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Original Research |

Mitigating Prenatal Zika Virus Infection in the AmericasMitigating Prenatal Zika Virus Infection in the Americas FREE ONLINE FIRST

Martial L. Ndeffo-Mbah, PhD; Alyssa S. Parpia, MPH; and Alison P. Galvani, PhD
[+] Article, Author, and Disclosure Information

This article was published at www.annals.org on 26 July 2016.


From Yale School of Public Health and Yale University, New Haven, Connecticut.

Acknowledgment: The authors thank the 3 peer reviewers for their constructive comments and suggestions.

Grant Support: By the National Institutes of Health (grants U01 GM087719 and U01 GM105627).

Disclosures: Authors have disclosed no conflicts of interest. Forms can be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M16-0919.

Editors' Disclosures: Christine Laine, MD, MPH, Editor in Chief, reports that she has no financial relationships or interests to disclose. Darren B. Taichman, MD, PhD, Executive Deputy Editor, reports that he has no financial relationships or interests to disclose. Cynthia D. Mulrow, MD, MSc, Senior Deputy Editor, reports that she has no relationships or interests to disclose. Deborah Cotton, MD, MPH, Deputy Editor, reports that she has no financial relationships or interest to disclose. Jaya K. Rao, MD, MHS, Deputy Editor, reports that she has stock holdings/options in Eli Lilly and Pfizer. Sankey V. Williams, MD, Deputy Editor, reports that he has no financial relationships or interests to disclose. Catharine B. Stack, PhD, MS, Deputy Editor for Statistics, reports that she has stock holdings in Pfizer and Johnson & Johnson.

Reproducible Research Statement:Study protocol and data set: Not available. Statistical code: Available at https://github.com/mln27/ZikaCodes/Pregnancy_delay_Code.

Requests for Single Reprints: Martial L. Ndeffo-Mbah, PhD, Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, 135 College Street, Suite 200, New Haven, CT 06510; e-mail, Martial.Ndeffo-Mbah@yale.edu.

Current Author Addresses: Drs. Ndeffo-Mbah and Galvani and Ms. Parpia: Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, 135 College Street, Suite 200, New Haven, CT 06510.

Author Contributions: Conception and design: M.L. Ndeffo-Mbah.

Analysis and interpretation of the data: M.L. Ndeffo-Mbah.

Drafting of the article: M.L. Ndeffo-Mbah, A.S. Parpia.

Critical revision of the article for important intellectual content: M.L. Ndeffo-Mbah, A.P. Galvani.

Final approval of the article: M.L. Ndeffo-Mbah, A.S. Parpia, A.P. Galvani.

Statistical expertise: M.L. Ndeffo-Mbah.

Obtaining of funding: M.L. Ndeffo-Mbah, A.P. Galvani.

Administrative, technical, or logistic support: A.S. Parpia, A.P. Galvani.

Collection and assembly of data: M.L. Ndeffo-Mbah, A.S. Parpia.


Ann Intern Med. Published online 26 July 2016 doi:10.7326/M16-0919
© 2016 American College of Physicians
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Background: Because of the risk for Zika virus infection in the Americas and the links between infection and microcephaly, other serious neurologic conditions, and fetal death, health ministries across the region have advised women to delay pregnancy. However, the effectiveness of this policy in reducing prenatal Zika virus infection has yet to be quantified.

Objective: To evaluate the effectiveness of pregnancy-delay policies on the incidence and prevalence of prenatal Zika virus infection.

Design: Vector-borne Zika virus transmission model fitted to epidemiologic data from 2015 to 2016 on Zika virus infection in Colombia.

Setting: Colombia, August 2015 to July 2017.

Patients: Population of Colombia, stratified by sex, age, and pregnancy status.

Intervention: Recommendations to delay pregnancy by 3, 6, 9, 12, or 24 months, at different levels of adherence.

Measurements: Weekly and cumulative incidence of prenatal infections and microcephaly cases.

Results: With 50% adherence to recommendations to delay pregnancy by 9 to 24 months, the cumulative incidence of prenatal Zika virus infections is likely to decrease by 17% to 44%, whereas recommendations to delay pregnancy by 6 or fewer months are likely to increase prenatal infections by 2% to 7%. This paradoxical exacerbation of prenatal Zika virus exposure is due to an elevated risk for pregnancies to shift toward the peak of the outbreak.

Limitation: Sexual transmission was not explicitly accounted for in the model because of limited data but was implicitly subsumed within the overall transmission rate, which was calibrated to observed incidence.

Conclusion: Pregnancy delays can have a substantial effect on reducing cases of microcephaly but risks exacerbating the Zika virus outbreak if the duration is not sufficient. Duration of the delay, population adherence, and the timing of initiation of the intervention must be carefully considered.

Primary Funding Source: National Institutes of Health.


Human cases of infection with the Zika flavivirus were first detected in Uganda and the United Republic of Tanzania in 1952, with a case recorded in Nigeria 2 years later (1). The virus then spread into Asia, with widespread population exposure in Indonesia, Malaysia, and Pakistan from 1969 to 1983; Yap Island in the Federated States of Micronesia in 2007; French Polynesia from 2013 to 2014; and Brazil at the end of 2014, leading to the spread of Zika virus across the rest of Latin America in 2015 and 2016 (1). Zika virus has been isolated from various species of Aedes mosquitoes, including Aedes aegypti, which is the primary vector for the ongoing Zika virus outbreak across Latin America and the Caribbean (2). The potential for Zika virus transmission by A albopictus raises concern about the threat of dissemination of the virus beyond the habitat range of A aegypti (3).

Most Zika virus infections are asymptomatic (4). Symptomatic cases are predominantly mild, characterized by fever, headache, myalgia, maculopapular rash, joint pain, and conjunctivitis (4). Although Zika virus illnesses are generally self-limiting, the virus can cause serious birth defects, including microcephaly, and neurologic disease, such as Guillain–Barré syndrome (57). In addition to microcephaly, studies have shown fetal abnormalities among about 30% of infants born to women with confirmed Zika virus infection during pregnancy (8). These abnormalities can include in utero growth restriction, central nervous system malformations, complications of amniotic fluid volume and artery flow, and fetal death (810).

Studies have estimated more than a doubling of microcephaly cases in Brazil overall from the end of November 2015 to the beginning of February 2016, which has been linked to prenatal Zika virus infection (11). A surge in central nervous system malformations, including microcephaly, was also recorded during the 2013 Zika virus outbreak in French Polynesia (12). An elevated number of microcephaly cases has recently been observed in Colombia, to which Zika virus spread in September 2015 (13).

Health ministries across Latin America and the Caribbean have advised women to postpone pregnancy, with recommended delays of 6 to 8 months in Colombia, 1 year in Jamaica, and 2 years in El Salvador (14). Health authorities in Brazil and Ecuador have made similar recommendations without specifying the duration (14). However, these recommendations have not been met by concerted action from governments to facilitate adherence. Without wider availability of effective contraception options throughout Latin America and the Caribbean, people may resort to riskier birth control methods. Furthermore, 56% of all pregnancies in Latin America are unplanned (15, 16), which may limit the extent to which policy recommendations can affect the timing of pregnancies throughout populations. In addition, a surge in pregnancies is likely to occur after the period of abstention. Consequently, the need is urgent to evaluate the implications of the extent and timing of pregnancy delay as an effective strategy to avert microcephaly and other fetal abnormalities caused by Zika virus infection.

