Urgent investment in surveillance systems and global partnerships are needed to prepare for the pandemics that will continue to emerge in the coming decades. The following are three key challenges that pertain to creating useful epidemic forecasts during an outbreak.
The first challenge: Misaligned incentives. Academics are largely incentivised to write scientific articles and to fund their work through individually led grants... Companies are incentivised by profit, and are rightly beholden to national regulatory frameworks and the public with respect to the data they collect.
The second challenge: Gap between (1) technological or methodological innovation, which often occurs in academic settings in high-income countries, and (2) implementation in field settings, frequently done by NGOs or governments in low-income and middle-income countries.
The third challenge: Epidemic forecasting is inherently uncertain... [With] emerging outbreaks—with COVID-19 highlighting this point—we often lack accurate data about case counts and biological processes driving an epidemic, let alone the behavioural responses of people affected, making it challenging to swiftly adapt or interpret very complex models on the spatiotemporal scales relevant for decision making.
‘These innovations will remain dislocated and impractical until the challenges above are addressed. Encouragingly, all three issues could be improved by moving much of the focus of funding and expertise to the populations most vulnerable to epidemics.’
Read here (The Lancet, March 17, 2020)
