The impact of the Covid pandemic on tourism

Measuring social, cultural, economical background

Examining data from three countries:

Hungary - Romania/Transylvania – Italy

Research Report

Erasmus+ HEAL ALL

2020-1-HU01-KA203-078799

HEAlthy Life ALLiance

for Health Tourism Education Development and Reorganisation

Authors:

P. Takács, M. Móré, Gy. Mara, F. Martignago, E. Lázár, I. Miklóssy, G. Vámosi, M. Láczay,

Z. Szakál, Zs. Kristóf, L. Varga, B. Nagy, B. Varga P., G. Helmeczi, K. Tóth, L. Székely, E. Bálint,

B. Bandiziol, A. Horváth, A. Gurzó, K. Lövei-Kalmár, E. Orosz K., Sz. Zs. Varga

The impact of the Covid pandemic on tourism. Consumer Research Report, 2023 - Erasmus+ HEAL ALL. Measuring social, cultural, economical background. Examining data from three countries: Hungary - Romania/Transylvania – Italy. Erasmus+ HEAL ALL, 2020-1-HU01-KA203-078799

ISBN:

Contents

Abstract. 4

INTRODUCTION.. 5

The Covid-19 and its effects. 5

Materials and methods. 10

RESULTS. 12

Basic analysis - Italy. 12

Basic analysis Transylvania. 15

Basic analysis - Hungary. 17

Appearance of areas of interest in the three samples. 19

Covid involvement. 21

Estimation of changes in tourist habits. 22

DISCUSSION.. 23

LITERATURE. 24

APPENDIX. 26

I. List of attached files. 26

II. A few comments – based ont he results of the research and the processing of the literature. 27

III. Additional sources used during the research. 36

Abstract

Introduction: During the coronavirus pandemic, many aspects of individual and social human existence suffered forced changes. It was no different in the field of tourism either - in fact, there were especially big changes in this service sector and in the areas related to it. Within the framework of the Heal All Erasmus grant (as a background study), the impact of the virus on tourism was researched in three countries (Hungary, Romania - mainly Transylvania, Italy).

Methods and materials: The investigations were conducted by means of a questionnaire. The questions concerned a) individual (and at the same time family) travel habits (before and immediately after the pandemic), b) the background of the virus (the level of knowledge and degree of involvement in certain issues), c) future plans and behavioral patterns. The basic socio-economic situation of the respondents was also assessed.

Results: After cleaning the data and querying the basic sample characteristics, the differences in the sub-samples of each country were visible and revealed. In the Hungarian sample, a larger young group (high school graduates) was visible, and in the Italian sample there was a larger group that was older, perhaps already retired. In the Transylvanian sample, the proportion of those pursuing higher education was higher. The Hungarian and Transylvanian sub-samples were perhaps closer to each other, the Italian sub-sample differed more from the other two. These results led to the decision that the comparison of sub-samples would not give real results, since samples with different basic characteristics were available from the populations of the three countries under investigation. Thus, the subsamples were compared using only percentage data. The further analyzes were therefore not aimed at the differences between the countries, but rather at the changes in tourism habits caused by Covid in the given samples.

A factor analysis was carried out for each tourism branch - separately for each country. The result showed that the respondents interpreted the same major branches - they reflected the same grouping in all three countries.

The analysis of the complex effect of the pandemic showed the difference between the sub-samples. The Transylvanian/Romanian sub-sample showed a (significantly) greater involvement of the pandemic. The Italian and Hungarian sub-samples indicated almost the same involvement.

The respondents also indicated differences in the changes in tourism habits in the sub-samples. There was one question in which the responses of all three countries showed a similar correlation (opinion did not change: the question of interest in urban and rural tourism experiences). The largest change was indicated by respondents from Transylvania. In their case, there was a significant difference in five of the seven questions (travel domestic or foreign; duration of travel; target; transport; travel mode). In the case of Hungarian and Italian respondents, there were significant differences in three questions (HU: travel domestic or foreign; duration; nature or culture; IT: target; transport; travel mode).

Discussion: The results reflect the picture of the effects of the pandemic that has already been presented in many places. It can clearly be said that social groups in different economic and social situations were able to respond to the challenges in different ways. Currently, perhaps not enough time has passed for humanity to be able to paint a real picture of the actual effects of the pandemic. The areas and extent of the "covid aftermath / post covid" are doubtful. The consequences that are hidden below the surface and can be felt in the long term - in economic, social, health and individual health and other areas - are only now beginning to unfold. Their deep analysis (e.g. meta-analysis) and the correct interpretation of the results do not only allow for historical/historical descriptions. The pandemic allows a deeper insight into the processes of the systems operated by people. The hitherto unseen situations showed (and will show later) the strengths and weaknesses in the individual subsystems, the strong and weak nodes in the connection networks. The same ideas can be interpreted in the field of tourism. The presented research was only able to reflect a very small detail of the changes, but there is no doubt that it is no longer possible to return to the state before the pandemic - the branches of tourism are being restructured - the tourist service provider must adapt to this situation.

Appendix: During the research work related to the tender and the discussion of the results, a lot of experience was accumulated in the research team. We found it worthwhile to summarize them and present them to the readers in a more structured way. These thoughts are included in the Appendix 'A few comments – based on the results of the research and the processing of the literature' at the end of the paper.

Keywords: Covid-19, pandemic, effects, tourism, Heal All

INTRODUCTION

During the coronavirus pandemic, many aspects of individual and social human existence suffered forced changes. It was no different in the field of tourism either - in fact, there were especially big changes in this service sector and in the areas related to it.

Within the framework of the Heal All Erasmus + grant (as a background study), the impact of the virus pandememic on tourism was researched in three countries (Hungary, Romania - mainly Transylvania, Italy).

The publication presents the results in the following sections.

The first chapter provides a brief historical description of the development of the pandemic. The summary describes the beginnings of the worldwide epidemic, describes the goals and partial results of the Heal All application and the development of the pandemic in the countries participating in the application. The next chapter presents the research questionnaire, the method of data collection, and the basic analysis that determined the main direction of the further analysis studies. The results of the descriptive and analytical study are presented in the third chapter. The Discussion chapter summarizes and interprets the results. During the research work related to the tender and the discussion of the results, a lot of experience was accumulated in the research team. We found it worthwhile to summarize them and present them to the readers in a more structured way. These thoughts are included in the Appendix 'A few comments – based on the results of the research and the processing of the literature' at the end of the paper.

The Covid-19 and its effects

COVID-19, also known as the coronavirus disease, is a highly contagious respiratory illness caused by a novel (new) coronavirus. It was first identified in Wuhan, China in December 2019 and has since spread globally, becoming a pandemic.

The virus is primarily spread through respiratory droplets when an infected person talks, coughs or sneezes. COVID-19 primarily attacks the respiratory system, but it can also affect other organs and systems.

Common symptoms of COVID-19 include fever, cough, shortness of breath, fatigue, body aches, loss of taste or smell, and a sore throat. Some people may also experience gastrointestinal symptoms such as nausea, vomiting and diarrhea. In severe cases, COVID-19 can lead to pneumonia, acute respiratory distress syndrome (ARDS), organ failure, and death.

It's important to practice preventive measures to slow the spread of COVID-19, such as washing your hands frequently, wearing a mask in public settings, practicing physical distancing, and avoiding large gatherings. Vaccines are also available for individuals over the age of 16 in most countries and are an effective way to reduce the risk of getting sick from COVID-19.

It is crucial that individuals take the pandemic seriously and follow public health guidelines to help control its spread and protect themselves and others.

The rapid spread of the virus was facilitated by international travel, leading to widespread community transmission in many countries. The virus has also been found to spread more easily in crowded and enclosed spaces, making control and containment efforts challenging. The pandemic has had a significant impact on public health, economies, and daily life globally.

SARS-CoV-2 beginnings. The timeline of the COVID-19 pandemic is as follows [1][2]:

· December 12, 2019: The first cases of COVID-19 are reported in Wuhan, China.

· December, 2019: The World Health Organization (WHO) China National Center has received reports of several cases of pneumonia of unknown origin, symptoms of which include shortness of breath and fever. Most of these cases were linked to Wuhan, China (Huanan Seafood Wholesale Market).

· January 1, 2020: Huanan Seafood Wholesale Market in Wuhan has been closed in China. Reason: concern about a resurgence of the 2002-2004 SARS (Severe Acute Respiratory Syndrome Coronavirus or SARS-CoV-1).

· January 2, 2020: WHO started dealing with cases at three organizational levels (national office, regional office and headquarters). The WHO Incident Management Support Team (IMST) became operational according to protocol.

· January 3, 2020: China notified the WHO of 40 new cases - similarly cases of pneumonia of unknown etiology.

· January (beginning) 2020: The virus is identified as a new strain of coronavirus and begins to spread beyond China.

· January (beginning), 2020: The genetic sequence of the atypical pneumonia virus, named Wuhan-Hu-1, was discovered by professor Yong-Zhen Zhang at Fudan University in Shanghai. The full genetic sequence of the virus will remain unavailable to the rest of the world for a significant period of time.

· January 10, 2020: The WHO begins using the term "2019 Novel Coronavirus" or "2019-nCoV" for the disease.

· January 10, 2020: Edward C. Holmes (University of Sydney, Australia, in collaboration with Zhang) uploaded the Wuhan Pandemic virus genome sequence “Wuhan-Hu-1” (MN908947) to GenBank.

· January 11, 2020: The WHO received the genetic sequence of the virus from China.

· January 11, 2020: The USA (CDC, Level 1 or “practice usual precautions.”) has warned travelers about the increased dangers of traveling to the Chinese province of Wuhan.

· January 11, 2020: China has announced the first death linked to the new virus.

· January 13, 2020: The Thai Ministry of Public Health - relying on laboratory tests - announced the first appearance of the SARS-CoV-2 virus outside of China.

· January 14, 2020: The WHO confirmed the transmission of the SARS-CoV-2 virus from person to person.

· January 15, 2020: The Japanese Ministry of Health, Labor and Welfare also reports a case outside of China, which is also a laboratory-confirmed case.

· January 17, 2020: The USA has begun screening passengers for symptoms of the 2019 novel coronavirus on flights from Wuhan, China to San Francisco and on connecting domestic flights.

· January 19, 2020: 282 laboratory-confirmed cases of 2019 novel coronavirus were reported from four countries: China (278 cases), Thailand (2 cases), Japan (1 case) and the Republic of Korea (1 case).

· January 20, 2020: The first laboratory-confirmed case of the Cov-2 coronavirus in the United States (the samples were taken on January 18 in Washington state). On the same day United States has activated its Emergency Operations Center (EOC) to respond to the emerging outbreak.

· January 21, 2020: The virus has a "face" (Alissa Eckert and Dan Higgins - red and white virus image).

· January 21, 2020: China confirms human-to-human transmission of SARS-CoV-2 virus.

· January 22, 2020: The WHO International Health Regulations Emergency Committee has not declared SARS-CoV-2 a Public Health Emergency of International Concern (PHEIC).

· January 24, 2020: The US Food and Drug Administration (FDA) has announced that it is "taking critical steps to advance the development of medical countermeasures against the novel coronavirus."

· January 28, 2020: CDC issues a Level 3 travel health advisory for China and US officials are ordered back from Wuhan.

· January 30, 2020: US confirms human-to-human transmission of SARS-CoV-2 virus.

…

· February, 2020: The number of infections and deaths increased; austerity measures begin around the world.

…

· March 11,  2020: More than 118,000 infections and 4,291 deaths have been linked to the virus in 114 countries. The World Health Organization declares COVID-19 a global pandemic.

· March-April 2020: Many countries implement lockdowns and restrictions on movement to slow the spread of the virus.

…

· Summer 2020: Some countries begin to ease restrictions, but many experience a resurgence in cases. – Essentially, by the summer of 2020, the virus had spread across the Earth [30].

…

· Late 2020: Multiple COVID-19 vaccines are developed and begin to be distributed globally.

· 2021: Rollout of vaccines continues, with many countries prioritizing their most vulnerable populations.

· 2022: The pandemic continues to evolve, with new variants emerging and countries adjusting their response strategies based on the latest data and guidance from health experts.

· 2023: By the summer of 2023, Covid has receded; however, it has not yet completely disappeared.

