Identifying Areas at Greatest Risk for Recent Zika Virus Importation — New York City, 2016

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Introduction: The New York City Department of Health and Mental Hygiene sought to detect and minimize the risk of local, mosquito-borne Zika virus (ZIKV) transmission. We modeled areas at greatest risk for recent ZIKV importation, in the context of spatially biased ZIKV case ascertainment and no data on the local spatial distribution of persons arriving from ZIKV-affected countries.

Methods: For each of 14 weeks during June-September 2016, we used logistic regression to model the census tract-level presence of any ZIKV cases in the prior month, using eight covariates from static sociodemographic census data and the latest surveillance data, restricting to census tracts with any ZIKV testing in the prior month. To assess whether the model discriminated better than random between census tracts with and without recent cases, we compared the area under the receiver operating characteristic (ROC) curve for each week’s fitted model versus an intercept-only model applied to cross-validated data. For weeks where the ROC contrast test was significant at P < 0.05, we output and mapped the model-predicted individual probabilities for all census tracts, including those with no recent testing.

Results: The ROC contrast test was significant for 8 of 14 weekly analyses. No covariates were consistently associated with the presence of recent cases. Modeled risk areas fluctuated across these 8 weeks, with Spearman correlation coefficients ranging from 0.30 to 0.93, all P < 0.0001. Areas in the Bronx and upper Manhattan were in the highest risk decile as of late June, while as of late August, the greatest risk shifted to eastern Brooklyn.

Conclusion: We used observable characteristics of areas with recent, known travel-associated ZIKV cases to identify similar areas with no observed cases that might also be at-risk each week. Findings were used to target public education and Aedes spp. mosquito surveillance and control. These methods are applicable to other conditions for which biased case ascertainment is suspected and knowledge of how cases are geographically distributed is important for targeting public health activities.

The First Outbreak of Autochthonous Zika Virus in Sabah, Malaysian Borneo

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Background: Zika virus (ZIKV) infection is a public health concern. The first ZIKV outside Africa was detected in mosquito in Malaysia. More than six decades ago, serological surveys indicated the presence of human infection with ZIKV in the Malaysian Borneo state of Sabah. It has also been demonstrated that orangutans in Sabah have antibodies against ZIKV. Several years ago, a case of human ZIKV infection was reported in a traveler who visited Sabah. Therefore, it is thought that ZIKV is endogenous to Sabah and is widely distributed.  During the recent global epidemic of ZIKV, the first autochthonous case and two subsequent autochthonous cases were detected in Sabah. Because ZIKV infection is mainly asymptomatic or mildly symptomatic, the extent of ZIKV infection in the population of Sabah is not known. Furthermore, the presence of ZIKV in vector mosquitoes and animals has not been investigated. Therefore, the present study was performed to analyze the outbreak cases of ZIKV infection and to determine their relationship with the burden of ZIKV infection in the local population, mosquitoes, and wild nonhuman primates in Sabah. 

Methods: Serum and urine samples were collected from two local patients with ZIKV infection, their household members, and those who resided within 400m of the patients’ residences. Serum samples were also collected from four wild Maca fascicularis. Mosquito samples, mostly female Aedes albopictus, were collected from 30 sites in Kota Kinabalu. The presence of ZIKV was assessed by RT-qPCR and RT-PCR. Phylogenetic analysis was performed using the neighbor-joining method.  

Results: Two cases of ZIKV infection were identified by reverse-transcription quantitative PCR (RT-qPCR) in residents of Kota Kinabalu, and the Taiwanese health authorities reported one case in an individual who visited Kota Kinabalu during the study period. All household members of both local patients and people living within a 400 m radius of the patients were negative for ZIKV. Furthermore, mosquitoes collected from the surroundings of the residences and places visited by the patients and four serum samples from M. fascicularis were also negative for ZIKV. A phylogenetic tree constructed using the nucleotide sequences of the envelope genes of ZIKV showed that the strains from Sabah formed a cluster with strains from Thailand and Cambodia, and belong to the Asian lineage. 

Conclusions: Our study revealed that ZIKVs in Sabah is of Asian lineage and are not related to the recent outbreak strains in the Americas and Singapore. ZIKV infection in Sabah is sporadic, possibly because of limited transmission of the virus. Further studies are needed to characterize the evolutionary history of ZIKV in Sabah to understand the epidemiology of this infection in Borneo.

Rapid Molecular Detection of Zika Virus in Acute-Phase Urine Samples Using the Recombinase Polymerase Amplification Assay

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Background: Currently the detection of Zika virus (ZIKV) in patient samples is done by real-time RT-PCR. Samples collected from rural area are sent to highly equipped laboratories for screening. A rapid point-of-care test is needed to detect the virus, especially at low resource settings.