In this study, we developed a data-driven Zika virus transmission model to evaluate the effectiveness of pregnancy-delay recommendations in reducing the incidence and prevalence of prenatal Zika virus infection in Colombia. We hypothesized that the effectiveness of mass pregnancy delays in reducing prenatal Zika virus infections depends on the duration of the delay, the population-level adherence to the policy recommendation, and the timing of initiation of the strategy relative to the peak incidence of infection within the community of interest.

In the absence of vaccines or treatments for Zika virus infection, and given the limited evidence on the effectiveness of vector control in curtailing the spread of A aegypti–borne diseases, such as dengue and chikungunya (17), public health authorities in many countries in the Americas affected by Zika virus have made recommendations to women and couples to postpone pregnancy (14). When durations have been specified, recommended delays have ranged from 6 months to 2 years. We developed a data-driven Zika virus transmission model to evaluate the effect of a mass pregnancy-delay strategy in which women of reproductive age avoid pregnancy for the recommended duration, at varying degrees of adherence.

Mathematical Model

We developed a disease transmission model for the spread of Zika virus in Colombia that included both human and mosquito population dynamics. We stratified the modeled human population by sex (male or female), age (prereproductive, reproductive, or postreproductive), and pregnancy status (nonpregnant or pregnant). We also distinguished between early and later stages of pregnancy to evaluate the conservative assumption in our base case that only women infected during their first trimester are at risk for giving birth to a child with Zika-induced microcephaly (18). In scenario analyses, we also considered the possibility that Zika virus may cause microcephaly at any point during pregnancy. The model parameters were quantified with entomologic data specific to A aegypti, demographic data specific to Colombia, and epidemiologic data specific to Zika virus and dengue (Table).

Table Jump PlaceholderTable. Epidemiologic Parameters and Distributions 

To simulate Zika virus transmission, the mosquito population was subdivided into 3 epidemiologic classes: susceptible (SV), exposed (EV), and infected (IV). Susceptible mosquitoes became exposed (entering the class OE) at a rate that depended on the human force of infection (λH), and exposed mosquitoes became infected at a rate that depended on the extrinsic incubation period (τV). Mosquito population dynamics incorporated seasonality through the mosquito birth rate (39). We defined the force of infection as a function of the biting rate of mosquitoes (c), the proportion of persons with infection (either symptomatic [IHS] or asymptomatic [IHA]), and their respective probabilities of infecting a mosquito (βh[IHS + IHA]/NH, where NH was the size of the human population). Thus, λH = c βh(IHS + IHA)/NH.

The human population was subdivided into 5 epidemiologic classes: susceptible (SH), exposed (EH), symptomatic infected (IHS), asymptomatic infected (IHA), and recovered (RH). Susceptible persons became exposed at a rate of λO, which depended on the biting rate of mosquitoes, the proportion of infected mosquitoes and their infectivity (βVIV/NV, where NV was the total number of adult mosquitoes), and the density ratio of mosquitoes to people (NV/NH). Thus, λO = c βVIV/NH. Exposed persons became infected at a rate of α, with a proportion (r) transitioning into the symptomatic class (IHS) and a proportion (1 − r) transitioning into the asymptomatic class (IHA). Infectious persons recovered at a rate of γ into the RH class. We assumed lifelong immunity after infection, consistent with closely related flaviviruses, such as those for dengue (40) and yellow fever (41), and consistent with the persistence of neutralizing Zika virus antibodies observed in previously infected persons (37). Further description of the model equations can be found in the Supplement.

Model Fitting

We used a Bayesian melding approach (42) to fit our model to epidemiologic data on weekly suspected and confirmed symptomatic cases of Zika virus infection in Colombia from 11 October 2015 to 31 March 2016 (43) while also accounting for the large proportion of unreported asymptomatic cases typical of Zika virus infection (4). The Bayesian melding approach combined prior information about model input parameters (Table) with data on incidence of Zika virus infection. We implemented a sample-importance-resample algorithm to identify the input parameter values that generated epidemic curves that most closely matched the data on Zika virus infection. Specifically, we ran 200 000 model simulations, sampling randomly from the prior distributions of input parameters in each simulation. Throughout the sampling process, we weighted each simulation according to its likelihood-based compatibility with the data. We then resampled (with replacement) from the simulations, with the probability of selection proportional to the weight of the simulation. Under this approach, the simulation resampled most frequently (the mode) is considered the best-fitting simulation. The 2.5th and 97.5th percentiles were used to obtain 95% credible intervals (CrIs) for model parameters and output. The 95% CrI is the interval within which the values of the input and output parameters of the model lie with a 95% probability, given the epidemiologic data. After fitting, we validated our model projections against weekly case data from 1 April to 8 May 2016. Further details of the model fitting process can be found in the Supplement.

To compute the value of the basic reproductive number (R0), which is the average number of secondary human infections generated throughout the entire infectious period of a single human (44, 45), we applied the next-generation matrix method (a computational method used to derive R0 from transmission dynamics models) to our fitted model (44, 45).

Data Sources

Cases reported by the National Institute of Health of Colombia from 11 October 2015 to 8 May 2016 were used to fit our Zika virus transmission model (43). These reported cases constitute weekly nationwide suspected and laboratory-confirmed cases of Zika virus infection.

Suspected cases were defined as persons presenting at a hospital or clinic with rash, fever (temperature >37.2 °C), and at least 1 of the following symptoms within 5 days of symptom onset that could not be explained by other medical conditions: nonpurulent conjunctivitis or conjunctival hyperemia, arthralgia, myalgia, headache, or malaise. In addition, they had to have been in a place at less than 2200 m elevation with autochthonous Zika virus transmission within the 15 days before symptom onset. Laboratory-confirmed cases were suspected cases who had positive results for Zika virus on reverse transcriptase polymerase chain reaction testing.

Statistical Analysis

In addition to mass pregnancy delays, we considered an individual-based, pregnancy-delay strategy, in which women of reproductive age independently decide to postpone pregnancy. In this scenario, the decision to delay pregnancy was made continuously over time rather than at a specific point of time with all other women who decided to delay pregnancy, as with the mass strategy. We evaluated the effect of pregnancy delay on reducing prenatal exposure to Zika virus, as well as the marginal effects of individual decisions to delay pregnancy longer than recommended by health policy.

We conducted a 1-way sensitivity analysis to evaluate the effect of model parameters on the timing of peak incidence of Zika virus infection and the number of cumulative microcephaly cases (to evaluate the effectiveness of mass pregnancy-delay strategies). To assess interactions between pregnancy delay and vector-control measures, we considered varying reductions in rates of mosquito death and biting.

