Introduction:Contact tracing has been a key tool to contain the spread of diseases and was widely used by countries during the COVID-19 pandemic.However,evaluating the effectiveness of contact tracing has been challen...Introduction:Contact tracing has been a key tool to contain the spread of diseases and was widely used by countries during the COVID-19 pandemic.However,evaluating the effectiveness of contact tracing has been challenging.Approaches to contact tracing were diverse and country-dependent,with operations utilizing different tracing methods under varied environments.To provide guidance on contact tracing for future preparedness,we assessed the effectiveness of contact tracing methods under varied environments using Singapore's population structure and COVID-19 as the disease model.Methods:We developed a transmission network model using Singapore's contact tracing data and the characteristics of COVID-19 disease.We explored three different tracing methods that could be employed by contact tracing operations:forward tracing,extended tracing and cluster tracing.The forward tracing method covered the period starting two days before case isolation,the extended tracing method covered the period starting 16 days before case isolation,and the cluster tracing method combined forward tracing with cluster identification.Contact tracing operations traced detected cases from surveillance and issued interventions for identified contacts,and we constructed combinations of varied scenarios to replicate variability during pandemic,namely low case-ascertainment or high case-ascertainment and either testing of contacts or quarantine of contacts.We examined the impact of varied contact tracing operations on disease transmission and provider costs.Results:Model simulations showed that the effectiveness of contact tracing methods varied under the four different scenarios.Firstly,under low case-ascertainment with testing of contacts,contact tracing reduced transmission by 12%-22%,with provider costs ranging between US$2943.56 to US$5226.82 per infection prevented.The most effective tracing method to control infection was cluster tracing,followed by extended tracing and forward tracing.Secondly,under low case-ascertainment with quarantine of contacts,transmission was reduced by 46%-62%,with provider costs below US$4000 per infection prevented.The cluster method reduced transmission by 62%,enough to bring the reproduction number to close to unity and was the least costly.Extended tracing reduced transmission by 50%but costed the most,while forward tracing reduced transmission by 46%.Thirdly,under high case-ascertainment with testing of contacts,the average transmission was reduced by 20%-26%,with provider costs to prevent an infection ranging between US$1872.72 to US$3165.09.There was less variability between tracing methods,with cluster tracing reducing transmission the most,followed by extended tracing and forward tracing.Lastly,under high case-ascertainment and quarantine of contacts,contact tracing was the most effective,with provider costs below US$800 per infection prevented.All tracing methods were equally effective in disease containment,bringing the reproduction number below unity and stopping disease transmission early.Discussion:We conclude that contact tracing operated most effectively when implemented with high case-ascertainment rates and quarantine of contacts;disease transmission is stopped early,and the low number of contacts enable tracing operations to be more manageable and less costly.However,the pandemic situation can be dynamic,with fluctuations in resources available for case-ascertainment and quarantine adherence,which can impact the effectiveness of contact tracing.Adapting contact tracing methods to the situation can optimize disease control.Therefore,it is recommended to develop a flexible contact tracing approach that facilitates strategy switching based on resource availability and the skills of tracing operations.展开更多
Transmission potential of a pathogen,often quantified by the time-varying reproduction number R t,provides the current pace of infection for a disease and indicates whether an emerging epidemic is under control.In thi...Transmission potential of a pathogen,often quantified by the time-varying reproduction number R t,provides the current pace of infection for a disease and indicates whether an emerging epidemic is under control.In this study,we proposed a novel method,EpiMix,for R t estimation,wherein we incorporated the impacts of exogenous factors and random effects under a Bayesian regression framework.Using Integrated Nested Laplace Approx-imation,EpiMix is able to efficiently generate reliable,deterministic R t estimates.In the simulations and case studies performed,we further demonstrated the method's robust-ness in low-incidence scenarios,together with other merits,including its flexibility in selecting variables and tolerance of varying reporting rates.All these make EpiMix a potentially useful tool for real-time R t estimation provided that the serial interval distri-bution,time series of case counts and external influencing factors are available.展开更多
Background.Continuous glucose monitoring(CGM)offers an opportunity for patients with diabetes to modify their lifestyle tobetter manage their condition and for clinicians to provide personalized healthcare and lifesty...Background.Continuous glucose monitoring(CGM)offers an opportunity for patients with diabetes to modify their lifestyle tobetter manage their condition and for clinicians to provide personalized healthcare and lifestyle advice.However,analytic toolsare needed to standardize and analyze the rich data that emerge from CGM devices.This would allow glucotypes of patients tobe identified to aid clinical decision-making.Methods.In this paper,we develop an analysis pipeline for CGM data and applyit to 148 diabetic patients with a total of 8632 days of follow up.The pipeline projects CGM data to a lower-dimensional spaceof features representing centrality,spread,size,and duration of glycemic excursions and the circadian cycle.We then useprincipal components analysis and k-means to cluster patients’records into one of four glucotypes and analyze clustermembership using multinomial logistic regression.Results.Glucotypes differ in the degree of control,amount of time spent inrange,and on the presence and timing of hyper-and hypoglycemia.Patients on the program had statistically significantimprovements in their glucose levels.Conclusions.This pipeline provides a fast automatic function to label raw CGM datawithout manual input.展开更多
