Instability poses significant challenges to disease surveillance. Traditional surveillance systems rely on stable and predictable patterns to monitor and respond to disease outbreaks. When these patterns become unstable, it becomes harder to detect and respond to emerging threats in a timely manner. This can result in delayed interventions and increased morbidity and mortality.
