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10 Years of Emerging Pandemic Threat (EPT) PREDICT Program to Prevent Viral Pandemics: are we ready for Disease X?

Authors:

Abstract

Background: The USAID Emerging Pandemic Threats (EPT): PREDICT program began in 2009, designed to prepare the public health community to combat disease threats at the first stage of their emergence through an early warning system for detecting novel zoonotic diseases in parts of the world most vulnerable to disease emergence. Working with local partners in emerging infectious disease (EID) hotspots PREDICT aimed to characterize viral diversity in key wildlife species; identify high risk interfaces where viral spillover is most likely to occur; and identify and assess novel viruses most likely to impact human health. Methods: The PREDICT program, implemented in 30 countries in hotspot regions across Africa, Latin America and Asia, inclusive of Bangladesh. Working in collaboration with Government and NGO partners we conducted long-term epidemiological, ecological, and behavioral surveillance efforts to monitor for and estimate the risk of the spillover of viruses from key viral families. PREDICT surveillance consisted of the non-destructive sampling of wild animals, livestock and people. Samples included blood, saliva, urine, and feces, which were tested using viral family-level PCR assays and next generation sequencing to detect previously undescribed viruses. Results: We operationalized one health surveillance and sampled 145K animals and people across the 30 countries. PREDICT discovered 931 novel and detected 218 known viruses, including zoonotic pathogens of public health concern such as Ebola Zaire, Marburg, Nipah virus, MERS and SARS-like corona viruses and a novel Ebola virus species called Bombali virus virus. PREDICT responded to 23 zoonotic disease outbreaks in 10 countries. We strengthened laboratory system and zoonotic disease detection in over 60 laboratories around the world. We developed the One Health workforce by training more than 6000 people in over 30 countries. In Bangladesh, we estimated the approximate viral diversity in the Indian flying fox (Pteropus giganteus), a native frugivorous bat and the natural reservoir for Nipah virus. Conclusion: The PREDICT program used a collaborative One Health approach building the capacity for the detection and characterization of novel wildlife viruses. The program improved the understanding of the dynamics of zoonotic virus spillover, spread, evolution, and amplification of EIDs in order to inform prevention strategies and combat the risk of disease emergence. PREDICT strengthened workforce, laboratory capacity and improved the ability to prevent and respond to unknown disease outbreaks, Disease X, across the globe. Continued development of the next generation of One Health practitioners and sustainability of the One Health approach zoonotic surveillance is recommended Key words: Pandemics, Emerging, Novel, and virus
10th One Health Bangladesh Conference Abstract Book 2019
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lD 19-128:Ten Years of Emerging Pandemic Threat (EPT) PREDICT Program to Prevent Viral
Pandemics: Are we ready for Disease "X"?
Ariful lslaml Jonathan H Epsteinl, Melinda K Rostall, Emily Haganl, Mohamme dZiaur Rahman2, Meerjady
Sabrina Flora3, Petar Daszakl, Jonna K Mazeta and PREDICT Consortium
lEcoHeolth Allionce New York, NY, IJSA; 2tnstitute of Epidemiology Diseose Control and Research (IEDCRL
Mohokhqli, Dhaka, Bonglodesh;3lnternationol Centre for Diorrheol Disease Research, Banglodesh
(icddr.b), Dhako, Bangladesh; 4One Heqlth lnstitute, University of California Davis, California, IJSA.E mail
of corresponding author: orif@ecoheolthalliance.org
Background: The USAID Emerging Pandemic Threats (EPT): PREDICT program began in 2009, designed to
prepare the public health community to combat disease threats at the first stage of their emergence
through an early warning system for detecting novel zoonotic diseases in disease hotspots regions.
PREDICT aimed to characterize viral diversity in key animal species; identify high risk interfaces where virai
spillover is most likely to occur;.and identify and assess novel viruses most likely to impact human health.
Methods:The PREDICT program, implementedin24 countries in hotspot regions across Africa and Asia,
inclusive of Bangladesh. Working in collaboration with the Government partners in a combination of
longitudinal biological, ecological, and behavioral surveillance efforts to monitor spillover of viruses within
key viral families. PREDICT surveillance consisted of the non-destructive sampling of wild animals,
livestock and human. PREDICT tested 145000 animals and people samples using viral family-level PCR
assays and Next generationiequencing on previously undescribed viruses. Both molecular and serological
assays were used to determine spillover events. Results: We discovered 931 novel and 218 known viruses,
including zoonotic diseases of public health concern such as a novel strain of Ebola Bombali, Ebola Zaire,
Marburg virus, MERS and SARS-like corona viruses. We estimated the approximate viral diversity in the
lndian flying fox (Pteropusgiganteus), a native frugivorous,bat and the natural reservoir for Nipah virus.
PREDICT responded 23 zoonotic disease outbreaks in 10 countries. We strengthened laboratory system
and zoonotic disease detection in over 60 laboratories around the world. We dev'eloped the One
HealthOne Health workforce by training more than 6000 people in over 24 countries
Conctusion: The PREDICT program used a One Health approach building the capacity for detection and
characterization of novel viruses and improved the understanding of the dynamics of zoonotic virus
spillover, spread, evolution, and amplification of ElDs to inform prevention strategies and combat the risk.
of disease emergence. PREDICT strengthened workforce, laboratory capacity and improved our ability to
prevent and respond unknown Disease outbreak like Disease X across the globe. Continue to develop next
generation of One Health practitioners and sustain coordinated approach zoonotic surveillance is
recommended.
Key words: Pandemics, Emerging, Novel, and virus
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