Title: To Everything There Is a Season: from outbreaks to famine
Abstract: To achieve the United Nations Sustainable Development Goal 1 (SDG1): End poverty in all its forms everywhere, it is essential to understand its strong connection to two other SDGs: End hunger, achieve food security and improved nutrition, and promote sustainable agriculture (SDG2), and Reduce inequality within and among countries (SDG10). Progress in any one of these areas depends on advances in the others, as all three goals are deeply interwoven within the global public health agenda. Reliable data sources, well-tested models, and robust theoretical frameworks are critical to ensuring meaningful progress. In this talk, I will highlight three key lessons learned from modeling large-scale outbreaks, including the 2009 H1N1 Influenza Pandemic, the Cholera outbreak during Yemen's civil war (2016–2020), and the COVID-19 Pandemic, and illustrate advancements in data analytics through dynamic mapping, multilevel surveillance time series modeling, and outbreak signature decomposition. Using these examples, I will introduce ways for quantifying key characteristics of seasonality and assessing seasonal synchronization. I will conclude the talk by outlining the path forward for building operational forecast to recognize the effects of climate change manifested by disrupted seasonal patterns when seasonality of diseases and malnutrition mimics health inequalities and inadequacies. By recognizing these complex interrelationships, we can transform our approach to modeling and develop innovative strategies to address these challenges.
