This paper investigates the determinants of COVID-19 infection in the first 100 days of government actions. Using a debiased LASSO estimator, we explore how different measures of government nonpharmaceutical interventions affect new infections of COVID-19 for 37 lower and middle-income countries (LMCs). We find that closing schools, stay-at-home restrictions, and contact tracing reduce the growth of new infections, as do economic support to households and the number of health care workers. Notably, we find no significant effects of business closures. Finally, infections become higher in countries with greater income inequality, higher tourist inflows, poorly educated adults, and weak governance quality. We conclude that several policy interventions reduce infection rates for poorer countries. Further, economic and institutional factors are important; thereby justifying the use, and ultimately success, of economic support to households during the initial infection period.

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Using a rich individual level dataset from six countries, we examine the relationship between job loss and mental disorders during the first phase of the COVID‐19 pandemic. We consider four indicators of mental disorders based on their severity, viz. anxiety, insomnia, boredom, and loneliness. We draw our conclusions based on two groups of countries that differ by the timing of their peak infections count. Using a logit and a two‐stage least squares (TSLS) regression methods, we find that the people who lost their jobs due to the pandemic are more likely to suffer from mental disorders, especially insomnia and loneliness. Additionally, people with financial liabilities, such as housing mortgages, are among those vulnerable to anxiety. Women, urban residents, youth, low‐income groups, and tobacco users are more prone to mental disorders. The findings from this research have significant policy implications on infectious disease control measures and mental health conditions due to lockdowns and social distancing.