So by 2023, Covid-19 has moderated, but not disappeared. This is confirmed by the reports that are constantly available on the Internet even today [5][6]. Most experts are of the opinion that the virus will not disappear and, like the flu, will appear seasonally in the future [7]. There is no doubt that the characteristics of the spread of Covid-19 and its impact on populations and individuals appear as the aggregate of many factors [8][9]. There are many publications devoted to the exploration of these factors [10][11][12].

Inpact on the economy. The impact of COVID-19 on the global economy has been significant and far-reaching. Some of the key impacts include [19][20][21][22][23][24][26]:

· Job losses: The pandemic has resulted in widespread job losses, particularly in industries such as hospitality, tourism, and retail.

· Business closures: Many small and medium-sized businesses have been forced to close due to the pandemic, leading to further job losses.

· Stock market volatility: The stock markets have experienced significant volatility in response to the pandemic, with sharp drops followed by recoveries.

· Reduction in consumer spending: Consumers have been spending less due to job losses and economic uncertainty, which has impacted the economy further.

· Supply chain disruptions: The pandemic has resulted in disruptions to global supply chains, causing shortages of certain goods and impacting the manufacturing and retail sectors.

These impacts have been felt differently in different countries, depending on factors such as the severity of the outbreak, the effectiveness of the response, and the type of economy. Some countries have been hit particularly hard, while others have been more resilient.

Overall, the impact of COVID-19 on the global economy has been substantial, and the long-term effects are still being determined.

Impact on tourism. The impact of COVID-19 on the tourism industry has been significant and widespread. The pandemic has led to a sharp decline in international travel, with many countries implementing travel restrictions and border closures. The following are some of the key impacts of COVID-19 on the tourism industry [27][28][29]:

· Reduction in international travel: One of the most significant impacts of COVID-19 on tourism has been a sharp reduction in international travel. Many countries have implemented restrictions on incoming travelers and border closures, which have resulted in a decline in the number of tourists visiting popular destinations.

· Decrease in revenue: The reduction in international travel has resulted in a decline in revenue for the tourism industry, with hotels, restaurants, and tourist attractions all experiencing a decline in business. This has had a ripple effect on the local economy, as these businesses are major contributors to the local tax base and employ many people.

· Layoffs and job losses: The decline in the tourism industry has led to widespread job losses and layoffs, with many workers in the hospitality and tourism sectors losing their jobs. In some countries, the tourism industry is a significant employer, and the loss of jobs has had a significant impact on the local economy.

· Impact on related industries: The decline in the tourism industry has also impacted related industries, such as transportation and retail. For example, airlines have experienced a decline in revenue due to reduced demand for travel, and retail businesses have experienced a decline in sales as a result of reduced tourist spending.

· Shifting travel patterns: The pandemic has also resulted in a shift in travel patterns, with many travelers opting for domestic travel over international travel. This has had an impact on local economies, as the tourism industry in some countries is heavily reliant on international tourists.

The long-term impact of COVID-19 on the tourism industry is still uncertain, but it is clear that the pandemic has had a substantial impact on this sector, and recovery will take time. In the meantime, many countries are working to support their tourism industries and help businesses to recover from the pandemic.

The Heal All Erasmus+ project [25][35][36][37]. 'The aim of the HEALALL Project is the international cooperation of institutions supporting health tourism education. Over time, it has become increasingly clear that due to the consequences of the epidemic, tourism is one of the most sensitive sectors of the economy. It also turned out that there is a possibility of rapid regeneration in the sector dust. Training also needs to follow developments and, due to redesign, be prepared for change.'

'Two higher education institutions and universities are participating in the project: the University of Debrecen, Faculty of Health, Sapientia, University of Transylvania, Faculty of Miercurea Ciuc. Both faculties offer education in different areas of tourism. The other partner of the cooperation is INNOVA Northern Great Plain Nonprofit Ltd. (Hungary), a regional development and innovation agency established by the government to boost the regional economy and manage innovative initiatives. Project partner Marco Polo G.E.I.E. (Italy), set up in 2006 with the aim of promoting European partnerships, in particular in the HoReCa sector and in tourism mobility projects. '

'The main measurable results of the program will be:

· Comparative analysis of the tourism sector. The program includes the exchange of best practices at the international level.

· The universities and partners of the consortium assess the needs of the companies and customers interviewed.

· Curriculum subjects are also developed and operated in the most modern e-learning systems.

· The program promotes internationalization through the use of innovative digital access practices.

· A website will also be set up where tourism organizations and practitioners will find useful information. '

A questionnaire survey was prepared in connection with the tender, which provided background information for the tender materials. The primary purpose of the investigations was to reveal the impact of the virus on the surveyed visitors and to examine how individual tourism plans were modified as a result of the pandemic period experienced. Relevant comparisons for the three countries are not possible due to the different population characteristics. (these studies would not be completely methodologically sound either). However, interesting parallels can be drawn regarding the changes mediated by the three distinct (sub)samples.

Among other things, it takes place within the framework of the Heal All tender

- to create a website that supports student internships,

- for the organization of e-twinning educational practices: international, project-based, cooperative education-learning related to tourism;

- study trips between partners.

Covid situation in Heal All partner countries.

The pandemic situation in the partner countries participating in the tender was as follows.

The timeline of COVID-19 in Italy is as follows [13][14]:

· February 2020: The first cases of COVID-19 are reported in Italy, primarily in the northern region of Lombardy.

· March 2020: Italy imposes a nationwide lockdown, becoming one of the first countries to do so in response to the pandemic.

· Spring 2020: The country experiences a surge in cases and deaths, with the healthcare system becoming overwhelmed.

· Summer 2020: Italy begins to ease restrictions, but experiences a resurgence in cases in the fall.

· Late 2020-2021: Italy implements further restrictions and lockdowns in response to the pandemic, including a nationwide lockdown over the winter holiday period.

· 2022: Italy continues to respond to the pandemic, with vaccination efforts underway and measures in place to slow the spread of the virus.

The timeline of COVID-19 in Romania is as follows [15][16]:

· March 2020: The first cases of COVID-19 are reported in Romania.

· Spring 2020: Romania implements a state of emergency and various measures to slow the spread of the virus, including restrictions on gatherings and the closure of certain businesses.

· Summer 2020: Romania begins to ease restrictions, but experiences a resurgence in cases in the fall.

· Late 2020-2021: Romania implements further restrictions and lockdowns in response to the pandemic, including a curfew over the winter holiday period.

· 2022: Romania continues to respond to the pandemic, with vaccination efforts underway and measures in place to slow the spread of the virus.

· Transylvania is a historical region located in central Romania. The timeline of COVID-19 in Transylvania would have followed a similar pattern to the timeline of COVID-19 in Romania.

The timeline of COVID-19 in Hungary is as follows [17][18]:

· March 2020: The first cases of COVID-19 are reported in Hungary.

· Spring 2020: Hungary implements a state of emergency and various measures to slow the spread of the virus, including restrictions on gatherings and the closure of certain businesses.

· Summer 2020: Hungary begins to ease restrictions, but experiences a resurgence in cases in the fall.

· Late 2020-2021: Hungary implements further restrictions and lockdowns in response to the pandemic, including a curfew over the winter holiday period.

· 2022: Hungary continues to respond to the pandemic, with vaccination efforts underway and measures in place to slow the spread of the virus.

Materials and methods

The investigations were conducted by means of a questionnaire. The questions concerned a) individual (and at the same time family) travel habits (before and immediately after the pandemic), b) the background of the virus (the level of knowledge and degree of involvement in certain issues), c) future plans and behavioral patterns. The basic socio-economic situation of the respondents was also assessed.

Data collection and analysis. The questionnaire survey started in 2022. In the first step, the national questionnaires were prepared (Italian, Romanian, Hungarian – [QIT.html], [QTR.html], [QHU.html]) and then the partners scheduled the data collection in parallel. The survey was conducted online (Evasys system, Goole Questionnaire) and on paper. After the data collection was completed, the steps of creating the computer files and data cleaning followed. After the descriptive statistical calculations, the full analysis covered more complex questions and relationships. Statistical tests (cross-tab analysis, two-sample t-test, ANOVA, Kruskal-Wallis analysis, Principal Component Analysis (Varimax Rotation with Kaiser Normalization.)) were used in this analysis phase. The used program packages: Excel, SPSS V24. The margin of error used in the analysis was 5%. Response was voluntary. In the process of handling the data, it was not possible to identify individuals after answering. The data is handled in accordance with the Data Protection Regulations of the University of Debrecen.

The measuring device. The questionnaire consisted of four main modules.

I. I. Tourism consumer habits before Covid (2019) - This module assessed tourism habits before the pandemic. The questions asked about the purpose and duration of the trip, the form of transport used and other tourist characteristics.

II. Effects of Covid - The module assessed the impact of Covid. The questions asked how well the respondents knew about the Covid measures in their own country and how much these measures affected them.

III. Present and future vision - The module repeated the questions of module I from the post-Covid (2022) point of view and examined the respondent's future plans and opinions.

IV. Basic statistical data - This module asked questions (gender, age, education, etc.) that can be considered standard in other questionnaires.

Questions examining the respondents' opinions and experiences gave the opportunity to answer on ten-point scales. Examples: 1 - not typical of me ... 10 - very typical of me; 1 - not affected at all ... 10 - very significantly limited; 1 - I do not agree at all ... 10 - I completely agree. There were also questions that asked the respondents to give feedback between two options - a scale of 10 as well. The basic statistical data were queried in the traditional way.

A total of 2,320 people in the three countries filled out the questionnaire. In the questionnaire, one question (V4_6) related to which country the person filling in is from - Italy 602 people; Hungary 622 people; Romania/Transylvania 1084 people). 12 people did not answer this question. In addition, the partner country from which the answer came was also recorded (COUNTRY variable). When comparing the two variables, contradictory answers can be interpreted for a total of 51 people. [001_orszag_kizaras.htm] Doubtful respondents were excluded in some analysis phases.

Further analysis of the entire sample revealed significant differences between countries with regard to the following variables:

· Gender Analysis [010_V4_1_gender.htm]: The gender ratios showed a significant difference in the case of the three countries (chi-square test χ²(2, N = 2251) = 29.562, p = 0.000). In the Hungarian and Romanian/Transylvanian samples, the male-female ratio was 1/3 - 2/3. These rates were nearly identical (compare two countries; chi-square test χ² (1, N = 1651) = 3.936, p = 0.047). The Italian sample showed a ratio of 1/2 - 1/2.

· Age analysis [011_V4_2_age.htm]: Based on the processing of the age data, the average of the Hungarian sample was 37.79 years (standard deviation 16.131; 95% CI 36.45 - 39.14); the Romanian average was 33.40 years (standard deviation 9.961; 95% CI 32.80 – 33.99); the Italian mean was 50.83 years (standard deviation 18.167; 95% CI 49.37 – 52.29). Comparison of the sample means indicated a significant difference (ANOVA F(2, 2236) = 294.910, p = 0.000). Based on the post-hoc comparison, all samples differed from the others. According to the non-parametric Kruskal Wallis test, the differences were also significant (p=0.000). A significant difference also emerged when the Transylvanian and Hungarian samples were separated (two-sample t-test t(1637) = 6.796, p=0.000; Mann-Whitney U-test U(1638) = 263745.000, Z = -4.171, p = 0.000).

· Level of education analysis [012_V4_3_education.htm] Analysis: The level of education showed a significant difference in the sample of the three countries (χ² (4, N = 2254) = 278.119, p = 0.000). Basic education was the highest in the Hungarian sample (18.2% within the sample). Secondary education was almost the same in the Hungarian and Italian samples (48.7% and 43.2%). In the Romanian sample, the proportion of people with a higher education was the highest (69.1%).

· Marital status analysis [013_V4_4_marital.htm]: The difference between the samples was also significant according to marital status (χ2 (6, N = 2243) = 309.191, p = 0.000). In the Hungarian sample, the proportion of those living alone and those living in marriage was slightly higher than thirty percent (32.3% and 37.3%), the proportion living in a relationship was 27.7%. In the Transylvanian sample, the proportion of married people was 49.3%; 33.1% of the respondents lived in a relationship. In the Italian sample, the proportion of people living in a relationship was the highest (56.0%) and the proportion of people living alone was the second highest (26.0%).

· Living together analysis [014_V4_5_home.htm]: On the question of who the respondent lives with and who lives in the same household, there were also significantly different proportions in each country (χ2 (14, N = 2243) = 180.947, p = 0.000). The proportion of people living with partners was around 25%. Today's characteristic - the high proportion of older children living with their parents - was also reflected in the samples.

