Introduction

Coronavirus, also called as COVID-19, is a pandemic disease that has caused widespread concern about the economic hardships both for consumers and businessmen of various communities that are present across the globe. Most companies have their own business continuity plans but that may not fully address the fast moving unknown variables of an outbreak such as COVID-19 ( (Samuel & Devi, 2015); ‘COVID-19 global economic recession: Avoiding hunger must be at the centre of the economic stimulus’, 2020). As the COVID-19 unfolds, the economic market melts down because of the pandemic disease, thus pushing all the wealthy (Baheerati & Devi, 2018; Bank & Bank, 2020). A special report was made looking for the wealthy changes of the world’s most successful entrepreneurs (Fathima & Preetha, 2016; Soni, No date). Stock markets across the globe have dropped significantly for the past few months. With about 100 countries, that are closing national borders for the past few months and thus the tourism industry has come to a screeching halt. Global Economy has shrunk 1% in 2020 due to the COVID-19 pandemic (Atkeson, 2020; Ilankizhai & Devi, 2016). According to the analysis done by the UN Department of Economic And Social Affairs [DESA] says that the pandemic named COVID-19 has the capability of disrupting global supply chains and international trade.

UN DESA’s, world economic forecasting model estimated that the best and the worst case scenarios for global growth are prone to occur in the year of 2020. The severity of the economic impact depends on 2 factors, duration of restriction and movement of people during the economic activity in major countries.

Figure 1, Positive responses (71.03%) are in green colour, negative responses (15.89%) are in red colour and responses for maybe (13.08) are in blue colour.

Figure 2, Positive responses (42.06) are in blue colour and negative responses (57.94%) are in red colour.

Figure 3, Positive responses (49.53%) are in blue colour and negative responses (50.47%) are in red colour.

Figure 4, Responses for trade (40.19%) are in red colour, responses for unemployment (27.10%) are in green colour and responses for both (32.17%) are in blue colour.

Figure 5, Positive responses (46.73%) are in green colour, negative responses (31.78%) are in red colour and responses for both (21.50) are in blue colour.

Figure 6, Positive responses (67.29%) are in red colour and negative responses (32.71%) are in blue colour.

Figure 7, Positive responses (33.64%) re in green colour, negative responses (42.06%) are in red colour and responses for both (24.30%) are in blue colour.

Figure 8, Positive responses (33.64%) are in green colour, negative responses (42.06%)are in red colour and responses for maybe (24.30%) are in blue colour.

Figure 9, Positive responses (68.22%) are in blue colour and negative response (31.78%) are in red colour.

Figure 10, Positive responses (66.36%) are in blue colour and negative responses (33.64%) are in red colour.

Figure 11, Positive responses (63.55%) are in red colour and negative responses (36.45%) are in blue colour.

Figure 12, Positive responses (62.62%) are in red colour and negative responses (37.38%) are in blue colour.

Figure 13, Positive responses (70.09%) are in blue colour and negative responses (29.91%) are in red colour.

Figure 14, Positive response (43.93%) are in green colour, negative responses (27.10%) are in red colour and responses for maybe (28.97%) are in blue colour.

Figure 15, Positive responses (46.73%) are in green colour, negative responses (26.17%) are in red colour and responses for maybe (27.10%) are in blue colour.

Figure 16, X axis represents gender of study participants and Y axis represents the frequency of responses in relation to increase in gold price during this pandemic.

Figure 17, X axis represents gender of study participants and Y axis represents the frequency in response to change in market price.

Figure 18, X axis represents gender of study participants and Y axis represents the frequency of responses.

Figure 19, X axis represents gender of study participants and Y axis represents the frequency.

Figure 20, X axis represents gender of study participants and Y axis represents the frequency of responses.

China, the epicenter of COVID-19 pandemic, turning a corner (Harsha, 2015; Mallya & Silva, 2020; Toth, 2020). Number of reported local transmission cases are hovering near zero. Daily life is returning back to normal. However, the economic data for the first 2 months of the year 2020, shows that the real damages to the country’s finances. China’s business activity has slowed due to the increased spread of COVID-19. Other countries have also felt the impact of COVID-19 (Dave & Preetha, 2016).

