Evaluating COVID-19 Lockdown Policies For India: A Preliminary Modeling Assessment for Individual States

12 Pages Posted: 15 Apr 2020 Last revised: 29 May 2020

See all articles by Aditya Mate

Aditya Mate

Harvard University - Center for Research on Computation and Society

Jackson A Killian

Harvard University - Center for Research on Computation and Society

Bryan Wilder

Harvard University - Center for Research on Computation and Society

Marie Charpignon

Massachusetts Institute of Technology (MIT)

Ananya Awasthi

Independent

Milind Tambe

Harvard University - Center for Research on Computation and Society

Maimuna S. Majumder

Boston Children's Hospital - Computational Health Informatics Program; Harvard University - Harvard Medical School

Date Written: April 15, 2020

Abstract

Background: On March 24, India ordered a 3-week nationwide lockdown in an effort to control the spread of COVID-19. While the lockdown has been effective, our model suggests that completely ending the lockdown after three weeks could have considerable adverse public health ramifications. We extend our individual-level model for COVID-19 transmission to study the disease dynamics in India at the state level for Maharashtra and Uttar Pradesh to estimate the effect of further lockdown policies in each region. Specifically, we test policies which alternate between total lockdown and simple physical distancing to find "middle ground" policies that can provide social and economic relief as well as salutary population-level health effects.

Methods: We use an agent-based SEIR model that uses population-specific age distribution, household structure, contact patterns, and comorbidity rates to perform tailored simulations for each region. The model is first calibrated to each region using publicly available COVID-19 death data, then implemented to simulate a range of policies. We also compute the basic reproduction number R0 and case documentation rate for both regions.

Results: After the initial lockdown, our simulations demonstrate that even policies that enforce physical distancing while otherwise returning to normal activity could lead to widespread outbreaks in both states. However, "middle ground" policies that alternate weekly between total lockdown and physical distancing may lead to much lower rates of infection while simultaneously permitting some return to normalcy.

Keywords: COVID-19, India, modeling, agent-based model, physical distancing, lockdown

Suggested Citation

Mate, Aditya and Killian, Jackson and Wilder, Bryan and Charpignon, Marie and Awasthi, Ananya and Tambe, Milind and Majumder, Maimuna, Evaluating COVID-19 Lockdown Policies For India: A Preliminary Modeling Assessment for Individual States (April 15, 2020). Available at SSRN: https://ssrn.com/abstract=3575207 or http://dx.doi.org/10.2139/ssrn.3575207

Aditya Mate (Contact Author)

Harvard University - Center for Research on Computation and Society ( email )

33 Oxford Street
Cambridge, MA 02138
United States

Jackson Killian

Harvard University - Center for Research on Computation and Society ( email )

33 Oxford Street
Cambridge, MA 02138
United States

Bryan Wilder

Harvard University - Center for Research on Computation and Society ( email )

33 Oxford Street
Cambridge, MA 02138
United States

Marie Charpignon

Massachusetts Institute of Technology (MIT) ( email )

77 Massachusetts Avenue
50 Memorial Drive
Cambridge, MA 02139-4307
United States

Ananya Awasthi

Independent

Milind Tambe

Harvard University - Center for Research on Computation and Society ( email )

33 Oxford Street
Cambridge, MA 02138
United States

Maimuna Majumder

Boston Children's Hospital - Computational Health Informatics Program ( email )

United States

Harvard University - Harvard Medical School ( email )

25 Shattuck St
Boston, MA 02115
United States

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