· Economic situation analysis [015_V4_9_financial.htm]: The self-perception of the economic situation also indicated a significant difference in the three samples (χ2 (18, N = 2247) = 159.846, p = 0.000; ANOVA F(2, 2246) = 16.452, p = 0.000; Kruskal-Wallis test χ2 (2, N = 2247) = 38.220, p = 0.000).

· Job analysis [016_V4_10_work.htm]: In term existing job, the Hungarian and Transylvanian samples were the same (100%), in the Italian sample the proportion of workers was 44.2% (significant difference between countries, χ2 (2, N = 1948) = 908.946, p = 0.000).

· Car analysis [017_V4_11_car.htm]: All Hungarian and Transylvanian respondents had a car (100%), in the case of Italians this ratio was 68%. The difference was significant between countries (χ2 (2, N = 1167) = 418.894, p = 0.000).

In summary: In the Hungarian sample, a lerger young group (high school graduates) was visible, and in the Italian sample there was a larger group that was older, perhaps already retired. In the Transylvanian sample, the proportion of those pursuing higher education was higher. The Hungarian and Transylvanian sub-samples were perhaps closer to each other, the Italian sub-sample differed more from the other two.

These results led to the decision that the comparison of sub-samples would not give real results, since samples with different basic characteristics were available from the populations of the three countries under investigation. Thus, the subsamples were compared using only percentage data. The further analyzes were therefore not aimed at the differences between the countries, but rather at the changes in tourism habits caused by Covid in the given samples.

RESULTS

The data was processed in two steps. The first was the descriptive statistical analysis, which determined the response rates and the descriptive statistical characteristics associated with them. In the second step, deeper analyzes took place: The situation before and after the pandemic was compared within the countries. This was possible by combining the common questions of modules I and III.

In the further description, the links point to the raw calculation tables and diagrams - the textual description indicates which question, which variable is explained in the description.

Basic analysis - Italy

I. Tourism consumer habits before Covid (2019). (detailed data and graphs: [052_MI_descrA_IT.htm], [052_MI_descrB_IT.htm]

Italian respondents in terms of tourist habits:

a) domestic routes were preferred (question V1_1, answer 1: 30.33%; answer 10: 3.33; answer 5 and 6: 14.50%, 14.17%);

b) they chose a longer rest (question V1_2, answer 1 19.67%, answer 10 of several shorter paths 6.00%);

c) rather on the waterfront  / next to water (question V1_3, answer category 10: 21.05%; category 1: (mountainous region) 6.00%);

d) slightly preferring the urban environment (question V1_4, answer cartegory 10 (country): 7.67%, category 1 (city) 13.00%);

e) the choice of programs closer to nature and cultural programs in almost equal proportion (question V1_5, answer 1: 13.17%; answer 10: 5.83%; answer 5 and 6 válaszok: 18.00% and 20.00%);

f) most of the travel was by car (question V1_6, answer 1: 26.00%).

It is not typical

a) practicing water sports (question V1_11, answer 1: 56.17%);

b) cycling (question V1_13, answer 1: 54.00%);

c) interest in rural/village tourism  (question V1_16, answer 1: 22.50%, answer 10: 3.83%);

d) agritourism (question V1_17, answer 1: 18.50%),

e) skiing (question V1_18, answer 1: 53.33%),

f) mountain climbing/hiking (question V1_19, answer 1: 53.30%);

g) the demand for wellness (question V1_20, answer 1: 32.33%).

h) medical tourism (question V1_21, answer 1: 52.17%).

Typical

a) sightseeing (question V1_12, answer 10: 13.33%; answers 6-10 together: 65.70%);

b) interest in cultural tourism (question V1_14, answer 6-10 together 54.67%; answer 5: 14.17%).

Average

a) interest in gastrotourism has leveled off (question V1_15; not uniform distribution, but the details balance each other).

II. Effects of Covid. (detailed data and graphs: [052_MII_descrC_IT.htm]

63.17% of respondents were aware of the measures introduced in Italy affecting tourism (question V2_1, 36.83% did not know about such measures or did not answer the question). The closing of the borders did not greatly affect tourist trips for Italian respondents (question V2_2, 73.50% were aware of the restrictions; question V2_3, choice 1 (not affected) 30.50%; answer 10 (significantly affected) 9.83%). 75.67% commented on closures affecting tourism within the country's borders (question V2_4); 24.67% were not affected, 12.00% were significantly affected (question V2_5). 75.00% knew about the curfew (question V2_6; 25.00% did not answer or did not know about it). This restriction already showed a stronger effect (question V2_7, answers 6-10 together 60.17%, answer 5 8.50%). 83.33% stated that they were aware of assembly restrictions (question V2_8; 16.67% did not answer or did not know about it). The impact of gathering restrictions on travel was stronger in the affected category (question V2_9, answer 10 13.00%; 19.50% were not affected, but 60.00% of answers 6-10 together). 81.83% reported the closure and restrictions of catering facilities (question V2_10). 11.50% were significantly affected; not affected 19.67%; 6-10 answers together 59.50% (V2_11 question). The ban on leaving home was reported by 79.33% (question V2_12); 17.33% were not involved; 16.30% were significantly affected; 6-10 answers together 66.00% (V2_13 question). The obligation to keep distance was reported by 83.50% (question V2_14); the involvement (answer 10 10.50%) was less, not affected 15.67%; 6-10 answers together 63.50% (V2_15 question). 85.64% knew the obligation to wear a mask (question V2_16); 12.17% were significantly affected, 20.67% were not affected; 6-10 answers together 59.34% (question V2_17). In the case of 27.67% of the vaccination certificates, there was no problem; In the case of 8,670%, the involvement was significant (question V2_18). 70.00% knew the possible necessity of the PCR test in some areas (question V2_19). In the case of economic and material consequences, the proportion of those not affected (14.83%) and those significantly affected (8.33%); answer 5 was 14.00% (question V2_20). Regarding mental and physical consequences and dealing with them, there is a visible concentration from the mean value slightly towards involvement (question V2_21). Regarding the measures, a significant proportion marked the appropriate strictness (question V2_22, answer 5, 17.83%; answer 6 30.83%). Regarding the effectiveness of the measures, the respondents indicated the appropriate effectiveness (question V2_23, answers 6-10 65.84%). Mandatory vaccination showed agreement among the respondents (question V2_24). Disagreement (answer 1) was 8.33%; total agreement was 13.50%. 57.33% of respondents received four (!) vaccinations; 9.50% reported a single vaccination (question V2_25). The proportion of vaccinated people was 100.00% (average number of vaccinations 3.71, std. deviation 1.077; median 4).

III. Present and future vision. [052_MIII_descrD_IT.htm]

This chapter also includes answers from before Covid, for the sake of comparison.

To the question of how much travel habits have been changed by the pandemic, the Italian respondents typically indicated medium values or values above it (question V3_1; answer 1 14.83%; answer 10 9.83%; answers 5-8 with a value above 10%; 2-4 with a value below 10%). Regarding the frequency of travel, the middle value (answer 5) was the most common (question V3_2, 2-4; answers 6-10 with a value below 10; answer 5 23.05% - answer 1 is "I travel less", the 10 - and "I travel more") - the answers reflect fewer planned trips.

In the case of questions about details of trips, there was a significant change in 3 out of seven questions (Table 1). For the questions highlighted in bold, the analytical statistics indicated a significant change - see the details in the next chapter.

Question	Response 1 rate Before covid	Response 1 rate Before Covid	Response 1 rate After Covid (change/difference: after-before)	Response 10rate After Covid (change/difference: after-before)
V1_1 and V3_3 domestic or foreign	30.33%	3.33%	29.83% (-0.50)	1.67% (-1.66)
V1_2 and V3_4 one big or several short travel	19.67%	6.00%	19.17% (-0.50)	6.33% (0.33)
V1_3 and V3_5 waterside or mountains	6.00%	21.50%	6.67% (0.67)	18.17% (-3-33)
V1_4 and V3_6 city or countryside	13.00%	7.67%	13.17% (0.17)	7.83% (0.16)
V1_5 and V3_7 nature or culture	13.17%	5.83%	13.00% (-0.17)	5.00% (-0.83)
V1_6 and V3_8 car or public transport	26.00%	4.50%	29.33% (3.33)	3.50% (-1.00)
V1_7 and V3_9 land or air	6.50%	22.50%	9.67% (3.17)	4.50% (-18.00) (!)

Table 1 Response rates for pairs of questions concerning trip details. The analytical statistics indicated a significant change for the questions highlighted in bold - see the next chapter of the analysis.

In summary: Travel habits changed in a statistically demonstrable way in the case of the Italian answers, in several cases. The difference can be seen in the case of the purpose of travel (waterside-mountains) and the method of travel. The next chapter confirms these observations with the tools of analytical statistics.

The last four questions of the third module concerned the 2022 tourism plans. Based on these answers, the respondents indicated more domestic trips than the opposite (question V3_13, answer 1 - prefers not only domestic travel - 5.67%, answer 10 - prefers domestic travel - 18.00%). The response rates to question V3_14 are clustered around the middle value - domestic trips are expected to continue at the same rate (with a different audience). In a similar way, it can be stated that our travel habits are not expected to change (large proportions around the middle value), but some of the former travelers are withdrawing, while others promise to be more active (question V3_15, disagree with more trips 10.17%, agree and would travel more due to Covid after 11.00%). A larger proportion of respondents think that we will have to live with the restrictions caused by infectious diseases in the future (question V3_16, answer 10 11.17%; answer 1 - we do not have to count on infectious diseases in the future - 7.33% (the 6-10 answers in total 61.51; answers 5-10 in total 75.01%).

IV. Basic statistical data. [052_MIV_descrE_IT.htm]

In addition to general personal data, the questionnaire ended with a self-characteristic part.

The first question asked about the introverted/extroverted trait. The respondents preferred the outgoing, extroverted personality trait (question V4_12, answer 1 4.67%, answer 10 7.17%; answers 6-10 60.17%). The respondents mainly see themselves as middling in their assessment of modern and traditional attitudes (question V4_13, answer 1 (traditional) 8.00%, answer 10 (modern) 5.00%; answer 5 16.67%; answer 6 21.17%). They are typically technology-friendly (question V4_14, answer 1 (technology-friendly) 15.83%; answer 10 (technology-avoiding) 5.00%). 10.83% of respondents indicated that they are very open to new things (question V4_15, answer 1), 1.67% preferred old things (answer 5 18.83%; answers 1-4 47.00%). The respondents were more of a national sentiment (question V4_16, answer 1 (national sentiment) 11.50%; answer 10 (more cosmopolitan) 4.83; answer 5 17.00%, answer 6 21.50%; answers 1-4 39.83 %).

Basic analysis Transylvania

I. Tourism consumer habits before Covid (2019).

[051_MI_descrA_TR.htm], [051_MI_descrB_TR.htm]

Transylvanian respondents in terms of tourist habits

a. they preferred foreign trips (question V1_1, cases 7-8-9-10 all indicate a ratio above 10%; answers 1-2-3-4 are below 10%);

b. they chose longer rest (question V1_2, answer 1 14.42%, answer 10 of several shorter trips 19.43%);

c. rather on the waterfront (question V1_3, answer category 10 28.95%);

d. both in a city or in a rural environment (question V1_4, answer 10 (rural) 15.56%, answer 1 (city) 13.70%);

e. among them, the choice of programs closer to nature is also clear (question V1_5, answer 1 24.61%);

f. the trip was mostly made by car (question V1_6, answer 1 40.39%).

Which are not typical

a. playing water sports (question V1_11, answer 1 36.33%);

b. cycling (question V1_13, answer option 1 31.10%), agritourism (question V1_17, answer 1 30.77%);

c. skiing (question V1_18, answer 1 41.15);

d. mountain climbing/hiking (question V1_19, answer 1 19.44%, although the other answer options (2-10) are relatively evenly distributed);

e. medical tourism (question V1_21, answer 1 23.52% and the other answer options are relatively evenly distributed here as well).

Which are typical

a. the. sightseeing (question V1_12, answer option 10, 25.48%);

b. b. the demand for wellness (question V1_20, answer 10 31.64%).

Average rating

a. interest in cultural tourism (question V1_14);

b. interest in gastro-tourism was balanced (question V1_15, answer 1 9.46%, 13.16% marked this area as 10);

c. interest in rural/village tourism is also evenly distributed (question V1_16, answer 1 10.16%, answer 10 9.33%).