In Canada, nearly 1 million people have applied for unemployment benefits. Hard hit countries like Italy, Spain, etc. which already had suffered high unemployment and are expected to see heavy economic blows (Abigail, 2019; Amburgey & Birinci, 2020). The UN estimates that COVID-19 can cause upto $2 Trillion shortfall in the global income (Berardis et al., 2020). Bright side is that analysts have forecasted the recovery in the 3rd quarter in the year of 2020 (David, 2019; Gans & 2020a, ; Harrs & No date, ). Investors are tearing up that the spread of coronavirus could destroy economic growth and the government action is not enough to decline the spread of the coronavirus (Gans & 2020b, ; Shruthi & Preetha, 2018). In response, the central banks of many countries have slashed interest rates. At the sectoral level, tourism and travel related industries have the hardest hit and the authorities have encouraged social distancing and consumers to stay indoors (Bank et al., 2020; Choudhari & Jothipriya, 2016).

The main aim of this study is to create awareness about the economic impact that occurs due to COVID-19. Crisis drop values are only for low level export. Other branches that are affected remain as a mystery. Data about the crisis is revealed only after the report is given out. Survey, a set of questions is to be passed onto the people and collected the response on how they are affected in terms of the economy.

Materials and Methods

This study is a questionnaire based survey. The people were selected at random. The questions were prepared on their own and were distributed through an online survey link, the study in the general population including south indian based Chennai population. The participants were explained about the purpose of this study in detail. The pros of this study are the depth view of the impact that is caused due to the lockdown in the global scale is analysed along with the considered variables. The cons of this study is the psychology of the people suffering in this global impact is not yet understood clearly. The sampling of the survey is about 100. The sampling method is simple random sampling. The measure to be taken to minimize sampling bias are survey software participants randomly and to avoid asking irrelevant questions. The internal validity depends on the independent variable. The external validity is to justify results. A questionnaire, about 15 questions, was prepared. Data collection software was used. The method of representation of each variable is pie chart. The statistical test used is paired ‘t’ test. The independent variables are sex, weight, hair, attitude, personality, etc. The dependent variable is age. The type of analysis is descriptive analysis. The results were collected and analysed carefully using software (SPSS) inferential statistics were done using chi square test.

Results and Discussion

Figure 16 shows out of 68% of the population who are aware, 36% constitute male and 32% constitute female. Hence, males are more aware of the increase in the gold price than females. Association between gender and awareness about the increase in gold price was done by using Chi square test. (Pearson’s Chi square value: 1.260, P value: 0.313 (>0.05), hence insignificant)

Figure 17 shows out of 67% of the participants who were aware 36% are male and 31% are female. Hence, males are more aware of the change in the share market values globally. Association between gender and change in the share market values globally was done using Chi square test. (Pearson’s Chi square value: 0.786, P value: 0.424 (>0.05), hence insignificant)

Figure 18 shows out of the 75% of the population who have knowledge about the impact for app creators, 42% constitutes male and 33% constitutes female. Hence, males have more knowledge regarding the impact for app creators. Association between gender and knowledge regarding the impact for app creators was done using Chi square test. (Pearson’s Chi square value: 0.104, P value: 0.832 (>0.05), hence Statistically insignificant)

Figure 19 shows out of 47% of the participants who are aware of the contribution of fuel to the global economy, 25% constitutes male and 22% constitutes female. Hence, males are more aware of the contribution of fuel to the global economy than females. Association between gender and the contribution of fuel to the global economy was done using Chi square test.(Pearson’s Chi square value: 0.542, P value: 0.804 (>0.05), hence Statistically insignificant)

Figure 20 shows out of the 50% of the participants who are aware of the stockpile of petroleum, 25% are males and 25% are females. Hence, both males and females are equally aware that the stockpile of petroleum. Association between gender and stockpile of petroleum was done using Chi square test. (Pearson’s Chi square: 5.031, P value: 0.084 (0.05), hence, Statistically insignificant)

The survey was conducted among a small scale population and the results were statistically analysed and were studied. When asked about the knowledge of awareness about the impact of COVID-19 on global wealth, the majority i.e. 71% responded that it has an effect, about 16% did not have any idea and the rest 13% were not sure about the impact. When asked about the impact of the lockdown due to coronavirus on the country economy, there is a tie, i.e. 50% responded that it is increased and 50% responded that it is decreased. When asked about the knowledge awareness about the change in share market values globally, 63% population were aware and the rest 37% population were not aware.

