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Article: Use of Bluetooth contact tracing technology to model COVID-19 quarantine policies in high-risk closed populations.

Sun, Yinxiaohe / Koo, Joel Ruihan / Park, Minah / Yi, Huso / Dickens, Borame L / Cook, Alex R

2023 Volume 9, Page(s) 20552076231178418

Abstract: Containment measures in high-risk closed settings, like migrant worker (MW) dormitories, are critical for mitigating emerging infectious disease outbreaks and protecting potentially vulnerable populations in outbreaks such as coronavirus disease 2019 ( ... ...

Abstract	Containment measures in high-risk closed settings, like migrant worker (MW) dormitories, are critical for mitigating emerging infectious disease outbreaks and protecting potentially vulnerable populations in outbreaks such as coronavirus disease 2019 (COVID-19). The direct impact of social distancing measures can be assessed through wearable contact tracing devices. Here, we developed an individual-based model using data collected through a Bluetooth wearable device that collected 33.6M and 52.8M contact events in two dormitories in Singapore, one apartment style and the other a barrack style, to assess the impact of measures to reduce the social contact of cases and their contacts. The simulation of highly detailed contact networks accounts for different infrastructural levels, including room, floor, block, and dormitory, and intensity in terms of being regular or transient. Via a branching process model, we then simulated outbreaks that matched the prevalence during the COVID-19 outbreak in the two dormitories and explored alternative scenarios for control. We found that strict isolation of all cases and quarantine of all contacts would lead to very low prevalence but that quarantining only regular contacts would lead to only marginally higher prevalence but substantially fewer total man-hours lost in quarantine. Reducing the density of contacts by 30% through the construction of additional dormitories was modelled to reduce the prevalence by 14 and 9% under smaller and larger outbreaks, respectively. Wearable contact tracing devices may be used not just for contact tracing efforts but also to inform alternative containment measures in high-risk closed settings.
Language	English
Publishing date	2023-06-08
Publishing country	United States
Document type	Journal Article
ZDB-ID	2819396-9
ISSN	2055-2076
ISSN	2055-2076
DOI	10.1177/20552076231178418
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: ChampKit: A framework for rapid evaluation of deep neural networks for patch-based histopathology classification.

Kaczmarzyk, Jakub R / Gupta, Rajarsi / Kurc, Tahsin M / Abousamra, Shahira / Saltz, Joel H / Koo, Peter K

Computer methods and programs in biomedicine

2023 Volume 239, Page(s) 107631

Abstract: Background and objective: Histopathology is the gold standard for diagnosis of many cancers. Recent advances in computer vision, specifically deep learning, have facilitated the analysis of histopathology images for many tasks, including the detection ... ...

Abstract	Background and objective: Histopathology is the gold standard for diagnosis of many cancers. Recent advances in computer vision, specifically deep learning, have facilitated the analysis of histopathology images for many tasks, including the detection of immune cells and microsatellite instability. However, it remains difficult to identify optimal models and training configurations for different histopathology classification tasks due to the abundance of available architectures and the lack of systematic evaluations. Our objective in this work is to present a software tool that addresses this need and enables robust, systematic evaluation of neural network models for patch classification in histology in a light-weight, easy-to-use package for both algorithm developers and biomedical researchers. Methods: Here we present ChampKit (Comprehensive Histopathology Assessment of Model Predictions toolKit): an extensible, fully reproducible evaluation toolkit that is a one-stop-shop to train and evaluate deep neural networks for patch classification. ChampKit curates a broad range of public datasets. It enables training and evaluation of models supported by timm directly from the command line, without the need for users to write any code. External models are enabled through a straightforward API and minimal coding. As a result, Champkit facilitates the evaluation of existing and new models and deep learning architectures on pathology datasets, making it more accessible to the broader scientific community. To demonstrate the utility of ChampKit, we establish baseline performance for a subset of possible models that could be employed with ChampKit, focusing on several popular deep learning models, namely ResNet18, ResNet50, and R26-ViT, a hybrid vision transformer. In addition, we compare each model trained either from random weight initialization or with transfer learning from ImageNet pretrained models. For ResNet18, we also consider transfer learning from a self-supervised pretrained model. Results: The main result of this paper is the ChampKit software. Using ChampKit, we were able to systemically evaluate multiple neural networks across six datasets. We observed mixed results when evaluating the benefits of pretraining versus random intialization, with no clear benefit except in the low data regime, where transfer learning was found to be beneficial. Surprisingly, we found that transfer learning from self-supervised weights rarely improved performance, which is counter to other areas of computer vision. Conclusions: Choosing the right model for a given digital pathology dataset is nontrivial. ChampKit provides a valuable tool to fill this gap by enabling the evaluation of hundreds of existing (or user-defined) deep learning models across a variety of pathology tasks. Source code and data for the tool are freely accessible at https://github.com/SBU-BMI/champkit.
MeSH term(s)	Humans ; Neural Networks, Computer ; Algorithms ; Software ; Neoplasms ; Histological Techniques
Language	English
Publishing date	2023-05-30
Publishing country	Ireland
Document type	Journal Article
ZDB-ID	632564-6
ISSN	1872-7565 ; 0169-2607
ISSN (online)	1872-7565
ISSN	0169-2607
DOI	10.1016/j.cmpb.2023.107631
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Article ; Online: Modelling the Impact of Mass Testing to Transition from Pandemic Mitigation to Endemic COVID-19.

