A cluster-randomized trial of client and provider directed financial interventions to align incentives with appropriate case management in private medicine retailers: Results of the TESTsmART trial in Lagos, Nigeria.

Malaria remains a major health priority in Nigeria. Among children with fever who seek care, less than a quarter gets tested for malaria, leading to inappropriate use of the recommended treatment for malaria; Artemisinin-based Combination Therapy (ACT). Here we test an innovative strategy to target ACT subsidies to clients seeking care in Nigeria's private retail health sector who have a confirmed malaria diagnosis. We supported point-of-care malaria testing (mRDTs) in 48 Private Medicine Retailers (PMRs) in the city of Lagos, Nigeria and randomized them to two study arms; a control arm offering subsidized mRDT testing for USD $0.66, and an intervention arm where, in addition to access to subsidized testing as in the control arm, clients who received a positive mRDT at the PMR were eligible for a free (fully subsidized) first-line ACT and PMRs received USD $0.2 for every mRDT performed. Our primary outcome was the proportion of ACTs dispensed to individuals with a positive diagnostic test. Secondary outcomes included proportion of clients who were tested at the PMR and adherence to diagnostic test results. Overall, 23% of clients chose to test at the PMR. Test results seemed to inform treatment decisions and resulted in enhanced targeting of ACTs to confirmed malaria cases with only 26% of test-negative clients purchasing an ACT compared to 58% of untested clients. However, the intervention did not offer further improvements, compared to the control arm, in testing rates or dispensing of ACTs to test-positive clients. We found that ACT subsidies were not passed on to clients testing positive in the intervention arm. We conclude that mRDTs could reduce ACT overconsumption in Nigeria's private retail health sector, but PMR-oriented incentive structures are difficult to implement and may need to be complemented with interventions targeting clients of PMRs to increase test uptake and adherence. Trials registration: Clinical Trials Registration Number: NCT04428307. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7816435/ Correction: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9476591/.

How should a cluster randomized trial be analyzed?

In cluster randomized trials, individuals from the same cluster tend to have more similar outcomes than individuals from different clusters. This correlation must be taken into account in the analysis of every cluster trial to avoid incorrect inferences. In this paper, we describe the principles guiding the analysis of cluster trials including how to correctly account for intra-cluster correlations as well as how to analyze more advanced designs such as stepped-wedge and cluster cross-over trials. We then describe how to handle specific issues such as small sample sizes and missing data.

A cluster-randomized trial of client and provider-directed financial interventions to align incentives with appropriate case management in retail medicine outlets: Results of the TESTsmART Trial in western Kenya.

ACTs are responsible for a substantial proportion of the global reduction in malaria mortality over the last ten years, made possible by publicly-funded subsidies making these drugs accessible and affordable in the private sector. However, inexpensive ACTs available in retail outlets have contributed substantially to overconsumption. We test an innovative, scalable strategy to target ACT-subsidies to clients with a confirmatory diagnosis. We supported malaria testing(mRDTs) in 39 medicine outlets in western Kenya, randomized to three study arms; control arm offering subsidized mRDT testing (0.4USD), client-directed intervention where all clients who received a positive RDT at the outlet were eligible for a free (fully-subsidized) ACT, and a combined client and provider directed intervention where clients with a positive RDT were eligible for free ACT and outlets received 0.1USD for every RDT performed. Our primary outcome was the proportion of ACT dispensed to individuals with a positive diagnostic test. Secondary outcomes included proportion of clients tested at the outlet and adherence to diagnostic test results. 43% of clients chose to test at the outlet. Test results informed treatment decisions, resulting in targeting of ACTs to confirmed malaria cases- 25.3% of test-negative clients purchased an ACT compared to 75% of untested clients. Client-directed and client+provider-directed interventions did not offer further improvements, compared to the control arm, in testing rates(RD = 0.09, 95%CI:-0.08,0.26) or dispensing of ACTs to test-positive clients(RD = 0.01,95% CI:-0.14, 0.16). Clients were often unaware of the price they paid for the ACT leading to uncertainty in whether the ACT subsidy was passed on to the client. This uncertainty undermines our ability to definitively conclude that client-directed subsidies are not effective for improving testing and appropriate treatment. We conclude that mRDTs could reduce ACT overconsumption in the private retail sector, but incentive structures are difficult to scale and their value to private providers is uncertain. Trial registration: ClinicalTrials.gov NCT04428307.

Autism Caregiver Coaching in Africa (ACACIA): Protocol for a type 1-hybrid effectiveness-implementation trial.