Figure 1 represents that when asked about the knowledge of awareness about the impact of COVID-19 on global wealth, the majority i.e. 71.03% responded that it has an effect and but 15.89% responded that it did not have any effect and the rest 13.08% were not sure about the impact. Figure 2 represents that when asked about the effect on the tourism industry, 57.9% of the population responded that it has increased and the rest 42.1% responded to it has decreased. Figure 3 represents that when asked about the effect of the lockdown due to coronavirus on the country economy, there is a tie, i.e. 50.5% responded that it is increased and 49.5% responded that it is decreased. Figure 4 represents that when asked about the sector where there would be most impact, 271% responded that it would be unemployment, 40.2% responded that it would be trade, export and import and 32.7% population responded that it could be both unemployment and trade, could have an equal impact. Figure 5 represents that when asked about the lockdown effect on transport facilities, 46.7% responded that it has an effect and 31.8% responded that it has no effect and the rest 21.5% responded that there could be some effect. Figure 6 represents that when asked about the rise in cost of food products during lockdown 67.3% responded that they have noticed it but 32.7% responded that they have not noticed it. Figure 7 represents that when asked about which sector does the coronavirus have a major impact in industries, 46.7% opted for trade as a sector that has a major impact during this lockdown, 31.8% responded that it is unemployment and the rest about 21.5% responded that it is the transport sector that gets more impact than the others. Figure 8 represents that when asked about the cost of living of an individual, whether they have increased or not, 33.6% responded that it has increased, 42.1% responded that it has not increased and the rest 24.3% was not even sure about the impact. Figure 9 represents that when asked about the effect of lockdown concept on gaming companies, 68.2% of the population responded that the gaming companies are benefited and the rest 31.8% of the population responded that it is not benefitted. Figure 10 represents that when asked about the effect of the lockdown concept on entertainment media, 66.4% of the population responded that they are benefitted and the rest 33.6% responded that they are not benefited. Figure 11 represents that when asked about the increase in change in the gold price, 63.6% responded that there is an increase and the rest 36.4% responded that there was no increase. Figure 12 represents that when asked about the knowledge awareness about the change in share market values globally, 62.6% of the population were aware and the rest 37.4% of the population were not aware. Figure 13 represents that when asked about the impact of app creators, 70.1% responded that they are benefitted through some apps like zoom, google classrooms, etc. and the rest, 29.9% responded that they were not benefited. Figure 14 represents that when asked about the knowledge of fuel as a contribution to the global economy, 43.9% responded yes, 27.1% responded no and the rest 29% was not sure. Figure 15 represents that when asked about the need of indian government to stockpile petroleum, 46.7% responded that it is necessary to stockpile petroleum while 26.2% responded that it is of no need and the rest 27.1% was not sure.

When gender was compared with the increase in gold price, the P value was 0.313 and it was found statistically insignificant (Figure 16). When gender was compared with the change in the share market values globally, the P value was 0.424 and it was found statistically insignificant (Figure 17). When gender was compared with impact for app creators like google classroom, video conference call, etc, the P value was 0.832 and it was found statistically insignificant (Figure 18). When gender was compared with the contribution of fuel to the global economy, the p value was 0.804 and it was found statistically insignificant (Figure 19). When Gender was compared with the stockpile of petroleum, the p value was 0.084 and it was found to be statistically non significant (Figure 20).

According to the previous researchers, financing strategy emphasizes the key elements in the spread of communicable diseases. Financial risks and global household that are exposed are very much significant. More than 50% of the population are aware of the impact of global wealth due to the pandemic disease. 82% of this study matches the above study (Engelgau, Karan, & Mahal, 2012). This study is not similar to the above study (Fernandes & No date, ). It is more or less similar to the above study (Iyer, Devi, & Priya, 2019). It is more or less similar to the above study (Swathy & Sethu, 2015). Only 63% of this study matches the above study (Timothy, Devi, & Priya, 2019). According to the previous researchers, the prevalence of the communicable diseases, various risk factors demonstrated various different patterns among various degrees of socio-economic Inequalities (Hosseinpoor et al., 2012). It is more or less similar to the above study (Devi & Sethu, 2018; Ghaffar, Reddy, & Singhi, 2004; Renuka & Sethu, 2015).

This study was done on a small scale population. It can also be done on a large scale population with more number of questions and with more information about this disease. Emergence of communicable and non-communicable diseases loading to the health issue suggest the need for services that should increase in the future.

Conclusions

Within the limits of the present study, it is evident that the majority of the population were aware of the impact caused on the global wealth due to the pneumonia associated with the global pandemic outbreak, COVID-19. This survey may help the society to be conscious of global wealth and thereby maintain their own wealth.

Conflict of Interest

Nil.

Funding Support

Nil.