Koo, Joel R / Cook, Alex R / Lim, Jue Tao / Tan, Ken Wei / Dickens, Borame L

Viruses

2022 Volume 14, Issue 5

Abstract: ... the impact on the healthcare system of the liminal wave. We used GeoDEMOS-R, an agent-based model ...

Abstract	As countries transition from pandemic mitigation to endemic COVID-19, mass testing may blunt the impact on the healthcare system of the liminal wave. We used GeoDEMOS-R, an agent-based model of Singapore's population with demographic distributions and vaccination status. A 250-day COVID-19 Delta variant model was run at varying maximal rapid antigen test sensitivities and frequencies. Without testing, the number of infections reached 1,021,000 (899,400-1,147,000) at 250 days. When conducting fortnightly and weekly mass routine rapid antigen testing 30 days into the outbreak at a maximal test sensitivity of 0.6, this was reduced by 12.8% (11.3-14.5%) and 25.2% (22.5-28.5%). An increase in maximal test sensitivity of 0.2 results a corresponding reduction of 17.5% (15.5-20.2%) and 34.4% (30.5-39.1%). Within the maximal test sensitivity range of 0.6-0.8, test frequency has a greater impact than maximal test sensitivity with an average reduction of 2.2% in infections for each day removed between tests in comparison to a 0.43% average reduction per 1% increase in test frequency. Our findings highlight that mass testing using rapid diagnostic tests can be used as an effective intervention for countries transitioning from pandemic mitigation to endemic COVID-19.
MeSH term(s)	COVID-19/diagnosis ; COVID-19/epidemiology ; COVID-19/prevention & control ; Disease Outbreaks ; Humans ; Pandemics/prevention & control ; SARS-CoV-2
Language	English
Publishing date	2022-05-05
Publishing country	Switzerland
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2516098-9
ISSN	1999-4915 ; 1999-4915
ISSN (online)	1999-4915
ISSN	1999-4915
DOI	10.3390/v14050967
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Article ; Online: Application of the network scale-up method to estimate the sizes of key populations for HIV in Singapore using online surveys.

Quaye, Sharon Esi Duoduwa / Cheng, Yuwei / Tan, Rayner Kay Jin / Koo, Joel R / Prem, Kiesha / Teo, Alvin Kuo Jing / Cook, Alex R

Journal of the International AIDS Society

2023 Volume 26, Issue 3, Page(s) e25973

Abstract: Introduction: Singapore lacks robust data on the sizes of the key populations that are most at risk for HIV. Using the network scale-up method for hidden or hard-to-reach populations, we estimate the sizes of five key populations-male clients of female ... ...