II. Effects of Covid. [051_MII_descrC_TR.htm]

88.96% of respondents were aware of the measures introduced in Romania affecting tourism (question V2_1, 11.04% did not know about such measures or did not answer the question). The closing of the borders affected tourist trips in Transylvania to a greater extent than the Hungarian respondents (question V2_2, 92.43% were aware of the restrictions; question V2_3, choice 1 (not affected) 10.48%; answer 10 (significantly affected) 21.52%). 87.07% commented on closures within the country's borders affecting tourism (question V2_4); 8.36% were not affected, 15.97% were significantly affected (question V2_5). 97.69% knew about the curfew (question V2_6; 2.03% did not answer). This restriction has already shown a strong effect (question V2_7). 42.91% indicated significant involvement; not affected 4.08%. This question indicates significantly greater involvement in Transylvania than Hungarian answers. 94.37% said they were aware of assembly restrictions (question V2_8; 4.80% did not answer or did not know about it). The impact of gathering restrictions on travel was stronger in the affected category (question V2_9, answer 10 24.00%; not affected 10.33%). 97.41% reported the closure and restrictions of catering facilities (question V2_10). The issue of involvement is much larger: 31.29% were significantly affected; not affected 4.55% (question V2_11). The ban on leaving home was reported by 93.17% (question V2_12); 6.41% were not involved. On the other hand, 42.38% were significantly affected (question V2_13, this is a much higher proportion than the Hungarian proportion). The obligation to keep distance was reported by 97.23% (question V2_14); the involvement (answer 10 23.37%) was higher, not affected 6.80% (question V2_15). 99.35% knew the obligation to wear a mask (question V2_16); 35.53% were significantly affected, 10.05% were not affected (question V2_17). The mandatory vaccination certificate was not a problem for 16.88%; In the case of 34.51%, however, the negative involvement was significant (question V2_18). 97.14% knew the possible necessity of the PCR test in some areas (question V2_19). In the case of economic and financial consequences, the proportion of those not affected (44.68%) and those significantly affected (55.32%) is significantly different (1 or 10 answers only) than in the case of Hungarian respondents (question V2_20). Many people reported mental and physical consequences and dealing with them (question V2_21). Half of the respondents indicated involvement in category 5 or above (5-10 answers 64.83%; 10 answer category 11.44%). With regard to the measures, a significant proportion indicated excessive strictness (question V2_22, 20.98%); but answer 5 was also strong (this is medium strictness, with 18.57%). However, the distribution of the question clearly indicated overly strict measures. The response regarding effectiveness (question V2_23) seems to be contradictory, as the indication of ineffectiveness was stronger among the respondents (11.93%) compared to the indication of effectiveness (3.63%). Answer 5 was the strongest answer in this case (17.89%). Mandatory vaccination was also divisive among the respondents (question V2_24). Disagreement (23.35%) was stronger than full agreement (16.53%). 33.33% (one third) of the respondents received two vaccinations; 12.38% reported a vaccination (question V2_25). The proportion of unvaccinated people was 33.99% (average number of vaccinations 1.40, std. deviation 1.159; median 2) - this is much higher than the Italian (0.00%) and Hungarian (9.27%) data.   

III. Present and future vision. [051_MIII_descrD_TR.htm]

This chapter also includes answers from before Covid, for the sake of comparison.

In response to the question of how much travel habits have been changed by the pandemic, Transylvanian respondents typically indicated medium values or values above. While the extreme values (1-2 and 9-10) occurred in a smaller proportion (question V3_1; answer 1 was 11.72%; answer 10 9.49%; answers 5-8 with a value above 10%; 2-4 with a value below 10%). Regarding the frequency of travel, the middle value (answer 5) was the most common (question V3_2, 1-4; answers 6-10 with a value below 10%; answer 5 18.48% - answer 1 meant "I travel less", the number 10 means "I travel more").

In the case of questions about details of trips, there was a significant change in 5 out of seven questions (Table 2). For the questions highlighted in bold, the analytical statistics indicated a significant change - see the details in the next chapter of the analysis.

Question	Response 1 rate Before covid	Response 1 rate Before Covid	Response 1 rate After Covid (change/difference: after-before)	Response 10rate After Covid (change/difference: after-before)
V1_1 and V3_3 domestic or foreign	9.43%	14.05%	18.26% (8.83)	16.68% (2.63)
V1_2 and V3_4 one big or several short travel	14.42%	9.43%	15.13% (0.71)	13.74% (4.31)
V1_3 and V3_5 waterside or mountains	6.75%	28.95%	10.58% (3.83)	30.06% (1.11)
V1_4 and V3_6 city or countryside	13.70%	15.58%	15.29% (1.59)	16.68% (1.10)
V1_5 and V3_7 nature or culture	26.61%	4.16%	27.89% (1.28)	4.80% (0.64)
V1_6 and V3_8 car or public transport	40.39%	5.73%	48.80% (8.41)	4.55% (-1.18)
V1_7 and V3_9 land or air	7.86%	44.40%	7.07% (-0.79)	48.19% (3.79)

Table 2 – Response rates for pairs of questions concerning trip details. The analytical statistics indicated a significant change for the questions highlighted in bold - see the next chapter of the analysis.

In summary: In several cases, travel habits change in a statistically demonstrable way in the case of Transylvanian responses. The difference was shown in terms of domestic-foreign trips, the length of the trip and the purpose of the trip (waterside-mountains), and the method of travel. The next chapter confirms these observations with the tools of analytical statistics.

The last four questions of the third module concerned the plans for 2022. Based on these, the respondents indicated slightly more traveling abroad than the opposite (question V3_13, answer 1 - prefers not only domestic travel - 14.78%, answer 10 - prefers domestic travel - 8.79%). This is somewhat contrary to the response rate to question V3_14, according to which 30.12% disagree that they will travel less domestically (2.81% agree). The respondents intend to travel more (question V3_15, disagree with more travel 6.64%, agree and would travel more after Covid 22.99%). It can be clearly stated that a larger proportion of the respondents believe that we will have to live with the restrictions caused by infectious diseases in the future (question V3_16, answer 10 9.71%; answer 1 - we do not have to count on infectious diseases in the future - 17.18% ( this is an outlier; on the other hand, answers 6-10 total 48.13%; answers 5-10 total 60.92%).

IV. Basic statistical data. [051_MIV_descrE_TR.htm]

In addition to general personal data, the questionnaire ended with a self-characteristic part. The first question asked about the introverted/extroverted trait. The respondents preferred the outgoing, extroverted personality trait (question V4_12, answer 1 2.59%, answer 10 4.43%). The respondents see themselves as modern rather than traditional V4_13 question, answer 1 (traditional) 2.88%, answer 10 (modern) 11.71%. Answer 5 was 19.42%; 62.27% were between 6-10 answer options. They are typically technology-friendly (question V4_14, answer 1 (technology-friendly) 22.52%; answer 10 (technology-avoiding) 2.04%). 14.02% of respondents indicated that they were very open to new things (question V4_15, answer 1), 2.41% preferred old things (answer 5 24.70%; answers 1-4 51.80%). The respondents were more of a national sentiment (question V4_16, answer 1 (national sentiment) 12.91%; answer 10 (more cosmopolitan) 4.83%; answer 5 25.53%)%.

Basic analysis - Hungary

I. Tourism consumer habits before Covid (2019).

[050_MI_descrA_HU.htm], [050_MI_descrB_HU.htm]

The Hungarian respondents in terms of tourist habits

a. domestic routes were preferred (question V1_1, answer 1 32.81%);

b. rather they chose longer rest (question V1_2, answer 1 19.76%, but answer 10 of several shorter trips is also significant 13.29%);

c. on the waterfront (question V1_3, answer category 10 27.62%)

d. be it a city or rural environment (question V1_4, answer 10 19.30%, answer 1 17.72%);

e. the choice of programs closer to nature is clear (question V1_5, answer 1 29.02%);

f. the trip was mostly made by car (question V1_6, answer 1 48.24%).

Which are not typical

a. practicing water sports (question V1_11, answer 1 44.25%);

b. cycling (question V1_13, answer option 1 38.15%);

c. gastrotourism (question V1_15, answer 1 18.32%, although 14.49% marked this area of interest - answer 10);

d. rural/village tourism (question V1_16, answer 1 23.64%);

e. agritourism (question V1_17, answer 1 42.83%);

f. skiing (question V1_18, answer 1 57.77%);

g. mountain climbing/hiking (question V1_19, answer 1 30.42%);

h. medical tourism (question V1_21, answer 1 34.21%);

i. extreme interest in cultural tourism, or indifference to such programs (question V1_14).

Which are typical

a. sightseeing (question V1_12, answer option 10, 23.95%);

b. the demand for wellness (question V1_20, answer 10 22.55%, but the proportion of those not interested (answer 1) 14.69%).

II. Effects of Covid. [050_MII_descrC_HU.htm]

83.89% of respondents knew about the measures introduced in Hungary affecting tourism (question V2_1, 16.11% did not know about such measures or did not answer the question). The closure of the borders did not affect tourist trips for the most part (question V2_2, 82.93% were aware of the restrictions; question V2_3, choice 1 (not affected) 36.89%; answer 10 (significantly affected) 14.61%). 66.20% commented on closures within the country's borders affecting tourism (question V2_4); 31.13% were not affected, 9.81% were significantly affected (question V2_5). 91.5% knew about the curfew (question V2_6; 5.9% did not answer). This restriction already showed a stronger effect (question V2_7). 22.68% indicated significant involvement; not affected 21.61%. 85.02% stated that they were aware of assembly restrictions (question V2_8; 14.98% did not answer or did not know about it). The impact of gathering restrictions on travel was stronger in the non-affected category (question V2_9, 31.14%; significantly affected 14.10%). 88.33% reported the closure and restrictions of catering facilities (question V2_10). The question of involvement is almost the same: 20.11% were significantly affected; not affected 19.74% (question V2_11). The ban on leaving home was reported by 79.27% (question V2_12); 26.49% were not affected; 21.46% were significantly affected (question V2_13). The obligation to keep distance was reported by 93.38% (question V2_14); but lack of involvement (21.49%) rather than significant involvement (14.57%) was the characteristic (question V2_15). 95.99% knew the obligation to wear a mask (question V2_16); 26.12% were significantly affected, 19.86% were not affected (question V2_17). In the case of 29.78% of the vaccination certificates, there was no problem; in the case of 23.47%, however, the involvement was significant (question V2_18). 89.72% knew the possible necessity of the PCR test in some areas (question V2_19). In the case of economic and material consequences, the proportion of those not affected (20.67%) and those significantly affected (19.96%) was almost the same (question V2_20). Many people reported mental and physical consequences and dealing with them (question V2_21). Half of the respondents indicated involvement in category 5 or above (answers 5-10 68.35%; answer 10 13.29%). With regard to the measures, a significant proportion indicated excessive strictness (question V2_22, 13.66%); but the most typical were answers 5 and 6 (20.67% and 20.32%, together 40.99%). The response regarding effectiveness (question V2_23) seems to be contradictory, as the indication of ineffectiveness was stronger among the respondents (11.93%) compared to the indication of effectiveness (7.02%). Questions 5 and 6 were also the strongest answers in this case (17.54% and 18.95%; together 36.49%). Mandatory vaccination was also very divisive among the respondents (question V2_24). Disagreement and full agreement were almost the same (17.54%; 17.37%). 47.55% (almost half) of the respondents took three vaccinations; 32.87% reported two vaccinations (question V2_25). The proportion of unvaccinated people was 9.27% (average number of vaccinations 2.31, std. deviation 0.988; median 3).    

III. Present and future vision. [050_MIII_descrD_HU.htm]

This chapter also includes answers from before Covid, for the sake of comparison.

To the summary question, to what extent travel habits have been modified by the pandemic, the response "no" was somewhat typical (question V3_1; answer 1 22.32%; answer 10 10.90%). Regarding the frequency of travel, a definite decline is visible (question V3_2, answers 1-6 combined, 76.36% - answer 1 is "I travel less", 10 is "I travel more").

In the case of the questions about the details of the trips, there was a significant change in three out of seven questions (Table 3). These are the parts highlighted in bold in the table - see details in the next chapter.

