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Article ; Online: DOPE: D-Optimal Pooling Experimental design with application for SARS-CoV-2 screening.

Daon, Yair / Huppert, Amit / Obolski, Uri

Journal of the American Medical Informatics Association : JAMIA

2021 Volume 28, Issue 12, Page(s) 2562–2570

Abstract: Objective: Testing individuals for the presence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the pathogen causing the coronavirus disease 2019 (COVID-19), is crucial for curtailing transmission chains. Moreover, rapidly testing many ... ...

Abstract	Objective: Testing individuals for the presence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the pathogen causing the coronavirus disease 2019 (COVID-19), is crucial for curtailing transmission chains. Moreover, rapidly testing many potentially infected individuals is often a limiting factor in controlling COVID-19 outbreaks. Hence, pooling strategies, wherein individuals are grouped and tested simultaneously, are employed. Here, we present a novel pooling strategy that builds on the Bayesian D-optimal experimental design criterion. Materials and methods: Our strategy, called DOPE (D-Optimal Pooling Experimental design), is built on a novel Bayesian formulation of pooling. DOPE defines optimal pooled tests as those maximizing the mutual information between data and infection states. We estimate said mutual information via Monte-Carlo sampling and employ a discrete optimization heuristic to maximize it. Results: We compare DOPE to other, commonly used pooling strategies, as well as to individual testing. DOPE dominates the other strategies as it yields lower error rates while utilizing fewer tests. We show that DOPE maintains this dominance for a variety of infection prevalence values. Discussion: DOPE has several additional advantages over common pooling strategies: it provides posterior distributions of the probability of infection rather than only binary classification outcomes; it naturally incorporates prior information of infection probabilities and test error rates; and finally, it can be easily extended to include other, newly discovered information regarding COVID-19. Conclusion: DOPE can substantially improve accuracy and throughput over current pooling strategies. Hence, DOPE can facilitate rapid testing and aid the efforts of combating COVID-19 and other future pandemics.
MeSH term(s)	Bayes Theorem ; COVID-19 ; Humans ; Pandemics ; Research Design ; SARS-CoV-2
Language	English
Publishing date	2021-08-03
Publishing country	England
Document type	Journal Article
ZDB-ID	1205156-1
ISSN	1527-974X ; 1067-5027
ISSN (online)	1527-974X
ISSN	1067-5027
DOI	10.1093/jamia/ocab169
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Article: An accurate model for SARS-CoV-2 pooled RT-PCR test errors.

Daon, Yair / Huppert, Amit / Obolski, Uri

Royal Society open science

2021 Volume 8, Issue 11, Page(s) 210704

Abstract: Pooling is a method of simultaneously testing multiple samples for the presence of pathogens. Pooling of SARS-CoV-2 tests is increasing in popularity, due to its high testing throughput. A popular pooling scheme is Dorfman pooling: ... ...

Abstract	Pooling is a method of simultaneously testing multiple samples for the presence of pathogens. Pooling of SARS-CoV-2 tests is increasing in popularity, due to its high testing throughput. A popular pooling scheme is Dorfman pooling: test
Language	English
Publishing date	2021-11-03
Publishing country	England
Document type	Journal Article
ZDB-ID	2787755-3
ISSN	2054-5703
ISSN	2054-5703
DOI	10.1098/rsos.210704
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Article: Pneumococcal Competition Modulates Antibiotic Resistance in the Pre-Vaccination Era: A Modelling Study.

Lourenço, José / Daon, Yair / Gori, Andrea / Obolski, Uri

Vaccines

2021 Volume 9, Issue 3

Abstract: The ongoing emergence of antibiotic resistant strains and high frequencies of antibiotic resistance ... ...

Abstract	The ongoing emergence of antibiotic resistant strains and high frequencies of antibiotic resistance of
Language	English
Publishing date	2021-03-16
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2703319-3
ISSN	2076-393X
ISSN	2076-393X
DOI	10.3390/vaccines9030265
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Article ; Online: Estimating COVID-19 outbreak risk through air travel.

Daon, Yair / Thompson, Robin N / Obolski, Uri

Journal of travel medicine

2020 Volume 27, Issue 5

Abstract: Background: Substantial limitations have been imposed on passenger air travel to reduce transmission of severe acute respiratory syndrome coronavirus 2 between regions and countries. However, as case numbers decrease, air travel will gradually resume. ... ...

