The relationship between populism and COVID-19 vaccination rates in the Czech Republic

• Thesis title in Czech: Vztah mezi populismem a úrovní vakcinace proti COVID-19 v České republice
• Thesis title in English: The relationship between populism and COVID-19 vaccination rates in the Czech Republic
• English key words: Global Health Security Index (GHSI), Mitigation measures, COVID-19
• Academic year of topic announcement: 2019/2020
• Thesis type: Bachelor's thesis
• Thesis language: angličtina
• Department: Institute of Economic Studies (23-IES)
• Supervisor: PhDr. Miroslav Palanský, Ph.D.
• Author: hidden - assigned by the advisor
• Date of registration: 24.07.2020
• Date of assignment: 24.07.2020
• Date and time of defence: 07.09.2022 09:00
• Venue of defence: Opletalova - Opletalova 26, O206, Opletalova - místn. č. 206
• Date of electronic submission: 01.08.2022
• Date of proceeded defence: 07.09.2022
• Opponents: prof. PhDr. Michal Bauer, Ph.D.

References

Bibliography

Emma Bennett, Lauren H. K. Chappell, Jacob Curran-Sebastian, Rajenki Das, Elizabeth Fearon, Martyn Fyles, Ian Hall, Thomas House, Hugo Lewkowicz, Katrina A. Lythgoe, Christopher E. Overton, Xiaoxi Pang, Lorenzo Pellis, Francesca Scarabel, Helena B. Stage, Bindu Vekaria, Luke Webb, Challenges in control of Covid-19:short doubling time and long delay to effect of interventions, March 2020.

Qanta A Ahmed, Shahul H Ebrahim, Ernesto Gozzer, Ziad A Memish, Patricia Schlagenhauf, Covid-19 and community mitigation strategies in a pandemic, March 2020.

Yuri Bruinen de Bruin, Peter Clevestig, Claudio Colosio, Margarida Goulart, Maryam Zare Jeddi, Anne-Sophie Lequarre, Josephine McCourt, Filippo Pigazzani, Initial impacts of global risk mitigation measures taken during the combatting of the COVID-19 pandemic, 2020.
Ngozi A Erondu, Ebere Okereke, Ahmed Razavi, The Global Health Security Index: what value does it add?, 2020.

Thomas J. Bollyky, Sawyer Crosby, Joseph L Dieleman, Samantha Kiernan, All bets are off for measuring pandemic preparedness, June 2020.

Thomas Hale, Beatriz Kira, Anna Petherick, Toby Phillips, Sam Webster, Oxford Covid-19 Government Response Tracker (OxCGRT), 2020.

Roy M Anderson, Hans Heesterbeek, T Deirdre Hollingsworth, Don Klinkenberg, How will country-based mitigation measures influence the course of the COVID-19 epidemic?, Mar 2020.How

Preliminary scope of work in English

Research question and motivation

The main research question I have chosen is how the degree of preparedness of states (measured using GHSI) and mitigation measures taken by them during the pandemic of COVID-19 will affect the impact of the disease and help to minimise damage on public health.

The coronavirus pandemic started in China in December 2019 and since that time it has spread all over the world where has caused enormous harm to public health and economic growth. For several reasons, current situation cannot be compared to previous epidemics which took place in world history. Three main factors that make today’s situation unique can be highlighted. First of all, today’s world is much more integrated than it was a few years ago. The modern world is interconnected and highly mobile, therefore it is a significant challenge for countries to take the spread of the virus under control. Secondly, insufficient knowledge of this new virus resulted in confusion and mixed recommendations from professionals about what measures and restrictions should be imposed in order to minimise the risk. Lastly, the disease caused by COVID-19 can be completely asymptomatic. It can lead to plenty of difficulties such as diagnostic problems, disability to assess all risks correctly and consequently, problems in making rational decisions which main goal is to improve public health.