Question	Response 1 rate Before covid	Response 1 rate Before Covid	Response 1 rate After Covid (change/difference: after-before)	Response 10rate After Covid (change/difference: after-before)
V1_1 and V3_3 domestic or foreign	32.81%	14.31%	39.27% (6.46)	10.82% (-3.49)
V1_2 and V3_4 one big or several short travel	19.76%	13.29%	16.26% (-3.50)	14.51% (1.22)
V1_3 and V3_5 waterside or mountains	11.01%	27.62%	11.58% (0.57)	25.79% (-1.83)
V1_4 and V3_6 city or countryside	17.72%	19.30%	18.20% (0.48)	17.84% (-1.46)
V1_5 and V3_7 nature or culture	29.02%	6.29%	27.37% (-1.65)	7.19% (0.90)
V1_6 and V3_8 car or public transport	48.24%	9.15%	46.67% (-1.57)	8.25% (0.90)
V1_7 and V3_9 land or air	10.86%	46.23%	9.98% (-0.88)	46.23% (0.00)

Table 3 – Response rates for pairs of questions concerning trip details. The analytical statistics indicated a significant change for the questions highlighted in bold - see the next chapter of the analysis.

In summary: In some cases, travel habits change in a statistically demonstrable way in the case of Hungarian answers. The difference was shown in terms of domestic-foreign trips and the length of the trip and the purpose of the trip (nature-culture). The next chapter confirms this observation with the tools of analytical statistics.

The last four questions of the third module concerned the plans for 2022. Based on these, the borrowers indicated that they prefer traveling domestically to the opposite (question V3_13, answer 1 - prefers not only domestic travel - 19.12%, answer 10 - prefers domestic travel - 20.88%). This is consistent with the response rate to question V3_14, according to which 30.42% disagree that they will travel less domestically (7.87% agree). The respondents intend to travel more (question V3_15, disagree with more travel 12.59%, agree and would travel more after Covid 19.58%). It can be clearly stated that a larger proportion of the respondents think that we will have to live with the restrictions caused by infectious diseases in the future (question V3_16, answer 10 17.54%; answer 1 - we do not have to count on infectious diseases in the future - 11.05%; answers between 6-10 total 60.10%).

IV. Basic statistical data. [050_MIV_descrE_HU.htm]

In addition to general personal data, the questionnaire ended with a self-characteristic part. The first such question asked about the introverted/extroverted trait. The respondents preferred the outgoing, extroverted personality trait (question V4_12, answer 1 6.90%, answer 10 18.41%). Respondents see themselves as modern rather than traditional (question V4_13, answer 1 (traditional) 7.89%, answer 10 (modern) 18.70%. They are typically technology-friendly (question V4_14, answer 1 (technology-friendly) 26.19%; answer 10 (technology-avoiding) 5.45%). 20.91% of respondents indicated that they are very open to new things (question V4_15, answer 1), 6.85% preferred old things. The respondents were more of a national sentiment (question V4_16, answer 1 (national sentiment) 13.73%; answer 10 (more cosmopolitan) 9.68%).

Appearance of areas of interest in the three samples

Depending on various background factors (age, education, financial situation, social background, family traditions, etc.), the interest of travelers is reflected in the individual tourism branches - with a positive or perhaps a negative weight (interested, not interested/indifferent, dismissive). Eleven questions of the questionnaire related to the individual assessment of these separable branches (self-characterization, self-declaration). The use of factor and principal component analysis methods is, on the one hand, suitable for revealing relationships and overlaps between variables, and on the other hand, human thinking and decision-making processes can also be grasped.

According to the results (separating the three countries), the branches that can be connected to each other emerge, and the larger directions of the individual areas of interest are distinguished. An evaluable model could be created in all three analyzes (Tables 4 and 5).

Component analysis	Hungary HU	Romania/Transylvania  RO/TR	Italy IT
KMO	0.681	0.693	0.880
Bartlett’s chi-square, df, p	1132.046 55 0.000	2071.645 55 0.000	3900.659 55 0.000
Number of components	4	4	2
Cumulative %	63.240	62.744	67.037

Table 4 – Model values of principal component analysis.

Rotated Component Matrix	HU				RO/TR				IT
	1	2	3	4	1	2	3	4	1	2
V1_11 Water sports (kayak, canoe, sailing, windsurfing, diving, etc.)	,797						,716		,819
V1_18 Ski tourism	,767						,758		,841
V1_19 Mountain climbing, cross-country running, hiking, caving	,539				,337		,564		,857
V1_13 Cycling tourism	,481		,434		,417		,553		,852
V1_12 Sightseeing		,816				,843				,775
V1_14 Cultural tourism		,867				,854				,794
V1_15 Gastrotourism		,562	,372		,339	,558				,807
V1_16 Rural tourism			,809		,846				,419	,720
V1_17 Agrotourism			,779		,790				,342	,728
V1_20 Wellness tourism				,818				,851	,601	,440
V1_21 Medical tourism				,820				,805	,795

Table 5 - Principal component analysis of the questions concerning the areas of interest of the three countries - rotated component matrices. The highlighted elements illustrate the connections in each country.

One of the connections that can be highlighted is related to sports. In all three models, water sports, skiing, climbing and hiking belong to one component. In the Hungarian and Transylvanian models, cycling is already moving into the framework of rural and agrotourism (in the Italian model it is not essentially separated from sports) - linked to gastrotourism, sightseeing and visiting cultural destinations. The Transylvanian and Hungarian samples essentially reflect the same structure, the individual tourism branches are not presented in detail separately in the Italian answers [060_HU_interests.htm], [061_TR_interests.htm], [062_IT_interests.htm].

Covid involvement

The summation (distribution) of the separate involvement questions (V2.3-V2.18; 9 questions) and the scores assigned to them can be seen in Figure 1 and Table 6 (histogram based on the data of all three countries).

The analysis of variance and the Kruskal-Wallis test also indicated a significant difference between the countries (with values 9 and 90: F(2, 2146) = 117.601, p = 0.000; excluding values 9 and 90: : F(2, 2007) = 94.486, p = 0.000). The post-hoc analysis showed a clear greater involvement of the Transylvanian group; and after excluding the values of 9 and 90, the Hungarian respondents seem to be the least affected. It should be noted that 28 of the Hungarian respondents gave a value of 9 or 90, 32 of the Transylvanian respondents, and 79 of the Italian respondents. These results are also supported by the non-parametric Kruskal-Wallis tests (chi-square = 199.408, df = 2, p = 0.000; chi-square = 166.440, df = 2, p = 0.000). [064_sum_interests_inferential.htm]

Descriptives
Covid_affect
	N	Mean	Std. Deviation	Std. Error	95% Confidence Interval for Mean		Minimum	Maximum
					Lower Bound	Upper Bound
2 Hungary	504	48,67	21,591	,962	46,78	50,56	9	90
3 Romania - TR	1043	62,50	17,460	,541	61,44	63,56	9	90
4 Italy	602	49,70	22,809	,930	47,87	51,52	9	90
Total	2149	55,67	21,136	,456	54,78	56,56	9	90

Descriptives – Values 9 and 90 are excluded
Covid_affect2
	N	Mean	Std. Deviation	Std. Error	95% Confidence Interval for Mean		Minimum	Maximum
					Lower Bound	Upper Bound
2 Hungary	476	48,96	19,935	,914	47,17	50,76	10	89
3 Romania - TR	1011	61,87	16,849	,530	60,83	62,91	10	89
4 Italy	523	53,37	18,325	,801	51,79	54,94	10	89
Total	2010	56,60	18,827	,420	55,78	57,42	10	89

Table 6 - The descrition of the separate involvement questions (V2.3-V2.18; 9 questions).

Figure 1 A Distribution of the variable created by combining questions evaluating the effects of Covid-19. The figure on the right is the histogram without extreme values of 9 and 90.

Estimation of changes in tourist habits

In the questionnaire, module I and III questions can be paired (V1_1 and V3_3 domestic or foreign; V1_2 and V3_4 one big or several short travel; V1_3 and V3_5 waterfront or mountains; V1_4 and V3_6 city or countryside; V1_5 and V3_7 nature or culture; V1_6 and V3_8 car or public transport ; V1_7 and V3_9 land or air). Module I recorded the response during Covid-19, module III recorded the response after Covid-19. Examining the differences provides an opportunity to show the direct and indirect effects of Covid-19 in terms of tourist habits. The results of the comparison (paired two-sample t-test and Wilcoxon paired rank test) are summarized in Table 7 (detailed calculations: [030_pairedTT_Wilcox.htm], [ 030_V1_1_and_V3_3_domest.htm]).

There was one question in which the responses of all three countries showed a similar correlation (opinion did not change, question pair V1_4 and V3_6): the question of interest in urban and rural tourism experiences.

The largest change was indicated by respondents from Transylvania. In their case, there was a significant difference in five of the seven questions. In the case of Hungarian and Italian respondents, there were significant differences in three questions. In the case of Transylvanian and Italian answers, there were changes in three identical questions; in the case of Hungarian and Transylvanian respondents, for two questions; and in the case of the Italian and Hungarian answers, not in any case. However, observing the direction of the change, other differences also emerge (this is indicated by the arrows and signs in the table - the text evaluation can be read pasted into the table).

Questions	HU	RO/TR	IT
V1_1 and V3_3 domestic or foreign	t(571) = 4.427, p = 0.000	t(1078) = 7.486, p = 0.000	t(599) = 1.418, p = 0.157
	N1 = 573, N2 = 573, Z = -4.474, p = 0.000	N1 = 1082, N2 = 1079, Z = -7.402, p = 0.000	N1 = 600, N2 = 600, Z = -1.150, p = 0.250
	↓ -	↓ -

The opinions of the Hungarian and Transylvanian respondents both point in the direction of a higher proportion of domestic trips. The Italian result has not changed.

Questions	HU	RO/TR	IT
V1_2 and V3_4 one big or several short travel	t(570) = -3.068, p = 0.002	t(1076) = -3.491, p = 0.001	t(599) = -0.870, p = 0.385
	N1 = 572, N2 = 573, Z = -3.095, p = 0.002	N1 = 1082, N2 = 1077, Z = -3.618, p = 0.000	N1 = 600, N2 = 600, Z = ,-0.714 p = 0.475
	↑ +	↑ +

The opinions of the Hungarian and Transylvanian respondents both point in the direction of shorter routes.

Questions	HU	RO/TR	IT
V1_3 and V3_5 waterside or mountains	t(568) = 0.546, p = 0.585	t(1076) = 4.755, p = 0.000	t(599) = 3.093, p = 0.002
	N1 = 572, N2 = 570, Z = -0.496, p = 0.620	N1 = 1081, N2 = 1078, Z = -4.623, p = 0.000	N1 = 600, N2 = 600, Z = -3.352, p = 0.001
		↓ -	↓ -

Transylvanian and Italian respondents indicated a higher proportion of trips to the mountains.

Questions	HU	RO/TR	IT
V1_4 and V3_6 city or countryside	t(562) = 0.820, p = 0.412	t(1076) = -1.290, p = 0.197	t(599) = -1.205, p = 0.229
	N1 = 570, N2 = 566, Z = 0.928, p = 0.353	N1 = 1080, N2 = 1079, Z = -1.082, p = 0.279	N1 = 600, N2 = 600, Z = -1.136, p = 0.256

No change.

Questions	HU	RO/TR	IT
V1_5 and V3_7 nature or culture	t(567) = -2.547, p = 0.011	t(1080) = 0.829, p = 0.407	t(599) = 0.425, p = 0.669
	N1 = 572, N2 = 570, Z = -2.599, p = 0.009	N1 = 1081, N2 = 1083, Z = -0.658, p = 0.510	N1 = 600, N2 = 600, Z = -0.133, p = 0.895
	↑ +

The Hungarian respondents indicated a higher proportion of cultural interest.

Questions	HU	RO/TR	IT
V1_6 and V3_8 car or public transport	t(563) = -0.536, p = 0.592	t(1076) = 2.154, p = 0.031	t(599) = 2.308, p = 0.021
	N1 = 568, N2 = 570, Z = -0.590, p = 0.555	N1 = 1082, N2 = 1077, Z = -2.025, p = 0.043	N1 = 600, N2 = 600, Z = -2.730, p = 0.006
		↓ -	↓ -

Transylvanian and Italian respondents indicated a higher proportion of car use.

Questions	HU	RO/TR	IT
V1_7 és V3_9 land or air	t(568) = 0.042, p = 0.966	t(1073) = -3.198, p = 0.001	t(599) = 10.425, p = 0.000
	N1 = 571, N2 = 571, Z = -0.348, p = 0.728	N1 = 1081, N2 = 1075, Z = -2.817, p = 0.005	N1 = 600, N2 = 600, Z = -9.654, p = 0.000
		↑ +	↓ -

Transylvanians indicate a higher proportion of land transport, and Italians a higher proportion of air transport.

