Framework for Strengthening Community-Based Surveillance Systems to Detect Zoonotic Disease Outbreaks Early

• Author(s): Funmi Eko Ezeh; Stephanie Onyekachi Oparah
• Paper ID: 1711298
• Page: 488-515
• Published Date: 30-06-2019
• Published In: Iconic Research And Engineering Journals
• Publisher: IRE Journals
• e-ISSN: 2456-8880
• Volume/Issue: Volume 2 Issue 12 June-2019

Abstract

The emergence and re-emergence of zoonotic diseases represent critical threats to global health security, demanding innovative surveillance approaches that bridge the gap between traditional public health systems and community-level detection capabilities. This study develops a comprehensive framework for strengthening community-based surveillance (CBS) systems specifically designed to detect zoonotic disease outbreaks at their earliest stages, thereby enabling rapid response and containment measures. The framework integrates principles from One Health approaches, participatory epidemiology, and digital health technologies to create sustainable, locally-owned surveillance mechanisms that complement formal health systems. Through systematic analysis of existing CBS models, technological innovations, and implementation experiences across diverse geographical and epidemiological contexts, this research identifies critical components necessary for effective early warning systems at the community level. The framework addresses fundamental challenges including community engagement strategies, capacity building protocols, data collection and transmission methodologies, integration with formal surveillance systems, and sustainability mechanisms. Particular emphasis is placed on leveraging mobile health technologies, training community health workers and animal health personnel, establishing event-based surveillance protocols, and creating feedback mechanisms that maintain community participation. The study examines successful CBS implementations in resource-limited settings, extracting lessons learned and best practices applicable to various contexts. Results demonstrate that well-designed CBS systems can significantly reduce detection times for zoonotic disease events, improve outbreak response effectiveness, and build community resilience against emerging infectious disease threats. The framework provides actionable guidance for public health authorities, development partners, and community organizations seeking to establish or strengthen CBS systems for zoonotic disease detection. Key recommendations emphasize the importance of intersectoral collaboration, sustained financing mechanisms, cultural adaptation of surveillance tools, and continuous quality improvement processes. This research contributes to the growing body of evidence supporting community-based approaches as essential components of comprehensive disease surveillance architecture, particularly in settings where formal health infrastructure is limited or geographically inaccessible.

Keywords

Community-Based Surveillance, Zoonotic Diseases, Early Detection, One Health, Participatory Epidemiology, Mobile Health, Outbreak Response, Disease Surveillance Systems, Community Health Workers, Emerging Infectious Diseases

Citations

IRE Journals:
Funmi Eko Ezeh, Stephanie Onyekachi Oparah "Framework for Strengthening Community-Based Surveillance Systems to Detect Zoonotic Disease Outbreaks Early" Iconic Research And Engineering Journals Volume 2 Issue 12 2019 Page 488-515

IEEE:
Funmi Eko Ezeh, Stephanie Onyekachi Oparah "Framework for Strengthening Community-Based Surveillance Systems to Detect Zoonotic Disease Outbreaks Early" Iconic Research And Engineering Journals, 2(12)