Ashok Krishnamurthy

Dr. Ashok Krishnamurthy is working on several projects including the application of mathematical models to track the spatial spread of Ebola in the DRC and tracking COVID-19 in Nigeria, and the Czech Republic.


Spatiotemporal tracking of COVID-19 using open-source gridded population rasters and mathematical modelling
Ashok Krishnamurthy

We present a spatial SVEIRD (which stands for Susceptible, Vaccinated, Exposed, Infectious, Recovered and Dead compartments) epidemic model to capture the transmission dynamics of the spread of COVID-19 and provide insight that would support the Public Health officials towards informed, data-driven decision making.

We use the freely available population count data downloaded as a gridded raster map from to assess the geographical spread COVID-19. Each grid cell has a population count, which is divided into disease compartments. Each grid cell can transmit disease to its neighbors, with probabilities that decline exponentially with the Euclidean distance.

Predicting the transmission dynamics of COVID-19 using mathematical models is challenging and comes with a lot of uncertainty. First, we run the spatial simulations under the worst-case scenario, in which there are no major public health interventions. Next, we account for mitigation efforts including strict mask wearing and social distancing mandates, targeted lockdowns, and widespread vaccine rollout to vaccinate priority groups. Predictions for disease prevalence with and without mitigation efforts are presented via time-series graphs for the epidemic compartments. All simulations are carried out using R programming language.

Open Data