Abstract: Malaria is the deadliest parasitic mosquito-borne disease. Transmission rates and geographic distribution are being heavily influenced by climate change. As the effect of climate change on underdeveloped countries continues to worsen, the number of rates simultaneously follows. Although there is a correlation evident, the relationship between the two is still very complex (United Nations). The rates between countries may vary by a multitude of external factors and the effects that climate change is having in various places around the globe differ from one another. In Africa, so many as 2 million people contract the disease and approximately 400,000 die each year (WHO). In America, there are about 1,500 cases and approximately 5 deaths each year (WHO). This unequal distribution in contraction and death rates is profound. Universally increasing temperatures and rainfall from climate change has further increased transmission and contraction rates in underdeveloped countries. Through my research, I wanted to explore the reasons as to why underdeveloped, impoverished countries experience disproportionally high rates of malaria and how environmental effects play a vital role in the increasing rates.
Introduction: Uganda, Ghana, Democratic Republic of the Congo, Burkina Faso, and Kenya are the top 5 countries with highest malaria rates (WorldAtlas). These 5 countries also experience an unequal distribution of deaths from the disease. Developing countries do not have the resources to treat many of the most prevalent, fatal diseases. Climate change and the effects it has on the environment plays a key role in the increasing susceptibility of the disease in these countries. I wanted to determine the ways in which climate change is affecting these increasing rates and in turn, investigate a correlation- if any, between death rates from the disease and GDP per capita of each country. A lack of resources and access to adequate healthcare also contribute to the increased rates, however I wanted to focus my research primarily on the relationship between climate change, increasing rates of transmission, and deaths within these countries.
Biology of Malaria: Malaria is a mosquito-borne disease that affects humans and is primarily prevalent within subtropical regions. It is caused by parasites transmitted by mosquitoes that attack one’s red blood cells (CDC). These parasites are carried through female Anopheles mosquitoes (CDC). The parasite itself is called Plasmodium and directly enters the blood stream once bitten (CDC). Once it enters the body, it begins to multiply and mature within the liver. Soon after, the parasite infects the red blood cells where they are then destroyed and can eventually all die. There are 4 specific types of Plasmodium parasites that can infect humans. The 4 types are: Plasmodium falciparum, P. ovale, P. vivax, and P. malariae (CDC). Mosquitoes are most drawn to wetter, more humid environments that serve as ideal breeding grounds for them to lay their eggs (Mosquito World). If a person becomes infected, they may suffer a wide variety of symptoms ranging from slight discomfort to death (WHO). It is easily treatable with correct and quick treatment, although many of the countries which are at highest risk have very little to no means of resources for treatment. Below is a figure displaying the parasite’s transmission and life cycle for further biological understanding.
Figure 1: The malaria parasite life cycle (CDC).
Materials and Methods: The types of methods I utilized for my research project were qualitative and also quantitative. The project was based on a global-scale, and therefore I was required to collect data through informational interviews. The interview was held over zoom, considering the current state of COVID-19 and societal conditions. The interview was intended to gather qualitative and some quantitative information from Dr. Chapman- a primatologist who studies primate species in Uganda. Through the interview, I hoped to gather data on increased disease transmission within impoverished communities, the effects of climate change on these increasing rates, how poverty plays a role, as well as the differences in rates between places like Africa and North America. In addition to my primary questions, I had recorded other questions which further assisted my research. Questions such as, “Why can’t these countries gain the access they need to adequate treatment?” allowed me to determine or identify other important information needed to analyze my overall questions for the study. I also gathered preexisting numerical data through credible online sources like the CDC, WHO, or any factual, governmental-based site. Through these methods of data collection, I was able to gain more insight as to why underdeveloped nations experience such disproportionally high rates of malaria. I was also able to gain more insight into how the effects of climate change play a role in these disproportional rates.
