Infectious diseases are one of the leading causes of death in today’s changing world. Their impact is especially severe for developing and newly industrialized countries, including those in sub-Saharan Africa. According to a World Health Organization report, in 2013, 90% of the approximately 630,000 deaths worldwide from malaria occurred in this region. Most of these cases involved children younger than 5 years old.
Because of the effects of malaria and other diseases, including cholera and pneumonia, a child born in sub-Saharan Africa is 15 times more likely to die by the age of 5 than a child in a developed country. However, the earlier that disease outbreak warnings are released, the more quickly action can be taken to prepare for the potential impact on a population.
The Science and Technology Research Partnership for Sustainable Development (SATREPS), a program funded by the Japan Agency for Medical Research and Development and the Japan International Cooperation Agency, promotes international research partnerships and collaboration between developing countries and Japan. Our project, Establishment of an Early-warning System for Infectious Diseases in Southern Africa Incorporating Climate Predictions, was initiated in 2014 following the successful completion of another SATREPS project on the southern African climate.
The current project focuses on creating a disease outbreak early-warning system over southern Africa that can be implemented effectively to fight infectious diseases. It also includes a training component for young researchers and students in South Africa.
As a part of this project, researchers from South Africa and Japan gathered in Pretoria, South Africa, to hold a symposium discussing recent findings and ways to interact with the country’s emerging researchers. Participants included members of research institutes from South Africa and Japan and comprised specialists in multidisciplinary fields, as well as local graduate students who have interests in climate modeling and infectious diseases. The symposium covered four topics:
- malaria and vector ecology
- cholera and pneumonia research
- disease transmission models
- climate prediction systems
Participants reported recent findings in their respective subprojects. For example, the South African Medical Research Council conducted laboratory experiments in Limpopo in an attempt to discover the entomological parameters of anopheline mosquitoes, the vector species responsible for the transmission of malaria between humans.
Another focus was on the collation of handwritten hospital admissions records for malaria, cholera, and pneumonia cases, emphasizing the need for collection of good quality data. These data serve as the input for sophisticated statistical studies, which use techniques including machine learning and Bayesian modeling. The data are essential for developing global climate models in relation to disease transmission that depend on the epidemiological characteristics of the diseases.
As a result of this meeting, a lecture series was held at the University of Limpopo to teach students about weather and climate variability, climate change, disease vector ecology, and statistical methods, as well as the relationship between climate and health and epidemiology. Students interacted with the lecturers, engaged in the course material, and experienced a stimulating environment that deepened their understanding.
Although there will be challenges ahead, the achievements thus far have taken the project a significant step toward developing an early-warning system for infectious diseases in southern Africa.
—Takayoshi Ikeda and Yushi Morioka, Application Laboratory, Japan Agency for Marine-Earth Science and Technology, Yokohama, Japan; email: firstname.lastname@example.org; and Caradee Y. Wright, South African Medical Research Council and University of Pretoria, Pretoria, South Africa
Citation: Ikeda, T., Y. Morioka, and C. Y. Wright (2016), Climate predictions and infectious diseases in southern Africa, Eos, 97, doi:10.1029/2016EO051401. Published on 5 May 2016.
Text © 2016. The authors. CC BY-NC-ND 3.0
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