the pandemic but have different degrees of impact. With the development of the pandemic, more vaccinations, and other implementation of transmission mitigation strategies, it is necessary to continue to study the long-term impact of the COVID-19 pandemic on the mental health of the population.

Novelty

Our parent paper on the research on depression of the COVID-19 epidemic in the Netherlands mainly studied and compared the patients with depression symptoms and people without depression symptoms affected by the epidemic. Comparing the research of the Netherlands, the situation in the United States is different, and the number of responses to the questionnaire is larger than that of the Dutch research, and different results will be obtained. Also, we use the daily and monthly death data of confirmed cargoes during the epidemic to explore the impact of the COIVD-19 epidemic on people’s mental health, which has a more quantitative result than relying on only questionnaire responses. The questionnaire data source is no longer a fixed experimental object but a random sample of participants from different regions. Thus a higher randomness sample is more statistically meaningful.

References

1. Pan, K., PhD, Kok, A. A., PhD, Eikelenboom, M., LLM, Horsfall, M., MSc, Jörg, F., & Luteijn, R. A. (2020). The mental health impact of the COVID-19 pandemic on people with and without depressive, anxiety, or obsessive-compulsive disorders: A longitudinal study of three Dutch case-control cohorts (pp. 121-129, Rep.). Amsterdam: Department of Psychiatry, Amsterdam Public Health, Amsterdam University Medical Center.

2. Census Bureau, U. (2020). Indicators of anxiety or depression based on Reported frequency of symptoms during last 7 days. Retrieved April 06, 2021, from https://data.cdc.gov/NCHS/Indicators-of-Anxiety-or-Depression-Based-on-Repor/8pt5-q6wp

3. Nirmita Panchal, R., & 2021, F. (2021, February 10). The implications of Covid-19 for mental health and substance use. Retrieved April 06, 2021, from https://www.kff.org/coronavirus-covid-19/issue-brief/the-implications-of-covid-19-for-mental-health-and-substance-use/

4. Johns Hopkins, U. (2021, February 28). Novel Corona Virus 2019 DATASET. Retrieved April 06, 2021, from https://www.kaggle.com/sudalairajkumar/novel-corona-virus-2019-dataset?select=time_series_covid_19_deaths_US.csv

5. Patient health Questionnaire (PHQ-9 & PHQ-2). (2020, June). Retrieved April 06, 2021, from https://www.apa.org/pi/about/publications/caregivers/practice-settings/assessment/tools/patient-health

6. Sapra, A., Bhandari, P., Sharma, S., Chanpura, T., & Lopp, L. (2020, May 21). Using generalized anxiety disorder-2 (gad-2) and gad-7 in a primary care setting. Retrieved April 06, 2021, from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7306644/

7. W.H.O. (2019, November 28). Mental disorders. Retrieved April 06, 2021, from https://www.who.int/news-room/fact-sheets/detail/mental-disorders