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The Effects of Different Malaria Prevention Measures: Panel Data Analysis
Název práce v češtině: Účinky vybraných opatření k prevenci malárie: analýza panelových dat
Název v anglickém jazyce: The Effects of Different Malaria Prevention Measures: Panel Data Analysis
Klíčová slova: Malárie, Preventivní Opatření, Panelová Data, Regresní Analýza, Bootstrapová Metoda, Shluková Analýza
Klíčová slova anglicky: Malaria, Preventive Measures, Panel Data, Regression Analysis, Bootstrapping, Cluster Analysis
Akademický rok vypsání: 2018/2019
Typ práce: diplomová práce
Jazyk práce: angličtina
Ústav: Institut ekonomických studií (23-IES)
Vedoucí / školitel: Mgr. Barbara Pertold-Gebicka, M.A., Ph.D.
Řešitel: skrytý - zadáno vedoucím/školitelem
Datum přihlášení: 09.04.2019
Datum zadání: 09.04.2019
Datum a čas obhajoby: 16.06.2020 09:00
Datum odevzdání elektronické podoby:07.05.2020
Datum proběhlé obhajoby: 16.06.2020
Oponenti: PhDr. Lucie Bryndová
 
 
 
Kontrola URKUND:
Seznam odborné literatury
K, Wangdi, Furuya-kanamori L, Clark J, et al. Comparative effectiveness of malaria prevention measures: a systematic review and network meta-analysis. Parasites [online]. 2018, 11(1), 210 [cit. 2019-05-01]. DOI: 10.1186/s13071-018-2783-y. ISSN 17563305.

G, Gachelin, Garner P, Ferroni E, Verhave JP a Opinel A. Evidence and strategies for malaria prevention and control: a historical analysis. Malaria Journal [online]. 2018, 17(1), 96 [cit. 2019-05-01]. DOI: 10.1186/s12936-018-2244-2. ISSN 14752875.

HAILU, Alemayehu, Bernt LINDTJØRN, Wakgari DERESSA, Taye GARI, Eskindir LOHA a Bjarne ROBBERSTAD. Cost-effectiveness of a combined intervention of long lasting insecticidal nets and indoor residual spraying compared with each intervention alone for malaria prevention in Ethiopia. Cost Effectiveness and Resource Allocation [online]. 2018, 16(1), 1-17 [cit. 2019-05-01]. DOI: 10.1186/s12962-018-0164-1. ISSN 14787547.

NYAVOR, Kunche delali, Margaret KWEKU, Isaac AGBEMAFLE, Wisdom TAKRAMAH, Ishmael NORMAN, Elvis TARKANG a Fred BINKA. Assessing the ownership, usage and knowledge of Insecticide Treated Nets (ITNs) in Malaria Prevention in the Hohoe Municipality, Ghana. Pan African Medical Journal [online]. 2017, 28, 1-8 [cit. 2019-05-01]. DOI: 10.11604/pamj.2017.28.67.9934. ISSN 19378688.

JN, Hogarh, Agyekum TP, Bempah CK, Owusu-ansah EDJ, Avicor SW, Awandare GA, Fobil JN a Obiri-danso K. Environmental health risks and benefits of the use of mosquito coils as malaria prevention and control strategy. Malaria Journal [online]. 2018, 17(1), 265 [cit. 2019-05-01]. DOI: 10.1186/s12936-018-2412-4. ISSN 14752875.

