
NSF Org: |
DEB Division Of Environmental Biology |
Recipient: |
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Initial Amendment Date: | May 9, 2016 |
Latest Amendment Date: | July 8, 2016 |
Award Number: | 1642174 |
Award Instrument: | Standard Grant |
Program Manager: |
Katharina Dittmar
kdittmar@nsf.gov (703)292-7799 DEB Division Of Environmental Biology BIO Directorate for Biological Sciences |
Start Date: | May 1, 2016 |
End Date: | October 31, 2017 (Estimated) |
Total Intended Award Amount: | $199,991.00 |
Total Awarded Amount to Date: | $199,991.00 |
Funds Obligated to Date: |
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History of Investigator: |
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Recipient Sponsored Research Office: |
1523 UNION RD RM 207 GAINESVILLE FL US 32611-1941 (352)392-3516 |
Sponsor Congressional District: |
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Primary Place of Performance: |
PO BOX 118525 Gainesville FL US 32611-8525 |
Primary Place of
Performance Congressional District: |
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Unique Entity Identifier (UEI): |
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Parent UEI: |
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NSF Program(s): | Ecology of Infectious Diseases |
Primary Program Source: |
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Program Reference Code(s): |
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Program Element Code(s): |
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Award Agency Code: | 4900 |
Fund Agency Code: | 4900 |
Assistance Listing Number(s): | 47.074 |
ABSTRACT
This RAPID award will develop estimates of the transmission capability and potential global burden of infection of the Zika virus. These estimates are urgently needed but difficult to obtain because of inaccuracies in blood tests and under reporting of infections. Using existing serum samples together with mathematical modeling, the project will fill knowledge gaps about i) transmission parameters for Zika, ii) the consistency of surveillance approaches, and iii) the global risk of Zika transmission. This approach will also capture information about other viral infections (e.g., chikungunya and dengue) and the potential for future spread. Results from this project will be relevant to the Zika public health emergency, and the researchers have set in place mechanisms to share quality-assured interim and final data as rapidly and widely as possible, including with public health and research communities.
This project will use mathematical models informed by sample serology to estimate the transmission potential for Zika across the globe. Currently, the utility of inference is limited with surveillance reports alone and traditional serological methods, the latter because of cross-reactivity between arboviruses. This project will use a new low-cost, high throughput assay to test for the historic exposure of different antibodies for Zika and other arboviruses. It will compare the rate susceptible individuals in communities that acquire different arboviruses over time. From these results, geostatistical models to predict the force of infection will be developed and risk maps for Zika and other arboviruses will be validated. This knowledge will be used to characterize the shared epidemiology of arboviral diseases around the world.
PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH
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PROJECT OUTCOMES REPORT
Disclaimer
This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.
Zika virus (ZIKV) recently emerged in the Americas and was declared a Public Health Emergency of International Concern by the WHO. Though Zika cases have been reported since the 1940s, the true burden of Zika is unknown. Estimates of the transmission potential and global burden of infection from ZIKV are fundamental to the design and targeting of effective interventions, but cannot be readily inferred from surveillance data due to misclassification with similar diseases like dengue, underreporting, and high proportions of asymptomatic disease
We combined mathematical modeling and novel serological testing of existing blood samples from five countries around the world to estimate key transmission parameters and risk maps for ZIKV. While the primary focus of this project was ZIKV, the data generated and methods employed could also be applied to related arboviruses (such as dengue, chikungunya and Japanese encephalitis). The spatial overlap between ZIKV and similar diseases also provides key insight into the future spread of Zika and other viruses.
We first developed statistical techniques to better analyze data from the SHERPADES-Luminex assay, a novel test for past exposure to ZIKV and related viruses, using well characterized samples from Colombia and the Philippines. We tested over 5,000 existing serum samples using this assay. Initial results from Bangladesh, Burkina Faso and Gabon showed little or no evidence of ZIKV circulation. Results from the Philippines showed that around 8% of the population had been infected. Finally, results from Colombia showed closer to 55% ZIKV seropositivity. There is strong evidence of the circulation of other arboviruses across these locations. Using the results of the serological testing of samples from Burkina Faso, we fit mathematical models of the past circulation of different arboviruses in the region. In particular, we have been able to demonstrate that there have been four short-lived outbreaks of chikungunya in Burkina Faso over the past 60 years (Figure 1, attached). There is no previous report of chikungunya in the country. Further, we demonstrate the recent entry of chikungunya into Gabon, with no circulation prior to 2007.
Estimates of the reproductive number of Zika in counties in Florida in which local cases occurred ranged between 0.3 and 0.7, suggesting that on average each case resulted in 0.3 to 0.7 locally acquired cases.
We believe these results will be informative to public health decision makers when planning prevention and intervention strategies for Zika and related arboviral diseases. We have also partnered with local researchers in several countries to provide training in the SHERPADES-Luminex assay used in this study, and hope that it may be used as a surveillance and clinical tool moving forward.
Last Modified: 03/02/2018
Modified by: Derek A Cummings
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