tetano
Editor, Senior Moderator
Disaster Med Public Health Prep
. 2020 Sep 9;1-23.
doi: 10.1017/dmp.2020.321. Online ahead of print.
Prediction of the Peak, Effect of Intervention and Total Infected by the Coronavirus Disease in India
Parth Vipul Shah[SUP] 1 [/SUP]
Affiliations
Abstract
Objective: We study the effect of the coronavirus disease 2019 (COVID-19) in India and model the epidemic to guide those involved in formulating policy and building healthcare capacity.
Methods: This effect is studied using the SEIR compartmental model. We estimate the infection rate using a least square method with Poisson noise and calculate the reproduction number.
Results: The infection rate is estimated to be 0.270 and the reproduction number to be 2.70. The approximate peak of the epidemic will be August 9, 2020. A 25% drop in infection rate will delay the peak by 11 days for a 1 month intervention period. The total infected individuals in India will be 9% of the total population.
Conclusion: The predictions are sensitive to changes in the behaviour of people and their practice of social distancing.
Keywords: COVID-19; India; SEIR compartmental model; infection rate; intervention; peak prediction.
. 2020 Sep 9;1-23.
doi: 10.1017/dmp.2020.321. Online ahead of print.
Prediction of the Peak, Effect of Intervention and Total Infected by the Coronavirus Disease in India
Parth Vipul Shah[SUP] 1 [/SUP]
Affiliations
- PMID: 32900400
- DOI: 10.1017/dmp.2020.321
Abstract
Objective: We study the effect of the coronavirus disease 2019 (COVID-19) in India and model the epidemic to guide those involved in formulating policy and building healthcare capacity.
Methods: This effect is studied using the SEIR compartmental model. We estimate the infection rate using a least square method with Poisson noise and calculate the reproduction number.
Results: The infection rate is estimated to be 0.270 and the reproduction number to be 2.70. The approximate peak of the epidemic will be August 9, 2020. A 25% drop in infection rate will delay the peak by 11 days for a 1 month intervention period. The total infected individuals in India will be 9% of the total population.
Conclusion: The predictions are sensitive to changes in the behaviour of people and their practice of social distancing.
Keywords: COVID-19; India; SEIR compartmental model; infection rate; intervention; peak prediction.