Defining and estimating effects in cluster randomized trials: A methods comparison.

Across research disciplines, cluster randomized trials (CRTs) are commonly implemented to evaluate interventions delivered to groups of participants, such as communities and clinics. Despite advances in the design and analysis of CRTs, several challenges remain. First, there are many possible ways to specify the causal effect of interest (eg, at the individual-level or at the cluster-level).

Predictors of Seeking Care for Influenza-Like Illness in a Novel Digital Study.

Background: Previous research has estimated that >50% of individuals experiencing influenza-like illness (ILI) do not seek health care. Understanding factors influencing care-seeking behavior for viral respiratory infections may help inform policies to improve access to care and protect public health. We used person-generated health data (PGHD) to identify factors associated with seeking care for ILI.

Assessing the impact of group antenatal care on gestational length in Rwanda: A cluster-randomized trial.

Background: Research on group antenatal care in low- and middle-income contexts suggests high acceptability and preliminary implementation success.

Methods: We studied the effect of group antenatal care on gestational age at birth among women in Rwanda, hypothesizing that participation would increase mean gestational length. For this unblinded cluster randomized trial, 36 health centers were pair-matched and randomized; half continued individual antenatal care (control), half implemented group antenatal care (intervention).

Super learner analysis of real-time electronically monitored adherence to antiretroviral therapy under constrained optimization and comparison to non-differentiated care approaches for persons living with HIV in rural Uganda.

Introduction: Real-time electronic adherence monitoring (EAM) systems could inform on-going risk assessment for HIV viraemia and be used to personalize viral load testing schedules. We evaluated the potential of real-time EAM (transferred via cellular signal) and standard EAM (downloaded via USB cable) in rural Uganda to inform individually differentiated viral load testing strategies by applying machine learning approaches.

Methods: We evaluated an observational cohort of persons living with HIV and treated with antiretroviral therapy (ART) who were monitored longitudinally with standard EAM from 2005 to 2011 and real-time EAM from 2011 to 2015.

Group antenatal care versus standard antenatal care and effect on mean gestational age at birth in Rwanda: protocol for a cluster randomized controlled trial.

Group antenatal care has demonstrated promise as a service delivery model that may result in improved outcomes compared to standard antenatal care in socio-demographic populations at disparately high risk for poor perinatal outcomes. Intrigued by results from the United States showing lower preterm birth rates among high-risk women who participate in group antenatal care, partners working together as the Preterm Birth Initiative - Rwanda designed a trial to assess the impact of group antenatal care on gestational age at birth. This study is a pair-matched cluster randomized controlled trial with four arms.

A general approach for combining diverse rare variant association tests provides improved robustness across a wider range of genetic architectures.

The widespread availability of genome sequencing data made possible by way of next-generation technologies has yielded a flood of different gene-based rare variant association tests. Most of these tests have been published because they have superior power for particular genetic architectures. However, for applied researchers it is challenging to know which test to choose in practice when little is known a priori about genetic architecture.

Evaluating the impact of genotype errors on rare variant tests of association.

The new class of rare variant tests has usually been evaluated assuming perfect genotype information. In reality, rare variant genotypes may be incorrect, and so rare variant tests should be robust to imperfect data. Errors and uncertainty in SNP genotyping are already known to dramatically impact statistical power for single marker tests on common variants and, in some cases, inflate the type I error rate.

A new quantitative and low-cost determination method of nitrate in vegetables, based on deconvolution of UV spectra.

A new UV-spectrophotometric method for the determination of nitrate in vegetables is presented. The method is based on the spectral deconvolution: UV spectrum of a sample is considered as a linear combination of absorption spectra, named reference spectra. The combination of a small number of spectra of reference allows to reconstitute the shape of UV spectrum of an unknown sample.

Long-term evaluation of a sequential batch reactor (SBR) treating dairy wastewater for carbon removal.

Many dairy industries have been using SBR wastewater treatment plants because they allow optimal working condition to be reached. However, to take advantage of SBR capabilities, strong process automation is needed. The aim of this work is to study the factors that influence SBR performance to improve modelling and control.