A data-driven approach to COVID-19: Resources, policies, and best practices

The grand scale of the COVID-19 pandemic has impacted all aspects of human life. It has revealed worldwide many systemic deficiencies in understanding, preparedness, and control of the disease. To improve the situation, a data-driven approach can guide the use of resources, aid policies, and benefit from the best practices of data acquisition, sharing, and dissemination. Public health decision-making and action depend critically on the timely availability of reliable data. In this study, we described the data types and principles that are useful for better understanding of the pandemic. We focused on public policies such as lockdown and social distancing. We observed a possible impact of change in mobility on different urban populations in the US. Finally, we discussed the potential of objective policies such as limited and local lockdown to balance the dual goals of preventing contagion while also maintaining economic stability with careful consideration for vulnerable populations.

Abstract licence: CC BY-NC-SA

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