Date of Award
Paul C. Sutton, Ph.D.
Climate change, Highland malaria, Infectious diseases, Malaria, Spatial analysis, Spatio-temporal dynamics
In the highlands of East Africa, the most populated regions in Africa, temperature is assumed to be intimately connected to the patterns of malaria both in time and space. A large section of the Ethiopian population in this region has historically been shielded from the disease mainly due to the altitudes in the highland regions that have remained free of the disease. However, the region has also seen a large part of its population being affected by malaria in epidemic outbreaks that seem to follow climatic anomalies, especially those of inter-annual increases in temperature. This project examines the inter-annual variability in the distribution of disease incidence over space and explores how changes in these distributions correlate to corresponding climate variability. By using extensive records of disease cases at high spatial resolution, it explores how population at the high end of the disease transmission range is affected by inter-annual climate variability. It further examines factors at play in the persistence of the disease in these low-transmission highland fringes to draw lessons for better targeting of interventions. With lessons learnt from the micro-scale investigations of associations between spread of the disease and generalizable factors, especially climatic factors, the project scales up to the national level to explore the risk of malaria transmission among the Ethiopian population, and how these risks have changed with the observed climatic factors in the last few decades. Finally, it quantifies the potential impacts of climate change on the spatial spread and intensity of malaria incidence and risks in a country whose population has doubled in the last 30 years.
In chapter two, at a micro-scale and with high resolution disease and climate data, we examine the impact of inter-annual climate variation on the spatial distribution of malaria incidence over time. With the looming climate change in mind, we examine and infer what this could mean for the future. The impact of global warming on insect-borne diseases and on highland malaria in particular remains controversial. Temperature is known to influence transmission intensity through its effects on the population growth of the mosquito vector and on pathogen development within the vector. Spatio-temporal data at a regional scale in the highlands of Ethiopia provide an opportunity to examine how the spatial distribution of the disease changes with the interannual variability of temperature. We provide evidence for an increase in altitude of the malaria distribution in warmer years. This implies that climate change will, without mitigation, result in an increase of the malaria burden in the densely populated highlands of Africa and other regions with similar conditions.
In chapter three, we stay at the same scale as in Paper II, and explore factors that explain the persistence of malaria in this low transmission epidemic prone region. A better understanding of malaria's persistence in highly seasonal environments such as highlands and desert fringes requires identifying the factors behind the spatial and temporal reservoir of the pathogen in the low transmission season. In these 'unstable' malaria regions, such reservoirs play a critical role during the low transmission season by allowing persistence between seasonal outbreaks. In the highlands of East Africa, the most populated epidemic regions in Africa, temperature is expected to be intimately connected to spatial persistence because of pronounced altitudinal gradients. It is not clear, however, that variation in altitude is in itself sufficient to explain persistence of the disease during the low season, and that other environmental and demographic factors, in particular population density are not also major factors. We address this question with an extensive spatio-temporal data set of confirmed monthly Plasmodium falciparum cases from 1995 to 2005 that finely resolves space in an Ethiopian highland. Using a Bayesian approach for parameter estimation and a generalized linear mixed model that includes a spatially-structured random effect, we demonstrate that population density is important to disease persistence during the low transmission season. As malaria risk usually decreases in more urban environments with increased human densities, this counter-intuitive finding identifies novel control targets during the low transmission season in African highlands. It also underscores limitations of current coupled vector-host models of the population dynamics of the disease, which do not typically incorporate an explicit effect of population density.
In chapter four, we scale-up to the national level and explore the use of climate factors to quantify spatially explicit malaria risk for Ethiopia. Climate suitability for malaria transmission has been used to account for Africa's continental distribution of the disease and to estimate the potential effects of climate change. So far, the limited application of the standard suitability index on smaller spatial scales, and the coarse resolution of future climate scenarios, which can overestimate malaria suitability, have hampered adequate estimation of the regional impact of global warming in the highly populated African highlands. In this chapter we intend to validate the existing African malaria Suitability index for Ethiopian conditions in order to study potential shifts in the epidemiology of malaria with past and predicted warming. With a modified suitability index for Ethiopia, we estimate that since the 1970s 12% of the rural population has become exposed to the disease, and 7% of the rural population who live in areas above 1000m. shifted into the "stable" malaria category. These figures reflect less than 1 degrees of warming that have occurred between 1975 and 2010. With 2 and 3 degrees of additional warming possible in the 21th century, the proportion of Ethiopia's population safe from malaria is likely to decrease to 10% and 5% respectively from 31% in the pre-1990 baseline assessment. At the same time, endemic stable malaria is predicted to affect 51% and 64% of the population respectively compared to 22% pre-1990s. With a shifting uphill burden of malaria, epidemic risk will occur in vulnerable populations without previous disease exposure. This risk will materialize in exceptionally warm years that can now be forecasted with reasonable accuracy; epidemic warning and timely intervention should be able to avoid severe morbidity and mortality. However, the populations that are shifted into the stable malaria category due to warming will have to rely on the continuation of assistance that has alleviated Ethiopia's malaria burden in the last decade, and future scientific progress to improve malaria control and keep ahead of developing drug and insecticide resistance. Despite applying a 50% reduction in malaria caused mortality to account for the reported progress achieved in Africa since 2000, we conservatively estimate that 2521 children and 1646 adults (above 15 years of age) die in Ethiopia each year from warming that has occurred so far. At current levels of technology, control effort and population in Ethiopia, a 3 degree increase in temperature would result in an eight fold increase in these figures.
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Siraj, Amir Said, "Climate Driven Changes to Malaria Transmission Patterns in Ethiopian Highlands" (2015). Electronic Theses and Dissertations. 1238.
Received from ProQuest
Amir Said Siraj
Epidemiology, Climate Change, Environmental Science