Mathematics Against Covid-19

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.

Covid-19 Pandemic Tracking in Rwanda

We use a stochastic transmission dynamic model developed by Kucharski et al. (2020), to model the dynamics of covid-19 in Wuhan, China. The model accounts for a possible change in the transmission rate before and after some movement restrictions have been instituted (i.e lockdown, curfew, flight travel restrictions, etc). Parameters for the incubation and infectious periods were taken from the above study, while all other parameters were estimated to match COVID-19’s dynamics in Rwanda. Note that predicted number of deaths were estimated to be 1.7% of the total confirmed cases. All patients are assumed to spend an average of 21 days from the confirmation of diagnostic, to recovery. Current number of active cases is the difference between total cases and number of deaths and recoveries.

Country-level data was provided by the Rwanda Biomedical Center, which is the institution leading the Rwandan efforts to tackle the pandemic in Rwanda, under the Ministry of Health. For more info, visit