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Fujimoto K, Kuo J, Stott G, Lewis R, Chan HK, Lyu L, Veytsel G, Carr M, Broussard T, Short K, Brown P, Sealy R, Brown A, Bahl J. Beyond scale-free networks: integrating multilayer social networks with molecular clusters in the local spread of COVID-19. Sci Rep 2023; 13:21861. [PMID: 38071385 PMCID: PMC10710469 DOI: 10.1038/s41598-023-49109-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2023] [Accepted: 12/04/2023] [Indexed: 12/18/2023] Open
Abstract
This study evaluates the scale-free network assumption commonly used in COVID-19 epidemiology, using empirical social network data from SARS-CoV-2 Delta variant molecular local clusters in Houston, Texas. We constructed genome-informed social networks from contact and co-residence data, tested them for scale-free power-law distributions that imply highly connected hubs, and compared them to alternative models (exponential, log-normal, power-law with exponential cutoff, and Weibull) that suggest more evenly distributed network connections. Although the power-law model failed the goodness of fit test, after incorporating social network ties, the power-law model was at least as good as, if not better than, the alternatives, implying the presence of both hub and non-hub mechanisms in local SARS-CoV-2 transmission. These findings enhance our understanding of the complex social interactions that drive SARS-CoV-2 transmission, thereby informing more effective public health interventions.
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Affiliation(s)
- Kayo Fujimoto
- School of Public Health, University of Texas Health Science Center at Houston, 7000 Fannin Street, UCT 2514, Houston, TX, 77030, USA.
| | - Jacky Kuo
- School of Public Health, University of Texas Health Science Center at Houston, 7000 Fannin Street, UCT 2514, Houston, TX, 77030, USA
| | - Guppy Stott
- Institute of Bioinformatics, University of Georgia, 501 D.W. Brooks Drive, Athens, GA, 30602, USA
| | - Ryan Lewis
- School of Public Health, University of Texas Health Science Center at Houston, 7000 Fannin Street, UCT 2514, Houston, TX, 77030, USA
| | - Hei Kit Chan
- School of Public Health, University of Texas Health Science Center at Houston, 7000 Fannin Street, UCT 2514, Houston, TX, 77030, USA
| | - Leke Lyu
- Institute of Bioinformatics, University of Georgia, 501 D.W. Brooks Drive, Athens, GA, 30602, USA
| | - Gabriella Veytsel
- Institute of Bioinformatics, University of Georgia, 501 D.W. Brooks Drive, Athens, GA, 30602, USA
| | | | | | | | - Pamela Brown
- City of Houston Health Department, Houston, TX, USA
| | - Roger Sealy
- City of Houston Health Department, Houston, TX, USA
| | - Armand Brown
- City of Houston Health Department, Houston, TX, USA
| | - Justin Bahl
- Institute of Bioinformatics, University of Georgia, 501 D.W. Brooks Drive, Athens, GA, 30602, USA.
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Kunkel A, Veytsel G, Bonaparte S, Meek H, Ma X, Davis AJ, Bonwitt J, Wallace RM. Defining county-level terrestrial rabies freedom using the United States National Rabies Surveillance System: a surveillance data analysis (Preprint). JMIR Public Health Surveill 2022; 9:e43061. [PMID: 37027194 PMCID: PMC10131775 DOI: 10.2196/43061] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2022] [Revised: 01/27/2023] [Accepted: 02/14/2023] [Indexed: 02/16/2023] Open
Abstract
BACKGROUND Rabies is a deadly zoonotic disease with nearly 100% fatality rate. In the United States, rabies virus persists in wildlife reservoirs, with occasional spillover into humans and domestic animals. The distribution of reservoir hosts in US counties plays an important role in public health decision-making, including the recommendation of lifesaving postexposure prophylaxis upon suspected rabies exposures. Furthermore, in surveillance data, it is difficult to discern whether counties have no cases reported because rabies was not present or because counties have an unreported rabies presence. These epizootics are monitored by the National Rabies Surveillance System (NRSS), to which approximately 130 state public health, agriculture, and academic laboratories report animal rabies testing statistics. Historically, the NRSS classifies US counties as free from terrestrial rabies if, over the previous 5 years, they and any adjacent counties did not report any rabies cases and they tested ≥15 reservoir animals or 30 domestic animals. OBJECTIVE This study aimed to describe and evaluate the historical NRSS rabies-free county definition, review possibilities for improving this definition, and develop a model to achieve more precise estimates of the probability of terrestrial rabies freedom and the number of reported county-level terrestrial rabies cases. METHODS Data submitted to the NRSS by state and territorial public health departments and the US Department of Agriculture Wildlife Services were analyzed to evaluate the historical rabies-free definition. A zero-inflated negative binomial model created county-level predictions of the probability of rabies freedom and the expected number of rabies cases reported. Data analyzed were from all animals submitted for laboratory diagnosis of rabies in the United States from 1995 to 2020 in skunk and raccoon reservoir territories, excluding bats and bat variants. RESULTS We analyzed data from 14,642 and 30,120 county-years in the raccoon and skunk reservoir territories, respectively. Only 0.85% (9/1065) raccoon county-years and 0.79% (27/3411) skunk county-years that met the historical rabies-free criteria reported a case in the following year (99.2% negative predictive value for each), of which 2 were attributed to unreported bat variants. County-level model predictions displayed excellent discrimination for detecting zero cases and good estimates of reported cases in the following year. Counties classified as rabies free rarely (36/4476, 0.8%) detected cases in the following year. CONCLUSIONS This study concludes that the historical rabies freedom definition is a reasonable approach for identifying counties that are truly free from terrestrial raccoon and skunk rabies virus transmission. Gradations of risk can be measured using the rabies prediction model presented in this study. However, even counties with a high probability of rabies freedom should maintain rabies testing capacity, as there are numerous examples of translocations of rabies-infected animals that can cause major changes in the epidemiology of rabies.
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Affiliation(s)
- Amber Kunkel
- Division of High-Consequence Pathogens and Pathology, National Center for Emerging & Zoonotic Infectious Diseases, US Centers for Disease Control and Prevention, Atlanta, GA, United States
- Epidemic Intelligence Service, US Centers for Disease Control and Prevention, Atlanta, GA, United States
| | - Gabriella Veytsel
- Division of High-Consequence Pathogens and Pathology, National Center for Emerging & Zoonotic Infectious Diseases, US Centers for Disease Control and Prevention, Atlanta, GA, United States
| | - Sarah Bonaparte
- Division of High-Consequence Pathogens and Pathology, National Center for Emerging & Zoonotic Infectious Diseases, US Centers for Disease Control and Prevention, Atlanta, GA, United States
| | - Haillie Meek
- Epidemiology Elective Program, US Centers for Disease Control and Prevention, Atlanta, GA, United States
| | - Xiaoyue Ma
- Division of High-Consequence Pathogens and Pathology, National Center for Emerging & Zoonotic Infectious Diseases, US Centers for Disease Control and Prevention, Atlanta, GA, United States
| | - Amy J Davis
- Wildlife Services, Animal and Plant Health Inspection Service, United States Department of Agriculture, Fort Collins, CO, United States
| | - Jesse Bonwitt
- Division of High-Consequence Pathogens and Pathology, National Center for Emerging & Zoonotic Infectious Diseases, US Centers for Disease Control and Prevention, Atlanta, GA, United States
| | - Ryan M Wallace
- Division of High-Consequence Pathogens and Pathology, National Center for Emerging & Zoonotic Infectious Diseases, US Centers for Disease Control and Prevention, Atlanta, GA, United States
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