Abstract	Background: Substantial limitations have been imposed on passenger air travel to reduce transmission of severe acute respiratory syndrome coronavirus 2 between regions and countries. However, as case numbers decrease, air travel will gradually resume. We considered a future scenario in which case numbers are low and air travel returns to normal. Under that scenario, there will be a risk of outbreaks in locations worldwide due to imported cases. We estimated the risk of different locations acting as sources of future coronavirus disease 2019 outbreaks elsewhere. Methods: We use modelled global air travel data and population density estimates from locations worldwide to analyse the risk that 1364 airports are sources of future coronavirus disease 2019 outbreaks. We use a probabilistic, branching-process-based approach that considers the volume of air travelers between airports and the reproduction number at each location, accounting for local population density. Results: Under the scenario we model, we identify airports in East Asia as having the highest risk of acting as sources of future outbreaks. Moreover, we investigate the locations most likely to cause outbreaks due to air travel in regions that are large and potentially vulnerable to outbreaks: India, Brazil and Africa. We find that outbreaks in India and Brazil are most likely to be seeded by individuals travelling from within those regions. We find that this is also true for less vulnerable regions, such as the United States, Europe and China. However, outbreaks in Africa due to imported cases are instead most likely to be initiated by passengers travelling from outside the continent. Conclusions: Variation in flight volumes and destination population densities creates a non-uniform distribution of the risk that different airports pose of acting as the source of an outbreak. Accurate quantification of the spatial distribution of outbreak risk can therefore facilitate optimal allocation of resources for effective targeting of public health interventions.
MeSH term(s)	Africa/epidemiology ; Air Travel ; Airports ; Betacoronavirus ; COVID-19 ; China/epidemiology ; Communicable Diseases, Imported ; Coronavirus Infections/diagnosis ; Coronavirus Infections/epidemiology ; Coronavirus Infections/transmission ; Europe/epidemiology ; Global Health ; Humans ; Pandemics ; Pneumonia, Viral/diagnosis ; Pneumonia, Viral/epidemiology ; Pneumonia, Viral/transmission ; Population Surveillance ; Risk Assessment ; SARS-CoV-2 ; South America/epidemiology ; Travel Medicine ; United States/epidemiology
Keywords	covid19
Language	English
Publishing date	2020-06-04
Publishing country	England
Document type	Journal Article
ZDB-ID	1212504-0
ISSN	1708-8305 ; 1195-1982
ISSN (online)	1708-8305
ISSN	1195-1982
DOI	10.1093/jtm/taaa093
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Article ; Online: The impact of cross-reactive immunity on the emergence of SARS-CoV-2 variants.

Thompson, Robin N / Southall, Emma / Daon, Yair / Lovell-Read, Francesca A / Iwami, Shingo / Thompson, Craig P / Obolski, Uri

Frontiers in immunology

2023 Volume 13, Page(s) 1049458

Abstract: Introduction: A key feature of the COVID-19 pandemic has been the emergence of SARS-CoV-2 variants with different transmission characteristics. However, when a novel variant arrives in a host population, it will not necessarily lead to many cases. ... ...

Abstract	Introduction: A key feature of the COVID-19 pandemic has been the emergence of SARS-CoV-2 variants with different transmission characteristics. However, when a novel variant arrives in a host population, it will not necessarily lead to many cases. Instead, it may fade out, due to stochastic effects and the level of immunity in the population. Immunity against novel SARS-CoV-2 variants may be influenced by prior exposures to related viruses, such as other SARS-CoV-2 variants and seasonal coronaviruses, and the level of cross-reactive immunity conferred by those exposures. Methods: Here, we investigate the impact of cross-reactive immunity on the emergence of SARS-CoV-2 variants in a simplified scenario in which a novel SARS-CoV-2 variant is introduced after an antigenically related virus has spread in the population. We use mathematical modelling to explore the risk that the novel variant invades the population and causes a large number of cases, as opposed to fading out with few cases. Results: We find that, if cross-reactive immunity is complete (i.e. someone infected by the previously circulating virus is not susceptible to the novel variant), the novel variant must be more transmissible than the previous virus to invade the population. However, in a more realistic scenario in which cross-reactive immunity is partial, we show that it is possible for novel variants to invade, even if they are less transmissible than previously circulating viruses. This is because partial cross-reactive immunity effectively increases the pool of susceptible hosts that are available to the novel variant compared to complete cross-reactive immunity. Furthermore, if previous infection with the antigenically related virus assists the establishment of infection with the novel variant, as has been proposed following some experimental studies, then even variants with very limited transmissibility are able to invade the host population. Discussion: Our results highlight that fast assessment of the level of cross-reactive immunity conferred by related viruses against novel SARS-CoV-2 variants is an essential component of novel variant risk assessments.
MeSH term(s)	Humans ; SARS-CoV-2/genetics ; COVID-19 ; Pandemics ; Cross Reactions
Language	English
Publishing date	2023-01-11
Publishing country	Switzerland
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2606827-8
ISSN	1664-3224 ; 1664-3224
ISSN (online)	1664-3224
ISSN	1664-3224
DOI	10.3389/fimmu.2022.1049458
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Book ; Online: DOPE

Daon, Yair / Huppert, Amit / Obolski, Uri

D-Optimal Pooling Experimental design with application for SARS-CoV-2 screening

2021

Abstract: Testing individuals for the presence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the pathogen causing the coronavirus disease 2019 (COVID-19), is crucial for curtailing transmission chains. Moreover, rapidly testing many potentially ... ...