Background.Limited evidence on the effectiveness of various types of social distancing measures,from voluntary physical distancing to a community-wide quarantine,exists for the Western Pacific Region(WPR)which has lar...Background.Limited evidence on the effectiveness of various types of social distancing measures,from voluntary physical distancing to a community-wide quarantine,exists for the Western Pacific Region(WPR)which has large urban and rural populations.Methods.We estimated the time-varying reproduction number(Rt)in a Bayesian framework using district-level mobility data provided by Facebook(i)to assess how various social distancing policies have contributed to the reduction in transmissibility of SARS-COV-2 and(ii)to examine within-country variations in behavioural responses,quantified by reductions in mobility,for urban and rural areas.Results.Social distancing measures were largely effective in reducing transmissibility,with Rt estimates decreased to around the threshold of 1.Within-country analysis showed substantial variation in public compliance across regions.Reductions in mobility were significantly lower in rural and remote areas than in urban areas and metropolitan cities(p<0:001)which had the same scale of social distancing orders in place.Conclusions.Our findings provide empirical evidence that public compliance and consequent intervention effectiveness differ between urban and rural areas in the WPR.Further work is required to ascertain the factors affecting these differing behavioural responses,which can assist in policy-making efforts and increase public compliance in rural areas where populations are older and have poorer access to healthcare.展开更多
基金supported by the Singapore Ministry of Health's National Medical Research Council under its National Epidemic Preparedness and Response R&D Funding Initiative(MOH-001041)Programme for Research in Epidemic Preparedness And REsponse(PREPARE).
文摘Introduction:Contact tracing has been a key tool to contain the spread of diseases and was widely used by countries during the COVID-19 pandemic.However,evaluating the effectiveness of contact tracing has been challenging.Approaches to contact tracing were diverse and country-dependent,with operations utilizing different tracing methods under varied environments.To provide guidance on contact tracing for future preparedness,we assessed the effectiveness of contact tracing methods under varied environments using Singapore's population structure and COVID-19 as the disease model.Methods:We developed a transmission network model using Singapore's contact tracing data and the characteristics of COVID-19 disease.We explored three different tracing methods that could be employed by contact tracing operations:forward tracing,extended tracing and cluster tracing.The forward tracing method covered the period starting two days before case isolation,the extended tracing method covered the period starting 16 days before case isolation,and the cluster tracing method combined forward tracing with cluster identification.Contact tracing operations traced detected cases from surveillance and issued interventions for identified contacts,and we constructed combinations of varied scenarios to replicate variability during pandemic,namely low case-ascertainment or high case-ascertainment and either testing of contacts or quarantine of contacts.We examined the impact of varied contact tracing operations on disease transmission and provider costs.Results:Model simulations showed that the effectiveness of contact tracing methods varied under the four different scenarios.Firstly,under low case-ascertainment with testing of contacts,contact tracing reduced transmission by 12%-22%,with provider costs ranging between US$2943.56 to US$5226.82 per infection prevented.The most effective tracing method to control infection was cluster tracing,followed by extended tracing and forward tracing.Secondly,under low case-ascertainment with quarantine of contacts,transmission was reduced by 46%-62%,with provider costs below US$4000 per infection prevented.The cluster method reduced transmission by 62%,enough to bring the reproduction number to close to unity and was the least costly.Extended tracing reduced transmission by 50%but costed the most,while forward tracing reduced transmission by 46%.Thirdly,under high case-ascertainment with testing of contacts,the average transmission was reduced by 20%-26%,with provider costs to prevent an infection ranging between US$1872.72 to US$3165.09.There was less variability between tracing methods,with cluster tracing reducing transmission the most,followed by extended tracing and forward tracing.Lastly,under high case-ascertainment and quarantine of contacts,contact tracing was the most effective,with provider costs below US$800 per infection prevented.All tracing methods were equally effective in disease containment,bringing the reproduction number below unity and stopping disease transmission early.Discussion:We conclude that contact tracing operated most effectively when implemented with high case-ascertainment rates and quarantine of contacts;disease transmission is stopped early,and the low number of contacts enable tracing operations to be more manageable and less costly.However,the pandemic situation can be dynamic,with fluctuations in resources available for case-ascertainment and quarantine adherence,which can impact the effectiveness of contact tracing.Adapting contact tracing methods to the situation can optimize disease control.Therefore,it is recommended to develop a flexible contact tracing approach that facilitates strategy switching based on resource availability and the skills of tracing operations.
