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Review
. 2016 Aug 12;353(6300):aaf8160.
doi: 10.1126/science.aaf8160. Epub 2016 Jul 14.

Assessing the global threat from Zika virus

Justin Lessler  1 , Lelia H Chaisson  2 , Lauren M Kucirka  3 , Qifang Bi  2 , Kyra Grantz  4 , Henrik Salje  5 , Andrea C Carcelen  6 , Cassandra T Ott  2 , Jeanne S Sheffield  7 , Neil M Ferguson  8 , Derek A T Cummings  4 , C Jessica E Metcalf  9 , Isabel Rodriguez-Barraquer  2
Affiliations
Review

Assessing the global threat from Zika virus

Justin Lessler et al. Science. .

Abstract

First discovered in 1947, Zika virus (ZIKV) infection remained a little-known tropical disease until 2015, when its apparent association with a considerable increase in the incidence of microcephaly in Brazil raised alarms worldwide. There is limited information on the key factors that determine the extent of the global threat from ZIKV infection and resulting complications. Here, we review what is known about the epidemiology, natural history, and public health effects of ZIKV infection, the empirical basis for this knowledge, and the critical knowledge gaps that need to be filled.

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Figures

Fig. 1
Fig. 1. Factors determining the global risk from ZIKV
(A) As long as ZIKV circulates anywhere, periodic introductions into ZIKV free regions will occur. Whether these lead to an epidemic depends on the reproductive number, R, a measure of transmission efficiency determined by local ecology and population susceptibility to ZIKV. (B) When R>1, introductions can result in significant epidemics, after which the virus may go locally extinct or become endemic. (C) ZIKV could be maintained endemically either in local non-human primates (the sylvatic cycle) or through ongoing human transmission. (D) Most ZIKV infections (75–80%) are asymptomatic, and those with symptoms are likely at highest risk for rare neurological complications (6, 63, 92), particularly Guillain-Barré (45). Adverse fetal outcomes, notably microcephaly, may also be more common when the mother is symptomatic. Owing to its association with pregnancy, ZIKV’s health impact depends on the fertility rate and the age distribution of infections. The age distribution mirrors the general population in ZIKV free (A) and epidemic (B) settings, but is a function of the force of infection in endemic settings (C) (4, 45). Appropriate control measures can reduce R, decreasing the probability of successful ZIKV invasion (A) and its subsequent impact (B–C) (see 116).
Fig. 2
Fig. 2. Current and potential distribution of ZIKV
(A) Spread of ZIKV across the globe to date. Countries are colored by the timing of the first indication of local ZIKV transmission by serologic evidence or confirmation of human cases. Solid shading indicates clusters of confirmed cases or seropositivity to ZIKV of >10% in some sub-population, while hatched colors indicate 5–10% seropositivity (serosurveys showing <5% seropositivity are not shown). Symbols indicate locations and timings of viral isolations from mosquitoes (triangles) and humans (circles). (B). Map of the global occurrence of the widely distributed ZIKV vectors Aedes aegypti and Aedes albopictus. Adapted from (100, 116). (C) Map of the occurrence of dengue, a closely related Aedes transmitted flavivirus. Adapted from (103). Shaded regions correspond to areas with predicted probability of vector or dengue occurrence of >30%. * - Somalia did not report the total percent ZIKV seropositive, but there were a small percentage of subjects seropositive to ZIKV and no other flavivirus, and a large percentage seropositive to two or more flaviviruses, so is included.
Fig. 3
Fig. 3. Schematic of the course of human and mosquito infection
Symptoms develop on average 6 days (95% range 3–11 days) after ZIKV infection (64). Approximately 9 days (95% range 4–14 days) after infection, antibodies start increasing: the first antibodies detectable will be IgM, which will later decline as IgG antibodies increase then persist indefinitely (note the timing of IgM/IgG switch is for illustrative purposes only and not meant to indicate actual length of IgM persistence). Viremia likely starts to increase before symptoms appear, and the magnitude and length of viremia will shape the risk of infection of susceptible mosquitoes that bite this host. After an incubation period, this infected mosquito will be able to transmit infection to susceptible humans (19). The interval from the initial to the subsequent human infection is the generation time of ZIKV, Tg (for estimates, see 116)).
Fig. 4
Fig. 4. Age stratified serosurveys provide important clues to local ZIKV epidemiology
Results must be interpreted with caution bacuse of the possibility of cross-reactivity with other flavivirus antibodies. (A–C) Ongoing ZIKV transmission, whether from endemic human transmission or a constant risk of zoonotic infection, manifests as a smooth increase in the proportion of the population seropositive with increasing age. This pattern is also consistent with frequent reintroductions leading to periodic outbreaks. If we assume that the risk of ZIKV infection is constant over a lifetime, we can estimate the force of infection (FOI): the proportion of the susceptible population infected each year. Serosurvey results consistent with ongoing transmission include: (A) Uburu, Nigeria, 1952 (13), (B) Central African Republic, 1979 (pink=female, red=male) (118), and (C) Malaysia, 1953–54 (16). Blue dashed lines and text represent the expected trajectory from the estimated FOI. (D–E) In areas without significant ZIKV transmission there will be very low levels of seropositivity across age groups, and no clear age pattern. Some individuals may still be seropositive due to cross-reactivity in serological assays, infection of travelers, and limited imported cases. Examples include (D) Central Nyanza, Kenya, 1966–1968 (121) and (E) Mid-Western Region, Nigeria, 1966–1967 (120). (F) Significant shifts in seropositivity between age groups inconsistent with ongoing transmission suggest past epidemics, e.g., results from a 1966–1968 serosurvey in the Malindi district of Kenya are consistent with one or more epidemics of ZIKV occurring 15–30 years prior (121). Similar patterns could also occur due to differences in infection risk by age or a sharp reduction in transmission intensity at some point in the past.
Fig. 5
Fig. 5. ZIKV Phylogenetics
(A) Maximum likelihood tree of phylogenetic relationships between 43 flaviviruses (numbers indicate support from 1,000 ultrafast bootstrap replicates), with antigenic clusters from Calisher et al. indicated by color (162). (B) The phylogenetic relationship between ZIKV strains isolated from throughout the globe. Whole-genome nucleotide sequences were aligned using Clustal Omega (163) and trees were constructed using IQ-TREE (164) under a GTRM+G+I evolutionary model.
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