COVID-19 Projection for Puducherry/புதுச்சேரி
Data-driven modelling of pandemic, Nature Sci Rep 11, 6741 (2021)
May 10, 2021
Jun 30, 2021
Projections for confirmed, recovered, active, and deceased
Covid-19 cases in Puducherry are provided. The prevalence estimates from serosurveys have
been included in the model. However, the scenario curves below show only the officially
tested cases for Covid-19.
Model predictions updated/issued on May 10, 2021.
Assumptions of COVID-19 Wave II Model
- 3800 vaccinated every day, and the vaccine is 70% effective
- Two unreported cases for every reported case
- Lockdown-like restrictions: local lockdown, city lockdown, strict curfew, etc. "Social distance" parameter in the model is fitted similar to the previous year (2020) lockdown
- Un-lock: Social distance parameter is restored to post-lockdown values of 2020
- No inter-state transmission of COVID-19, including air travel
- S0: No Lockdown - worst-case
- S1: Scenario I - 30-day lockdown from 10th May,2021 with 50% effectiveness
- S2: Scenario II - 30-day lockdown from 10th May,2021
- Data from 23 March, 2021 is used partially to tune the parameters of the data-driven model. These results are current as of May 10, 2021.
- The severity of the infection is taken into consideration while modeling the infectious death rate function (see the rate functions in the model).
- What if the lockdown-like restrictions are not followed as in 2020?: All projections will follow the No-Lockdown scenario.
- What if the post-lockdown "social distance" parameter values follow the pre-lockdown values of 2021 instead of the post-lockdown values of 2020? The spread will be worse, and another scenario analysis needs to be performed.
- What if the restrictions, inoculation, recovery, and herd immunity improve/worsen compare to the present situation? One can claim that the mathematical model has failed and proven wrong. In reality, we failed the mathematical model by feeding incorrect parameters.
- District-wise numbers are computed with the Puducherry parameters to compare the actual data of the respective district with the Puducherry's trend. Hence, Districts' curves are not projections but indicate how the individual District got affected (better/worse) than the Puducherry average.
- COVID19-India API
- Google Data Studio
- Special thanks to all well wishers and colleagues for the discussion and feedback on our model.
- Deepak wishes to acknowledge DST Inspire and Arcot Ramachandran Young Investigator Awards.
- Sashi wishes to acknowledge SERB, DST, DRDO, DAAD and AvH for the grants that supported for the development of ParMooN.