Title |
Detailed Transmission Network Analysis of a Large Opiate-Driven Outbreak of HIV Infection in the United States.
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Published in |
Journal of Infectious Diseases, October 2017
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DOI | 10.1093/infdis/jix307 |
Pubmed ID | |
Authors |
Ellsworth M Campbell, Hongwei Jia, Anupama Shankar, Debra Hanson, Wei Luo, Silvina Masciotra, S Michele Owen, Alexandra M Oster, Romeo R Galang, Michael W Spiller, Sara J Blosser, Erika Chapman, Jeremy C Roseberry, Jessica Gentry, Pamela Pontones, Joan Duwve, Paula Peyrani, Ron M Kagan, Jeannette M Whitcomb, Philip J Peters, Walid Heneine, John T Brooks, William M Switzer |
Abstract |
In January 2015, an outbreak of undiagnosed human immunodeficiency virus (HIV) infections among persons who inject drugs (PWID) was recognized in rural Indiana. By September 2016, 205 persons in this community of approximately 4400 had received a diagnosis of HIV infection. We report results of new approaches to analyzing epidemiologic and laboratory data to understand transmission during this outbreak. HIV genetic distances were calculated using the polymerase region. Networks were generated using data about reported high-risk contacts, viral genetic similarity, and their most parsimonious combinations. Sample collection dates and recency assay results were used to infer dates of infection. Epidemiologic and laboratory data each generated large and dense networks. Integration of these data revealed subgroups with epidemiologic and genetic commonalities, one of which appeared to contain the earliest infections. Predicted infection dates suggest that transmission began in 2011, underwent explosive growth in mid-2014, and slowed after the declaration of a public health emergency. Results from this phylodynamic analysis suggest that the majority of infections had likely already occurred when the investigation began and that early transmission may have been associated with sexual activity and injection drug use. Early and sustained efforts are needed to detect infections and prevent or interrupt rapid transmission within networks of uninfected PWID. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 17 | 53% |
Venezuela, Bolivarian Republic of | 1 | 3% |
United Kingdom | 1 | 3% |
United Arab Emirates | 1 | 3% |
New Zealand | 1 | 3% |
Colombia | 1 | 3% |
Japan | 1 | 3% |
Unknown | 9 | 28% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 20 | 63% |
Scientists | 9 | 28% |
Practitioners (doctors, other healthcare professionals) | 3 | 9% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 72 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 13 | 18% |
Researcher | 11 | 15% |
Other | 7 | 10% |
Student > Master | 7 | 10% |
Student > Doctoral Student | 6 | 8% |
Other | 10 | 14% |
Unknown | 18 | 25% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 15 | 21% |
Nursing and Health Professions | 8 | 11% |
Agricultural and Biological Sciences | 6 | 8% |
Computer Science | 5 | 7% |
Biochemistry, Genetics and Molecular Biology | 5 | 7% |
Other | 12 | 17% |
Unknown | 21 | 29% |