Emily S Jentes1, R Ryan Lash2, Michael A Johansson3, Tyler M Sharp3, Ronnie Henry2, Oliver J Brady4, Mark J Sotir2, Simon I Hay5, Harold S Margolis3, Gary W Brunette2. 1. Division of Global Migration and Quarantine, Centers for Disease Control and Prevention (CDC), 1600 Clifton Road, MS E-03, Atlanta, GA 30333, USA ejentes@cdc.gov. 2. Division of Global Migration and Quarantine, Centers for Disease Control and Prevention (CDC), 1600 Clifton Road, MS E-03, Atlanta, GA 30333, USA. 3. Division of Vector-Borne Diseases, CDC, San Juan, Puerto Rico 00920. 4. Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK Oxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Oxford OX3 7BN, UK. 5. Oxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Oxford OX3 7BN, UK Institute for Health Metrics and Evaluation, University of Washington, Seattle, 2301 Fifth Ave., Suite 600 Seattle, WA 98121.
Abstract
BACKGROUND: International travel can expose travellers to pathogens not commonly found in their countries of residence, like dengue virus. Travellers and the clinicians who advise and treat them have unique needs for understanding the geographic extent of risk for dengue. Specifically, they should assess the need for prevention measures before travel and ensure appropriate treatment of illness post-travel. Previous dengue-risk maps published in the Centers for Disease Control and Prevention's Yellow Book lacked specificity, as there was a binary (risk, no risk) classification. We developed a process to compile evidence, evaluate it and apply more informative risk classifications. METHODS: We collected more than 839 observations from official reports, ProMED reports and published scientific research for the period 2005-2014. We classified each location as frequent/continuous risk if there was evidence of more than 10 dengue cases in at least three of the previous 10 years. For locations that did not fit this criterion, we classified locations as sporadic/uncertain risk if the location had evidence of at least one locally acquired dengue case during the last 10 years. We used expert opinion in limited instances to augment available data in areas where data were sparse. RESULTS: Initial categorizations classified 134 areas as frequent/continuous and 140 areas as sporadic/uncertain. CDC subject matter experts reviewed all initial frequent/continuous and sporadic/uncertain categorizations and the previously uncategorized areas. From this review, most categorizations stayed the same; however, 11 categorizations changed from the initial determinations. CONCLUSIONS: These new risk classifications enable detailed consideration of dengue risk, with clearer meaning and a direct link to the evidence that supports the specific classification. Since many infectious diseases have dynamic risk, strong geographical heterogeneities and varying data quality and availability, using this approach for other diseases can improve the accuracy, clarity and transparency of risk communication. Published by Oxford University Press 2016. This work is written by US Government employees and is in the public domain in the US.
BACKGROUND: International travel can expose travellers to pathogens not commonly found in their countries of residence, like dengue virus. Travellers and the clinicians who advise and treat them have unique needs for understanding the geographic extent of risk for dengue. Specifically, they should assess the need for prevention measures before travel and ensure appropriate treatment of illness post-travel. Previous dengue-risk maps published in the Centers for Disease Control and Prevention's Yellow Book lacked specificity, as there was a binary (risk, no risk) classification. We developed a process to compile evidence, evaluate it and apply more informative risk classifications. METHODS: We collected more than 839 observations from official reports, ProMED reports and published scientific research for the period 2005-2014. We classified each location as frequent/continuous risk if there was evidence of more than 10 dengue cases in at least three of the previous 10 years. For locations that did not fit this criterion, we classified locations as sporadic/uncertain risk if the location had evidence of at least one locally acquired dengue case during the last 10 years. We used expert opinion in limited instances to augment available data in areas where data were sparse. RESULTS: Initial categorizations classified 134 areas as frequent/continuous and 140 areas as sporadic/uncertain. CDC subject matter experts reviewed all initial frequent/continuous and sporadic/uncertain categorizations and the previously uncategorized areas. From this review, most categorizations stayed the same; however, 11 categorizations changed from the initial determinations. CONCLUSIONS: These new risk classifications enable detailed consideration of dengue risk, with clearer meaning and a direct link to the evidence that supports the specific classification. Since many infectious diseases have dynamic risk, strong geographical heterogeneities and varying data quality and availability, using this approach for other diseases can improve the accuracy, clarity and transparency of risk communication. Published by Oxford University Press 2016. This work is written by US Government employees and is in the public domain in the US.