Abstract	Testing individuals for the presence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the pathogen causing the coronavirus disease 2019 (COVID-19), is crucial for curtailing transmission chains. Moreover, rapidly testing many potentially infected individuals is often a limiting factor in controlling COVID-19 outbreaks. Hence, pooling strategies, wherein individuals are grouped and tested simultaneously, are employed. We present a novel pooling strategy that implements D-Optimal Pooling Experimental design (DOPE). DOPE defines optimal pooled tests as those maximizing the mutual information between data and infection states. We estimate said mutual information via Monte-Carlo sampling and employ a discrete optimization heuristic for maximizing it. DOPE outperforms common pooling strategies both in terms of lower error rates and fewer tests utilized. DOPE holds several additional advantages: it provides posterior distributions of the probability of infection, rather than only binary classification outcomes; it naturally incorporates prior information of infection probabilities and test error rates; and finally, it can be easily extended to include other, newly discovered information regarding COVID-19. Hence, we believe that implementation of Bayesian D-optimal experimental design holds a great promise for the efforts of combating COVID-19 and other future pandemics. Comment: 18 pages, 3 figures
Keywords	Statistics - Applications ; Quantitative Biology - Quantitative Methods ; Statistics - Computation ; 62K05 ; 92C60 (Primary) 62C10 (Secondary)
Subject code	310
Publishing date	2021-03-05
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Estimating COVID-19 outbreak risk through air travel

Daon, Yair / Thompson, Robin N / Obolski, Uri

medRxiv

Abstract: Background: COVID-19 has spread rapidly across the globe during the first several months of 2020, creating a pandemic. Substantial, non-discriminatory limitations have been imposed on air travel to inhibit this spread. As the disease prevalence and ... ...

Abstract	Background: COVID-19 has spread rapidly across the globe during the first several months of 2020, creating a pandemic. Substantial, non-discriminatory limitations have been imposed on air travel to inhibit this spread. As the disease prevalence and incidence will decrease, more specific control measures will be sought so that commercial air travel can continue to operate yet not impose a high threat of COVID-19 resurgence. Methods: We use modelled global air travel data and population density estimates to analyse the risk posed by 1364 airports to initiate a COVID-19 outbreak. We calculate the risk using a probabilistic approach that considers the volume of air travelers between airports and the R0 of each location, scaled by population density. This exercise is performed globally as well as specifically for two potentially vulnerable locations: Africa and India. Results: We show that globally, many of the airports posing the highest risk are in China and India. An outbreak of COVID-19 in Africa is most likely to originate in a passenger travelling from Europe. On the other hand, the highest risk to India is from domestic travellers. Our results are robust to changes in the underlying epidemiological assumptions. Conclusions: Variation in flight volumes and destinations creates a non-uniform distribution of the risk different airports pose to resurgence of a COVID-19 outbreak. We suggest the method presented here as a tool for the estimation of this risk. Our method can be used to inform efficient allocation of resources, such as tests identifying infected passengers, so that they could be differentially deployed in various locations.
Keywords	covid19
Language	English
Publishing date	2020-04-20
Publisher	Cold Spring Harbor Laboratory Press
Document type	Article ; Online
DOI	10.1101/2020.04.16.20067496
Database	COVID19

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Article ; Online: Estimating COVID-19 outbreak risk through air travel

Daon, Yair / Thompson, Robin N / Obolski, Uri

Abstract	Background: COVID-19 has spread rapidly across the globe during the first several months of 2020, creating a pandemic. Substantial, non-discriminatory limitations have been imposed on air travel to inhibit this spread. As the disease prevalence and incidence will decrease, more specific control measures will be sought so that commercial air travel can continue to operate yet not impose a high threat of COVID-19 resurgence. Methods: We use modelled global air travel data and population density estimates to analyse the risk posed by 1364 airports to initiate a COVID-19 outbreak. We calculate the risk using a probabilistic approach that considers the volume of air travelers between airports and the R0 of each location, scaled by population density. This exercise is performed globally as well as specifically for two potentially vulnerable locations: Africa and India. Results: We show that globally, many of the airports posing the highest risk are in China and India. An outbreak of COVID-19 in Africa is most likely to originate in a passenger travelling from Europe. On the other hand, the highest risk to India is from domestic travellers. Our results are robust to changes in the underlying epidemiological assumptions. Conclusions: Variation in flight volumes and destinations creates a non-uniform distribution of the risk different airports pose to resurgence of a COVID-19 outbreak. We suggest the method presented here as a tool for the estimation of this risk. Our method can be used to inform efficient allocation of resources, such as tests identifying infected passengers, so that they could be differentially deployed in various locations.
Keywords	covid19
Publisher	MedRxiv; WHO
Document type	Article ; Online
DOI	10.1101/2020.04.16.20067496
Database	COVID19

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Article ; Online: Estimating COVID-19 outbreak risk through air travel

Daon, Yair / Thompson, Robin N / Obolski, Uri

Journal of Travel Medicine

2020 Volume 27, Issue 5

Abstract: Abstract Background Substantial limitations have been imposed on passenger air travel to reduce transmission of severe acute respiratory syndrome coronavirus 2 between regions and countries. However, as case numbers decrease, air travel will gradually ... ...

