We review economic arguments for using public policy to accelerate vaccine supply during a pandemic. Rapidly vaccinating a large share of the global population helps avoid economic, mortality, and social losses, which in the case of Covid-19 mounted into trillions of dollars. However,...

Mental health disorders account for a significant share of the overall global disease burden. The economic losses from such disorders are staggeringly large, particularly in low-income countries, where people are faced with several unexpected shocks. We test whether improved communication can...

Childhood vaccinations are an important input to disease prevention, but vaccination rates have declined over the last decade due largely to parental fears about vaccine dangers. Education campaigns on the safety of vaccines seem to have little impact. Anecdotal evidence on disease outbreaks...

This article reviews the global health and economic consequences of the 1918 influenza pandemic, with a particular focus on topics that have seen a renewed interest because of COVID-19. We begin by providing an overview of key contextual and epidemiological details as well as the data that are...

Covid-19 is the single largest threat to global public health since the Spanish Influenza pandemic of 1918-20. Was the world better prepared in 2020 than it was in 1918? After a century of public health and basic science research, pandemic response and mortality outcomes should be better than in...

This paper studies how better access to public health insurance affects infant mortality during pandemics. Our analysis combines cross-state variation in mandated eligibility for Medicaid with two influenza pandemics -- the 1957-58 "Asian Flu" pandemic and the 1968-69 "Hong Kong Flu" -- that...

We study the role of global supply chains in the impact of the Covid-19 pandemic on GDP growth for 64 countries. We discipline the labor supply shock across sectors and countries using the fraction of work in the sector that can be done from home, interacted with the stringency with which...

We use dynamic panel data models to generate density forecasts for daily Covid-19 infections for a panel of countries/regions. At the core of our model is a specification that assumes that the growth rate of active infections can be represented by autoregressive fluctuations around a downward...

We examine how policymakers should react to a pandemic when there is significant uncertainty regarding key parameters relating to the disease. In particular, this paper explores how optimal mitigation policies change when incorporating uncertainty regarding the Case Fatality Rate (CFR) and the...