Association of national and regional lockdowns with COVID-19 infection rates in Pune, India

Area of Science:

• Epidemiology
• Public Health
• Infectious Disease Modeling

Background:

• Assessing lockdown impacts is crucial for pandemic management, especially in resource-limited settings.
• Pune, India, experienced a significant COVID-19 burden during the first wave.
• Understanding lockdown effectiveness informs future public health strategies.

Purpose of the Study:

• To evaluate the impact of national and regional lockdowns on COVID-19 incidence in Pune, India.
• To analyze epidemic growth patterns before, during, and after lockdown periods.
• To model the natural epidemic trajectory and compare it with observed data.

Main Methods:

• Utilized anonymized individual-level data from Pune's public health surveillance (Feb 1 - Sep 15, 2020).
• Assessed weekly incident COVID-19 cases, infection rates, and epidemic curves stratified by lockdown status, demographics, and population density.
• Employed multilevel Poisson regression to quantify lockdown effects and geospatial mapping for spatial analysis.
• Modeled the natural epidemic using a compartmental model.

Main Results:

• Out of 241,629 tested individuals, 64,526 (26%) were positive for SARS-CoV-2.
• Lockdowns delayed the epidemic peak by approximately 8 weeks compared to the modeled natural epidemic.
• Incident COVID-19 cases were 43% lower during the nationwide lockdown and 22% lower during the regional lockdown compared to the unlocking period.
• These reductions were consistent across age groups and population densities.

Conclusions:

• Both national and regional lockdowns demonstrably slowed COVID-19 infection rates in a densely populated urban Indian setting.
• Lockdowns played a significant role in COVID-19 control efforts, offering valuable lessons for pandemic management.
• Findings highlight the public health utility of mobility restrictions in infectious disease outbreaks.