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School closures and suspension of non-essential economic activities are highly effective respiratory-pandemic mitigation strategies because they effectively interrupt disease transmission. However, they come with high societal costs. Most of these costs are borne by workers who lose their income, especially those who are not supported by welfare benefits, and students whose future income depends on their education. In countries where many households live close to the poverty line, closures should be designed to minimize impacts on the most vulnerable. The objective of this study is to learn and compare policy responses that minimize the number of people that fall below the poverty line, maximize GDP, or maximize societal welfare in a model of the COVID-19 outbreak in the Philippines. Toward this objective, we quantify societal welfare in terms of lives, education, GDP, and we introduce poverty as a novel fourth dimension. We then use a population microsimulation model, an epidemiological model, and GDP and education projections to determine intervention strategies involving the partial closure of schools and economic sectors with the objective of mitigating the epidemic while minimizing societal losses. We find the cost of reducing poverty is substantial in terms of the other outcomes, making a case for poverty reduction as an important tool for increasing societal resilience and preparedness for crises such as pandemics. From a modeling perspective, we identify the need for timely data collection in order to create tools to assist in future epidemics.