We considered an alternative model structure with the assumption that asymptomatic persons did not contribute to disease transmission. We evaluated the effect of this assumption on R0 and our projections of prenatal Zika virus infections and microcephaly cases with and without pregnancy delay.

To identify the contribution of each model parameter to the variability of the outcome measure, we calculated the partial rank correlation coefficients (PRCCs) between input and output variables (46). A positive PRCC is when an increase in an input variable results in an increase in the output variable; a negative PRCC is when an increase in an input variable results in a decrease in the output variable. In addition, the magnitude of the PRCC is a measure of the contribution of an input variable to the uncertainty of an output variable. All analyses were performed using MATLAB R2015b (MathWorks). The code is available at https://github.com/mln27/ZikaCodes/Pregnancy-delay_Code.

Role of the Funding Source

The study was funded by the National Institutes of Health, which had no role in the study design; collection, analysis, or interpretation of the data; writing of the report; or the decision to submit the manuscript for publication.

Model Calibration

Using prior distributions of parameters based on epidemiologic and clinical studies, we derived a posterior distribution for each epidemiologic parameter (Table) for which the model yielded the best estimate of the trajectory of reported cases of Zika virus infection (Figure 1). We validated the weekly incidence of symptomatic cases projected by our model against weekly reported cases in Colombia from 1 April to 8 May 2016. The proportion of cumulative cases of Zika virus infection that occurred among women was estimated by our model to be 65.0% (95% CrI, 62% to 69%) compared with the empirical estimate of 63.6% (47), and the proportion of cumulative cases that occurred among adults of reproductive age was estimated to be 64.7% (CrI, 59% to 67%) versus the empirical estimate of 62.8% (47). Our model projections show that Zika virus infection may become endemic in Colombia by mid-2017 (Figure 1).

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Figure 1.

Trajectories of the model fitted to data from the October 2015 to March 2016 Zika virus outbreak in Colombia (solid circles).

Model projections were validated against data from April to May 2016 (solid squares). The solid line represents the mode of the posterior sample, the dotted line represents the mean, and the shaded area indicates the 95% credible interval. Fitting was done under the assumption that both symptomatic and asymptomatic cases are infectious.

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Model Projections and Intervention Effectiveness

We calculated the basic reproductive ratio (R0) of the ongoing Zika virus epidemic in Colombia to be 1.25 (CrI, 0.6 to 2.05). We used the fitted model to estimate the number of cases of Zika virus infection and prenatal infections, both symptomatic and asymptomatic, that would occur by the end of 2016 if the epidemic were to continue unabated. We projected that the outbreak will result in a total of 1.18 (CrI, 0.50 to 2.07) million cases and 11 768 (CrI, 6907 to 22 300) prenatal infections during the first trimester of pregnancy among currently affected communities. Applying the risk for microcephaly associated with Zika virus infection during the first trimester from the French Polynesia outbreak (48), we estimated that 112 (CrI, 50 to 446) microcephaly cases will occur in Colombia from prenatal infection in 2016 from both symptomatic and asymptomatic cases. Alternatively, if the risk for microcephaly is associated with infection at any time during pregnancy, the estimate of prenatal infections increases to 29 230 (CrI, 17 760 to 56 500) in 2016, leading to 278 (CrI, 126 to 860) microcephaly cases. These estimates are probably conservative given that the rate of microcephaly seems to have been much lower in the French Polynesia outbreak than in the ongoing outbreak in the Americas (8, 48, 49).

We evaluated the effect of mass pregnancy-delay strategies ranging from 3 to 24 months for mitigating prenatal Zika virus infection from the onset of the outbreak until June 2017. We found that if the delay was initiated 1 week after the onset of the epidemic, delays of 6 months or less were likely to increase prenatal exposure and the prevalence of microcephaly cases compared with no delay (Figure 2). Moreover, the effectiveness of these short-duration strategies was shown to decrease with increasing adherence (Figure 3, top). This paradoxical exacerbation arises because the surge in pregnancies after the period of abstinence would occur near the incidence peak of the epidemic (Figure 2).

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Figure 2.

Temporal effect of 3- to 24-mo mass delays in pregnancy (with 50% adherence) on weekly prenatal Zika virus infections (top) and cumulative microcephaly cases (bottom).

Curves for 6-, 9-, and 12-mo delays are superimposable on the 24-mo curve up to where each line veers off.

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Figure 3.

Effect of delays in pregnancy on cumulative incidence of prenatal Zika virus infection until July 2017 for delays of 3 to 24 mo and adherence of 25% to 75%.

Bars represent mean values, and error bars represent 95% credible intervals. Top. Reduction in cumulative incidence with mass strategy. Middle. Reduction in cumulative incidence with individual-based strategy. Bottom. Incremental increase in incidence reduction for individual decisions to delay pregnancy beyond a 6-mo mass delay.

Grahic Jump Location

We compared the effectiveness of mass strategies versus individual-based strategies, where women independently choose to postpone pregnancy. For delays of 9 months or longer, mass strategies were more effective than individual-based strategies at reducing prenatal infections (Figure 3). Mass strategies were less effective than individual-based strategies for delays of 6 months or less (Figure 3). With 50% adherence to 3- to 6-month pregnancy-delay recommendations, the incidence of prenatal exposure was projected to increase by 2.1% (CrI, −4.6% to 2.1%) to 7.6% (CrI, −5.6% to 8.7%) for mass strategies and, conversely, to decrease by 7.5% (CrI, 3.0% to 8.2%) to 8.9% (CrI, 3.2% to 10.1%) for individual-based strategies (Figure 3, middle). For delays of 9 to 24 months, mass strategies decreased prenatal incidence by 16.8% (CrI, 1.9% to 35.5%) to 43.8% (CrI, 40.3% to 47.2%), and individual-based strategies reduced incidence by 9.5% (CrI, 2.3% to 10.9%) to 10.3% (CrI, 3.3% to 12.1%) (Figure 3, middle). We evaluated the marginal benefit of individual decisions to delay pregnancy beyond the recommended duration for a mass strategy. For a 6-month mass strategy, an extended individual delay was predicted to result in an incremental reduction in prenatal infections of 10.4% (CrI, 6.9% to 16.9%) to 21.4% (CrI, 10.8% to 27.8%), depending on the adherence to and duration of the individual delay (Figure 3, bottom).

We evaluated the effect of the timing of initiation of a delay in pregnancy on the effectiveness of mass strategies. We found that the optimal timing for initiation of a recommended delay depended on its duration (Figure 4). A 6-month delay was most effective when it was initiated 4 months into the outbreak, whereas the optimal timing of initiation of a 9-month delay was 2 months into the outbreak (Figure 4). However, regardless of the stage of the epidemic at which the delay was initiated, a delay of more than 6 months was shown to be more effective in reducing prenatal exposure than a shorter delay (Figure 4).

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Figure 4.

Effect of mass pregnancy-delay strategy, with adherence of 50%, on prevalence of prenatal Zika virus infection when pregnancy delay was implemented at different points in the outbreak.

2M = 2 mo after onset of epidemic; 4M = 4 mo after onset of epidemic; 6M = 6 mo after onset of epidemic; P = epidemic peak; S = 1 wk after onset of epidemic.

