Travel Surveillance and Genomics Uncover a Hidden Zika Outbreak during the Waning Epidemic.
Ontology highlight
ABSTRACT:
SUBMITTER: Grubaugh ND
PROVIDER: S-EPMC6716374 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:We surveyed pregnant women from the United States to assess the prevention practices they used when traveling to countries with ongoing Zika virus (ZIKV) outbreaks. Of the 749 who agreed to participate, 710 completed the survey's travel questions and 59 of those had traveled to a ZIKV outbreak area in the past 12 months. Only 43% of the women who had traveled to ZIKV outbreak areas reported frequently using mosquito repellant with 32% stating they did not use it at all. They also did not frequently use other recommended methods to prevent mosquito bites. With the established risks to babies born to women who contract the ZIKV during pregnancy, it is a great concern that a large number of women who travel to outbreak areas during pregnancy are not protecting themselves against mosquito bites. Pregnant women need to be educated on the importance of taking precautions.
| S-EPMC5928737 | biostudies-other
Project description:Since its peak in early 2016, the incidence of Zika virus (ZIKV) cases has declined to such low levels that Phase 3 field efficacy trials may be infeasible. While great progress was made to rapidly advance several vaccine candidates into Phase 1 and 2 clinical trials, in the absence of sustained viral transmission it may be difficult to evaluate the effectiveness of ZIKV vaccine candidates by conducting traditional clinical disease endpoint efficacy studies. However, ZIKV is still circulating at low levels in some areas and is likely to re-emerge in naïve populations or in sites of prior epidemics once population immunity wanes. Therefore, the public health need for a ZIKV vaccine remains. To facilitate continued ZIKV vaccine development efforts, the World Health Organization's Initiative for Vaccine Research and the National Institutes of Health's National Institute of Allergy and Infectious Diseases co-hosted a meeting of experts in March 2018 to identify strategies to demonstrate vaccine effectiveness in view of waning ZIKV disease incidence. This paper outlines points for consideration for developers, regulators, and other stakeholders working towards a licensed ZIKV vaccine. These deliberations may also be applicable to development of vaccines for other emerging infections where the size, unpredictability, and ephemeral nature of outbreaks makes clinical disease endpoint efficacy trials to demonstrate vaccine effectiveness infeasible.
| S-EPMC6357529 | biostudies-other
Project description:BACKGROUND:Zika virus caused thousands of congenital anomalies during a recent epidemic. Because Zika emerged in areas endemic for dengue and these related flaviviruses elicit cross-reactive antibodies, it is challenging to serologically monitor pregnant women for Zika infection. METHODS:A prospective cohort of 253 pregnant women was established in León, Nicaragua. Women were followed during prenatal care through delivery. Serologic specimens were obtained at each visit, and birth outcome was recorded. Established flavivirus serologic methods were adapted to determine Zika seroprevalence, and a stepwise testing algorithm estimated timing of Zika infection in relation to pregnancy. RESULTS:Zika seroprevalence was approximately 59% among women tested. Neutralization testing was highly concordant with Zika NS1 BOB results. Per study algorithm, 21% (40/187) of women were classified as experiencing Incident ZIKV infection during pregnancy. Importantly, the Incident ZIKV group included mostly women pregnant during the 2016 Zika epidemic peak and the only 3 subjects in the cohort with RT-PCR-confirmed infections. Approximately 17% of births had complications; 1.5% (3/194) manifesting clinical criteria of congenital Zika syndrome, one was RT-PCR-confirmed as a case of congenital Zika syndrome. Adverse birth outcome did not correlate with timing of Zika infection. CONCLUSIONS:By leveraging prenatal care systems, we developed a simple algorithm for identifying women who were likely infected by Zika during pregnancy.
| S-EPMC7122769 | biostudies-literature
Project description:OBJECTIVE:To identify newborns with congenital Zika infection (CZI) at a maternity hospital in Salvador, Brazil, during the 2016 microcephaly outbreak. METHODS:A prospective study enrolled microcephalic and normocephalic newborns with suspected CZI between January and December 2016. Serology (immunoglobulins IgM and IgG) and quantitative reverse transcriptase polymerase chain reaction (RT-qPCR) for the Zika virus were performed. Demographic and clinical characteristics of newborns with and without microcephaly were compared. RESULTS:Of the 151 newborns enrolled, 32 (21.2%) were classified as microcephalic. The majority of these cases were born between January and May 2016. IgM and IgG Zika virus antibodies were detected in 5 (23.8%) and 17 (80.9%) microcephalic newborn blood samples, respectively. Six (24%) microcephalic newborns tested positive for Zika virus by RT-qPCR in urine or placenta samples. Thirteen (11.8%) normocephalic newborns also tested positive for Zika virus by PCR in urine, plasma, or placenta samples, while IgM antibodies against Zika were detected in 4 (4.2%) others. CONCLUSIONS:Identification of 17 normocephalic CZI cases, confirmed by IgM serology or RT-qPCR for Zika virus, provides evidence that CZI can present asymptomatically at birth. This finding highlights the need for prenatal and neonatal screening for Zika virus in endemic regions.
