Earlier Outbreak Detection-A Generic Model and Novel Methodology to Guide Earlier Detection Supported by Data From Low- and Mid-Income Countries.

Lindsay Steele,Emma Orefuwa,Silvia Bino,Shepherd Roee Singer,Julius Lutwama,Petra Dickmann

doi:10.3389/fpubh.2020.00452

Abstract

Infectious disease outbreaks can have significant impact on individual health, national economies, and social well-being. Through early detection of an infectious disease, the outbreak can be contained at the local level, thereby reducing adverse effects on populations. Significant time and funding have been invested to improve disease detection timeliness. However, current evaluation methods do not provide evidence-based suggestions or measurements on how to detect outbreaks earlier. Key conditions for earlier detection and their influencing factors remain unclear and unmeasured. Without clarity about conditions and influencing factors, attempts to improve disease detection remain ad hoc and unsystematic.Methods: We developed a generic five-step disease detection model and a novel methodology to use for data collection, analysis, and interpretation. Data was collected in two workshops in Southeast Europe (n = 33 participants) and Southern and East Africa (n = 19 participants), representing mid- and low-income countries. Through systematic, qualitative, and quantitative data analyses, we identified key conditions for earlier detection and prioritized factors that influence them. As participants joined a workshop format and not an experimental setting, no ethics approval was required.Findings: Our analyses suggest that governance is the most important condition for earlier detection in both regions. Facilitating factors for earlier detection are risk communication activities such as information sharing, communication, and collaboration activities. Impeding factors are lack of communication, coordination, and leadership.Interpretation: Governance and risk communication are key influencers for earlier detection in both regions. However, inadequate technical capacity, commonly assumed to be a leading factor impeding early outbreak detection, was not found a leading factor. This insight may be used to pinpoint further improvement strategies.

Highlights

BackgroundThe outbreak of Ebola viral hemorrhagic fever disease in West Africa stressed the importance of functional and reliable health systems that enable early disease detection, rapid response, and sustainable recovery
The necessary condition domains are based on the following categories that were used during data collection at the incubator workshops: governance, technical capacity, human resource capacity, knowledge, skills, and attitudes/beliefs
Legislation and standard operating procedures lay the groundwork for all aspects of disease detection

Summary

Introduction

BackgroundThe outbreak of Ebola viral hemorrhagic fever disease in West Africa stressed the importance of functional and reliable health systems that enable early disease detection, rapid response, and sustainable recovery. In the aftermath of the 2003 outbreak of the severe acute respiratory syndrome (SARS), the World Health Organization (WHO) updated the International Health Regulations (IHR 2005) and called for all Member States to build and strengthen their capacities to prevent, detect, and respond to infectious disease outbreaks, especially for those diseases that have the potential of international spread. The IHR (2005) addressed modern threats by expanding the usual infectious disease notification requirements to include “all events potentially constituting a public health emergency of international concern (PHEIC) [2]. Through this binding agreement, Member States are required to establish core capacities and mechanisms for rapid detection of public health risks, as well as the prompt risk assessment, notification, and response to these risks. Risk communication as a core capacity under the IHR plays an Surveillance Narrative: Early Detection

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