Grahic Jump Location
Scenario and Global Sensitivity Analyses

Our 1-way sensitivity analysis indicated that the A aegypti biting rate on humans, the relative risk for exposure to Zika virus in women of reproductive age, and the vector density–dependent mosquito-to-human transmission rate had the greatest effect on the time to peak incidence from the onset of the outbreak and the number of microcephaly cases (Supplement Figure 3). Specifically, we showed that the time to peak incidence increased and the number of microcephaly cases decreased as these parameters decreased (Supplement Figure 3). These relationships imply that vector-control measures that reduce A aegypti density or contacts with women of reproductive age not only could reduce microcephaly incidence but may also postpone the timing to the incidence peak of the epidemic.

To evaluate the effect of the infectiousness of asymptomatic cases on our model projections, we considered an alternative model structure with the assumption that only symptomatic cases were infectious (Table and Supplement Figure 4). Under this assumption, we estimated R0 in Colombia to be 3.27 (CrI, 2.15 to 5.47) and estimated that the outbreak would result in a total of 1.04 (CrI, 0.60 to 2.45) million cases and 11 777 (CrI, 7424 to 23 375) prenatal infections during the first trimester of pregnancy by July 2017. The proportion of cumulative cases of Zika virus infection that occurred among women was estimated to be 68.2% (CrI, 62% to 69%), and the proportion of cumulative cases that occurred among men or women of reproductive age was estimated to be 66.1% (CrI, 59% to 67%). Results of interventions (not shown) were similar to the base-case scenario for which asymptomatic and symptomatic cases were assumed to be equally infectious.

The global sensitivity analysis showed that the period of human infectiousness, A aegypti lifespan, and relatively elevated risk for Zika virus infection in women of reproductive age had an appreciable effect on the number of prenatal infections in the 2 transmission scenarios (Supplement Figure 5). When we assumed that only symptomatic cases were infectious, the proportion of such cases was shown to have a substantial effect on the number of prenatal infections (Supplement Figure 5).

We evaluated the effect of delaying pregnancy as an intervention strategy for mitigating prenatal Zika virus infections during an outbreak. Our results show that pregnancy-delay strategies are more effective at reducing prenatal exposure when the delay lasts more than 6 months and is initiated early in an outbreak. Because the incidence peak of the epidemic occurs around 8 months into the outbreak, a strategy to delay pregnancy by more than 9 months, initiated at the onset of the epidemic, would allow women of reproductive age to avoid being pregnant during the incidence peak, when risk for exposure to Zika virus is highest. A strategy to delay pregnancy by 6 months or less, initiated at the onset of the epidemic, is likely to exacerbate prenatal exposures due to the surge in pregnancies after the period of abstinence that may occur near the incidence peak of the epidemic. Consequently, the optimal duration of a delay in pregnancy depends on the stage at which an affected community is in the epidemic, which will determine the timing of the local incidence peak and the period of highest risk for exposure to Zika virus for pregnant women.

Cases of sexual transmission of Zika virus from infected men to female partners have been reported during outbreaks (50, 51), likely due to the presence of the virus in the semen of infected men (52). Because most cases of Zika virus infection are asymptomatic, pregnant women are at risk for contracting the virus from either infected A aegypti mosquitoes or infected partners. Given the limited data on sexual transmission, we did not explicitly account for it in our model. Nonetheless, fitting our model to incidence data did implicitly account for cases that arose from sexual transmission; therefore, this transmission route was effectively subsumed within our overall rate of transmission. We anticipate that explicitly accounting for sexual transmission could result in higher effectiveness in reducing prenatal infections for pregnancy delays longer than 6 months due to the apparent longer-term persistence of Zika virus in semen versus mosquitoes (53). As more data on the risk for sexual transmission of the virus become available, future studies should investigate its relative contribution to outbreaks.

The quantitative results of our study could be refined as more accurate data on laboratory-confirmed and validated suspected cases become available. Although the data we used for our analysis are the only publicly available epidemiologic data on Zika virus infection in Colombia, fewer than 10% of these reported cases are laboratory-confirmed, and symptoms among persons with suspected infection may also be attributable to other causes, such as dengue and chikungunya, which are cocirculating in Colombia (54). Moreover, many cases of Zika virus infection are probably not reported because of the high rate of mild and asymptomatic cases observed during previous outbreaks (4, 5). Therefore, more data are urgently needed to assess the magnitude of the ongoing outbreak in the Americas. However, data refinement is unlikely to affect the qualitative nature of our results with regard to the effectiveness of mass and individual-based pregnancy-delay strategies, which were shown to be robust to a wide range of parameter values through extensive uncertainty and sensitivity analyses.

Our analysis did not focus on the feasibility of a specific birth control method. Rather, we evaluated the impact of any effective pregnancy-delay strategy in reducing prenatal exposure to Zika virus in communities in the Americas that are at risk for an outbreak. Practical birth control measures that could be implemented for individual-based and mass pregnancy-delay strategies include condom use, oral contraceptives, intrauterine devices, contraceptive injections, and abstinence, although widespread implementation of these methods may be challenging due to the sociocultural composition of the affected countries and the high rate of unplanned pregnancies (15, 16). Sociologic studies are needed to evaluate the acceptability and feasibility of large-scale delays in pregnancy and the likely rate of adherence in different sociocultural settings. Ultimately, advocating for large-scale delays in pregnancy without providing effective birth control measures is of limited utility. Thus, pregnancy-delay guidelines should be provided in conjunction with widespread dissemination of effective contraceptive measures and education.

Overall, mass delays in pregnancy may be an effective strategy for mitigating the burden of prenatal Zika virus infection within affected communities and communities at imminent risk for outbreaks. However, a mass delay should be used as a reactive strategy rather than a preemptive one, particularly if adherence to the recommendation wanes before the epidemic peaks. Consideration of the demographic and socioeconomic repercussions of prolonged pregnancy delays on affected communities should also be considered. In our analysis, reported cases of Zika virus infection in Colombia were the sole source for estimates of the timing of the incidence peak of the epidemic. Additional epidemiologic data are urgently needed to better characterize the timing of peak incidence for a Zika virus outbreak in a given community.

Given the current Zika virus outbreak in Puerto Rico and the risk for dissemination of the virus to the Gulf Coast region of the continental United States, the Centers for Disease Control and Prevention has issued recommendations on the timing of pregnancy after exposure to Zika virus and the harms of unprotected sexual intercourse during pregnancy in areas of autochthonous transmission and with male partners who have or are at risk for infection (55). Our results indicate that in regions with risk for autochthonous transmission, a mass pregnancy delay of 9 months would probably be an effective strategy for mitigating Zika-induced microcephaly cases and would balance the risk for potential exacerbation of prenatal exposure that could arise from clustering of pregnancies around the peak of the epidemic. Individual decisions to delay pregnancy should account for the local incidence of Zika virus infection, which highlights the importance of surveillance, monitoring, and reporting by the Centers for Disease Control and Prevention.

