Transforming zoonotic disease surveillance and spatial epidemiology: Improving content, detail, and data infrastructure

Abstract Background Emerging and endemic zoonoses continue to have adverse global impacts. One Health approaches promoting multisectoral, transdisciplinary collaboration are important methods to address zoonoses threats through disease surveillance, prevention, control, and response. We conducted a One Health Zoonotic Disease Prioritization (OHZDP) workshop in the United States (US) to identify zoonotic diseases of greatest national concern that should be jointly addressed by the Centers for Disease Control (CDC), US Department of Agriculture (USDA), Department of the Interior, and partners. Methods We used CDC’s OHZDP tool to prioritize zoonoses. Workshop participants selected criteria for prioritization, and developed questions and weights for each criterion. Questions were answered using available literature and expert opinion with subsequent scoring resulting in a ranked zoonotic disease list. After agreeing on a final prioritized disease list, participants used components of the One Health Systems Mapping and Analysis Resource Toolkit, developed by USDA and University of Minnesota, to review multidisciplinary coordination processes for the prioritized zoonotic diseases. Results Participants selected epidemic or pandemic potential, disease severity, economic impact, introduction or increased transmission potential, and national security as criteria to prioritize 56 zoonoses. The eight prioritized zoonotic diseases for the US were zoonotic influenzas, salmonellosis, West Nile virus, plague, emerging coronaviruses (e.g., SARS, MERS), rabies, brucellosis, and Lyme disease. Agencies then discussed recommendations to enhance One Health approaches to surveillance, response, prevention, and control of the prioritized zoonoses. Key themes and next steps for further implementation of One Health approaches were identified. Conclusion This OHZDP workshop represents the first use of a One Health approach to zoonotic disease prioritization in the United States. It is a critical step forward in US government agency collaboration using One Health approaches. Further, the workshop created a foundation for future US government One Health systems strengthening for the prioritized zoonoses. Disclosures All authors: No reported disclosures.

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Identifying current and emerging resources and tools utilized for detection, prediction, and visualization of viral zoonotic disease clusters: a Delphi study

JAMIA Open ◽

10.1093/jamiaopen/ooz015 ◽

2019 ◽

Vol 2 (3) ◽

pp. 306-311

Author(s):

Rachel Beard ◽

Matthew Scotch

Keyword(s):

Decision Support ◽

Delphi Study ◽

Disease Surveillance ◽

Health Personnel ◽

System Development ◽

Zoonotic Disease ◽

Current Data ◽

Cluster Detection ◽

Local Health ◽

Preventative Measures

Abstract Zoonotic disease surveillance presents a substantial problem in the management of public health. Globally, zoonoses have the potential to spread and negatively impact population health economic growth, and security. This research was conducted to investigate the current data sources, analytical methods, and limitations for cluster detection and prediction with particular interest in emerging bioinformatics tools and resources to inform the development of zoonotic surveillance spatial decision support systems. We recruited 10 local health personnel to participate in a Delphi study. Participants agreed cluster detection is a priority, though mathematical modeling methods and bioinformatics resources are not commonly used toward this endeavor. However, participants indicated a desire to utilize preventative measures. We identified many limitations for identifying clusters including software availability, appropriateness, training, and usage of emerging genetic data. Future decision support system development should focus on state health personnel priorities and tasks to better utilize emerging developments and available data.

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Who’s worried about turkeys? How ‘organisational silos’ impede zoonotic disease surveillance

Sociology of Health & Illness ◽

10.1111/j.1467-9566.2012.01501.x ◽

2012 ◽

Vol 35 (2) ◽

pp. 200-212 ◽

Cited By ~ 16

Author(s):

Colin Jerolmack

Keyword(s):

Disease Surveillance ◽

Zoonotic Disease

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Animals as Early Detectors of Bioevents: Veterinary Tools and a Framework for Animal-Human Integrated Zoonotic Disease Surveillance

Public Health Reports ◽

10.1177/003335490812300310 ◽

2008 ◽

Vol 123 (3) ◽

pp. 300-315 ◽

Cited By ~ 14

Author(s):

Diane M. Gubernot ◽

Benita L. Boyer ◽

Marina S. Moses

Keyword(s):

Disease Surveillance ◽

Zoonotic Disease

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Cross-Sectoral Zoonotic Disease Surveillance in Western Kenya: Identifying Drivers and Barriers Within a Resource Constrained Setting

Frontiers in Veterinary Science ◽

10.3389/fvets.2021.658454 ◽

2021 ◽

Vol 8 ◽

Author(s):

Lian Francesca Thomas ◽

Jonathan Rushton ◽

Salome A. Bukachi ◽

Laura C. Falzon ◽

Olivia Howland ◽

...