基金suppoted by Singapore’s Ministry of Education(through a Tier 1 grant),the National University of Singapore(through a Reimagine Research grant),and the Singapore Ministry of Health’s National Medical Research Council under its National Epidemic Preparedness and Response R&D Funding Initiative(MOH-001041)Programme for Research in Epidemic Preparedness And REsponse(PREPARE).
文摘Transmission potential of a pathogen,often quantified by the time-varying reproduction number R t,provides the current pace of infection for a disease and indicates whether an emerging epidemic is under control.In this study,we proposed a novel method,EpiMix,for R t estimation,wherein we incorporated the impacts of exogenous factors and random effects under a Bayesian regression framework.Using Integrated Nested Laplace Approx-imation,EpiMix is able to efficiently generate reliable,deterministic R t estimates.In the simulations and case studies performed,we further demonstrated the method's robust-ness in low-incidence scenarios,together with other merits,including its flexibility in selecting variables and tolerance of varying reporting rates.All these make EpiMix a potentially useful tool for real-time R t estimation provided that the serial interval distri-bution,time series of case counts and external influencing factors are available.
基金the Singapore Population Health Improvement Centre(NMRC/CG/C026/2017_NUHS)(to YM,SAT,and ARC).
文摘Background.Continuous glucose monitoring(CGM)offers an opportunity for patients with diabetes to modify their lifestyle tobetter manage their condition and for clinicians to provide personalized healthcare and lifestyle advice.However,analytic toolsare needed to standardize and analyze the rich data that emerge from CGM devices.This would allow glucotypes of patients tobe identified to aid clinical decision-making.Methods.In this paper,we develop an analysis pipeline for CGM data and applyit to 148 diabetic patients with a total of 8632 days of follow up.The pipeline projects CGM data to a lower-dimensional spaceof features representing centrality,spread,size,and duration of glycemic excursions and the circadian cycle.We then useprincipal components analysis and k-means to cluster patients’records into one of four glucotypes and analyze clustermembership using multinomial logistic regression.Results.Glucotypes differ in the degree of control,amount of time spent inrange,and on the presence and timing of hyper-and hypoglycemia.Patients on the program had statistically significantimprovements in their glucose levels.Conclusions.This pipeline provides a fast automatic function to label raw CGM datawithout manual input.
基金MP,JTL,ARC,and BLD have received study funding from Singapore Population Health Improvement Centre(NMRC/CG/C026/2017_NUHS)the COVID-19 grant(COVID19RF-004)+1 种基金LW has received funding from the European Research Council(grant no.804744)the EPSRC Impact Acceleration Grant(RG90413).
文摘Background.Limited evidence on the effectiveness of various types of social distancing measures,from voluntary physical distancing to a community-wide quarantine,exists for the Western Pacific Region(WPR)which has large urban and rural populations.Methods.We estimated the time-varying reproduction number(Rt)in a Bayesian framework using district-level mobility data provided by Facebook(i)to assess how various social distancing policies have contributed to the reduction in transmissibility of SARS-COV-2 and(ii)to examine within-country variations in behavioural responses,quantified by reductions in mobility,for urban and rural areas.Results.Social distancing measures were largely effective in reducing transmissibility,with Rt estimates decreased to around the threshold of 1.Within-country analysis showed substantial variation in public compliance across regions.Reductions in mobility were significantly lower in rural and remote areas than in urban areas and metropolitan cities(p<0:001)which had the same scale of social distancing orders in place.Conclusions.Our findings provide empirical evidence that public compliance and consequent intervention effectiveness differ between urban and rural areas in the WPR.Further work is required to ascertain the factors affecting these differing behavioural responses,which can assist in policy-making efforts and increase public compliance in rural areas where populations are older and have poorer access to healthcare.