Table 7 Comparison of matching questions on travel habits by country. The first rows contain the results of the paired two-sample t-tests in the sub-tables; the second line shows Wilxocon's test results.

DISCUSSION

The changes and impacts differed from country to country and region to region, but in general, tourism has changed in many ways as a result of the pandemic. At the beginning of the pandemic, many countries closed their borders and imposed strict travel restrictions to prevent the spread of the virus. This immediately drastically reduced the number of international and domestic trips. Many tourism businesses around the world, including airlines, hotels, restaurants and tour guides, have faced severe economic difficulties. Many businesses were forced to downsize or close completely. Due to health and safety regulations, tourism businesses have had to implement new standards such as social distancing, hygiene measures and health checks. By 2023, the restrictions were almost completely lifted – but not completelly [31][32].

According to tourism literature, local tourism has become more popular due to restrictions on international travel. Many people preferred domestic trips or short-term trips. Virtual travel and online tourism have also become popular during the pandemic. Many tourist attractions and museums offered digital tours and virtual experiences to those who stayed at home. The pandemic has focused attention on the environmental effects of tourism. Fewer tourists appeared in many places, which made it possible to restore the natural environment, and interest in sustainable tourism also increased [33][34].

But these effects are not general and not equal. According to the Heal All research, the samples of the examined countries have slightly different characteristics (in the Hungarian sample, a larger young group (high school graduates), in the Italian sample a larger group that was older, perhaps already retired, in the Transylvanian sample, the proportion of those pursuing higher education was higher) already caused significant differences in responses.

It can clearly be said that social groups in different economic and social situations were able to respond to the challenges in different ways. Currently, perhaps not enough time has passed for humanity to be able to paint a real picture of the actual effects of the pandemic. The areas and extent of the "covid aftermath / post covid" are doubtful. The consequences that are hidden below the surface and can be felt in the long term - in economic, social, health and individual health and other areas - are only now beginning to unfold. Their deep analysis (e.g. meta-analysis) and the correct interpretation of the results do not only allow for historical/historical descriptions. The pandemic allows a deeper insight into the processes of the systems operated by people. The hitherto unseen situations showed (and will show later) the strengths and weaknesses in the individual subsystems, the strong and weak nodes in the connection networks. The same ideas can be interpreted in the field of tourism. The presented research was only able to reflect a very small detail of the changes, but there is no doubt that it is no longer possible to return to the state before the pandemic - the branches of tourism are being restructured - the tourist service provider must adapt to this situation.

LITERATURE

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6. COVID-19 Dashboard by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University (JHU) https://gisanddata.maps.arcgis.com/apps/dashboards/bda7594740fd40299423467b48e9ecf6 (2023.08.15.)

7. Telenti, A., Arvin, A., Corey, L. et al. After the pandemic: perspectives on the future trajectory of COVID-19. Nature 596, 495–504 (2021). https://doi.org/10.1038/s41586-021-03792-w (2023.08.15.)

8. European Centre for Disease Prevention and Control, Covid-19. https://www.ecdc.europa.eu/en/covid-19  (2023.08.15.)

9. COVID-19 pandemic by country – wikipedia. https://en.wikipedia.org/wiki/Category:COVID-19_pandemic_by_country (2023.08.15.)

10. Kim H, Apio C, Ko Y, Han K, Goo T, Heo G, Kim T, Chung HW, Lee D, Lim J, Park T. Which National Factors Are Most Influential in the Spread of COVID-19? Int J Environ Res Public Health. 2021 Jul 16;18(14):7592. doi: 10.3390/ijerph18147592. PMID: 34300044; PMCID: PMC8307075. (2023.08.15.)

11. Cao W, Chen C, Li M, Nie R, Lu Q, Song D, Li S, Yang T, Liu Y, Du B, Wang X. Important factors affecting COVID-19 transmission and fatality in metropolises. Public Health. 2021 Jan;190:e21-e23. doi: 10.1016/j.puhe.2020.11.008. Epub 2020 Nov 19. PMID: 33339626; PMCID: PMC7674010. (latitude (connected with  temperature), wind speed, the total number of participants in major sports events, and GDP per capita) (2023.08.15.)

12. Azuma, K., Yanagi, U., Kagi, N. et al. Environmental factors involved in SARS-CoV-2 transmission: effect and role of indoor environmental quality in the strategy for COVID-19 infection control. Environ Health Prev Med 25, 66 (2020). https://doi.org/10.1186/s12199-020-00904-2 (environmental factors, indoor environmental quality) (2023.08.15.)

13. Worldometer – covid – Italy. https://www.worldometers.info/coronavirus/country/italy/ (2023.08.15.)

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15. Worldometer – covid – Romania. https://www.worldometers.info/coronavirus/country/romania/  (2023.08.15.)

16. COVID-19 pandemic in Romania. https://en.wikipedia.org/wiki/COVID-19_pandemic_in_Romania (2023.08.15.)

17. Worldometer – covid – Hungary. https://www.worldometers.info/coronavirus/country/hungary/ (2023.08.15.)

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19. https://openknowledge.worldbank.org/server/api/core/bitstreams/e1e22749-80c3-50ea-b7e1-8bc332d0c2ff/content (2023.08.15.)

20. The economic impacts of the COVID-19 crisis. The WorldBank. https://www.worldbank.org/en/publication/wdr2022/brief/chapter-1-introduction-the-economic-impacts-of-the-covid-19-crisis (2023.08.15.)

21. Dirk Willem te Velde, The economic impact of coronavirus: five lessons and challenges. https://odi.org/en/insights/the-economic-impact-of-coronavirus-five-lessons-and-challenges/

22. Naseer S, Khalid S, Parveen S, Abbass K, Song H, Achim MV. COVID-19 outbreak: Impact on global economy. Front Public Health. 2023 Jan 30;10:1009393. doi: 10.3389/fpubh.2022.1009393. PMID: 36793360; PMCID: PMC9923118. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9923118/ (2023.08.15.)

23. Copenhagen economics, Economic consequences of the COVID-19 pandemic. https://copenhageneconomics.com/wp-content/uploads/2021/12/copenhagen-economics_economic-consequences-covid-19.pdf (2023.08.15.)

24. World Development Report 2022. Chapter 1. The economic impacts of the COVID-19 crisis. https://www.worldbank.org/en/publication/wdr2022/brief/chapter-1-introduction-the-economic-impacts-of-the-covid-19-crisis (2023.08.15.)

25. Heal All Erasmus+ project homepage. https://healall.eu/home/ (2023.08.15.)

26. Naseer S, Khalid S, Parveen S, Abbass K, Song H and Achim MV (2023) COVID-19 outbreak: Impact on global economy. Front. Public Health 10:1009393. doi: 10.3389/fpubh.2022.1009393

27. Lagos DG, Poulaki P, Lambrou P. COVID-19 and Its Impact on Tourism Industry. Adv Exp Med Biol. 2021;1318:815-824. doi: 10.1007/978-3-030-63761-3_45. PMID: 33973213.

28. Jaffar Abbas, Riaqa Mubeen, Paul Terhemba Iorember, Saqlain Raza, Gulnara Mamirkulova, Exploring the impact of COVID-19 on tourism: transformational potential and implications for a sustainable recovery of the travel and leisure industry. Current Research in Behavioral Sciences, Volume 2, 2021, 100033, ISSN 2666-5182, https://www.sciencedirect.com/science/article/pii/S2666518221000206 (2023.08.15.)

29. Impact assessment of the Covid-19 outbreak on international tourism. UNWTO, https://www.unwto.org/impact-assessment-of-the-covid-19-outbreak-on-international-tourism (2023.08.15.)

30. HealthMap, Covid-19. https://www.healthmap.org/covid-19/ (2023.08.15.)

31. Caroline Westbrook, Which countries still have Covid travel restrictions in 2023? Rules explained. https://metro.co.uk/2023/05/17/which-countries-still-have-covid-travel-restrictions-in-2023-rules-explained-18800903/ (2023.06.01.)

32. Billy Jiang, 20 Countries That Still Have COVID Travel Restrictions. https://www.thatsmags.com/china/post/36063/holiday-planner-travel-restrictions-update-june-2023 (2023.07.09.)

33. Steve Brock, Here are 8 ways travel will change after the pandemic. https://www.nationalgeographic.com/travel/article/heres-how-covid-is-changing-travel-according-to-the-experts (2023.08.15.)

34. Marques Santos, A., Madrid, C., Haegeman, K. and Rainoldi, A., Behavioural changes in tourism in times of Covid-19, Publications Office of the European Union, Luxembourg, 2020, ISBN 978-92-76-20401-5, doi:10.2760/00411, JRC121262.

35. Varga Levente, Miklóssy Ildikó, Nagy Benedek, Szakál, Zoltán, Nádasdi, Kristóf Zsolt, Paulikné, Varga Barbara, Helmeczi, Gabriella, Székely, Leila, Nádasdiné, Tóth Kitti, Takács, Péter: Együttműködésen alapuló, projekt szemléletű oktatás a digitális térben A HEAL-ALL projekt eTwinning tapasztalatai az egészségügyi oktatás területén. In: Moravcsikné, Dr. Kornyicki Ágota; Jávorné, Erdei Renáta (szerk.) II. Várandósság és egészséges életkezdet : Dr. Adorján Gusztáv Tamás Emlékkonferencia absztraktfüzet és programfüzet, Debreceni Egyetem Egészségtudományi Kar (2023) p. 16.

36. Péter, Takács; Ildikó, Miklóssy; Benedek, Nagy; Zoltán, Szakál; Kristóf, Zsolt Nádasdi; Barbara, Paulikné Varga; Gabriella, Helmeczi; Kitti, Nádasdiné Tóth; Levente, Varga: The impact of the coronavirus epidemic on tourism - HEAL-ALL survey. In: Rusinné, Fedor Anita; Tóth, Dalma; Zakor-Broda, Rita (szerk.) XIV. Nemzetközi Nyíregyházi Doktorandusz és Posztdoktori Konferencia : Absztraktkötet. Debreceni Egyetem Egészségtudományi Kar (2022) 167 p. p. 163.

37. Takács Péter, Kristóf Zsolt, Láczay Magdolna, Lövei-Kalmár Katalin, Paulikné Varga Barbara, Szakál Zoltán, Varga Levente: HEAL-ALL - Pályázat az egészségturizmus oktatás fejlesztésére. In: Rusinné Fedor Anita; Balla Petra (szerk.) Magyar Tudomány Ünnepe 2020 „Jövőformáló Tudomány – Generációk Egymásért” Kutatási innovációk és új eredmények : Absztraktfüzet. Debreceni Egyetem Egészségügyi Kar (2020) 28 p. p. 17.

APPENDIX

I. List of attached files

· 001_orszag_kizaras.htm

· 010_V4_1_gender.htm

· 011_V4_2_age.htm

· 012_V4_3_education.htm

· 015_V4_9_financial.htm

· 016_V4_10_work.htm

· 017_V4_11_car.htm

· 030_pairedTT_Wilcox.htm

· 030_V1_1_and_V3_3_domest.htm

· 050_MIII_descrD_HU.htm

· 050_MII_descrC_HU.htm

· 050_MIV_descrE_HU.htm

· 050_MI_descrA_HU.htm

· 050_MI_descrB_HU.htm

· 051_MIII_descrD_TR.htm

· 051_MII_descrC_TR.htm

· 051_MIV_descrE_TR.htm

· 051_MI_descrA_TR.htm

· 051_MI_descrB_TR.htm

· 052_MIII_descrD_IT.htm

· 052_MII_descrC_IT.htm

· 052_MIV_descrE_IT.htm

· 052_MI_descrA_IT.htm

· 052_MI_descrB_IT.htm

· 060_HU_interests.htm

· 061_TR_interests.htm

· 062_IT_interests.htm

· 064_sum_interests_inferential.htm

· QHU.html

· QIT.html

· QTR.html

II. A few comments – based ont he results of the research and the processing of the literature

The coronavirus pandemic has had such a great impact on the history of mankind that it is impossible to give a complete overview right now. The wikipedia entry itself contains around 700 references - perhaps the most in the encyclopedia system. During the literature research and the processing of the data, many thoughts and comments were made. Let some of them follow here - more freely, some facts and statements without references.