Previous studies and Data: To further enhance my study, I utilized components of previous studies performed by other researchers that helped me to validate my own in further detail. Since my research project was based on a global scale, it was impossible for me to gather physical data in my country of study. Therefore, it was important that I used information and data which had already been collected in these countries as solid groundwork for me to build upon my own. Exploring the link between climate change, poverty, and malaria is difficult. There are many confounding variables that play a role in the linkage between the three issues of study. For example, determining what exactly causes poverty and how climate change is affecting underdeveloped nations are two major questions vital to understanding this study with many possible answers. While they can be answered in many different ways, it was important that I explored many more questions in depth and based my research on the interview questions that I felt were most applicable to this individualized study. One existing study that I found to be particularly useful is Potential Impact of Global Climate Change on Malaria Risk. Martens and his colleagues explored the link between temperature and transmission rate by using reliable software and technology to accurately predict what a country’s transmission rate would be in a number of years, when incorporating the theoretical increase of temperatures due to climate change (Martens et. al). The initial method used to individually analyze each component was the integrated systems approach. The study also used a scenario-based climatology model to predict the effect of increased temperatures on malarial transmission rates. Since I did not have access to these expensive and professional models, I used the numbers which had already been deduced from studies such as these to incorporate into my overall analysis. Furthermore, after I collected my new data, I created an original diagram to comprehensively display the links between malaria, climate change, and poverty altogether and the exacerbated effects (Figure 3). A second study that I found to be particularly useful for my own study is Modeling the Effects of Weather and Climate Change on Malaria Transmission. This team explored the role that mathematical models can play in analyzing the effects of climate change on malaria transmission. A third article I found to be useful is Malaria and Poverty. This article explores the correlation between malaria and poverty and thus the increased rates of the disease in impoverished communities. It aims to analyze how the cycle between poverty and malaria is continuous and is difficult to break out of. It discusses how Africa is one of the top countries suffering the worst from poverty and is consequently suffering the worst from malaria. A fourth article I found to be particularly useful is Impact of climate change on global malaria distribution. This team used temperature and rainfall simulations from the Coupled Model Intercomparison Project Phase 5 climate models to compare 5 malaria impact models for 3 different time periods. They analyzed 3 malaria outcomes at both global and regional levels. The disease projections were based on 5 differing global climate models. The results demonstrated an overall total global increase in climate suitability and a total increase in the populations at risk. While I did not merely use any data or copy any of the collection strategies from these studies, each of them allowed me to become more knowledgeable in various areas to better enhance my own study and research. In addition to the other studies and my own interview, I also utilized other numerical and statistical data provided by government, credible sources. The disproportionately high share of the global malaria burden is attributed to the African Region (WHO). In 2019, the region was home to 94% of malaria cases and deaths (WHO). In regard to poverty rates, in sub-Saharan Africa, 41% of the population is living off of less than $1.90 (Children International).
GDP and Malaria Correlation Factor: An additional component of my research was configuring a potential correlation between GDP per capita and consequent malaria rates in various countries. I hypothesized that there would be a negative association- meaning as malaria rates went up, GDP per capita went down. Generally, GDP per capita is a strong indication of a country’s wealth (Focus Economics). Since my project was about determining why underdeveloped, impoverished countries experience disproportionally high rates of malaria and also how climate change plays an effect- adding this small component was an effective way to enhance my overall goals of the study, while drawing more connections between poverty and disease. The article titled The Growth Costs of Malaria ran a logistically similar study which focused on determining the association- if any, between disease and GDP. Since extensive and international means of data collection would be required to effectively deduce my own results, I utilized sources which already provided recent numerical data. The United States’ GDP per capital in 2019 was: $65,281 (MacroTrends). Ghana’s GDP per capital in 2019 was: $2,202 (MacroTrends). Researching various impoverished countries and their subsequent GDP rates and comparing them to that of developed, economically stable countries like America allowed me to draw a close parallel between poverty, GDP per capita, and disease rates. In turn, this additional correlation factor in my study solidified my understanding of the interrelating factors between disease and poverty.
Results (The Interview): To simplify my data results from the interview with Dr. Chapman, I created a table, shown below, with the a few of the exact questions which I asked and the most important parts of his responses. I asked a total of 20 questions but decided to only include the questions which I felt were most applicable for my study and ones that would contribute the most to my data collection. The left column holds the question, the right column holds a bullet-point list of each of the most important parts of each response in a paraphrased, shortened format to incorporate the details in the most efficient way.
| In what ways do you feel that climate change has already affected your research over the many years you’ve done work within Uganda? |
· Brought in more opportunity · Made data more valuable because it’s long term · Made people more aware of the need for more long-term data to understand what’s happening in ecosystems · It’s a ‘plus’ to conservation studies and we have to take advantage of it · Provided another motivation for conservation efforts
|
| Do you feel that climate change and poverty are interrelated via correlation, causation, or again, perhaps some other type of relationship? |
· Poverty leads to increased use of resources- prohibits conservation and promotes deforestation · People in African communities cutting down hectares of land for personal resources to feed their children and families- contributes to climate change · Direct correlation between poverty and deforestation and thus climate change · Overconsumption, not just impoverished cities cutting down forests- but it’s the rich that want the goods that leads to more cutting down of the forests
|
| In what ways is the act of deforestation in your particular place of study affecting the monkeys and other mammals in which you study? |
· Around Kibale National Park, the forest is all basically almost gone- the only monkeys that are significant now are within the park itself (no current deforestation because it essentially already happened) · The Congo and the Amazon are experiencing HUGE deforestation rates (increasing every year) · West African forests are basically gone
|
| Do you think that climate change in general has some type of effect on the disease rates in various countries? |
· CC is connected to increasing disease · Increasing temps means infected stages of larvae stick around longer so increased parasite vectors and breed faster, increasing malaria · CC means increased rainfall which increases breeding grounds for vectors and mosquitoes · CC is connected very heavily to malaria and malaria in Africa in particular
|
Figure 2: Table displaying the questions and answers of interview questions with Dr. Chapman.