Keyword(s):

Data Sharing ◽

Disease Surveillance ◽

Animal Health ◽

National Level ◽

Zoonotic Disease ◽

Political Will ◽

Western Kenya ◽

Physical Infrastructure ◽

Legislative Framework ◽

Clear Identification

Background: Collaboration between the human and animal health sectors, including the sharing of disease surveillance data, has the potential to improve public health outcomes through the rapid detection of zoonotic disease events prior to widespread transmission in humans. Kenya has been at the forefront of embracing a collaborative approach in Africa with the inception of the Zoonotic Disease Unit in 2011. Joint outbreak responses have been coordinated at the national level, yet little is currently documented on cross-sectoral collaboration at the sub-national level.Methods: Key informant interviews were conducted with 28 disease surveillance officers from the human and animal health sectors in three counties in western Kenya. An inductive process of thematic analysis was used to identify themes relating to barriers and drivers for cross-sectoral collaboration.Results: The study identified four interlinking themes related to drivers and barriers for cross-sectoral collaboration. To drive collaboration at the sub-national level there needs to be a clear identification of “common objectives,” as currently exemplified by the response to suspected rabies and anthrax cases and routine meat hygiene activities. The action of collaboration, be it integrated responses to outbreaks or communication and data sharing, require “operational structures” to facilitate them, including the formalisation of reporting lines, supporting legislation and the physical infrastructure, from lab equipment to mobile phones, to facilitate the activities. These structures in turn require “appropriate resources” to support them, which will be allocated based on the “political will” of those who control the resources.Conclusions: Ongoing collaborations between human and animal disease surveillance officers at the sub-national level were identified, driven by common objectives such as routine meat hygiene and response to suspected rabies and anthrax cases. In these areas a suitable operational structure is present, including a supportive legislative framework and clearly designated roles for officers within both sectors. There was support from disease surveillance officers to increase their collaboration, communication and data sharing across sectors, yet this is currently hindered by the lack of these formal operational structures and poor allocation of resources to disease surveillance. It was acknowledged that improving this resource allocation will require political will at the sub-national, national and international levels.

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State-Level Zoonotic Disease Surveillance in the United States

Zoonoses and Public Health ◽

10.1111/j.1863-2378.2011.01401.x ◽

2011 ◽

Vol 58 (8) ◽

pp. 523-528 ◽

Cited By ~ 6

Author(s):

M. Scotch ◽

P. Rabinowitz ◽

C. Brandt

Keyword(s):

United States ◽

Disease Surveillance ◽

State Level ◽

The United States ◽

Zoonotic Disease

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Origin and cross-species transmission of bat coronaviruses in China

10.1101/2020.05.31.116061 ◽

2020 ◽

Cited By ~ 11

Author(s):

Alice Latinne ◽

Ben Hu ◽

Kevin J. Olival ◽

Guangjian Zhu ◽

Libiao Zhang ◽

...

Keyword(s):

Phylogenetic Analysis ◽

Severe Acute Respiratory Syndrome ◽

Causative Agent ◽

Disease Surveillance ◽

Sequence Data ◽

Zoonotic Disease ◽

Host Switching ◽

Phylogenetic Distance ◽

Statistical Framework ◽

Geographic Regions

AbstractBats are presumed reservoirs of diverse coronaviruses (CoVs) including progenitors of Severe Acute Respiratory Syndrome (SARS)-CoV and SARS-CoV-2, the causative agent of COVID-19. However, the evolution and diversification of these coronaviruses remains poorly understood. We used a Bayesian statistical framework and sequence data from all known bat-CoVs (including 630 novel CoV sequences) to study their macroevolution, cross-species transmission, and dispersal in China. We find that host-switching was more frequent and across more distantly related host taxa in alpha-than beta-CoVs, and more highly constrained by phylogenetic distance for beta-CoVs. We show that inter-family and -genus switching is most common in Rhinolophidae and the genus Rhinolophus. Our analyses identify the host taxa and geographic regions that define hotspots of CoV evolutionary diversity in China that could help target bat-CoV discovery for proactive zoonotic disease surveillance. Finally, we present a phylogenetic analysis suggesting a likely origin for SARS-CoV-2 in Rhinolophus spp. bats.

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