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A) Pandemic in the human history: Pandemics have played a significant role in human history and have had a profound impact on societies and civilizations. Some of the most notable pandemics in human history include:

The Plague of Athens (430 BCE): This pandemic, which was likely caused by the bubonic plague, decimated the city of Athens during the Peloponnesian War and is thought to have contributed to the city's eventual defeat. []

The Justinian Plague (541-542 CE): This pandemic, which was also caused by the bubonic plague, swept through the Byzantine Empire and is estimated to have killed as many as 100 million people. []

The Black Death (1331-1353 CE): This pandemic, which was caused by the bubonic, pneumonic, and septicemic plagues, is considered one of the deadliest pandemics in human history, killing an estimated 75-200 million people across Europe, Asia, and Africa. []

The Third Cholera Pandemic (1852-1960): This pandemic, caused by the Vibrio cholerae bacterium, resulted in multiple outbreaks across the world, including in Europe, Africa, and Asia. []

The Yellow Fever Pandemic (1881-1905): This pandemic, caused by the yellow fever virus, resulted in outbreaks in several countries in Africa and the Americas. []

The Spanish Flu (1918-1920): This pandemic, which was caused by the H1N1 influenza virus, was one of the deadliest pandemics in modern history, killing an estimated 50-100 million people worldwide. []

The AIDS Pandemic (1981-present): This pandemic, which is caused by the human immunodeficiency virus (HIV), has had a significant impact on global health and has resulted in an estimated 32 million deaths. []

The H1N1 Pandemic (2009-2010): This pandemic, caused by the H1N1 influenza virus, resulted in a global outbreak and was declared a pandemic by the World Health Organization (WHO). []

The Ebola Pandemic (2014-2016): This pandemic, caused by the Ebola virus, resulted in a large outbreak in West Africa and was the largest Ebola outbreak in history.

The SARS Pandemic (2002-2004): This pandemic, caused by the severe acute respiratory syndrome coronavirus (SARS-CoV), resulted in outbreaks in several countries in Asia and was eventually contained by global health efforts.

B) Are epidemics/pandemics more common nowadays than in the past? It is difficult to say with certainty whether epidemics and pandemics are more common now than in the past, as improved monitoring and reporting systems make it easier to detect and respond to outbreaks in real-time. However, some factors that may contribute to an increase in the frequency and severity of epidemics and pandemics include:

Rapid global travel and transportation: The ease and speed with which people and goods can move around the world increases the risk of rapid spread of infectious diseases.

Crowded living conditions: Densely populated urban areas can facilitate the spread of infectious diseases and make it more difficult to control outbreaks.

Changes in land use and environmental degradation: Deforestation, agriculture, and urbanization can bring humans into closer contact with wildlife, increasing the risk of zoonotic diseases (diseases that are transmitted from animals to humans).

Antimicrobial resistance: The overuse and misuse of antibiotics and other antimicrobial agents can lead to the development of drug-resistant bacteria, making it more difficult to treat infections.

Weak health systems: In some regions, weak health systems and limited resources can make it more difficult to detect, respond to, and control outbreaks.

C) The frequency of pandemic alert will be more? It is difficult to predict the future frequency of pandemics with certainty, but experts generally believe that the risk of pandemics will continue to increase. There are several factors that are likely to contribute to this trend (see list below). Given these trends, it is likely that the frequency of pandemics will increase in the coming years, and that continued vigilance and preparedness will be necessary to prevent and control future outbreaks.

Globalization and increased travel: The ease and speed of travel and trade make it easier for diseases to spread across borders and reach new populations.

Climate change: Changes in temperature, rainfall patterns, and other factors can impact the distribution and behavior of disease vectors, increasing the risk of outbreaks.

Deforestation and land use change: These activities can displace animal populations, leading to greater exposure to new diseases and increasing the risk of spillover into human populations.

Antimicrobial resistance: The widespread use of antibiotics and other antimicrobial agents has led to the emergence of drug-resistant pathogens, making it more difficult to treat and prevent infections.

Health system preparedness: The ability of health systems to respond effectively to outbreaks is key to controlling their spread and minimizing the impact on public health.

D) Pandemic among animals: Pandemics can occur among animals as well as humans. Animal pandemics can have significant impacts on agriculture, trade, and the food supply, as well as on the health and welfare of the affected animals. They can also potentially spill over and infect humans, as in the case of Avian Flu and Swine Flu. Therefore, it is important to monitor and control animal diseases to prevent the spread of pandemics.

Foot and Mouth Disease (FMD) - a highly contagious viral disease that affects cloven-hoofed animals, such as cattle, pigs, sheep, and goats. []

Avian Flu (H5N1) - a strain of the influenza virus that primarily affects birds, but can also infect humans and other animals. []

Swine Flu (H1N1) - a strain of the influenza virus that primarily affects pigs, but can also infect humans and other animals. []

Rabies - a viral disease that primarily affects mammals, such as dogs, bats, and raccoons. []

Rift Valley Fever - a viral disease that primarily affects cattle and sheep, but can also infect humans and other animals. []

E) The main effects of Covid-19: The COVID-19 pandemic has had far-reaching effects on many aspects of society and the global economy, including health, politics, economics, and daily life. Some of the main effects of COVID-19 include:

Health effects: The most significant effect of COVID-19 is the health impact. The virus is highly contagious and can cause severe respiratory illness, with symptoms ranging from mild to severe. It can also result in death, particularly in older adults and those with underlying health conditions. The pandemic has also put a tremendous strain on healthcare systems around the world, leading to shortages of medical supplies, overwhelmed hospitals, and overwhelmed healthcare workers.

Economic effects: The COVID-19 pandemic has had a major impact on the global economy. Businesses have closed, unemployment rates have risen, and consumer spending has decreased, leading to a significant slowdown in the economy. The travel and hospitality industries have been particularly hard-hit, with many companies experiencing significant losses and laying off workers. Governments around the world have implemented various measures to support their economies, including stimulus packages, tax relief, and other financial support measures.

Political effects: The COVID-19 pandemic has also had significant political effects. The response to the pandemic has become a major political issue, with many countries implementing measures such as lockdowns and travel restrictions to slow the spread of the virus. The pandemic has also highlighted existing inequalities and disparities in healthcare systems, leading to calls for reforms and improvements in healthcare systems around the world.

Social effects: The COVID-19 pandemic has also had major social effects. The lockdowns and travel restrictions have disrupted daily life, leading to increased stress and anxiety, and a decline in mental health. The pandemic has also led to a shift in the way people work and socialize, with many people now relying on technology to stay connected with friends and family. The pandemic has also put a strain on relationships and has led to increased domestic violence and child abuse in some areas.

Environmental effects: The COVID-19 pandemic has also had some unintended environmental effects. The slowdown in economic activity has resulted in reduced emissions and improved air quality in many cities. However, the increased use of single-use plastics, such as face masks and gloves, has led to an increase in plastic waste. The pandemic has also led to a reduction in global travel, which has had a positive impact on the environment, but has also led to decreased revenue for the tourism industry and a decrease in conservation funding in some areas.

F) What are the most important questions about Covid-19 pandemic? It is difficult to identify a single most important question about the COVID-19 pandemic as the situation is complex and impacts various aspects of society in different ways.

Direct (short term)

· What is COVID-19 and how is it spread?

· What are the symptoms of COVID-19 and how is it diagnosed?

· What measures can be taken to prevent the spread of COVID-19?

· What are the current global statistics on the spread and impact of COVID-19?

· What is the current status of the global response to COVID-19, including the development of vaccines and treatments?

· What are the implications of COVID-19 for travel, business, and the economy?

· What steps are being taken by governments and organizations to support individuals and communities affected by the pandemic?

· What is the long-term impact of COVID-19 on society, including on public health, the economy, and social and cultural norms?

and Indirect (long term)

· How can we effectively control and prevent the spread of COVID-19?

· How can we ensure access to vaccines and treatments for all populations?

· What are the long-term health effects of COVID-19 and how can we best manage them?

· How can we support communities and individuals who have been disproportionately affected by the pandemic, such as those in low-income countries, essential workers, and people of color?

· How can we prevent and mitigate the economic, social, and political impacts of the pandemic, such as job losses and increased inequality?

· How can we improve our ability to respond to future pandemics and other global health threats?

G) Different starting states and situations - different responses: Different countries and different social groups may have responded to the COVID-19 pandemic in different ways. The reactions appeared as a complex effect of many factors. For example, the economic development of a country, cultural habits, government measures, the development and condition of the health infrastructure and professional staff, and the attitude of the population are all influencing factors.

Some examples of different reactions:

Government measures/actions: Countries have introduced measures to slow down the spread of the epidemic to different degrees and in different ways. Some countries have imposed strict lockdowns, while others have imposed more lenient restrictions. These measures affected economic activities and daily life.

Healthcare infrastructure: Countries with strong and well-functioning health systems were able to respond more easily to the epidemic. The capacity of the health care system, medical equipment and the number of health professionals were key to an effective response. The highly qualified workforce acted as a life-saving factor, in a proven way [].

Cultural customs and traditions: Cultural differences strongly influenced how people and communities responded to the epidemic. For example, societies where social cohesion is important were able to apply the rules of social distancing and mask wearing much more difficult.

Economic impacts and jobs: Countries with different economic situations may have responded to the challenges in different ways. In developing countries - where individual and family reserves are smaller; many people support themselves from their day jobs - the closures have caused severe economic hardship. Developed countries were able to provide greater economic support to the population.

Communication and social/community awareness: Countries and groups that communicated effectively about the epidemic and raised awareness of precautions were better able to meet the challenge. The lack of information and the spread of false information made it difficult to manage the epidemic.

Use of digital technology: Individual countries and societies have used digital technologies in work, education and online communication to varying degrees. Those among whom these digital options were previously widespread adapted to the social distancing measures more easily.

H) Italy - Romania/Transylvania: Italy and Romania responded to the COVID-19 pandemic in different ways, as the two countries have differences due to their own economic, social and cultural environment. Some typical examples of the differences:

Government Actions and Timing: Italy was one of the first European countries to experience a serious outbreak of the virus. The country quickly imposed strict lockdowns to slow the spread. Romania also introduced restrictions, but the timing and severity of the measures differed between the two countries.

Health infrastructure and resources: Italy's healthcare system has become heavily strained during the epidemic, especially in the Lombardy region. The Italian healthcare infrastructure came close to collapse due to the challenge of the very high number of diseases. Similar problems arose in Romania, as the healthcare system there was also overloaded in many places.

Social and cultural customs: Italian society is characterized by strong cohesion and the significant role of family ties. The distancing measures introduced due to the epidemic contradicted these traditional values. Family ties are also important in Romania, but the structure of society and cultural customs are different from Italy. These differences and their effects have intensified during the epidemic.

Economic situation and support: Italy's economy is heavily dependent on tourism, which has suffered badly due to the pandemic. The country introduced extensive economic support programs to alleviate the crisis. The economic effects were also felt in Romania, but the country's economy and support options are different from Italy - because of this, the critical points appeared elsewhere.

Communication and social/community awareness: In both countries, the way and effectiveness of communication between governments and health authorities influenced the response of the public. Transparency of information and informing people about the epidemic situation was key in both countries.

I) Hungary – Romania/Transylvania: Hungary and Romania reacted to the COVID-19 pandemic in different ways, as the two countries show differences due to their own cultural, economic and social contexts. Some examples of differences:

Government Actions and Timing: Both countries have introduced restrictions and measures to slow the spread of the epidemic. Hungary introduced stricter lockdowns, such as a curfew, while Romania also introduced restrictions, but they allowed more space for the population to meet their daily needs.

Health infrastructure and resources: The healthcare systems of both countries faced serious challenges during the epidemic. In both Hungary and Romania, the burden on the health infrastructure and the issue of patient care was key.

Economic situation and support: The economies of the two countries suffered from the pandemic, but the basic economic situation and the support mechanisms were different. Hungary introduced economic aid programs to mitigate the effects of the crisis, while economic challenges in Romania required different measures.

Social and cultural customs: Family and community ties are important in both Hungary and Romania, but social customs differ. These habits may have influenced how people responded to social distancing measures and other precautions.

Communication and awareness: The communication of governments and health authorities influenced people's conscious behavior in the epidemic situation. Effectiveness and transparency of communication were key in both countries.

J) Hungary - Italy: Both Hungary and Italy reacted differently to the COVID-19 pandemic, as both countries have differences arising from their own economic, social and cultural contexts.

Government Actions and Timing: Italy was one of the first and most severely affected European countries at the beginning of the pandemic. The country has imposed strict lockdowns, including territorial restrictions. Hungary also introduced restrictions, but the timing of closures and measures differed between the two countries.