Discussion: After analyzing the interview and my other means of data collection, I devised a flowchart displaying the 3 primary variables which are being discussed in this study. In the boxes, I included a short description of the steps in which take place when ‘variable 1’ exacerbates- or has an effect on ‘variable 2’. In this sense, variable 1 is represented as the term that the arrow is leaving, whereas variable 2 is represented as the term that the arrow is pointing to. While the relationship between the 3 variables is still incredibly complex, the arrows demonstrate how each variable exacerbates the other. Therefore, I demonstrated that climate change exacerbates poverty and diseases- separately and poverty exacerbates diseases. This chart does not display the only potential relationships but aims to point out the connections that I had personally made from my study.
Figure 3: Original flow chart created from data displaying the 3 variables and the exacerbated effects on one another.
Conclusion: The relationship between climate change, poverty, and malaria is still very complex- nonetheless, it is there. Before I began my study, I hypothesized that climate change, poverty, and malaria were all related to one another- in some distinct way. Although, my interview and investigation of other, credible sources and the data they provided allowed me to better understand the underlying factors which contribute overall to the interrelatedness of one another. Through my analysis, I was able to conclude that climate change exacerbates diseases, by providing warmer and wetter breeding grounds for transmission vectors. Climate change also exacerbates poverty by exploiting resources and causing further monetary difficulties in a country. Additionally, poverty exacerbates disease rates as lower financial stability limits resource usage and availability to treat illness in suffering communities. As proven by various other countries around the world through different studies, this cycle is incredibly difficult to break. However, efforts such as extensive research, funding, and providing resources to countries in need can help to alleviate some of these strains and improve the quality of life for those in countries which are suffering the most from climate change, poverty, and disease.
References
Awash Teklehaimanot, and Paola Mejia. “Malaria and Poverty.” Annals of the New York Academy of Sciences, vol. 1136, no. 1, 2008, pp. 32–37., doi:10.1196/annals.1425.037.
By, and Watch. “Facts & Statistics About Africa: Children International: Help African Kids in Need.” Children International, www.children.org/global-poverty/global-poverty-facts/africa.
Caminade, Cyril, et al. “Impact of Climate Change on Global Malaria Distribution.” PNAS, National Academy of Sciences, 4 Mar. 2014, www.pnas.org/content/111/9/3286.
“CDC – Malaria – About Malaria – Biology.” Centers for Disease Control and Prevention, Centers for Disease Control and Prevention, 16 July 2020, www.cdc.gov/malaria/about/biology/index.html.
CDC – Malaria – Malaria Worldwide – Impact of Malaria. (2020, February 25). Retrieved November 18, 2020, from https://www.cdc.gov/malaria/malaria_worldwide/impact.html
Climate Change and Malaria – A Complex Relationship. (n.d.). Retrieved November 18, 2020, from https://www.un.org/en/chronicle/article/climate-change-and-malaria-complex-relationship
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FocusEconomics. “What Is GDP per Capita?” FocusEconomics | Economic Forecasts from the World’s Leading Economists, 29 Mar. 2014, www.focus-economics.com/economic-indicator/gdp-per-capita.
“Ghana GDP Per Capita 1960-2020.” MacroTrends, www.macrotrends.net/countries/GHA/ghana/gdp-per-capita.
Malaria. (n.d.). Retrieved November 18, 2020, from https://www.afro.who.int/health-topics/malaria
Martens, W. J. (n.d.). Potential impact of global climate change on malaria risk. Retrieved November 19, 2020, from https://ehp.niehs.nih.gov/doi/abs/10.1289/ehp.95103458
Mccarthy, Desmond, et al. “The Growth Costs of Malaria.” 2000, doi:10.3386/w7541.
“Mosquito Habitats.” Mosquito World, 11 May 2015, www.mosquitoworld.net/about-mosquitoes/habitats/.
Parham, Paul Edward, and Edwin Michael. “Modeling the Effects of Weather and Climate Change on Malaria Transmission.” Environmental Health Perspectives, vol. 118, no. 5, 2010, pp. 620–626., doi:10.1289/ehp.0901256.
Pariona, Amber. “Countries With The Highest Rates Of Malaria.” WorldAtlas, WorldAtlas, 25 Apr. 2017, www.worldatlas.com/articles/countries-with-the-highest-rates-of-malaria.html.
“U.S. GDP Per Capita 1960-2020.” MacroTrends, www.macrotrends.net/countries/USA/united-states/gdp-per-capita.
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