Communication in times of crisis is essential. However, there is often a mismatch between the language of governments, aid providers, doctors, and those to whom they are providing aid. Commercial MT systems are reasonable tools to turn to in these scenarios. But how effective are these tools for translating to and from low resource languages, particularly in the crisis or medical domain? In this study, we evaluate four commercial MT systems using the TICO-19 dataset, which is composed of pandemic-related sentences from a large set of high priority languages spoken by communities most likely to be affected adversely in the next pandemic. We then assess the current degree of ``readiness'' for another pandemic (or epidemic) based on the usability of the output translations.

翻译：危机时期的沟通至关重要。然而，政府、援助提供者、医生与受援者之间的语言往往存在不匹配。商业机器翻译系统是此类场景中可考虑的合理工具。但这些工具在翻译低资源语言时效果如何？特别是在危机或医学领域？在本研究中，我们使用TICO-19数据集评估了四种商业机器翻译系统。该数据集包含大量高优先级语言的疫情相关句子，这些语言的使用群体最有可能在下一次疫情中受到不利影响。随后，我们基于输出翻译的可用性，评估了当前应对另一场疫情（或流行病）的"准备就绪"程度。