Presently, countries all over the world attempt to reduce the growth of infection and decrease the mortality rate. It is a big question what specific factors influence on ability of countries to cope with this situation successfully. I would like to consider two such factors which I suppose play important role in capability of different countries to fight negative consequences of pandemic. The first factor is country preparedness to face global epidemical and health problems which can be assessed with the Global Health Security Index (GHSI). This index is a tool which provides the possibility to evaluate the reliability of health care in each country. This index illustrates the preparedness of different countries to keep people in safe, cure them, prevent and response on emergency situations (particularly, the pandemic). The first factor also can be measured using data on Domestic General Government Health Expenditure (as % of General Government Expenditure). The second factor is mitigation measures that were introduced in the majority of countries to prevent spread of the disease between people. Mitigation measures consist of mobility and social restrictions (main purpose of these restrictions is to limit the movement of people and their social activities such as participation in conferences, political events, religious gatherings, cultural celebrations and other mass events). Moreover, mitigation measures include physical distancing and hygiene measures. This factor can be evaluated using so called stringency index. This index is based on the information about containment and closer policies and public information campaigns. This information is contained in the database of Oxford Covid-19 Government Response Tracker (OxCGRT).

There are two hypotheses related with the efficiency of different country policy responses to COVID-19 which I would like to state. The first hypothesis is that countries which have the higher degree of preparedness have better chances to go through pandemic successfully (these countries will have lower mortality rate). The main aim of the GHSI is to evaluate possibilities of countries to ensure people’s safety and provide them with medical help in health threatening conditions (including epidemic). That is why the GHSI score is significant and the higher GHSI score should mean that country has more opportunities to solve epidemic problems. The second hypothesis is that the GHSI is important, but not sufficient for the prediction of the efficiency of response. Another significant factor is the speed of reaction of states to pandemic. In other words, how fast did countries implement stringent control measures in order to constrain the spread of COVID-19? The assumption is that the faster reaction is positively correlated with lower mortality rate.

Contribution

As I have already mentioned, the current epidemic situation differs from many others because of the rapid growth rate of disease, world integration and challenges of diagnostic. As a result, the high level of health security is not enough for successful response. There are countries with high GHSI score (like England) which failed in attempt to minimise negative effects of the coronavirus. At the same time there are countries (like Vietnam) with lower score which achieved positive results and significantly reduce the negative effects. Such examples can demonstrate the importance of mitigation measures and the rapidity of their implementation (the second factor). Besides, the second factor seems to be more essential.

However, now it is not possible to say which parameter is more essential. My main purpose is to analyse all parameters and test my hypotheses by using data about different countries policy responses and their preparedness (which will be more complete next year). It will help to determine the most effective factor.

In addition, I would like to emphasise the probable role of another factor which cannot be precisely assessed, but which can be discussed in the thesis. This factor is the degree of people’s trust in science, in health security, in public institutions and their preparedness to follow all recommendations of authorities in order to avoid risks to be infected.

Methodology

I will collect data which will contain the information about how rapid response of different countries all over the world was on spread of COVID-19 and how fast they implemented mitigation measures, social and mobility limitations, economic restrictions and rules of hygienic protection. Moreover, I will collect the data which will show indexes (GHSI) of preparedness of different states. Then I will build a regression model which will illustrate the relation between consequences of pandemic (which primarily will be evaluated using death rate) and two considered variables (two factors which I have mentioned above). After testing this model in R I will be able to say which factor gives better explanation of coronavirus effects and confirm or reject my hypotheses.

Outline

Introduction

a) the importance of my topic
b) the description of the problem
c) the purpose of the thesis
d) the organization of my thesis

The analysis of existing knowledge

a) different aspects of pandemic
b) why the current situation is unique
c) why considered factors are significant (explanation in detail)
d) overview of other factors which can affect consequences of COVID-19
e) the explanation of my hypotheses

Methodology

a) collecting, classification and interpretation of data
b) how I build the regression model
c) Testing the hypotheses

Results

a) confirm / reject the hypotheses
b) my interpretation of results

Conclusion

a) summarise all results and make a conclusion
b) if my research was useful (application of my research)
c) my own thoughts and reasoning