MANGENI, Judith nekesa, Diana MENYA, Andrew OBALA, Alyssa PLATT a Wendy prudhomme O'MEARA. Development and validation of a rapid assessment tool for malaria prevention. Malaria Journal [online]. 2016, 15, 1-12 [cit. 2019-05-01]. DOI: 10.1186/s12936-016-1575-0. ISSN 14752875.
Předběžná náplň práce
Motivation:
Every year, the number of people dying on malaria is approaching 500 000. Therefore, malaria belongs to one of the greatest threats around the world affecting mainly emerging countries. In my diploma thesis, I would like to focus on preventive measures that help decrease the number of deaths caused by malaria. Many organizations (WHO, UNICEF) try to help malarial countries by providing them funds or different preventive commodities. I would like to study the impact of these preventive measures on occurrence of malaria. Furthermore, there exist only a few studies discovering the general problem of malaria prevention. Most of the existing studies are aimed only at one concrete preventive control or one concrete country, mostly African region (such as study by J. Gimnig, P.Otieno and V. Were (2016) focused on Western Kenya or study by T. Solomon, E. Loha, W. Deressa, T. Gari, H. Overgaard and B. Lindtjorn (2019) from Ethiopia). The research by K. Wangdi, L. Furuya-Kanamori and J. Clark (2018) studies malaria prevention as general. For that purpose, they used Bayesian approach. However, using old data, they did not consider modern measures such as long-lasting insecticide nets. Therefore, I would like to get new information about malaria prevention from the research in my diploma thesis.

Hypotheses:
1) The first hypotheses I will be testing is whether the greater availability of preventive measures helps to decrease the number of malaria deaths. My expectation is that they do help.

2) Another hypothesis is focused on the differences between continents. My question is whether there is a similar development in the countries belonging to the same continent.

3) Next hypothesis explores methodology, namely, whether the fixed effect model or random effect model is better for my analysis. I believe that fixed effect model works better as thanks to panel data structure, there exist country-specific characteristics that endogenously affect the relationship between preventive measures and number of deaths caused by malaria.

Methodology:
More concretely, I would like to study the effects of distribution of mosquito nets, distribution of indoor residual spraying, availability of preventive testing on malaria (including the availability of RDT – rapid diagnostic tests), availability of different drugs, the effect of participation in World Malaria Program and the effect of distributed funds intended to prevent malaria.

For the purpose of the analysis, I will collect the data from the World Health Organization and from the Demographic and Health Surveys Program. I will rely on panel data for countries, which are threatened by malaria (Africa, America, Eastern Mediterranean, South-East Asia and Western Pacific). The data are mostly available from 2005 to 2018. Information on preventive measures and on the number of malaria-related deaths will be expresses in per capita terms to allow for comparison of differently sized countries.

The relation between preventive measures and malaria-related deaths might be endogenous. Mainly because aid is heavily concentrated on countries with the highest prevalence of malaria distributing mosquitos. To deal with this potential endogeneity I will rely on the panel structure of the data. I will use panel data regression techniques: fixed effect model and random effect model. I will conduct both techniques, test their validity and compare their result. As stated above, my hypothesis is that fixed effect model should work better, because of the endogeneity. To check the robustness, I will use simulation based method – bootstrapping. It will serve as control for the stability of my analysis. As malaria kills very rapidly, I will be able to see the development over time, which contrasts with other diseases with longer incubation period.

Another possibility of dealing with the endogeneity of aid is reliance on exogenous variation in the inflow of international aid (caused by such events as outbreak or end of war conflicts).

Additionally, taking advantage of having the data for countries all over the world, I will use the cluster analysis (k-means clustering and hierarchical clustering) to compare the results for different groups of countries to see whether countries from the same continent are in the same cluster and do have the same properties.

Finally, I will compare the accuracy of results obtained from different methods.

Expected Contribution:
The contribution of my thesis would be in studying the effects of different preventive measures, which should help various organizations as well as local governments to know what helps the most. I could observe how effective are these programs in preventing malaria as well as compare their usefulness in different regions and their development over time. I would use the most recent available data, which were still not used for such research. The main advantage in contrast to other studies will be in external validity. My results will be taken for the whole world with focus on different regions. The existing studies on this topic are often aimed only at one concrete country and therefore cannot be generalized. To my best knowledge, generalized studies about the effects of malaria prevention using the most recent data cannot be almost found.

