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Our Impact

Over the past two years, dozens of organizations used Facebook's Data for Good products to improve wellbeing and save lives. Their most profound applications include disaster preparedness projects, vaccination campaigns, and effective deployment of services during times of natural disaster.

This study investigated the predictors of risk perception and its effect on older adults’ preventive behavior and/or medical care avoidance during the COVID-19 pandemic. The study found that... This study investigated the predictors of risk perception and its effect on older adults’ preventive behavior and/or medical care avoidance during the COVID-19 pandemic. The study found that significant predictors of higher risk perception were female gender, older age, poorer health, city residency, personally knowing someone who had COVID-19, and correct knowledge of vaccine/treatment. Higher risk perception was subsequently associated with higher frequency/probability of practicing preventive behavior and/or avoiding medical care. Knowledge had the strongest path coefficient with risk perception. Ultimately, disseminating correct information to older adults could help them evaluate infection risk accurately and educational programs on the precautions implemented at clinical settings to ensure patient safety may encourage older adults to seek timely medical care.

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COVID-19 Forecasts

Risk Perception, Preventive Behavior, and Medical Care Avoidance among American Older Adults During the COVID-19 Pandemic

This study investigated the predictors of risk perception and its effect on older adults’ preventive behavior and/or medical care avoidance during the COVID-19 pandemic. The study found that significant predictors of higher risk perception were female gender, older age, poorer health, city residency, personally knowing someone who had COVID-19, and correct knowledge of vaccine/treatment. Higher risk perception was subsequently associated with higher frequency/probability of practicing preventive behavior and/or avoiding medical care. Knowledge had the strongest path coefficient with risk perception. Ultimately, disseminating correct information to older adults could help them evaluate infection risk accurately and educational programs on the precautions implemented at clinical settings to ensure patient safety may encourage older adults to seek timely medical care.

This study evaluates the effects of lockdowns on human mobility and simulate how these changes may affect epidemic spread by analyzing aggregated mobility data from mobile phones. It shows that in... This study evaluates the effects of lockdowns on human mobility and simulate how these changes may affect epidemic spread by analyzing aggregated mobility data from mobile phones. It shows that in 2020 following lockdown announcements but prior to their implementation, both local and long distance movement increased in multiple locations, and urban-to-rural migration was observed around the world. To examine how these behavioral responses to lockdown policies may contribute to epidemic spread, the study developed a simple agent-based spatial model. The model shows that this increased movement has the potential to increase seeding of the epidemic in less urban areas, which could undermine the goal of the lockdown in preventing disease spread.

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Movement Range Maps

Lockdowns result in changes in human mobility which may impact the epidemiologic dynamics of SARS-CoV-2

This study evaluates the effects of lockdowns on human mobility and simulate how these changes may affect epidemic spread by analyzing aggregated mobility data from mobile phones. It shows that in 2020 following lockdown announcements but prior to their implementation, both local and long distance movement increased in multiple locations, and urban-to-rural migration was observed around the world. To examine how these behavioral responses to lockdown policies may contribute to epidemic spread, the study developed a simple agent-based spatial model. The model shows that this increased movement has the potential to increase seeding of the epidemic in less urban areas, which could undermine the goal of the lockdown in preventing disease spread.

Researchers from the Indian Institute of Technology – Tirupati (IIT-T) partnered with Facebook to create data-driven tools to help policymakers and public health experts to make informed decisions... Researchers from the Indian Institute of Technology – Tirupati (IIT-T) partnered with Facebook to create data-driven tools to help policymakers and public health experts to make informed decisions and interventions. IIT-T used Facebook movement maps and population density maps to analyze population movement and disease containment. IIT-T shared daily, visual reports with the state governments of Andhra Pradesh and Odisha on high-mobility regions, geographies with high outflows of people, and areas with high population density to help governments make decisions about interventions in red zones to help slow the spread of disease. IIT-T then developed a real-time COVID-19 response dashboard to visualize and understand the effectiveness of the lockdown imposed due to COVID-19.

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Movement Range Maps

COVID-19 Mobility Data Analysis in India

Researchers from the Indian Institute of Technology – Tirupati (IIT-T) partnered with Facebook to create data-driven tools to help policymakers and public health experts to make informed decisions and interventions. IIT-T used Facebook movement maps and population density maps to analyze population movement and disease containment. IIT-T shared daily, visual reports with the state governments of Andhra Pradesh and Odisha on high-mobility regions, geographies with high outflows of people, and areas with high population density to help governments make decisions about interventions in red zones to help slow the spread of disease. IIT-T then developed a real-time COVID-19 response dashboard to visualize and understand the effectiveness of the lockdown imposed due to COVID-19.

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