Faculty Editor: Dr. Heather Olins

As the harmful effects of human interactions with the planet become more clear, a strong debate on how to mitigate climate change has risen. Yet just as important as it is to examine  potential solutions, it is also necessary to fully understand all the ways in which a changing climate affects the processes on earth. 

Due to the burning of fossil fuels, the release of greenhouse gases into the earth’s atmosphere, and the destruction of natural wildlife, humans have caused temperatures to rise on earth by an average of 1.5 degrees C since 1980; this global warming has caused unpredictable weather patterns; melting ice caps; increased wildfires; and more frequent, severe storms (7).

Although the discussion surrounding climate change often focuses on the changes to the abiotic systems of the earth, various living populations and species have been adversely affected. Additionally, climate change is altering human interaction with the populations around them, most significantly with pathogens.

A warmer climate has long been linked to higher rates of disease spread. Malaria, Dengue Fever, West Nile virus, and other pathogens have historically seen greater rates of occurence in tropical or subtropical climates, especially during the warmer months (1). The heightened virulence of these diseases is due to their vector-borne nature. A vector-borne illness is one that spreads through a secondary carrier, like a rat. In this case the vector, or means of transmission is through mosquitoes. The Plasmodium parasite in the mosquito that causes malaria can reproduce and mature to adulthood faster in warm weather, thereby requiring more blood from humans, leading to more frequent bites and transmissions (2).

The clearest correlation between climate change and increased disease transmission is through rising temperatures. According to the Intergovernmental Panel on Climate Change (IPCC), rising temperatures will extend the transmission season of malaria and a cause larger geographical range for the disease (2). The cases of malaria in the Northwest Frontier Province of Pakistan have already given a sampling of this increase, skyrocketing from a few hundred in 1983 to over 34,000 in 1990. This sharp rise correlated to increased rainfall in October, and a mean rise of 2 degrees C and 1.5 degrees C in November and December, respectively (6). 

However, rising temperatures are not the only way climate change is affecting malaria. A study conducted by Stanford University found that “deforestation has a strong positive effect on malaria incidence” in the Amazon basin region of Brazil. They found that a 10% increase in deforestation efforts led to a 3.3% increase in reported malaria cases (4). However, the relationship between deforestation and the spread of malaria is far more complex than simple correlation. Although deforestation creates more open spaces, stagnant water pools, and warmer temperatures favored by disease vectors, a higher rate of malaria slows down local economies and labor productivity. The disease affects the human workers within the deforestation industry. This in turn, leads to a lower level of deforestation, and the Stanford study estimated that a 1% increase in malaria incidence among deforestation laborers correlates to a 1.4% decrease in forest area cleared (4). This “bidirectional socioecological feedback” demonstrates the complicated and delicate ways human-induced environmental change impacts human’s health, productivity, and economy. Yet, this feedback system is not self-regulating. Despite the risk to public health, rainforest deforestation, especially in the Amazon, continues.

As humans face these new, emerging threats threats to global health, anticipation of and preparation for outbreaks becomes crucial. Yet due to the variability and unpredictable nature of the small scale environmental impacts of global climate change, modeling future outbreaks becomes incredibly difficult. There are three types of predictive models: statistical, process based, and landscape based (1). A statistical based model derives a relationship between specific environmental conditions and the spread of the disease. This type of model can predict the future spread of disease, but only if the climatic conditions were to remain constant. Constrastingly, process-based models use many equations to explain the relationship between climatic conditions and biological parameters like vector breeding, biting rates, incubation rates, and other indicators. This model explains how environmental changes would affect the biological systems of a disease, and therefore its spread (2). Landscape based models expand statistical models to include the effects of other factors, like vegetation type or changes to ground coverage (1). All three model types are essential for public health management. Associate Professor of Pediatrics in the Stanford Medical School Desiree LaBeaud explained that “we need to be able to predict what populations will be at risk for infectious diseases because prevention is always superior to reaction” (3). As the effects of climate change in the spread of disease become more pronounced, these models will become a guide map for prevention efforts.

Although seemingly distant, climate change’s effect on the spread of disease is a serious threat to global health. A Stanford study found that currently 6.01 billion people live in areas suitable, at least part of the year, for vector transmission from the A. aegypti mosquito (5). This particular mosquito can infect humans with dengue fever, chikungunya, Zika virus, and even eastern equine encephalitis (EEE). Without dramatic measure to change the ways in which humans interact with the planet, the number of at risk people will climb (5).

However, the relationship between a changing climate and the spread of this vector is not linear. In several different statistical models, Stanford researchers calculated the populations at risk in 2050, and 2080. They found that by 2050, the greater the rise in global temperatures, the greater the amount of people at risk. However, in 2080 the greatest risk for Aedes borne disease would occur at intermediate climate warming temperature (5). At the worst case climate scenario, equatorial regions would actually become too hot for the Aedes mosquitoes, thereby shifting the highest risk areas toward Earth’s poles. At intermediate scenarios, both the equatorial and other regions would become suitable for the mosquito.

This risk illustrates the need for preparation in global health providers. Even if drastic action is taken to diminish human’s influence on the climate, billions of people are still newly at risk for deadly diseases. This future crisis can no longer be fully averted, only mitigated. These findings further develop the need for immediate action against climate change, if only to reduce the future pandemic risks. The health and safety of the human race is in jeopardy, and the ever increasing future threat of vector-borne illnesses merits an extensive and serious overhaul of current trends, taking action to halt climate change (7).


  1. Climate Change and Infectious Disease. (2019). Retrieved October 11, 2019, from https://www.who.int/globalchange/climate/en/chapter6.pdf
  2. Cho, R., & Idakwoji, J. A. (2019, July 25). How Climate Change Is Exacerbating the Spread of Disease. Retrieved October 10, 2019, from https://blogs.ei.columbia.edu/2014/09/04/how-climate-change-is-exacerbating-the-spread-of-disease/ 
  3. Jordan, R. (2019, March 15). How does climate change affect disease? Retrieved from https://earth.stanford.edu/news/how-does-climate-change-affect-disease#gs.amueod
  4. MacDonald, A. J., & Mordecai, E. A. (2019, October 20). Amazon deforestation drives malaria transmission, and malaria burden reduces forest clearing. Retrieved from https://www.ncbi.nlm.nih.gov/pubmed/31611369
  5. Ryan, S. J., Carlson, C. J., Mordecai, E. A., & Johnson, L. R. (2019, March 28). Global expansion and redistribution of Aedes-borne virus transmission risk with climate change. Retrieved from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6438455/ 
  6. Bouma, M. J., Dye, C., & van der Kaay, H. J. (1996, August). Falciparum malaria and climate change in the northwest frontier province of Pakistan. Retrieved from https://www.ncbi.nlm.nih.gov/pubmed/8780449
  7. The Effects of Climate Change. (2019, September 30). Retrieved from https://climate.nasa.gov/effects/ 

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