Abstract	Abstract Background Substantial limitations have been imposed on passenger air travel to reduce transmission of severe acute respiratory syndrome coronavirus 2 between regions and countries. However, as case numbers decrease, air travel will gradually resume. We considered a future scenario in which case numbers are low and air travel returns to normal. Under that scenario, there will be a risk of outbreaks in locations worldwide due to imported cases. We estimated the risk of different locations acting as sources of future coronavirus disease 2019 outbreaks elsewhere. Methods We use modelled global air travel data and population density estimates from locations worldwide to analyse the risk that 1364 airports are sources of future coronavirus disease 2019 outbreaks. We use a probabilistic, branching-process-based approach that considers the volume of air travelers between airports and the reproduction number at each location, accounting for local population density. Results Under the scenario we model, we identify airports in East Asia as having the highest risk of acting as sources of future outbreaks. Moreover, we investigate the locations most likely to cause outbreaks due to air travel in regions that are large and potentially vulnerable to outbreaks: India, Brazil and Africa. We find that outbreaks in India and Brazil are most likely to be seeded by individuals travelling from within those regions. We find that this is also true for less vulnerable regions, such as the United States, Europe and China. However, outbreaks in Africa due to imported cases are instead most likely to be initiated by passengers travelling from outside the continent. Conclusions Variation in flight volumes and destination population densities creates a non-uniform distribution of the risk that different airports pose of acting as the source of an outbreak. Accurate quantification of the spatial distribution of outbreak risk can therefore facilitate optimal allocation of resources for effective targeting of public health interventions.
Keywords	General Medicine ; covid19
Language	English
Publisher	Oxford University Press (OUP)
Publishing country	uk
Document type	Article ; Online
ZDB-ID	1212504-0
ISSN	1708-8305 ; 1195-1982
ISSN (online)	1708-8305
ISSN	1195-1982
DOI	10.1093/jtm/taaa093
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Assessing COVID-19 vaccination strategies in varied demographics using an individual-based model.

Ben-Zuk, Noam / Daon, Yair / Sasson, Amit / Ben-Adi, Dror / Huppert, Amit / Nevo, Daniel / Obolski, Uri

Frontiers in public health

2022 Volume 10, Page(s) 966756

Abstract: Background: New variants of SARS-CoV-2 are constantly discovered. Administration of COVID-19 vaccines and booster doses, combined with the application of non-pharmaceutical interventions (NPIs: Methods: We developed an individual-based model of COVID- ...

Abstract	Background: New variants of SARS-CoV-2 are constantly discovered. Administration of COVID-19 vaccines and booster doses, combined with the application of non-pharmaceutical interventions (NPIs Methods: We developed an individual-based model of COVID-19 dynamics that considers age-dependent parameters such as contact matrices, probabilities of symptomatic and severe disease, and households' age distribution. As a case study, we simulate outbreak dynamics under the demographic compositions of two Israeli cities with different household sizes and age distributions. We compare two vaccination strategies: vaccinate individuals in a currently prioritized age group, or dynamically prioritize neighborhoods with a high estimated reproductive number. Total infections and hospitalizations are used to compare the efficiency of the vaccination strategies under the two demographic structures, in conjunction with different NPIs. Results: We demonstrate the effectiveness of vaccination strategies targeting highly infected localities and of NPIs actively detecting asymptomatic infections. We further show that different optimal vaccination strategies exist for each sub-population's demographic composition and that their application is superior to a uniformly applied strategy. Conclusion: Our study emphasizes the importance of tailoring vaccination strategies to subpopulations' infection rates and to the unique characteristics of their demographics (e.g., household size and age distributions). The presented simulation framework and findings can help better design future responses against the following emerging variants.
MeSH term(s)	COVID-19/epidemiology ; COVID-19/prevention & control ; COVID-19 Vaccines ; Demography ; Humans ; SARS-CoV-2 ; Vaccination
Chemical Substances	COVID-19 Vaccines
Language	English
Publishing date	2022-09-15
Publishing country	Switzerland
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2711781-9
ISSN	2296-2565 ; 2296-2565
ISSN (online)	2296-2565
ISSN	2296-2565
DOI	10.3389/fpubh.2022.966756
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