Our results indicate that delays in pregnancy alone will probably be insufficient to curtail Zika-related birth abnormalities. In the absence of a vaccine or therapeutic drugs for Zika virus infection, a combination of mass and individual pregnancy-delay strategies with effective vector-control measures is needed to curtail the spread and burden of the ongoing outbreak in the Americas. Our analyses suggest that delaying pregnancy in response to Zika virus outbreaks has the potential to be an effective component of a multifaceted strategy for reducing the effect of potential Zika-induced severe birth defects.

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CrossRef
 
McNeil DG Jr. Delaying pregnancy until Zika moves on. The New York Times.. 9 February 2016; D1.
 
Sedgh G, Singh S, Hussain R. Intended and unintended pregnancies worldwide in 2012 and recent trends. Stud Fam Plann. 2014; 45:301-14.
PubMed
CrossRef
 
Schuck-Paim C, López D, Simonsen L, Alonso W.  Unintended pregnancies in Brazil—a challenge for the recommendation to delay pregnancy due to Zika. PLoS Curr Outbreaks. 16 March 2016. Accessed at http://dx.doi.org/10.1371/currents.outbreaks.7038a6813f734c1db547240c2a0ba291 on 19 April 2016.
 
Bowman LR, Donegan S, McCall PJ. Is dengue vector control deficient in effectiveness or evidence?: systematic review and meta-analysis. PLoS Negl Trop Dis. 2016; 10:e0004551.
PubMed
CrossRef
 
Kleber de Oliveira W, Cortez-Escalante J, De Oliveira WT, do Carmo GM, Henriques CM, Coelho GE, et al. Increase in reported prevalence of microcephaly in infants born to women living in areas with confirmed Zika virus transmission during the first trimester of pregnancy—Brazil, 2015. MMWR Morb Mortal Wkly Rep. 2016; 65:242-7.
PubMed
CrossRef
 
United Nations.  World Population Prospects: The 2015 Revision. Key Findings and Advance Tables. Working Paper no. ESA/P/WP.241. New York: United Nations; 2015. Accessed at https://esa.un.org/unpd/wpp/Publications/Files/Key_Findings_WPP_2015.pdf on 22 June 2016.
 
Stykes J.  Fatherhood in the US: men's age at first birth, 1987-2010. Report no. FP-11-04. Bowling Green, OH: National Center for Family and Marriage Research; 2011. Accessed at www.bgsu.edu/content/dam/BGSU/college-of-arts-and-sciences/NCFMR/documents/FP/FP-11-04.pdf on 22 June 2016.
 
Bongaarts J, Blanc AK. Estimating the current mean age of mothers at the birth of their first child from household surveys. Popul Health Metr. 2015; 13:25.
PubMed
CrossRef
 
Eskenazi B, Wyrobek AJ, Sloter E, Kidd SA, Moore L, Young S, et al. The association of age and semen quality in healthy men. Hum Reprod. 2003; 18:447-54.
PubMed
CrossRef
 
Castelo-Branco C, Blümel JE, Chedraui P, Calle A, Bocanera R, Depiano E, et al. Age at menopause in Latin America. Menopause. 2006; 13:706-12.
PubMed
CrossRef
 
Hallett TB, Gregson S, Mugurungi O, Gonese E, Garnett GP. Assessing evidence for behaviour change affecting the course of HIV epidemics: a new mathematical modelling approach and application to data from Zimbabwe. Epidemics. 2009; 1:108-17.
PubMed
CrossRef
 
Harrington LC, Françoisevermeylen,Jones JJ, Kitthawee S, Sithiprasasna R, Edman JD, et al. Age-dependent survival of the dengue vector Aedes aegypti (Diptera: Culicidae) demonstrated by simultaneous release-recapture of different age cohorts. J Med Entomol. 2008; 45:307-13.
PubMed
CrossRef
 
Styer LM, Carey JR, Wang JL, Scott TW. Mosquitoes do senesce: departure from the paradigm of constant mortality. Am J Trop Med Hyg. 2007; 76:111-7.
PubMed
 
Trpis M, Häusermann W, Craig GB Jr. Estimates of population size, dispersal, and longevity of domestic Aedes aegypti aegypti (Diptera: Culicidae) by mark-release-recapture in the village of Shauri Moyo in eastern Kenya. J Med Entomol. 1995; 32:27-33.
PubMed
CrossRef
 
Sheppard PM, Macdonald WW, Tonn RJ, Grab B. The dynamics of an adult population of Aedes aegypti in relation to dengue haemorrhagic fever in Bangkok. J Anim Ecol. 1969; 38:661-702.
CrossRef
 
Lardeux F, Cheffort J. Ambient temperature effects on the extrinsic incubation period of Wuchereria bancrofti in Aedes polynesiensis: implications for filariasis transmission dynamics and distribution in French Polynesia. Med Vet Entomol. 2001; 15:167-76.
PubMed
CrossRef
 
Li MI, Wong PS, Ng LC, Tan CH. Oral susceptibility of Singapore Aedes (Stegomyia) aegypti (Linnaeus) to Zika virus. PLoS Negl Trop Dis. 2012; 6:e1792.
PubMed
CrossRef
 
Andraud M, Hens N, Marais C, Beutels P. Dynamic epidemiological models for dengue transmission: a systematic review of structural approaches. PLoS One. 2012; 7:e49085.
PubMed
CrossRef
 
Scott TW, Amerasinghe PH, Morrison AC, Lorenz LH, Clark GG, Strickman D, et al. Longitudinal studies of Aedes aegypti (Diptera: Culicidae) in Thailand and Puerto Rico: blood feeding frequency. J Med Entomol. 2000; 37:89-101.
PubMed
CrossRef
 
Manore CA, Hickmann KS, Xu S, Wearing HJ, Hyman JM. Comparing dengue and chikungunya emergence and endemic transmission in A. aegypti and A. albopictus. J Theor Biol. 2014; 356:174-91.
PubMed
CrossRef
 
Majumder MS, Cohn E, Fish D, Brownstein JS.  Estimating a feasible serial interval range for Zika fever. Bull World Health Organ. 2016. Accessed at http://dx.doi.org/10.2471/BLT.16.171009 on 22 June 2016.
 
Lessler JT, Ott CT, Carcelen AC, Konikoff JM, Williamson J, Bi Q, et al.  Times to key events in the course of Zika infection and their implications: a systematic review and pooled analysis. Bull World Health Organ. 2016. Accessed at http://dx.doi.org/10.2471/BLT.16.174540 on 22 June 2016.
 
Mallet HP, Vial AL, Musso D.  Bilan de l'épidémie à virus zika en Polynésie Française, 2013-2014. Bulletin d'Information sanitaires, épidémiologiques et statistiques. 2015:1-5.
 
