Joseph A. Lewnard, MPhil; Gregg Gonsalves, MPhil; Albert I. Ko, MD
Disclosures: Authors have disclosed no conflicts of interest. Forms can be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M16-1628.
Requests for Single Reprints: Joseph A. Lewnard, MPhil, Yale School of Public Health, 60 College Street, Suite 710, New Haven, CT 06520; e-mail, firstname.lastname@example.org.
Current Author Addresses: Mr. Lewnard and Dr. Ko: Yale School of Public Health, 60 College Street, Suite 710, New Haven, CT 06520.
Mr. Gonsalves: Yale Global Health Justice Partnership, PO Box 208215, New Haven, CT 06520
Author Contributions: Conception and design: J.A. Lewnard, G. Gonsalves, A.I. Ko.
Analysis and interpretation of the data: J.A. Lewnard, A.I. Ko.
Drafting of the article: J.A. Lewnard, G. Gonsalves, A.I. Ko.
Critical revision for important intellectual content: G. Gonsalves, A.I. Ko.
Final approval of the article: J.A. Lewnard, G. Gonsalves, A.I. Ko.
Statistical expertise: J.A. Lewnard.
Obtaining of funding: A.I. Ko.
Collection and assembly of data: J.A. Lewnard.
Lewnard JA, Gonsalves G, Ko AI. Low Risk of International Zika Virus Spread due to the 2016 Olympics in Brazil. Ann Intern Med. 2016;165:286-287. doi: 10.7326/M16-1628
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Published: Ann Intern Med. 2016;165(4):286-287.
Published at www.annals.org on 25 July 2016
Factors affecting travel-associated risk for ZIKV infection and spread.
Probability for infection based on the incidence rate (λ) in Rio de Janeiro state, calculated by dividing the total ZIKV infections (15 918 to 143 985 for lower and upper bounds, respectively, accounting for suspected underreporting and a 4:1 ratio of asymptomatic and symptomatic cases) in 2015 by the at-risk population (16.47 million ) and adjusting for the relative transmission intensity in August based on the seasonal dynamics of dengue (13.3 per 100 000 per month, compared with an annual average of 31.7 per 100 000 per month) (5). The formula 1 − e−λ(16/365) provides the estimated probability of an individual becoming infected over 16 days (median duration of international trips to Brazil for 2014 FIFA World Cup travelers) (9). Lower and upper bounds for total infections are each taken to follow Binom (n = Total travelers, p). The probability of an individual becoming infected and departing before clearing the infection is calculated by integrating the function f(t|λ)[1 − F(16 − t|λ)] for t in 0 to 16 days, assuming exponentially distributed interevent times with mass distribution f. Assuming 1-day transit time, the number remaining infected upon arrival is scaled by 1 − F(1|λ). The numbers departing and arriving before viral clearance are each binomially distributed. Excess visitors from each country during the 2014 FIFA World Cup were calculated via the difference in entries to Brazil during the months of June and July 2014 relative to the same months in 2013 (8). Numbered references in the figure apply to citations in the main text. FIFA = Fédération Internationale de Football Association; ZIKV = Zika virus infection.
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