Authors: Jason M Blaylock; Ashley Maranich; Kristen Bauer; Nancy Nyakoe; John Waitumbi; Luis J Martinez; Julia Lynch Journal: Travel Med Infect Dis Date: 2011-07-20 Impact factor: 6.211
Authors: Esther M Ellis; John C Neatherlin; Mark Delorey; Melvin Ochieng; Abdinoor Haji Mohamed; Daniel Ondari Mogeni; Elizabeth Hunsperger; Shem Patta; Stella Gikunju; Lilian Waiboic; Barry Fields; Victor Ofula; Samson Limbaso Konongoi; Brenda Torres-Velasquez; Nina Marano; Rosemary Sang; Harold S Margolis; Joel M Montgomery; Kay M Tomashek Journal: PLoS Negl Trop Dis Date: 2015-04-29
Authors: Thomas Jaenisch; Thomas Junghanss; Bridget Wills; Oliver J Brady; Isabella Eckerle; Andrew Farlow; Simon I Hay; Philip J McCall; Jane P Messina; Victor Ofula; Amadou A Sall; Anavaj Sakuntabhai; Raman Velayudhan; G R William Wint; Herve Zeller; Harold S Margolis; Osman Sankoh Journal: Emerg Infect Dis Date: 2014-10 Impact factor: 6.883
Authors: Tyler M Sharp; Linda Gaul; Atis Muehlenbachs; Elizabeth Hunsperger; Julu Bhatnagar; Rebekka Lueptow; Gilberto A Santiago; Jorge L Muñoz-Jordan; Dianna M Blau; Paul Ettestad; Jack D Bissett; Suzanne C Ledet; Sherif R Zaki; Kay M Tomashek Journal: MMWR Morb Mortal Wkly Rep Date: 2014-01-24 Impact factor: 17.586
Authors: Oliver J Brady; Peter W Gething; Samir Bhatt; Jane P Messina; John S Brownstein; Anne G Hoen; Catherine L Moyes; Andrew W Farlow; Thomas W Scott; Simon I Hay Journal: PLoS Negl Trop Dis Date: 2012-08-07
Authors: Samir Bhatt; Peter W Gething; Oliver J Brady; Jane P Messina; Andrew W Farlow; Catherine L Moyes; John M Drake; John S Brownstein; Anne G Hoen; Osman Sankoh; Monica F Myers; Dylan B George; Thomas Jaenisch; G R William Wint; Cameron P Simmons; Thomas W Scott; Jeremy J Farrar; Simon I Hay Journal: Nature Date: 2013-04-07 Impact factor: 49.962
Authors: Yesim Tozan; Tyler Y Headley; Maquines Odhiambo Sewe; Eli Schwartz; Tamar Shemesh; Jakob P Cramer; Kirsten A Eberhardt; Michael Ramharter; Nicole Harrison; Karin Leder; Andrea Angheben; Christoph Hatz; Andreas Neumayr; Lin Hwei Chen; Cornelis A De Pijper; Martin P Grobusch; Annelies Wilder-Smith Journal: Am J Trop Med Hyg Date: 2019-06 Impact factor: 2.345
Authors: Shengjie Lai; Michael A Johansson; Wenwu Yin; Nicola A Wardrop; Willem G van Panhuis; Amy Wesolowski; Moritz U G Kraemer; Isaac I Bogoch; Dylain Kain; Aidan Findlater; Marc Choisy; Zhuojie Huang; Di Mu; Yu Li; Yangni He; Qiulan Chen; Juan Yang; Kamran Khan; Andrew J Tatem; Hongjie Yu Journal: PLoS Negl Trop Dis Date: 2018-11-09
Authors: Sri Masyeni; Benediktus Yohan; I Ketut Agus Somia; Khin S A Myint; R Tedjo Sasmono Journal: J Travel Med Date: 2018-08-01 Impact factor: 8.490
Authors: Uma Sangumathi Kamaraj; Jun Hao Tan; Ong Xin Mei; Louise Pan; Tanu Chawla; Anna Uehara; Lin-Fa Wang; Eng Eong Ooi; Duane J Gubler; Hasitha Tissera; Lee Ching Ng; Annelies Wilder-Smith; Paola Florez de Sessions; Timothy Barkham; Danielle E Anderson; October Michael Sessions Journal: PLoS Negl Trop Dis Date: 2019-04-25
Authors: Emma J Quinn; Allena H-C Cheong; Julie K Calvert; Geoffrey Higgins; Trish Hahesy; David L Gordon; Jillian M Carr Journal: Trop Med Infect Dis Date: 2018-01-07