Fagbami AH. Zika virus infections in Nigeria: virological and seroepidemiological investigations in Oyo State. J Hyg (Lond). 1979; 83:213-9.
PubMed
CrossRef
 
Ioos S, Mallet HP, Leparc Goffart I, Gauthier V, Cardoso T, Herida M. Current Zika virus epidemiology and recent epidemics. Med Mal Infect. 2014; 44:302-7.
PubMed
CrossRef
 
Luz PM, Vanni T, Medlock J, Paltiel AD, Galvani AP. Dengue vector control strategies in an urban setting: an economic modelling assessment. Lancet. 2011; 377:1673-80.
PubMed
CrossRef
 
Gubler DJ. Dengue and dengue hemorrhagic fever. Clin Microbiol Rev. 1998; 11:480-96.
PubMed
 
Sawyer WA. The persistence of yellow fever immunity. Journal of Preventive Medicine. 1931; 5:413-28.
 
Poole D, Raftery AE. Inference for deterministic simulation models: the Bayesian melding approach. J Am Stat Assoc. 2000; 95:1244-55.
CrossRef
 
Pan American Health Organization; World Health Organization.  Suspected and confirmed Zika cases reported by countries and territories in the Americas, 2015-2016. 2016. Accessed at http://ais.paho.org/phip/viz/ed_zika_epicurve.asp on 26 May 2016.
 
van den Driessche P, Watmough J. Reproduction numbers and sub-threshold endemic equilibria for compartmental models of disease transmission. Math Biosci. 2002; 180:29-48.
PubMed
CrossRef
 
Pandey A, Atkins KE, Medlock J, Wenzel N, Townsend JP, Childs JE, et al. Strategies for containing Ebola in West Africa. Science. 2014; 346:991-5.
PubMed
CrossRef
 
Marino S, Hogue IB, Ray CJ, Kirschner DE. A methodology for performing global uncertainty and sensitivity analysis in systems biology. J Theor Biol. 2008; 254:178-96.
PubMed
CrossRef
 
Instituto Nacional de Salud.  Boletín Epidemiológico Semanal. Report no. 3. Bogotá, Colombia: Instituto Nacional de Salud; 2016. Accessed at www.ins.gov.co/boletin-epidemiologico/Boletn%20Epidemiolgico/2016%20Boletin%20epidemiologico%20semana%203.pdf on 22 June 2016.
 
Cauchemez S, Besnard M, Bompard P, Dub T, Guillemette-Artur P, Eyrolle-Guignot D, et al. Association between Zika virus and microcephaly in French Polynesia, 2013-15: a retrospective study. Lancet. 2016; 387:2125-32.
PubMed
CrossRef
 
Mlakar J, Korva M, Tul N, Popovic M, Poljšak-Prijatelj M, Mraz J, et al. Zika virus associated with microcephaly. N Engl J Med. 2016; 374:951-8.
PubMed
CrossRef
 
Musso D, Roche C, Robin E, Nhan T, Teissier A, Cao-Lormeau VM. Potential sexual transmission of Zika virus. Emerg Infect Dis. 2015; 21:359-61.
PubMed
CrossRef
 
Foy BD, Kobylinski KC, ChilsonFoy JL, Blitvich BJ, Travassos da Rosa A, Haddow AD, et al. Probable non–vector-borne transmission of Zika virus, Colorado, USA. Emerg Infect Dis. 2011; 17:880-2.
PubMed
CrossRef
 
Oster AM, Russell K, Stryker JE, Friedman A, Kachur RE, Petersen EE, et al. Update: interim guidance for prevention of sexual transmission of Zika virus—United States, 2016. MMWR Morb Mortal Wkly Rep. 2016; 65:323-5.
PubMed
CrossRef
 
Turmel JM, Abgueguen P, Hubert B, Vandamme YM, Maquart M, Le Guillou-Guillemette H, et al. Late sexual transmission of Zika virus related to persistence in the semen [Letter]. Lancet.. 2016.
PubMed
 
Rodriguez-Morales AJ, García-Loaiza CJ, Galindo-Marquez ML, Sabogal-Roman JA, Marin-Loaiza S, Lozada-Riascos CO, et al. Zika infection GIS-based mapping suggest high transmission activity in the border area of La Guajira, Colombia, a northeastern coast Caribbean department, 2015-2016: implications for public health, migration and travel [Letter]. Travel Med Infect Dis.. 2016; 14:286-8.
PubMed
CrossRef
 
Centers for Disease Control and Prevention.  Zika virus. Atlanta, GA: Centers for Disease Control and Prevention; 2016. Accessed at www.cdc.gov/zika/index.html on 10 June 2016.
 

Figures

Grahic Jump Location
Figure 1.

Trajectories of the model fitted to data from the October 2015 to March 2016 Zika virus outbreak in Colombia (solid circles).

Model projections were validated against data from April to May 2016 (solid squares). The solid line represents the mode of the posterior sample, the dotted line represents the mean, and the shaded area indicates the 95% credible interval. Fitting was done under the assumption that both symptomatic and asymptomatic cases are infectious.

Grahic Jump Location
Grahic Jump Location
Figure 2.

Temporal effect of 3- to 24-mo mass delays in pregnancy (with 50% adherence) on weekly prenatal Zika virus infections (top) and cumulative microcephaly cases (bottom).

Curves for 6-, 9-, and 12-mo delays are superimposable on the 24-mo curve up to where each line veers off.

Grahic Jump Location
Grahic Jump Location
Figure 3.

Effect of delays in pregnancy on cumulative incidence of prenatal Zika virus infection until July 2017 for delays of 3 to 24 mo and adherence of 25% to 75%.

Bars represent mean values, and error bars represent 95% credible intervals. Top. Reduction in cumulative incidence with mass strategy. Middle. Reduction in cumulative incidence with individual-based strategy. Bottom. Incremental increase in incidence reduction for individual decisions to delay pregnancy beyond a 6-mo mass delay.

Grahic Jump Location
Grahic Jump Location
Figure 4.

Effect of mass pregnancy-delay strategy, with adherence of 50%, on prevalence of prenatal Zika virus infection when pregnancy delay was implemented at different points in the outbreak.

2M = 2 mo after onset of epidemic; 4M = 4 mo after onset of epidemic; 6M = 6 mo after onset of epidemic; P = epidemic peak; S = 1 wk after onset of epidemic.

Grahic Jump Location

Tables

Table Jump PlaceholderTable. Epidemiologic Parameters and Distributions 

References

Kindhauser MK, Allen T, Frank V, Santhana RS, Dye C.  Zika: the origin and spread of a mosquito-borne virus. Bull World Health Organ. 2016. Accessed at http://dx.doi.org/10.2471/BLT.16.171082 on 22 June 2016.
 