Abstract	Introduction: Singapore lacks robust data on the sizes of the key populations that are most at risk for HIV. Using the network scale-up method for hidden or hard-to-reach populations, we estimate the sizes of five key populations-male clients of female sex workers (MCFSW), men who have sex with men (MSM), female sex workers (FSW), people who inject drugs (PWID) and transgender people-and profile the ages and ethnicities of respondents with the high-risk contacts they report knowing. Methods: We conducted a cross-sectional online survey between March and May 2019 (n = 2802) using a network scale-up instrument previously developed for Singapore. Participants were recruited using an existing panel and online advertising, and the sample reweighted by age, sex, ethnicity and education attained to represent the general adult population. We built a Bayesian hierarchical model to estimate the sizes of the five key populations for HIV in Singapore. Results: After adjustment, the sizes of the at-risk populations are estimated to be: 76,800 (95% credible interval [CI]: 64,200-91,800) MCFSW; 139,000 (95% CI: 120,000-160,000) MSM; 8030 (95% CI: 3980-16,200) FSW; 3470 (95% CI: 1540-7830) PWID and 18,000 (95% CI: 14,000-23,200) transgender people. Generally, men reported knowing more people in all the high-risk groups; older people reported knowing more MCFSW, FSW and transgender people; and younger people reported knowing more MSM. There was a bimodal effect of age on those who reported knowing more PWIDs: people in their 20s and 60s reported more contacts. Conclusions: This study demonstrates that a size estimation study of hidden populations is quickly and efficiently scalable through using online surveys in a socially conservative society, like Singapore, where key populations are stigmatized or criminalized. The approach may be suitable in other countries where stigma is prevalent and where barriers to surveillance and data collection are numerous.
MeSH term(s)	Adult ; Male ; Humans ; Female ; Aged ; Homosexuality, Male ; HIV Infections/epidemiology ; Sexual and Gender Minorities ; Cross-Sectional Studies ; Singapore/epidemiology ; Substance Abuse, Intravenous ; Bayes Theorem ; Sex Workers ; Surveys and Questionnaires
Language	English
Publishing date	2023-04-03
Publishing country	Switzerland
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2467110-1
ISSN	1758-2652 ; 1758-2652
ISSN (online)	1758-2652
ISSN	1758-2652
DOI	10.1002/jia2.25973
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Short-term and long-term epidemiological impacts of sustained vector control in various dengue endemic settings: A modelling study.

Sun, Haoyang / Koo, Joel / Dickens, Borame L / Clapham, Hannah E / Cook, Alex R

PLoS computational biology

2022 Volume 18, Issue 4, Page(s) e1009979

Abstract: As the most widespread viral infection transmitted by the Aedes mosquitoes, dengue has been estimated to cause 51 million febrile disease cases globally each year. Although sustained vector control remains key to reducing the burden of dengue, current ... ...

Abstract	As the most widespread viral infection transmitted by the Aedes mosquitoes, dengue has been estimated to cause 51 million febrile disease cases globally each year. Although sustained vector control remains key to reducing the burden of dengue, current understanding of the key factors that explain the observed variation in the short- and long-term vector control effectiveness across different transmission settings remains limited. We used a detailed individual-based model to simulate dengue transmission with and without sustained vector control over a 30-year time frame, under different transmission scenarios. Vector control effectiveness was derived for different time windows within the 30-year intervention period. We then used the extreme gradient boosting algorithm to predict the effectiveness of vector control given the simulation parameters, and the resulting machine learning model was interpreted using Shapley Additive Explanations. According to our simulation outputs, dengue transmission would be nearly eliminated during the early stage of sustained and intensive vector control, but over time incidence would gradually bounce back to the pre-intervention level unless the intervention is implemented at a very high level of intensity. The time point at which intervention ceases to be effective is strongly influenced not only by the intensity of vector control, but also by the pre-intervention transmission intensity and the individual-level heterogeneity in biting risk. Moreover, the impact of many transmission model parameters on the intervention effectiveness is shown to be modified by the intensity of vector control, as well as to vary over time. Our study has identified some of the critical drivers for the difference in the time-varying effectiveness of sustained vector control across different dengue endemic settings, and the insights obtained will be useful to inform future model-based studies that seek to predict the impact of dengue vector control in their local contexts.
MeSH term(s)	Aedes ; Animals ; Computer Simulation ; Dengue/epidemiology ; Dengue/prevention & control ; Incidence ; Mosquito Vectors
Language	English
Publishing date	2022-04-01
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2193340-6
ISSN	1553-7358 ; 1553-734X
ISSN (online)	1553-7358
ISSN	1553-734X
DOI	10.1371/journal.pcbi.1009979
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Article ; Online: Use of Bluetooth contact tracing technology to model COVID-19 quarantine policies in high-risk closed populations

