The Clinton Health Access Initiative, Inc. (CHAI) is a global health organization committed to saving lives and reducing the burden of disease in low-and middle-income countries, while strengthening the capabilities of governments and the private sector in those countries to create and sustain high-quality health systems that can succeed without our assistance. For more information, please visit: http://www.clintonhealthaccess.org
CHAI's global malaria program provides direct technical and operational support to countries around the globe to strengthen their malaria programs and reduce the burden of this preventable, treatable disease. We support governments to scale up effective interventions for prevention, diagnosis, treatment, and surveillance, with the goals of sustainably reducing the number of malaria-related illnesses and deaths worldwide in the short-term and accelerating progress towards malaria elimination in the long term.
Overview of Role:
CHAI is seeking a highly motivated individual with experience in disease surveillance systems, data analysis and public health research. This individual will assist with malaria surveillance system design and implementation, data analysis, mapping activities, and operational research studies to support malaria elimination in Central America. Support will focus on three countries in the region: Panama, Guatemala, and Honduras. The aim of this support is to ensure that national malaria programs and ministries of health are using robust evidence to inform their strategic and operational decision making. Strong communication and organizational skills are needed as s(he) will work closely with CHAI's Global and Regional Malaria Teams, and will help to translate epidemiological evidence to malaria programs and other partners in country. Further, it is expected that the Research Associate will need to collaborate with other academics and public health agencies to ensure CHAI's elimination work is complementary and not duplicative.
This role requires regular travel (up to 50%) to high risk, remote regions of the country with limited infrastructure and medical care.