by Joseph DeSisto
Both malaria and climate change are complex global problems that scientists are working hard to understand. Malaria, a mosquito-borne disease, kills roughly 600,000 people every year, mostly in Africa. Attempts to control malaria have been massive and relatively well-funded, but the disease continues to pose a serious threat to human life in the tropics. Climate change has no body count (yet), but will dramatically change our planet, altering weather patterns, sea levels, and human life.
These two problem have another thing in common: scientists use mathematical models to try and predict how they will change in the future. For example, climate scientists use past and current data on temperature, carbon emissions, and many other factors, to predict how the earth’s climate will change. Most models anticipate a global temperature increase of 2̊ to 6̊ by the year 2100 (e.g., Paaijmans et al. 2014). Those predictions may not be perfectly accurate, but that is the nature of predictions, and in the absence of time travel, it’s the best we can do.
Malaria, the microbes that cause it, and the mosquitos that carry it, are all affected by temperature. Scientists have tried developing models to predict how malaria infection rates will change as the world gets hotter. In general those predictions have been bleak: models tend to show an increase in the amount of people affected by malaria (e.g. Pascual et al. 2006, Paaijmans et al. 2014), on the basis that warmer temperatures are most hospitable to malaria-carrying mosquitos. They also show malaria spreading to areas that used to be too cool, like South Africa and the southeastern United States. Yet other models show a decrease in malaria on a global scale (Gething et al. 2010), and some suggest an increase in some areas but a decrease in others (Rogers and Randolph 2000).
Before looking forward, it’s important to look back – how has malaria changed in the last few years? The maps below show malaria infection rates (the percentage of people infected) across Africa, in 2000 (left) and 2010 (right). Darker colors mean more malaria.
The two maps may not look all that different, but look closely. The red arrow points to West Africa, where the darkest area has grown smaller. Malaria is still common there, but has declined. In Kenya and Tanzania (purple arrow), malaria has declined even more. Even though efforts to completely eradicate malaria have failed, improved mosquito control programs have been successful in reducing the threat of malaria in these regions of Africa.
A model is basically an equation, and in the case of malaria it serves to calculate R0: the basic reproduction number. The basic reproduction number is the answer to the question, for each person already afflicted with malaria, to how many other people will their infection spread? This gives us an idea of how many people are likely to contract malaria in a given year.
For example, if R0 is 15, that means every person with malaria is likely to pass it on to fifteen other people – that’s about the R0 value for measles. If R0 is 0.5, then on average, half of all malaria patients will pass their infection on to another. For all diseases, when R0 is less than 1.0, the disease will decline, and if R0 is greater, the disease will increase in the population. Very high values of R0 can lead to pandemic.
Malaria is a complicated disease, affected by all three players: humans, microbes (more on them later), and mosquitos. In turn, each of these players are affected by temperature, moisture, population density, and other local conditions. As a result, malaria’s basic reproductive number varies depending on where you are. In 2007, a group of scientists attempted to calculate R0 for 121 different human populations in Africa (Smith et al. 2007). The study had two important results.
First, R0 varied wildly across Africa. Although the average value was near 115, many populations had values below 10 and many more had values over 1,000. Second, some R0 were extremely high, approaching 10,000. Remember what this means – on average, each person with malaria has the potential to transmit their malaria to 10,000 other people!
In some cases the R0 value was greater than the human population, suggesting that everyone in the population had malaria when of course this was not the case. Is there a problem with the model? The scientists in question didn’t think so. Instead they pointed out that although malaria’s R0 is much higher than for most other diseases, malaria also takes much more time to spread (on average, 200 days per generation) because of its complex life cycle.
The parasites that cause malaria are single-celled, apparently simple, but with strange and complicated lives. I say parasites, plural, because there are at least five species that cause malaria, but all are protozoans in the genus Plasmodium. The cycle, of course, has no “beginning,” but we will start with the oocyst, a kind of “egg sac” containing multiple Plasmodium cells and surrounded by a protective membrane.
The oocyst lives in the body of a female Anopheles mosquito, and by the time the mosquito lands for a blood meal, the membrane bursts. Single-celled Plasmodium parasites surge forth, down the mosquito’s mouthparts, and into the blood-stream of an unsuspecting human. The freed cells are called sporozoites; they are worm-like and active, and waste no time snaking their way through the host’s body until they reach the liver.
Here the parasites eat, grow, and change shape. They divide and transform into masses of globular cells, similar to oocysts, once again enveloped in a bag-like protective layer. As time goes on, liver becomes tiresome, and the parasites crave blood. The bag of cells bursts, and the Plasmodium cells return to the blood stream. Now they have a new mission: find a red blood cell.