Yinxiaohe Sun / Joel Ruihan Koo / Minah Park / Huso Yi / Borame L Dickens / Alex R Cook

Digital Health, Vol

2023 Volume 9

Abstract	Containment measures in high-risk closed settings, like migrant worker (MW) dormitories, are critical for mitigating emerging infectious disease outbreaks and protecting potentially vulnerable populations in outbreaks such as coronavirus disease 2019 (COVID-19). The direct impact of social distancing measures can be assessed through wearable contact tracing devices. Here, we developed an individual-based model using data collected through a Bluetooth wearable device that collected 33.6M and 52.8M contact events in two dormitories in Singapore, one apartment style and the other a barrack style, to assess the impact of measures to reduce the social contact of cases and their contacts. The simulation of highly detailed contact networks accounts for different infrastructural levels, including room, floor, block, and dormitory, and intensity in terms of being regular or transient. Via a branching process model, we then simulated outbreaks that matched the prevalence during the COVID-19 outbreak in the two dormitories and explored alternative scenarios for control. We found that strict isolation of all cases and quarantine of all contacts would lead to very low prevalence but that quarantining only regular contacts would lead to only marginally higher prevalence but substantially fewer total man-hours lost in quarantine. Reducing the density of contacts by 30% through the construction of additional dormitories was modelled to reduce the prevalence by 14 and 9% under smaller and larger outbreaks, respectively. Wearable contact tracing devices may be used not just for contact tracing efforts but also to inform alternative containment measures in high-risk closed settings.
Keywords	Computer applications to medicine. Medical informatics ; R858-859.7
Subject code	600
Language	English
Publishing date	2023-06-01T00:00:00Z
Publisher	SAGE Publishing
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Short-term and long-term epidemiological impacts of sustained vector control in various dengue endemic settings

Haoyang Sun / Joel Koo / Borame L Dickens / Hannah E Clapham / Alex R Cook

PLoS Computational Biology, Vol 18, Iss 4, p e

A modelling study.

2022 Volume 1009979

Abstract	As the most widespread viral infection transmitted by the Aedes mosquitoes, dengue has been estimated to cause 51 million febrile disease cases globally each year. Although sustained vector control remains key to reducing the burden of dengue, current understanding of the key factors that explain the observed variation in the short- and long-term vector control effectiveness across different transmission settings remains limited. We used a detailed individual-based model to simulate dengue transmission with and without sustained vector control over a 30-year time frame, under different transmission scenarios. Vector control effectiveness was derived for different time windows within the 30-year intervention period. We then used the extreme gradient boosting algorithm to predict the effectiveness of vector control given the simulation parameters, and the resulting machine learning model was interpreted using Shapley Additive Explanations. According to our simulation outputs, dengue transmission would be nearly eliminated during the early stage of sustained and intensive vector control, but over time incidence would gradually bounce back to the pre-intervention level unless the intervention is implemented at a very high level of intensity. The time point at which intervention ceases to be effective is strongly influenced not only by the intensity of vector control, but also by the pre-intervention transmission intensity and the individual-level heterogeneity in biting risk. Moreover, the impact of many transmission model parameters on the intervention effectiveness is shown to be modified by the intensity of vector control, as well as to vary over time. Our study has identified some of the critical drivers for the difference in the time-varying effectiveness of sustained vector control across different dengue endemic settings, and the insights obtained will be useful to inform future model-based studies that seek to predict the impact of dengue vector control in their local contexts.
Keywords	Biology (General) ; QH301-705.5
Subject code	330
Language	English
Publishing date	2022-04-01T00:00:00Z
Publisher	Public Library of Science (PLoS)
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Importance of Geospatial Heterogeneity in Chronic Disease Burden for Policy Planning in an Urban Setting Using a Case Study of Singapore.

Tan, Ken Wei / Koo, Joel R / Lim, Jue Tao / Cook, Alex R / Dickens, Borame L

International journal of environmental research and public health

2021 Volume 18, Issue 9

Abstract: Chronic disease burdens continue to rise in highly dense urban environments where clustering of type II diabetes mellitus, acute myocardial infarction, stroke, or any combination of these three conditions is occurring. Many individuals suffering from ... ...

