Calculating the transmission rate within your cluster

For understanding the risks of our cluster; it is important to know the effective spread rate of infection.

Most of us have been tracking this epidemic based on R0. R0 is the basic reproduction number of an epidemic. It’s defined as the number of secondary infections produced by a single infected patient. If R0 is greater than one, the epidemic spreads quickly. If R0 is less than one, the epidemic spreads, but limps along and disappears before everyone becomes infected.

Common cold has R0 < 1; whereas measels has R0 > 10. The problem with R0 remains that it is static and doesn't take into account a risk-based approach.

The effective R value will change as per multiple parameters such as social distancing behaviours; average population density; number of vectors in the population and inter-zone mobility. Our production and consumption behaviours change and that changes the effective reproduction number at any time.

Every district in India is different and hence effective reproduction number (Rt) within each zone will be drastically different. We hence need to know the local reproduction numbers to be able to combat the epidemic locally and with resources available to us within the district. To completely lift the lockdown within a district and let economic activity revert to normal we need to get Rt < 1.0.

We can estimate Rt as a function of how many new cases appear each day. The relationship between the number of cases within the last 7 days and the number of cases today give us a hint of what Rt might be. Daily case counts, however, are imperfect due to changing testing capacity, lags in data reporting, and random chance but over a long period of time the values start depicting true value as more and more data becomes available.

On our district dashboard map we will be giving you an estimated Rt value so that policy decisions can be made based on that. We are trying to get this feature to you by 17th April 2020.