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Financing Global Early Warning Systems Country Case Study: Indonesia

Indonesia grappled with one of Southeast Asia’s highest COVID-19 caseloads, reporting nearly 7 million cases and 161,918 deaths as of December 2023. The pandemic’s ripple effects extended beyond the immediate health crisis. It disrupted the management of other prevalent illnesses, such as tuberculosis. The pandemic triggered a socioeconomic crisis in Indonesia—an additional 2.7 million individuals fell below the poverty line, unemployment surged to 7.1 percent, students lost on average one year of schooling, and it took two years for real GDP to rebound to 2019 levels.

Since 2020, the Milken Institute has promoted collaboration to develop and improve early warning systems (EWS) for pandemic preparedness and health security, convening experts and stakeholders to outline a vision for a global early warning network, as well as key considerations for governance, data, and financing. The early warning network would predict, detect, and monitor potential infectious disease outbreaks through cross-sector coordination, data collection, and data analysis, identifying unusual patterns or upticks in key indicators to prevent or mitigate disease spread.

To gain a more nuanced understanding of the challenge of creating a global EWS, the Institute conducted in-depth interviews with national and local stakeholders and organized roundtables, with a focus on Indonesia, Brazil, and Kenya.

This case study focuses on Indonesia, where an immense population (277.5 million people as of 2023), geographical distribution, and income disparity intensify the intricacies of health management across the nation.