Mathematics Against Covid-19

Overview of How AIMS is Supporting the Global Pandemic Response

AIMS Network researchers (students, staff, alumni and other affiliates) are contributing to the global response to the covid-19 pandemic by bringing our collective expertise in mathematical sciences to bear on important questions relevant to designing, assessing, and guiding the implementation of mitigating interventions and policies. The main areas in which we currently work are mentioned below. We are happy to collaborate with governments, the private sector, civil society, and others interested to make use of our expertise. Please use the contact information provided below to get in touch with us.

Current Focus Areas

Operational planning

Our researchers are building mathematical models of covid-19 epidemiology, the projections of which are useful for operational planning – e.g. for estimating the number of hospital beds and ventilators that a particular country will need. See this dashboard for example outputs from our modeling work.

Impact assessment of control policies

Our researchers are building mathematical models for use in assessing the impact of different mitigating interventions, and investigating control policy options available at community, national, regional and continental levels. Questions that these models can be used to answer include, but are not limited to, the following: What is the potential impact of a partial/complete lockdown on the control of covid-19? Which combination of interventions will achieve defined policy objectives?

Surveillance

Surveillance, including through tracing and testing potential infectious contacts, is key to defeating covid-19. Large-scale testing and rapid quarantining and isolation of suspected and confirmed cases, respectively, have thus far allowed South Korea to limit the impact of covid-19 even without a lockdown. South Korea conducted 514,621 tests between 3 Jan 2020 and 12 Apr 2020, representing an average of about 100 tests per million population per day. Achieving this level of population coverage requires a costly scale-up of testing capacity (equipment, reagents, human resources, etc.). Our researchers have developed a mathematical algorithm that might reduce by up to 70% the number of tests needed to achieve a given level of coverage. Please contact us if you would like to learn about this algorithm and to apply it in the field.

Other types of technical support

We are happy to provide technical support to governments, private sector, and others in need of generating actionable insights from data and mathematical models. We are currently supporting several African countries as well as the WHO through our membership in various technical expert groups.

Contact Information:

For general queries or to get in touch with our experts, please email:

Dr Christine Warugaba, MD, MPH
Senior Administrative Officer, Research
AIMS Global Network
cwarugaba@nexteinstein.org