Hayes EB. Zika virus outside Africa. Emerg Infect Dis. 2009; 15:1347-50.
PubMed
CrossRef
 
Marcondes CB, XimenesMde F. Zika virus in Brazil and the danger of infestation by Aedes (Stegomyia) mosquitoes. Rev Soc Bras Med Trop. 2016; 49:4-10.
PubMed
CrossRef
 
Duffy MR, Chen TH, Hancock WT, Powers AM, Kool JL, Lanciotti RS, et al. Zika virus outbreak on Yap Island, Federated States of Micronesia. N Engl J Med. 2009; 360:2536-43.
PubMed
CrossRef
 
Oehler E, Watrin L, Larre P, Leparc-Goffart I, Lastere S, Valour F, et al. Zika virus infection complicated by Guillain-Barre syndrome—case report, French Polynesia, December 2013. Euro Surveill.. 2014; 19.
PubMed
 
Cao-Lormeau VM, Blake A, Mons S, Lastère S, Roche C, Vanhomwegen J, et al. Guillain-Barré syndrome outbreak associated with Zika virus infection in French Polynesia: a case-control study. Lancet. 2016; 387:1531-9.
PubMed
CrossRef
 
Rasmussen SA, Jamieson DJ, Honein MA, Petersen LR. Zika virus and birth defects—reviewing the evidence for causality. N Engl J Med. 2016; 374:1981-7.
PubMed
CrossRef
 
Brasil P, Pereira JP Jr, Raja Gabaglia C, Damasceno L, Wakimoto M, Ribeiro Nogueira RM, et al. Zika virus infection in pregnant women in Rio de Janeiro—preliminary report. N Engl J Med.. 2016.
PubMed
 
Sarno M, Sacramento GA, Khouri R, do Rosário MS, Costa F, Archanjo G, et al. Zika virus infection and stillbirths: a case of hydrops fetalis, hydranencephaly and fetal demise. PLoS Negl Trop Dis. 2016; 10:e0004517.
PubMed
CrossRef
 
Tang H, Hammack C, Ogden SC, Wen Z, Qian X, Li Y, et al. Zika virus infects human cortical neural progenitors and attenuates their growth. Cell Stem Cell. 2016; 18:587-90.
PubMed
CrossRef
 
Alfaro-Murillo JA, Parpia AS, Fitzpatrick MC, Tamagnan JA, Medlock J, Ndeffo-Mbah ML, et al. A cost-effectiveness tool for informing policies on Zika virus control. PLoS Negl Trop Dis. 2016; 10:e0004743.
PubMed
CrossRef
 
European Centre for Disease Prevention and Control.  Rapid Risk Assessment: Microcephaly in Brazil Potentially Linked to the Zika Virus Epidemic. Stockholm, Sweden: European Centre for Disease Prevention and Control; 2015. Accessed at http://ecdc.europa.eu/en/publications/Publications/zika-microcephaly-Brazil-rapid-risk-assessment-Nov-2015.pdf on 22 June 2016.
 
Butler D. First Zika-linked birth defects detected in Colombia. Nature News. 2016; 531:153.
CrossRef
 
McNeil DG Jr. Delaying pregnancy until Zika moves on. The New York Times.. 9 February 2016; D1.
 
Sedgh G, Singh S, Hussain R. Intended and unintended pregnancies worldwide in 2012 and recent trends. Stud Fam Plann. 2014; 45:301-14.
PubMed
CrossRef
 
Schuck-Paim C, López D, Simonsen L, Alonso W.  Unintended pregnancies in Brazil—a challenge for the recommendation to delay pregnancy due to Zika. PLoS Curr Outbreaks. 16 March 2016. Accessed at http://dx.doi.org/10.1371/currents.outbreaks.7038a6813f734c1db547240c2a0ba291 on 19 April 2016.
 
Bowman LR, Donegan S, McCall PJ. Is dengue vector control deficient in effectiveness or evidence?: systematic review and meta-analysis. PLoS Negl Trop Dis. 2016; 10:e0004551.
PubMed
CrossRef
 
Kleber de Oliveira W, Cortez-Escalante J, De Oliveira WT, do Carmo GM, Henriques CM, Coelho GE, et al. Increase in reported prevalence of microcephaly in infants born to women living in areas with confirmed Zika virus transmission during the first trimester of pregnancy—Brazil, 2015. MMWR Morb Mortal Wkly Rep. 2016; 65:242-7.
PubMed
CrossRef
 
United Nations.  World Population Prospects: The 2015 Revision. Key Findings and Advance Tables. Working Paper no. ESA/P/WP.241. New York: United Nations; 2015. Accessed at https://esa.un.org/unpd/wpp/Publications/Files/Key_Findings_WPP_2015.pdf on 22 June 2016.
 
Stykes J.  Fatherhood in the US: men's age at first birth, 1987-2010. Report no. FP-11-04. Bowling Green, OH: National Center for Family and Marriage Research; 2011. Accessed at www.bgsu.edu/content/dam/BGSU/college-of-arts-and-sciences/NCFMR/documents/FP/FP-11-04.pdf on 22 June 2016.
 
Bongaarts J, Blanc AK. Estimating the current mean age of mothers at the birth of their first child from household surveys. Popul Health Metr. 2015; 13:25.
PubMed
CrossRef
 
Eskenazi B, Wyrobek AJ, Sloter E, Kidd SA, Moore L, Young S, et al. The association of age and semen quality in healthy men. Hum Reprod. 2003; 18:447-54.
PubMed
CrossRef
 
Castelo-Branco C, Blümel JE, Chedraui P, Calle A, Bocanera R, Depiano E, et al. Age at menopause in Latin America. Menopause. 2006; 13:706-12.
PubMed
CrossRef
 
Hallett TB, Gregson S, Mugurungi O, Gonese E, Garnett GP. Assessing evidence for behaviour change affecting the course of HIV epidemics: a new mathematical modelling approach and application to data from Zimbabwe. Epidemics. 2009; 1:108-17.
PubMed
CrossRef
 
Harrington LC, Françoisevermeylen,Jones JJ, Kitthawee S, Sithiprasasna R, Edman JD, et al. Age-dependent survival of the dengue vector Aedes aegypti (Diptera: Culicidae) demonstrated by simultaneous release-recapture of different age cohorts. J Med Entomol. 2008; 45:307-13.
PubMed
CrossRef
 
Styer LM, Carey JR, Wang JL, Scott TW. Mosquitoes do senesce: departure from the paradigm of constant mortality. Am J Trop Med Hyg. 2007; 76:111-7.
PubMed
 
Trpis M, Häusermann W, Craig GB Jr. Estimates of population size, dispersal, and longevity of domestic Aedes aegypti aegypti (Diptera: Culicidae) by mark-release-recapture in the village of Shauri Moyo in eastern Kenya. J Med Entomol. 1995; 32:27-33.
PubMed
CrossRef
 
Sheppard PM, Macdonald WW, Tonn RJ, Grab B. The dynamics of an adult population of Aedes aegypti in relation to dengue haemorrhagic fever in Bangkok. J Anim Ecol. 1969; 38:661-702.
CrossRef
 
Lardeux F, Cheffort J. Ambient temperature effects on the extrinsic incubation period of Wuchereria bancrofti in Aedes polynesiensis: implications for filariasis transmission dynamics and distribution in French Polynesia. Med Vet Entomol. 2001; 15:167-76.
PubMed
CrossRef
 
Li MI, Wong PS, Ng LC, Tan CH. Oral susceptibility of Singapore Aedes (Stegomyia) aegypti (Linnaeus) to Zika virus. PLoS Negl Trop Dis. 2012; 6:e1792.
PubMed
CrossRef
 
Andraud M, Hens N, Marais C, Beutels P. Dynamic epidemiological models for dengue transmission: a systematic review of structural approaches. PLoS One. 2012; 7:e49085.
PubMed
CrossRef
 
Scott TW, Amerasinghe PH, Morrison AC, Lorenz LH, Clark GG, Strickman D, et al. Longitudinal studies of Aedes aegypti (Diptera: Culicidae) in Thailand and Puerto Rico: blood feeding frequency. J Med Entomol. 2000; 37:89-101.
PubMed
CrossRef
 
Manore CA, Hickmann KS, Xu S, Wearing HJ, Hyman JM. Comparing dengue and chikungunya emergence and endemic transmission in A. aegypti and A. albopictus. J Theor Biol. 2014; 356:174-91.
PubMed
CrossRef
 
Majumder MS, Cohn E, Fish D, Brownstein JS.  Estimating a feasible serial interval range for Zika fever. Bull World Health Organ. 2016. Accessed at http://dx.doi.org/10.2471/BLT.16.171009 on 22 June 2016.
 