| S-EPMC7064952 | biostudies-literature
Project description:In 2018, the World Health Organization identified the Zika virus (ZIKV) as a pathogen that should be prioritized for public health research due to its epidemic potential. In this study, whole-genome sequencing (WGS) of travel-acquired ZIKV infections was used to examine the limitations of phylogenetic analysis. WGS and phylogenetic analysis were performed to investigate geographic clustering of samples from five Canadians with travel-acquired ZIKV infections and to assess the limitations of phylogenetic analysis of ZIKV sequences using a phylogenetic cluster approach. Genomic variability of ZIKV samples was assessed and for context, compared with hepatitis C virus (HCV) samples. Phylogenetic analysis confirmed the suspected region of ZIKV infection for one of five samples and one sample failed to cluster with sequences from its suspected country of infection. Travel-acquired ZIKV samples depicted low genomic variability relative to HCV samples. A floating patristic distance threshold classified all pre-2000 ZIKV sequences into separate clusters, while only Cambodian, Peruvian, Malaysian, and South Korean sequences were similarly classifiable. While phylogenetic analysis of ZIKV data can identify the broad geographical region of ZIKV infection, ZIKV's low genomic variability is likely to limit precise interpretations of phylogenetic analysis of the origins of travel-related cases.
| S-EPMC6848190 | biostudies-literature
Project description:Zika virus infection closely resembles dengue fever. It is possible that many cases are misdiagnosed or missed. We report a case of Zika virus infection in an Australian traveler who returned from Indonesia with fever and rash. Further case identification is required to determine the evolving epidemiology of this disease.
| S-EPMC3771291 | biostudies-literature
Project description:BackgroundZika virus (ZIKV) is an emerging mosquito-borne arbovirus that can produce serious public health consequences. In 2016, ZIKV caused an epidemic in many countries around the world, including the United States. ZIKV surveillance and vector control is essential to combating future epidemics. However, challenges relating to the timely publication of case reports significantly limit the effectiveness of current surveillance methods. In many countries with poor infrastructure, established systems for case reporting often do not exist. Previous studies investigating the H1N1 pandemic, general influenza and the recent Ebola outbreak have demonstrated that time- and geo-tagged Twitter data, which is immediately available, can be utilized to overcome these limitations.MethodsIn this study, we employed a recently developed system called Cloudberry to filter a random sample of Twitter data to investigate the feasibility of using such data for ZIKV epidemic tracking on a national and state (Florida) level. Two auto-regressive models were calibrated using weekly ZIKV case counts and zika tweets in order to estimate weekly ZIKV cases 1 week in advance.ResultsWhile models tended to over-predict at low case counts and under-predict at extreme high counts, a comparison of predicted versus observed weekly ZIKV case counts following model calibration demonstrated overall reasonable predictive accuracy, with an R2 of 0.74 for the Florida model and 0.70 for the U.S.ModelTime-series analysis of predicted and observed ZIKV cases following internal cross-validation exhibited very similar patterns, demonstrating reasonable model performance. Spatially, the distribution of cumulative ZIKV case counts (local- & travel-related) and zika tweets across all 50?U.S. states showed a high correlation (r?=?0.73) after adjusting for population.ConclusionsThis study demonstrates the value of utilizing Twitter data for the purposes of disease surveillance. This is of high value to epidemiologist and public health officials charged with protecting the public during future outbreaks.
| S-EPMC6570872 | biostudies-literature
Project description:Infectious diseases attack humans from time to time and threaten the lives and survival of people all around the world. An important strategy to prevent the spatial spread of infectious diseases is to restrict population travel. With the reduction of the epidemic situation, when and where travel restrictions can be lifted, and how to organize orderly movement patterns become critical and fall within the scope of this study. We define a novel diffusion distance derived from the estimated mobility network, based on which we provide a general model to describe the spatiotemporal spread of infectious diseases with a random diffusion process and a deterministic drift process of the population. We consequently develop a multi-source data fusion method to determine the population flow in epidemic areas. In this method, we first select available subregions in epidemic areas, and then provide solutions to initiate new travel flux among these subregions. To verify our model and method, we analyze the multi-source data from mainland China and obtain a new travel flux triggering scheme in the selected 29 cities with the most active population movements in mainland China. The testable predictions in these selected cities show that reopening the borders in accordance with our proposed travel flux will not cause a second outbreak of COVID-19 in these cities. The finding provides a methodology of re-triggering travel flux during the weakening spread stage of the epidemic.
| S-EPMC8550429 | biostudies-literature
Project description:We used latent class analysis to examine Zika virus-related information-accessing behavior of US residents during the 2016 international outbreak. We characterized 3 classes of information-accessing behavior patterns: universalists, media seekers, and passive recipients. Understanding these patterns is crucial to planning risk communication during an emerging health threat.
| S-EPMC7454085 | biostudies-literature
Project description:BackgroundTo understand operational challenges involved with responding to US measles outbreaks in 2017-19 and identify applicable lessons in order to inform preparedness and response operations for future outbreaks, particularly with respect to specific operational barriers and recommendations for outbreak responses among insular communities.MethodsFrom August 2019 to January 2020, we conducted 11 telephone interviews with 18 participants representing state and local health departments and community health centers that responded to US measles outbreaks in 2017-19, with a focus on outbreaks among insular communities. We conducted qualitative, thematic coding to identify and characterize key operational challenges and lessons identified by the interviewees.ResultsWe categorized principal insights into 5 topic areas: scale of the response, vaccination operations, exclusion policies, community engagement, and countering anti-vaccine efforts. These topics address resource-intensive aspects of these outbreak responses, including personnel demands; guidance needed to support response operations and reduce transmission, such as excluding exposed or at-risk individuals from public spaces; operational challenges and barriers to vaccination and other response activities; and effectively engaging and educating affected populations, particularly with respect to insular and vulnerable communities.ConclusionsMeasles outbreak responses are resource intensive, which can quickly overwhelm existing public health capacities. Early and effective coordination with trusted leaders and organizations in affected communities, including to provide vaccination capacity and facilitate community engagement, can promote efficient response operations. The firsthand experiences of public health and healthcare personnel who responded to measles outbreaks, including among insular communities, provide evidence-based operational lessons that can inform future preparedness and response operations for outbreaks of highly transmissible diseases.
| S-EPMC8042853 | biostudies-literature