Red blood cells are hollow and doughnut-shaped, like inflatable inner tubes. You use them to transport oxygen and carbon dioxide into and out of your body, with every breath. The blood cell’s membrane is thin, almost fluid, and easy for a Plasmodium cell to invade. Once inside, the parasite has two options. It can grow and divide, forming a new mass of cells (like the oocyst). If it does so, these cells will ultimately break out of their shelter to find new red blood cells of their own. More ambitious parasites, however, refrain from dividing. Instead they metamorphose, transforming into either male or female cells.
For the Plasmodium life cycle to complete, a second mosquito is required. The new mosquito lands on a malarial host, sucking up blood and with it, lots of red blood cells. Some of these are empty, but others, if Plasmodium is lucky, contain either male or female hitchhikers. In the mosquito’s digestive system, red blood cells burst open to release their passengers. The freed Plasmodium cells, male and female, meet and unite. Once they do, they are able to multiply and grow into a multi-celled oocyte, full of wriggling sporozoites ready to enter a new human host at the mosquito’s next meal.
For this system to work, mosquitos not only have to be infected with Plasmodium, but sporozoites have to be fully developed and ready to pounce when opportunity (i.e., a bite) comes along. Lots of mosquitos need to be biting people, so that at least some will slurp up the male and female cells when they are ready. Mosquitos need to have reasonable lifespans – those that meet their end in a frog’s belly or a spider’s web are of no use to Plasmodium. The mosquitos, in turn, have requirements of their own: they need optimal growing temperatures, pools of water in which to lay their eggs, and plenty of warm-bodied hosts from which to drink.
All of these factors (and many more) are variables that might appear in an equation to calculate R0. Smith and colleagues (2007) used them to calculate the R0 for all those 121 African populations. More recently, a group of scientists and mathematicians got together to predict how R0 will change with the earth’s climate (Ryan et al. 2015).
In general, both mosquitos and Plasmodium can only develop at temperatures between 63̊ and 93̊ F. That’s good, useful information, but not enough — each of Smith’s variables (mosquito life span, number of bites per person, etc.) is affected by temperature, but each in a slightly different way. Only by combining all of these factors, and considering how each will change under future climate conditions, can we accurately predict how the threat of malaria will change over time. That’s what Ryan and colleagues did, and published this month in Vector-Borne and Zoonotic Diseases.
It turns out that if you combine all those variables, you get a much more complex picture of how climate change and malaria interact. Although some areas will get warmer and more suitable for malaria, others will actually get too hot, so malaria will decline.
This particular study shows a decrease in malaria in West Africa, but an increase in East Africa. In other words, the hot-spot for malaria will shift east over the next six decades.
In the maps above, purple indicates the greatest increase in malaria transmission rates, while the palest tone indicates a decline in malaria.
Caution is important. When different models produce vastly different results, it usually means that some of those models are better than others. This model happens to consider more factors than many others, which suggest it may be more accurate, but as I have tried to show, malaria is a complex disease that will be affected by temperature in complex, hard-to-predict ways.
Having an idea of what the future might hold can inform us – where should we concentrate efforts to control malaria? Where will malaria pose the greatest threat to human health? This latest model suggests our focus will have to shift as Plasmodium, mosquitos, and malaria follow their optimal temperatures in an eastward march across Africa.
Gething P.W., D.L. Smith, A.P. Patil, A.J. Tatem, R.W. Snow, and S.I. Hay 2010. Climate change and the global malaria recession. Nature 465(7296): 342–346.
Noor A.M., D.K. Kinyoki, C.W. Mundia, C.W. Kabaria, J.W. Mutua, V.A. Alegana, I.S. Fall, and R.W. Snow. 2014. The changing risk of Plasmodium falciparum malaria infection in Africa: 2000-10: a spatial and temporal analysis of transmission intensity. The Lancet 383(9930): 1739-1747.
Paaijmans K.P., J.I. Blanford, R.G. Crane, M.E. Mann, L. Ning, K.V. Schreiber, and M.B. Thomas. 2014. Downscaling reveals diverse effects of anthropogenic climate warming on the potential for local environments to support malaria transmission. Climate Change 125: 479-488.
Pascual M., J.A. Ahumada, L.F. Chaves, X. Rodó, and M. Bouma. 2006. Malaria resurgence in the East African highlands: temperature trends revisited. Proceedings of the National Academy of Sciences U.S.A. 103(15): 5829–5834.
Rogers D.J. and S.E. Randolph. 2000. The global spread of malaria in a future, warmer world. Science 289: 1763–1766.
Ryan S.J., A. McNally, L.R. Johnson, E.A. Mordecai, T. Ben-Horin, K. Paaijmans, and K.D. Lafferty. 2015. Mapping physiological suitability limits for malaria in Africa under climate change. Vector-Borne and Zoonotic Diseases 15(12): ahead of print.
Smith D.L., F.E. McKenzie, R.W. Snow, and S.I. Hay. 2007. Revisiting the basic reproductive number for malaria and its implications for malaria control. PLOS Biology 5(3): e42. doi: 10.1371/journal.pbio.0050042