Abstract	Chronic disease burdens continue to rise in highly dense urban environments where clustering of type II diabetes mellitus, acute myocardial infarction, stroke, or any combination of these three conditions is occurring. Many individuals suffering from these conditions will require longer-term care and access to clinics which specialize in managing their illness. With Singapore as a case study, we utilized census data in an agent-modeling approach at an individual level to estimate prevalence in 2020 and found high-risk clusters with >14,000 type II diabetes mellitus cases and 2000-2500 estimated stroke cases. For comorbidities, 10% of those with type II diabetes mellitus had a past acute myocardial infarction episode, while 6% had a past stroke. The western region of Singapore had the highest number of high-risk individuals at 173,000 with at least one chronic condition, followed by the east at 169,000 and the north with the least at 137,000. Such estimates can assist in healthcare resource planning, which requires these spatial distributions for evidence-based policymaking and to investigate why such heterogeneities exist. The methodologies presented can be utilized within any urban setting where census data exists.
MeSH term(s)	Chronic Disease ; Cost of Illness ; Diabetes Mellitus, Type 2/epidemiology ; Humans ; Policy ; Singapore/epidemiology
Language	English
Publishing date	2021-04-21
Publishing country	Switzerland
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ISSN	1660-4601
ISSN (online)	1660-4601
DOI	10.3390/ijerph18094406
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Institutional, not home-based, isolation could contain the COVID-19 outbreak.

Dickens, Borame L / Koo, Joel R / Wilder-Smith, Annelies / Cook, Alex R

Lancet (London, England)

2020 Volume 395, Issue 10236, Page(s) 1541–1542

MeSH term(s)	Betacoronavirus ; COVID-19 ; Coronavirus ; Coronavirus Infections ; Humans ; Pandemics ; Pneumonia, Viral ; Public Health ; Quarantine ; SARS-CoV-2
Keywords	covid19
Language	English
Publishing date	2020-04-29
Publishing country	England
Document type	Letter ; Comment
ZDB-ID	3306-6
ISSN	1474-547X ; 0023-7507 ; 0140-6736
ISSN (online)	1474-547X
ISSN	0023-7507 ; 0140-6736
DOI	10.1016/S0140-6736(20)31016-3
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Article ; Online: Testing strategies to contain COVID-19 in migrant worker dormitories.

Koo, Joel R / Dickens, Borame L / Jin, Shihui / Lim, Jue Tao / Sun, Yinxiaohe / Tan, Ken Wei / Cook, Alex R

Journal of migration and health

2022 Volume 5, Page(s) 100079

Abstract: Introduction: COVID-19 transmission within overcrowded migrant worker dormitories is an ongoing global issue. Many countries have implemented extensive control measures to prevent the entire migrant worker population from becoming infected. Here, we ... ...

Abstract	Introduction: COVID-19 transmission within overcrowded migrant worker dormitories is an ongoing global issue. Many countries have implemented extensive control measures to prevent the entire migrant worker population from becoming infected. Here, we explore case count outcomes when utilizing lockdown and testing under different testing measures and transmissibility settings. Methods: We built a mathematical model which estimates transmission across 10 different blocks with 1000 individuals per block under different parameter combinations and testing conditions over the period of 1 month. We vary parameters including differences in block connectivity, underlying recovered proportions at the time of intervention, case importation rates and testing protocols using either PCR or rapid antigen testing. Results: We estimate that a relatively transmissible environment with fortnightly PCR testing at a relatively low initial recovered proportion of 40%, low connectivity where 10% of contacts occurred outside of the infected individuals' block and a high importation rate of Interpretation: Our findings support the need for either fortnightly PCR testing or weekly rapid antigen testing in high population density environments such as migrant worker dormitories. Repeated mass testing is highly effective, preventing localized site outbreaks and reducing the need for site wide lockdowns or other extensive social distancing measures within and outside of dormitories.
Language	English
Publishing date	2022-01-21
Publishing country	England
Document type	Journal Article
ISSN	2666-6235
ISSN (online)	2666-6235
DOI	10.1016/j.jmh.2022.100079
Database	MEDical Literature Analysis and Retrieval System OnLINE

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