Lessler JT, Ott CT, Carcelen AC, Konikoff JM, Williamson J, Bi Q, et al.  Times to key events in the course of Zika infection and their implications: a systematic review and pooled analysis. Bull World Health Organ. 2016. Accessed at http://dx.doi.org/10.2471/BLT.16.174540 on 22 June 2016.
 
Mallet HP, Vial AL, Musso D.  Bilan de l'épidémie à virus zika en Polynésie Française, 2013-2014. Bulletin d'Information sanitaires, épidémiologiques et statistiques. 2015:1-5.
 
Fagbami AH. Zika virus infections in Nigeria: virological and seroepidemiological investigations in Oyo State. J Hyg (Lond). 1979; 83:213-9.
PubMed
CrossRef
 
Ioos S, Mallet HP, Leparc Goffart I, Gauthier V, Cardoso T, Herida M. Current Zika virus epidemiology and recent epidemics. Med Mal Infect. 2014; 44:302-7.
PubMed
CrossRef
 
Luz PM, Vanni T, Medlock J, Paltiel AD, Galvani AP. Dengue vector control strategies in an urban setting: an economic modelling assessment. Lancet. 2011; 377:1673-80.
PubMed
CrossRef
 
Gubler DJ. Dengue and dengue hemorrhagic fever. Clin Microbiol Rev. 1998; 11:480-96.
PubMed
 
Sawyer WA. The persistence of yellow fever immunity. Journal of Preventive Medicine. 1931; 5:413-28.
 
Poole D, Raftery AE. Inference for deterministic simulation models: the Bayesian melding approach. J Am Stat Assoc. 2000; 95:1244-55.
CrossRef
 
Pan American Health Organization; World Health Organization.  Suspected and confirmed Zika cases reported by countries and territories in the Americas, 2015-2016. 2016. Accessed at http://ais.paho.org/phip/viz/ed_zika_epicurve.asp on 26 May 2016.
 
van den Driessche P, Watmough J. Reproduction numbers and sub-threshold endemic equilibria for compartmental models of disease transmission. Math Biosci. 2002; 180:29-48.
PubMed
CrossRef
 
Pandey A, Atkins KE, Medlock J, Wenzel N, Townsend JP, Childs JE, et al. Strategies for containing Ebola in West Africa. Science. 2014; 346:991-5.
PubMed
CrossRef
 
Marino S, Hogue IB, Ray CJ, Kirschner DE. A methodology for performing global uncertainty and sensitivity analysis in systems biology. J Theor Biol. 2008; 254:178-96.
PubMed
CrossRef
 
Instituto Nacional de Salud.  Boletín Epidemiológico Semanal. Report no. 3. Bogotá, Colombia: Instituto Nacional de Salud; 2016. Accessed at www.ins.gov.co/boletin-epidemiologico/Boletn%20Epidemiolgico/2016%20Boletin%20epidemiologico%20semana%203.pdf on 22 June 2016.
 
Cauchemez S, Besnard M, Bompard P, Dub T, Guillemette-Artur P, Eyrolle-Guignot D, et al. Association between Zika virus and microcephaly in French Polynesia, 2013-15: a retrospective study. Lancet. 2016; 387:2125-32.
PubMed
CrossRef
 
Mlakar J, Korva M, Tul N, Popovic M, Poljšak-Prijatelj M, Mraz J, et al. Zika virus associated with microcephaly. N Engl J Med. 2016; 374:951-8.
PubMed
CrossRef
 
Musso D, Roche C, Robin E, Nhan T, Teissier A, Cao-Lormeau VM. Potential sexual transmission of Zika virus. Emerg Infect Dis. 2015; 21:359-61.
PubMed
CrossRef
 
Foy BD, Kobylinski KC, ChilsonFoy JL, Blitvich BJ, Travassos da Rosa A, Haddow AD, et al. Probable non–vector-borne transmission of Zika virus, Colorado, USA. Emerg Infect Dis. 2011; 17:880-2.
PubMed
CrossRef
 
Oster AM, Russell K, Stryker JE, Friedman A, Kachur RE, Petersen EE, et al. Update: interim guidance for prevention of sexual transmission of Zika virus—United States, 2016. MMWR Morb Mortal Wkly Rep. 2016; 65:323-5.
PubMed
CrossRef
 
Turmel JM, Abgueguen P, Hubert B, Vandamme YM, Maquart M, Le Guillou-Guillemette H, et al. Late sexual transmission of Zika virus related to persistence in the semen [Letter]. Lancet.. 2016.
PubMed
 
Rodriguez-Morales AJ, García-Loaiza CJ, Galindo-Marquez ML, Sabogal-Roman JA, Marin-Loaiza S, Lozada-Riascos CO, et al. Zika infection GIS-based mapping suggest high transmission activity in the border area of La Guajira, Colombia, a northeastern coast Caribbean department, 2015-2016: implications for public health, migration and travel [Letter]. Travel Med Infect Dis.. 2016; 14:286-8.
PubMed
CrossRef
 
Centers for Disease Control and Prevention.  Zika virus. Atlanta, GA: Centers for Disease Control and Prevention; 2016. Accessed at www.cdc.gov/zika/index.html on 10 June 2016.
 

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Clinical Slide Sets

Terms of Use

The In the Clinic® slide sets are owned and copyrighted by the American College of Physicians (ACP). All text, graphics, trademarks, and other intellectual property incorporated into the slide sets remain the sole and exclusive property of the ACP. The slide sets may be used only by the person who downloads or purchases them and only for the purpose of presenting them during not-for-profit educational activities. Users may incorporate the entire slide set or selected individual slides into their own teaching presentations but may not alter the content of the slides in any way or remove the ACP copyright notice. Users may make print copies for use as hand-outs for the audience the user is personally addressing but may not otherwise reproduce or distribute the slides by any means or media, including but not limited to sending them as e-mail attachments, posting them on Internet or Intranet sites, publishing them in meeting proceedings, or making them available for sale or distribution in any unauthorized form, without the express written permission of the ACP. Unauthorized use of the In the Clinic slide sets will constitute copyright infringement.

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