An analysis of lockdowns in Chile reveals that wealth was critical in determining who stayed at home and who took a risk.
Latin American countries rushed to impose lockdowns and restrictions on mobility when COVID-19 struck in March 2020. Evidently, these public health measures would slow down the region’s growing economy. Still, it wasn’t clear how people would respond, especially when deciding between sacrificing their income or avoiding infection.
Santiago, Chile, was a prime example of this dynamic. It is one of the most prosperous cities in the region, but it also has a high level of socioeconomic inequality, which fueled violent protests against the government in late 2019.
In the early months of this pandemic, Gabriel Weintraub and a Chilean team of researchers conducted a Study to see how the lockdowns and shelter-in-place orders would impact the spread of the disease in Santiago. They found that socioeconomic disparities were a significant factor in how people responded to public health orders using cellphone data to track resident’s movements. This could be used to predict COVID-19 outbreaks.
Weintraub says that the different reactions of people to lockdowns were not surprising. The magnitude of the difference between wealthy and low-income communities was shocking.
These differences in mobility were essential indicators of an increase in the number of cases. The study concluded that a rise of 10% in mobility within a municipality was correlated to a 5% rise in infection rates.
Weintraub, his colleagues, and themselves concluded that lockdowns, shelter-at-home orders, and efforts to ease compliance for low-income neighborhoods were needed to contain the virus effectively.
Use phones to track risk
Researchers tracked Santiaguinos with the help of granular cell phone locations in a collaboration between Entel, Chile’s largest telecom provider, and Complex Systems Engineering Institute. The collected data was anonymized and taken from zones of 2,000-3,000 people.
Weintraub explains: “We tracked the movements of people on weekdays in the mornings and afternoons to identify patterns related to their work.” Researchers analyzed geolocated data from phones along with localized infection risk data, studying travel frequency to high-risk areas. We wondered what the impact of mobility is on infections. “We did an econometric study on this, and found that mobility reductions do reduce infections.”
Weintraub and his co-authors began collecting data at the beginning of March 2020 when Chilean officials closed schools and encouraged remote work from Santiago. The city’s first localized lockdown was implemented at the end of March 2020, affecting mainly the eastern part, where most residents are in the highest-income group. Despite the voluntary sheltering that was in place in these areas, the number of new infections remained low.
In April 2020, a second lockdown was imposed on lower-income areas. In these areas where residents depend on day labor in person, the infection rates continued to increase faster than in wealthier areas, which were no longer under lockdown. This led to a spike in cases by mid-May. The government then had to impose a lockdown on the entire city, which helped to slow the spread of the disease.
Balance Health and Wealth
Weintraub, researchers from ISCI, and the University of Chile collected data and made it accessible to the public via an online dashboard. They also met with the Ministry of Science and the Office of the President to inform them of their findings and inform the government regarding lockdowns and other measures.
After a few months, it became clear that lockdowns were effective but that low-income communities needed additional support to adhere to them. Chilean authorities had launched a fiscal package for small businesses and payroll workers. However, little was done to help low-income workers and informal workers. In May 2020, President Sebastian Pinera unveiled a comprehensive plan to support families, including healthcare, essential items, and financial assistance through cash transfers.
Weintraub says it’s difficult to determine how much of our work played in the decision. The study’s econometric model provided causal relationships which could be used to guide policymakers. Chile uses these indicators to drive the country’s strategy for managing the reopening economy. This is called Paso-a-Pasoopen, a new window that is still ongoing.
Lockdowns are one of the most effective non-medical ways to reduce COVID-19 infections. Weintraub says restricting mobility is a drastic step, primarily if implemented without complementing policies that address socioeconomic disparities, making it hard for many people to remain at home for weeks or days. He says that this leads to a more nuanced approach. “Maybe we shouldn’t restrict mobility so much, but rather restrict the risky interactions.”