Outline:
Introduction and motivation
Facts about malaria and its prevention around the world
Literature review
Description of data and methods
Panel data analysis
Cluster analysis
Results and discussion – globally and regionally
Conclusion
Předběžná náplň práce v anglickém jazyce
Motivation:
Every year, the number of people dying on malaria is approaching 500 000. Therefore, malaria belongs to one of the greatest threats around the world affecting mainly emerging countries. In my diploma thesis, I would like to focus on preventive measures that help decrease the number of deaths caused by malaria. Many organizations (WHO, UNICEF) try to help malarial countries by providing them funds or different preventive commodities. I would like to study the impact of these preventive measures on occurrence of malaria. Furthermore, there exist only a few studies discovering the general problem of malaria prevention. Most of the existing studies are aimed only at one concrete preventive control or one concrete country, mostly African region (such as study by J. Gimnig, P.Otieno and V. Were (2016) focused on Western Kenya or study by T. Solomon, E. Loha, W. Deressa, T. Gari, H. Overgaard and B. Lindtjorn (2019) from Ethiopia). The research by K. Wangdi, L. Furuya-Kanamori and J. Clark (2018) studies malaria prevention as general. For that purpose, they used Bayesian approach. However, using old data, they did not consider modern measures such as long-lasting insecticide nets. Therefore, I would like to get new information about malaria prevention from the research in my diploma thesis.

Hypotheses:
1) The first hypotheses I will be testing is whether the greater availability of preventive measures helps to decrease the number of malaria deaths. My expectation is that they do help.

2) Another hypothesis is focused on the differences between continents. My question is whether there is a similar development in the countries belonging to the same continent.

3) Next hypothesis explores methodology, namely, whether the fixed effect model or random effect model is better for my analysis. I believe that fixed effect model works better as thanks to panel data structure, there exist country-specific characteristics that endogenously affect the relationship between preventive measures and number of deaths caused by malaria.

Methodology:
More concretely, I would like to study the effects of distribution of mosquito nets, distribution of indoor residual spraying, availability of preventive testing on malaria (including the availability of RDT – rapid diagnostic tests), availability of different drugs, the effect of participation in World Malaria Program and the effect of distributed funds intended to prevent malaria.

For the purpose of the analysis, I will collect the data from the World Health Organization and from the Demographic and Health Surveys Program. I will rely on panel data for countries, which are threatened by malaria (Africa, America, Eastern Mediterranean, South-East Asia and Western Pacific). The data are mostly available from 2005 to 2018. Information on preventive measures and on the number of malaria-related deaths will be expresses in per capita terms to allow for comparison of differently sized countries.

The relation between preventive measures and malaria-related deaths might be endogenous. Mainly because aid is heavily concentrated on countries with the highest prevalence of malaria distributing mosquitos. To deal with this potential endogeneity I will rely on the panel structure of the data. I will use panel data regression techniques: fixed effect model and random effect model. I will conduct both techniques, test their validity and compare their result. As stated above, my hypothesis is that fixed effect model should work better, because of the endogeneity. To check the robustness, I will use simulation based method – bootstrapping. It will serve as control for the stability of my analysis. As malaria kills very rapidly, I will be able to see the development over time, which contrasts with other diseases with longer incubation period.

Another possibility of dealing with the endogeneity of aid is reliance on exogenous variation in the inflow of international aid (caused by such events as outbreak or end of war conflicts).

Additionally, taking advantage of having the data for countries all over the world, I will use the cluster analysis (k-means clustering and hierarchical clustering) to compare the results for different groups of countries to see whether countries from the same continent are in the same cluster and do have the same properties.

Finally, I will compare the accuracy of results obtained from different methods.

Expected Contribution:
The contribution of my thesis would be in studying the effects of different preventive measures, which should help various organizations as well as local governments to know what helps the most. I could observe how effective are these programs in preventing malaria as well as compare their usefulness in different regions and their development over time. I would use the most recent available data, which were still not used for such research. The main advantage in contrast to other studies will be in external validity. My results will be taken for the whole world with focus on different regions. The existing studies on this topic are often aimed only at one concrete country and therefore cannot be generalized. To my best knowledge, generalized studies about the effects of malaria prevention using the most recent data cannot be almost found.

Outline:
Introduction and motivation
Facts about malaria and its prevention around the world
Literature review
Description of data and methods
Panel data analysis
Cluster analysis
Results and discussion – globally and regionally
Conclusion
 
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