Health infrastructure and resources: The Italian healthcare system experienced an extremely high strain during the epidemic (see the situation in Lombardy). Hungary also faced healthcare challenges, but healthcare infrastructure and resource management differed between countries.

Economic situation and support: Italy's economy is significantly dependent on tourism, which has been severely affected by the pandemic. The country introduced extensive economic support programs to alleviate the crisis. Hungary also had economic measures, but the economic situation and support mechanisms were different.

Social and cultural customs/habits: Italy is characterized by strong family ties and community life, which have made it difficult to comply with social distancing measures. Family relationships are also important in Hungary, but social habits are different - these habits appeared in a different way and form during the fight against the virus.

Communication and awareness: Transparency of information and people's awareness were very important in both countries. Italian authorities and media have emphasized the severity of the outbreak and urged the public to take precautions. Significant communication efforts were also made in Hungary to raise awareness of the epidemic threat.

K) Different age groups, different effects, different reactions:

Older age groups: Older people (especially those over 60) were at greater risk from the virus. According to the aggregated data, a significant number of deaths from COVID-19 occurred in this age group. For this reason, in many countries, care homes for the elderly have been placed under increased protection and elderly people have been advised to avoid social contact.

Younger age groups: Younger age groups generally fell less seriously ill and had a lower death rate - at the same time, there were young people who became seriously ill. During the spread of the infection, the young age group could transfer the virus to vulnerable groups.

Economic effects: For the younger generations, the economic effects were more significant. Many young people's jobs were threatened by the crisis, especially in areas affected by the closures. Changes in education systems have also significantly affected young people, as classroom education has been replaced by online learning in many countries.

Mental health: The epidemic situation caused long-term stress and mental strain in different age groups. Isolation, insecurity and worry about health risk had a major impact on mental health and could affect people of all ages.

Compliance with protective measures: Different age groups had different attitudes towards protective measures. While some young people may have taken social distancing and wearing masks less seriously, older people were often more cautious about protecting their own health and the health of others.

L) Educational background: People with different educational backgrounds have been affected and responded to the effects of the COVID-19 pandemic in different ways. Education and related professional opportunities, financial situation and social background significantly influenced how people experienced and dealt with the consequences of the epidemic.

Job situation: People with higher education often have higher professional opportunities. These options allowed them to work remotely or flexibly. In contrast, people with lower levels of education often work in jobs that do not allow telecommuting and thus were at greater risk.

Economic effects: People with lower education often have less financial reserves, so they found themselves more easily faced with economic difficulties. Those who work in jobs that have been severely affected by the virus outbreak (such as hospitality or personal services) have experienced more hardship due to job losses and reduced income.

Access to education: People with higher levels of education generally had better access to online and distance learning when schools and universities were closed due to the pandemic. Access to digital tools and online learning was generally more difficult for those with less education (and their families).

Health awareness: Higher education is often associated with greater health awareness and better understanding of scientific information. This allowed them to better understand the nature of the epidemic and the importance of prevention.

Mental health: The mental health of people with lower levels of education may have suffered more during the pandemic, as they had fewer resources and support to deal with stress and anxiety.

M) The Young (teenager) age group: The high school age group, i.e. teenagers and young adults, reacted differently to the effects of the COVID-19 pandemic. Their lives and experiences are already different from children and adults, so their reactions were also specific.

Education and school life: For high school students, education and school life have undergone major changes during the pandemic. Many countries have switched to online education or blended learning methods, which has created new challenges for both students and teachers. School closures and social distancing have provided the basis for an increase in virtual communication and the use of technological tools.

Social relationships and isolation: For high school students, social relationships and spending time with friends are extremely important. Isolation, closures and distancing have left many young people feeling lonely or frustrated. At the same time, they tried to maintain their relationships with the help of digital tools.

School and future plans: For high school students, the epidemic may have changed their school and future plans. Those who graduated during the pandemic often chose a different career path. Those students for whom it was important to experience social experiences may have felt disappointed due to the lack of various events and programs.

Mental health: The epidemic and school changes may have caused a lot of stress and anxiety among high school students. Changes, unfamiliarity and lack of information had a negative impact on mental health. Those who may have previously struggled with mental health issues may have faced additional challenges.

Digital addiction: In times of online education and social distancing, high school students have had to spend more time with digital devices. This may have increased digital addiction and excessive attachment to online content.

N) Regarding the future... Based on the analyses, some general conclusions can perhaps be drawn for the future, especially in terms of preparing for and responding to similar situations and crises:

Development of flexible educational solutions: The pandemic has highlighted the need for education to be flexible so that students can learn beyond traditional school settings. In terms of online learning and the development of digital educational tools, it is important that students are able to continue their studies in the future due to school closures or other reasons.

Mental health support: The effects of the pandemic, such as isolation and anxiety, have drawn attention to the importance of mental health. In the future, it is important that communities, schools and health institutions pay more attention to mental health support and integrate the necessary knowledge in school programs.

Dealing with inequalities from different sources: The systematic examination of the pandemic highlighted the strengthening of social and economic inequalities among the effects of the epidemic. In the future, crisis management strategies must take into account the different needs of different groups and strata in order to prevent further growth of inequalities.

Strengthening social connections and flexibility: People's social connections and adaptability played a critical role during the pandemic. Healthy community relations and flexible thinking make it easier for people to adapt and find solutions to similar crises.

Fast and reliable flow of information: The lack of information and the spread of false information caused a serious problem during the pandemic. In the future, a reliable and fast flow of information may be crucial, contributing to proper information of the population and making the right decisions.

Developing emergency plans: The differing reactions underscore the importance of developing and testing emergency plans. States and institutions must have flexible plans that enable rapid response and intervention in similar crises.

O) Change of tourism: It is difficult to predict exactly how the tourism industry will change after the COVID-19 pandemic, but it is likely that there will be some permanent changes in the way people travel and in the way the industry operates. Some possible changes:

Increased focus on health and safety measures: With the COVID-19 pandemic, health and safety measures are likely to become a higher priority for both travelers and the tourism industry. This could result in increased use of technology such as contactless payment and virtual check-in, and more rigorous cleaning and sanitization procedures in hotels, restaurants, and tourist attractions.

Shift to domestic travel: The COVID-19 pandemic has resulted in a shift in travel patterns, with many travelers opting for domestic travel over international travel. This trend is likely to continue in the short-term, as some people may be hesitant to travel internationally until the pandemic is better controlled.

Increase in outdoor and nature-based tourism: With the pandemic, many people have come to appreciate the benefits of spending time in nature and outdoor spaces. This may result in an increase in outdoor and nature-based tourism, such as camping, hiking, and wildlife watching.

Growth of online travel booking: The COVID-19 pandemic has accelerated the trend towards online travel booking, as many people prefer to make travel arrangements from the safety of their own homes. This trend is likely to continue in the future, and the use of technology for booking and managing travel is likely to increase.

Increased interest in sustainable tourism: The COVID-19 pandemic has raised awareness of the impact of travel on the environment and the importance of sustainable tourism practices. This may result in increased demand for sustainable tourism options, such as eco-friendly hotels and sustainable transportation.

P) Prepare for the post-Covid-19 situation in tourism: To prepare for the post-COVID-19 situation in the tourism industry, there are several steps that individuals, organizations, and governments can take:

Enhance health and safety measures: With the COVID-19 pandemic, health and safety measures are likely to become a higher priority for both travelers and the tourism industry. This means enhancing cleaning and sanitization procedures, increasing the use of technology to minimize contact, and implementing health screening measures at points of entry.

Invest in technology: Technology will play a key role in the future of tourism, both in terms of travel booking and in enhancing the overall travel experience. This means investing in technology solutions to improve the online booking experience, enhancing virtual experiences for tourists, and using technology to provide real-time information about the health and safety situation at destinations.

Promote domestic and regional travel: With the shift towards domestic and regional travel, it is important to promote these destinations and provide travelers with information about the health and safety measures that are in place. This may involve working with local tourism boards and private sector organizations to develop and promote travel packages and itineraries.

Focus on sustainability: The COVID-19 pandemic has raised awareness of the impact of travel on the environment and the importance of sustainable tourism practices. This means promoting sustainable tourism options, such as eco-friendly hotels and sustainable transportation, and working to minimize the negative impacts of tourism on local communities and the environment.

Support local communities: The COVID-19 pandemic has had a devastating impact on the livelihoods of people in the tourism industry, including hotel and restaurant workers, tour guides, and transportation providers. It is important to support these communities and help them recover by promoting local businesses and supporting local economic development initiatives.

Diversify product offerings: Diversifying product offerings can help to mitigate the impact of future crises on the tourism industry. This can involve promoting new destinations or types of tourism, such as adventure or wellness tourism, or developing new products or services, such as sustainable tourism experiences or virtual reality experiences.

Foster partnerships: Building partnerships between the tourism industry, local communities, and governments can help to enhance the resilience and sustainability of the tourism industry. This can involve working with local organizations to develop sustainable tourism initiatives, partnering with hotels and other service providers to enhance the health and safety measures in place, and collaborating with governments to promote sustainable tourism practices.

Provide training and support: Providing training and support to workers in the tourism industry can help to build their resilience and enable them to adapt to changing conditions. This can involve providing training in new skills, such as the use of technology, or providing financial support to help workers weather economic downturns.

Encourage responsible travel: Encouraging responsible travel can help to build a more sustainable tourism industry and minimize the impact of tourism on local communities and the environment. This can involve promoting environmentally-friendly travel practices, such as reducing single-use plastics, or encouraging tourists to engage in responsible and sustainable tourism practices, such as supporting local businesses and minimizing the impact of their travel on the environment.

Embrace digital transformation: The COVID-19 pandemic has accelerated the pace of digital transformation in many industries, including the tourism industry. Embracing digital transformation can help to enhance the efficiency and competitiveness of the tourism industry, improve the overall travel experience for tourists, and minimize the risk of future crises. This can involve investing in digital solutions, such as virtual reality experiences or online travel booking platforms, or leveraging technology to enhance the health and safety measures in place.

Q) Covid-19 pandemic in the viewpoint of history: The COVID-19 pandemic is a historical event that will be studied and remembered for generations to come. In the viewpoint of history, the pandemic is likely to be seen as a major turning point in several ways.

Global Health: The COVID-19 pandemic has brought into sharp focus the importance of global health and the need for increased investment in public health systems and disease surveillance. The pandemic has also highlighted the importance of international cooperation in responding to global health threats.

Science and Innovation: The rapid development and distribution of COVID-19 vaccines is one of the largest and fastest mass vaccination campaigns in history and has demonstrated the power of science and innovation in addressing global health challenges.

Society and Culture: The pandemic has had a profound impact on society and culture, transforming the way we live, work, and interact with each other. This has resulted in increased use of technology and digital communication, changes in the workplace, and shifts in consumer behavior.

Economic and Political Systems: The COVID-19 pandemic has exposed the fragility of many economic and political systems, with devastating impacts on economies and jobs, and increasing disparities between the rich and poor. The pandemic has also led to a reconsideration of the role of government in protecting public health and supporting vulnerable populations.

Environmental Issues: The pandemic has led to reductions in greenhouse gas emissions, air and water pollution, and wildlife habitat destruction, as well as increased public awareness and concern about the impacts of human activities on the environment.

Health care systems: The COVID-19 pandemic has exposed the weaknesses and disparities in many health care systems and has led to a reconsideration of the importance of investing in public health infrastructure and resources.

Education: The pandemic has disrupted education systems around the world and has accelerated the adoption of online and remote learning technologies. This has implications for the future of education and may lead to a permanent shift in the way education is delivered.

Work and Employment: The pandemic has resulted in widespread job losses and economic uncertainty, leading to a reevaluation of the value of work, the role of the state in protecting workers, and the importance of a safety net.

Mental Health: The pandemic has taken a toll on mental health, with increased levels of anxiety, depression, and stress, and has highlighted the need for more investment in mental health services.

International Relations: The pandemic has exposed the importance of international cooperation and solidarity, but has also resulted in increased tensions and conflicts, particularly with regard to access to medical supplies and vaccines.

Overall, the COVID-19 pandemic will be seen as a defining moment in history, with far-reaching impacts on many aspects of society. It is likely to lead to lasting changes in the way we live, work, and interact with each other, and we will be remembered as a time of unprecedented global crisis and response.

III. Additional related literature sources used during the research

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