Methodology/Principal Findings: In this report, we describe the development of a reverse transcription isothermal recombinase polymerase amplification (RT-RPA) assay for the identification of ZIKV. RT-RPA assay was portable, sensitive (21 RNA molecules), and rapid (3-15 minutes). No cross-reactivity was detected to other flaviviruses, alphaviruses and arboviruses. Compared to real-time RT-PCR, the diagnostic sensitivity was 92%, while the specificity was 100%.

Conclusions/Significance: The developed assay is a promising platform for rapid point of need detection of ZIKV in low resource settings and elsewhere (e.g. during mass gathering).

Utility of a Dengue-Derived Monoclonal Antibody to Enhance Zika Infection In Vitro

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Introduction: Zika virus (ZIKV) has emerged in dengue (DENV) endemic areas, where these two related flaviviruses continue to co-circulate. DENV is a complex of four serotypes and infections can progress to severe disease. It is thought that this is mediated by antibody dependent enhancement (ADE) whereby antibodies from a primary DENV infection are incapable of neutralizing heterologous DENV infections with another serotype. ADE has been demonstrated among other members of the Flavivirus group.

Methods: We utilize an in vitro ADE assay developed for DENV to determine whether ZIKV is enhanced by a commonly available DENV serotype 2-derived monoclonal antibody (4G2).

Results: We show that ZIKV infection in vitro is enhanced in the presence of the 4G2 mAb.

Discussion: Our results demonstrate that ADE between ZIKV and DENV is possible and that the 4G2 antibody is a useful tool for the effects of pre-existing anti-DENV antibodies during ZIKV infections.

FLIRT-ing with Zika: A Web Application to Predict the Movement of Infected Travelers Validated Against the Current Zika Virus Epidemic

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Introduction: Beginning in 2015, Zika virus rapidly spread throughout the Americas and has been linked to neurological and autoimmune diseases in adults and babies. Developing accurate tools to anticipate Zika spread is one of the first steps to mitigate further spread of the disease. When combined, air traffic data and network simulations can be used to create tools to predict where infectious disease may spread to and aid in the prevention of infectious diseases. Specific goals were to: 1) predict where travelers infected with the Zika Virus would arrive in the U.S.; and, 2) analyze and validate the open access web application’s (i.e., FLIRT) predictions using data collected after the prediction was made.

Method: FLIRT was built to predict the flow and likely destinations of infected travelers through the air travel network. FLIRT uses a database of flight schedules from over 800 airlines, and can display direct flight traffic and perform passenger simulations between selected airports. FLIRT was used to analyze flights departing from five selected airports in locations where sustained Zika Virus transmission was occurring. FLIRT’s predictions were validated against Zika cases arriving in the U.S. from selected airports during the selected time periods.  Kendall’s τ and Generalized Linear Models were computed for all permutations of FLIRT and case data to test the accuracy of FLIRT’s predictions.

Results: FLIRT was found to be predictive of the final destinations of infected travelers in the U.S. from areas with ongoing transmission of Zika in the Americas from 01 February 2016 – 01 to April 2016, and 11 January 2016 to 11 March 2016 time periods. MIA-FLL, JFK-EWR-LGA, and IAH were top ranked at-risk metro areas, and Florida, Texas and New York were top ranked states at-risk for the future time period analyzed (11 March 2016 – 11 June 2016). For the 11 January 2016 to 11 March 2016 time period, the region-aggregated model indicated 7.24 (95% CI 6.85 – 7.62) imported Zika cases per 100,000 passengers, and the state-aggregated model suggested 11.33 (95% CI 10.80 – 11.90) imported Zika cases per 100,000 passengers.

Discussion: The results from 01 February 2016 to 01 April 2016 and 11 January 2016 to 11 March 2016 time periods support that modeling air travel and passenger movement can be a powerful tool in predicting where infectious diseases will spread next. As FLIRT was shown to significantly predict distribution of Zika Virus cases in the past, there should be heightened biosurveillance and educational campaigns to medical service providers and the general public in these states, especially in the large metropolitan areas.  

Radiological Characterization of Cerebral Phenotype in Newborn Microcephaly Cases from 2015 Outbreak in Brazil

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Introduction: Brazil is facing, since October of 2015, an outbreak of microcephalic fetuses. This outbreak is correlated with the beginning of circulation of Zika virus (ZIKV) in the country. Although it is clear that the size of the head is diminished in these fetuses, the brain phenotype associated with these malformations is unknown.

Methods: We collected computed tomography images of the microcephaly cases from the region of Natal, Rio Grande do Norte, from September 2015 to February 2016.

Findings: The microcephalies derived from the current outbreak are associated with intracerebral calcifications, malformation of the ventricular system, migratory disorders in the telencephalon and, in a lower frequency, malformation of the cerebellum and brainstem.

Discussion: The characteristics described herein are not usually found in other types of microcephaly. We suggest that this work can be used as a guideline to identify microcephaly cases associated to the current outbreak.