In epidemiology, the spread of a pandemic is described by mathematical models with certain parameters. The lockdowns can effectively change the values of the parameters in these models over time; hence making them time-dependent.
We have come up with an approach of reconstructing the time-dependence of one such important parameter called transmission rate, directly from the data.
The transmission rate turns out to be the product of contact rate (i.e. the number of contacts an individual experiences per day) and the probability of disease transmission if the contact is with an infectious individual. As we enforce lockdowns, travel bans and janata curfews, the contact rate will become time independent. This relationship over time has been captured from the data. The result for Italy, for data till 14 April 2020, has been the basis of the research.
The reconstructed transmission rate for Italy (for data till 14 April 2020) has been shown here. One first finds a raw reconstruction (grey) and then, it’s smoothed incarnations such as the moving average (green) and a smooth step down function (red). It is easy to see that, as a result of mitigation measures, the transmission rate decreases with time.
For more information, please refer to an early draft of the findings:
“Extracting the effective contact rate of COVID-19 pandemic” Gaurav Goswami, Jayanti Prasad and Mansi Dhuria.
We are currently improving our analysis by estimating the error in the result of the reconstruction. As more and more reliable data related to COVID-19 becomes available, it is important to focus our attention on improving the analysis and if possible, to try and relate the specific mitigation measures taken up by a given population (such as the various wards in a city, an entire city or an entire country) to the reconstructed transmission rate.
Covid-19, transmission rate, Lock-down, Data