Kidney function trajectories, associated factors, and outcomes in multiethnic Asian patients with type 2 diabetes.

Background: We examined the trajectory of estimated glomerular filtrate rate (eGFR), associated risk factors, and its relationship with end-stage kidney disease (ESKD) among a multiethnic patient population with type 2 diabetes in Singapore.

Methods: A follow-up study included 62 080 individuals with type 2 diabetes aged ≥18 years in a multi-institutional SingHealth Diabetes Registry between 2013 and 2019. eGFR trajectories were analyzed using latent class linear mixed models.

Associations between sleep trajectories up to 54 months and cognitive school readiness in 4 year old preschool children.

Purpose: This study explores the association between the duration and variation of infant sleep trajectories and subsequent cognitive school readiness at 48-50 months.

Methods: Participants were 288 multi-ethnic children, within the Growing Up in Singapore Towards healthy Outcomes (GUSTO) cohort. Caregiver-reported total, night and day sleep durations were obtained at 3, 6, 9, 12, 18, 24 using the Brief Infant Sleep Questionnaire and 54 months using the Child Sleep Habits Questionnaire.

Longitudinal HbA1c trajectory modelling reveals the association of HbA1c and risk of hospitalization for heart failure for patients with type 2 diabetes mellitus.

Background: Inconsistent conclusions in past studies on the association between poor glycaemic control and the risk of hospitalization for heart failure (HHF) have been reported largely due to the analysis of non-trajectory-based HbA1c values. Trajectory analysis can incorporate the effects of HbA1c variability across time, which may better elucidate its association with macrovascular complications. Furthermore, studies analysing the relationship between HbA1c trajectories from diabetes diagnosis and the occurrence of HHF are scarce.

Trajectories of reported sleep duration associate with early childhood cognitive development.

Study Objectives: Examine how different trajectories of reported sleep duration associate with early childhood cognition.

Methods: Caregiver-reported sleep duration data (n = 330) were collected using the Brief Infant Sleep Questionnaire at 3, 6, 9, 12, 18, and 24 months and Children's Sleep Habits Questionnaire at 54 months. Multiple group-based day-, night-, and/or total sleep trajectories were derived-each differing in duration and variability.

Geographical clusters of dengue outbreak in Singapore during the Covid-19 nationwide lockdown of 2020.

Dengue, a mosquito-transmitted viral disease, has posed a public health challenge to Singaporean residents over the years. In 2020, Singapore experienced an unprecedented dengue outbreak. We collected a dataset of geographical dengue clusters reported by the National Environment Agency (NEA) from 15 February to 9 July in 2020, covering the nationwide lockdown associated with Covid-19 during the period from 7 April to 1 June.

Energy, environmental, economic and social equity (4E) pressures of COVID-19 vaccination mismanagement: A global perspective.

Vaccination now offers a way to resolve the COVID-19 pandemic. However, it is critical to recognise the full energy, environmental, economic and social equity (4E) impacts of the vaccination life cycle. The full 4E impacts include the design and trials, order management, material preparation, manufacturing, cold chain logistics, low-temperature storage, crowd management and end-of-life waste management.

More Is Not Enough: A Deeper Understanding of the COVID-19 Impacts on Healthcare, Energy and Environment Is Crucial.

The coronavirus disease 2019 (COVID-19) pandemic has magnified the insufficient readiness of humans in dealing with such an unexpected occurrence. During the pandemic, sustainable development goals have been hindered severely. Various observations and lessons have been highlighted to emphasise local impacts on a single region or single sector, whilst the holistic and coupling impacts are rarely investigated.

Variations in longitudinal sleep duration trajectories from infancy to early childhood.

Objective: This study investigates variations in night, day, and total sleep trajectories across infancy and childhood in Asian children.

Participants: Participants consisted of a subset of 901 children, within the Growing Up in Singapore Towards healthy Outcomes cohort, which recruited 1247 pregnant women between June 2009 and September 2010.

Design: We used a novel conditional probabilistic trajectory model: a probabilistic model for mixture distribution, allowing different trajectory curves and model variances among groups to cluster longitudinal observations.

Spatial-temporal potential exposure risk analytics and urban sustainability impacts related to COVID-19 mitigation: A perspective from car mobility behaviour.

Coronavirus disease-2019 (COVID-19) poses a significant threat to the population and urban sustainability worldwide. The surge mitigation is complicated and associates many factors, including the pandemic status, policy, socioeconomics and resident behaviours. Modelling and analytics with spatial-temporal big urban data are required to assist the mitigation of the pandemic.

Early dengue outbreak detection modeling based on dengue incidences in Singapore during 2012 to 2017.

Dengue has been as an endemic with year-round presence in Singapore. In the recent years 2013, 2014, and 2016, there were several severe dengue outbreaks, posing serious threat to the public health. To proactively control and mitigate the disease spread, early warnings of dengue outbreaks, at which there are rapid and large-scale spread of dengue incidences, are extremely helpful.

Statistical modeling reveals the effect of absolute humidity on dengue in Singapore.

Weather factors are widely studied for their effects on indicating dengue incidence trends. However, these studies have been limited due to the complex epidemiology of dengue, which involves dynamic interplay of multiple factors such as herd immunity within a population, distinct serotypes of the virus, environmental factors and intervention programs. In this study, we investigate the impact of weather factors on dengue in Singapore, considering the disease epidemiology and profile of virus serotypes.

Comparability of results from pair and classical model formulations for different sexually transmitted infections.

The "classical model" for sexually transmitted infections treats partnerships as instantaneous events summarized by partner change rates, while individual-based and pair models explicitly account for time within partnerships and gaps between partnerships. We compared predictions from the classical and pair models over a range of partnership and gap combinations. While the former predicted similar or marginally higher prevalence at the shortest partnership lengths, the latter predicted self-sustaining transmission for gonorrhoea (GC) and Chlamydia (CT) over much broader partnership and gap combinations.

Evaluating temporal factors in combined interventions of workforce shift and school closure for mitigating the spread of influenza.

Background: It is believed that combined interventions may be more effective than individual interventions in mitigating epidemic. However there is a lack of quantitative studies on performance of the combination of individual interventions under different temporal settings.

Methodology/principal Findings: To better understand the problem, we develop an individual-based simulation model running on top of contact networks based on real-life contact data in Singapore.

Temporal factors in school closure policy for mitigating the spread of influenza.

Is school closure effective in mitigating influenza outbreaks? For Singapore, we developed an individual-based simulation model using real-life contact data. We evaluated the impacts of temporal factors - trigger threshold and duration - on the effectiveness of school closure as a mitigation policy. We found an upper bound of the duration of school closure, where further extension beyond which will not bring additional benefits to suppressing the attack rate and peak incidence.

Data dimensionality reduction with application to simplifying RBF network structure and improving classification performance.

For high dimensional data, if no preprocessing is carried out before inputting patterns to classifiers, the computation required may be too heavy. For example, the number of hidden units of a radial basis function (RBF) neural network can be too large. This is not suitable for some practical applications due to speed and memory constraints.

A noisy chaotic neural network for solving combinatorial optimization problems: stochastic chaotic simulated annealing.

Recently Chen and Aihara have demonstrated both experimentally and mathematically that their chaotic simulated annealing (CSA) has better search ability for solving combinatorial optimization problems compared to both the Hopfield-Tank approach and stochastic simulated annealing (SSA). However, CSA may not find a globally optimal solution no matter how slowly annealing is carried out, because the chaotic dynamics are completely deterministic. In contrast, SSA tends to settle down to a global optimum if the temperature is reduced sufficiently slowly.