Due to a confluence of environmental, ecological, societal, and epidemiological considerations, the risk of disease outbreak occurrence is increasing both in frequency and intensity. When spillover events cannot be stopped at their source, it is a race against the clock for health systems to prevent outbreaks from spreading into protracted epidemics or pandemics. To avoid unnecessary morbidity and mortality among humans and animals alike, as well as the associated socioeconomic consequences resulting from interventions required to control disease transmission, experts worldwide are developing and employing innovative strategies to strengthen the performance of health systems during outbreaks.
Timeliness metrics have been proposed as a tool to track, measure, and assess the speed with which health systems detect and respond to outbreaks. Given that a majority of outbreaks affect or involve the health of humans, animals, plants, or the environment, a set of One Health timeliness metrics have been proposed to ensure the tool is applicable to multisectoral outbreaks. In addition to measuring timeliness for milestones such as the outbreak start, date of detection, notification to relevant authorities, verification, diagnostic confirmation, response enacted, public communication, and outbreak end, the One Health timeliness metrics seek to track dates for predictive alerts signaling potential outbreaks, preventive responses to those alerts, and after-action review meetings between multidisciplinary stakeholders. This dissertation explores several aspects of the One Health timeliness metrics, including questions related to how milestones are being reported during multisectoral outbreaks, how feasible and useful implementation of this tool is, and what we can learn from the One Health timeliness metrics.
Evidence from both a global scoping review of thousands of outbreaks and a country-level analysis of multisectoral outbreaks in Uganda between 2018 and 2022 illustrate that while most One Health outbreak milestones are being reported with relative frequency, dates for predictive alerts of outbreaks, preventive responses, and after-action reviews are not. However, given findings from the scoping review that outbreaks reporting both a predictive alert and preventive response had shorter timeliness (defined as the median time in days) between most intervals compared to outbreaks not reporting preventive responses, this dissertation concludes that tracking these key One Health outbreak milestones may help optimize outbreak preparedness and prevention efforts. Furthermore, the perceived feasibility and utility of timeliness metrics, assessed through a mixed- methods study in Uganda, a country prone to outbreaks of diseases of high risk for epidemic or pandemic potential, suggests that stakeholders support the adoption of these metrics, despite remaining implementation challenges.
From an analysis of timeliness metrics during multisectoral outbreaks in Uganda between 2018 and 2022, we found that the two greatest predictors of speed in outbreak response were past experience with similar disease outbreaks and whether the outbreak was of a viral hemorrhagic fever. These findings highlight important lessons to be learned from timeliness metrics: Uganda remains unprepared for outbreaks of diseases the country is less familiar with, which includes a novel Disease X. However, we believe adoption of these metrics may facilitate the operationalization of the One Health approach, which stakeholders described as important but challenging in practice, which ultimately may contribute to faster overall timeliness for detection and response during multisectoral outbreaks.
This dissertation provides empirical evidence that the One Health timeliness metrics should be considered as a useful and informative tool to facilitate epidemic and pandemic preparedness and prevention efforts at a time when cross-cutting innovations to address this multifactorial challenge are essential.