BACKGROUND: While early autism intervention can significantly improve outcomes, gaps in implementation exist globally. These gaps are clearest in Africa, where forty percent of the world's children will live by 2050. Task-sharing early intervention to non-specialists is a key implementation strategy, given the lack of specialists in Africa. Naturalistic Developmental Behavioral Interventions (NDBI) are a class of early autism intervention that can be delivered by caregivers. As a foundational step to address the early autism intervention gap, we adapted a non-specialist delivered caregiver coaching NDBI for the South African context, and pre-piloted this cascaded task-sharing approach in an existing system of care. OBJECTIVES: First, we will test the effectiveness of the caregiver coaching NDBI compared to usual care. Second, we will describe coaching implementation factors within the Western Cape Department of Education in South Africa. METHODS: This is a type 1 effectiveness-implementation hybrid design; assessor-blinded, group randomized controlled trial. Participants include 150 autistic children (18-72 months) and their caregivers who live in Cape Town, South Africa, and those involved in intervention implementation. Early Childhood Development practitioners, employed by the Department of Education, will deliver 12, one hour, coaching sessions to the intervention group. The control group will receive usual care. Distal co-primary outcomes include the Communication Domain Standard Score (Vineland Adaptive Behavior Scales, Third Edition) and the Language and Communication Developmental Quotient (Griffiths Scales of Child Development, Third Edition). Proximal secondary outcome include caregiver strategies measured by the sum of five items from the Joint Engagement Rating Inventory. We will describe key implementation determinants. RESULTS: Participant enrolment started in April 2023. Estimated primary completion date is March 2027. CONCLUSION: The ACACIA trial will determine whether a cascaded task-sharing intervention delivered in an educational setting leads to meaningful improvements in communication abilities of autistic children, and identify implementation barriers and facilitators. TRIAL REGISTRATION: NCT05551728 in Clinical Trial Registry (https://clinicaltrials.gov).

Designing individually randomized group treatment trials with repeated outcome measurements using generalized estimating equations.

Individually randomized group treatment (IRGT) trials, in which the clustering of outcome is induced by group-based treatment delivery, are increasingly popular in public health research. IRGT trials frequently incorporate longitudinal measurements, of which the proper sample size calculations should account for correlation structures reflecting both the treatment-induced clustering and repeated outcome measurements. Given the relatively sparse literature on designing longitudinal IRGT trials, we propose sample size procedures for continuous and binary outcomes based on the generalized estimating equations approach, employing the block exchangeable correlation structures with different correlation parameters for the treatment arm and for the control arm, and surveying five marginal mean models with different assumptions of time effect: no-time constant treatment effect, linear-time constant treatment effect, categorical-time constant treatment effect, linear time by treatment interaction, and categorical time by treatment interaction. Closed-form sample size formulas are derived for continuous outcomes, which depends on the eigenvalues of the correlation matrices; detailed numerical sample size procedures are proposed for binary outcomes. Through simulations, we demonstrate that the empirical power agrees well with the predicted power, for as few as eight groups formed in the treatment arm, when data are analyzed using the matrix-adjusted estimating equations for the correlation parameters with a bias-corrected sandwich variance estimator.

When Shepherds Shed: Trajectories of Weight-Related Behaviors in a Holistic Health Intervention Tailored for US Christian Clergy.

Maintaining healthy behaviors is challenging. Based upon previous reports that in North Carolina (NC), USA, overweight/obese clergy lost weight during a two-year religiously tailored health intervention, we described trajectories of diet, physical activity, and sleep. We investigated whether behavior changes were associated with weight and use of health-promoting theological messages. Improvements were observed in sleep, calorie-dense food intake, and physical activity, with the latter two associated with weight loss. While theological messages were well-retained, their relationship with behaviors depended on the specific message, behavior, and timing. Findings offer insights into weight loss mechanisms, including the role of theological messages in religiously tailored health interventions.

Autism Caregiver Coaching in Africa (ACACIA): Protocol for a type 1-hybrid effectiveness-implementation trial.

Background: While early autism intervention can significantly improve outcomes, gaps in implementation exist globally. These gaps are clearest in Africa, where forty percent of the world's children will live by 2050. Task-sharing early intervention to non-specialists is a key implementation strategy, given the lack of specialists in Africa. Naturalistic Developmental Behavioral Interventions (NDBI) are a class of early autism intervention that can be delivered by caregivers. As a foundational step to address the early autism intervention gap, we adapted a non-specialist delivered caregiver coaching NDBI for the South African context, and pre-piloted this cascaded task-sharing approach in an existing system of care. Objectives: First, we will test the effectiveness of the caregiver coaching NDBI compared to usual care. Second, we will describe coaching implementation factors within the Western Cape Department of Education in South Africa. Methods: This is a type 1 effectiveness-implementation hybrid design; assessor-blinded, group randomized controlled trial. Participants include 150 autistic children (18-72 months) and their caregivers who live in Cape Town, South Africa, and those involved in intervention implementation. Early Childhood Development practitioners, employed by the Department of Education, will deliver 12, one hour, coaching sessions to the intervention group. The control group will receive usual care. Distal co-primary outcomes include the Communication Domain Standard Score (Vineland Adaptive Behavior Scales, Third Edition) and the Language and Communication Developmental Quotient (Griffiths Scales of Child Development, Third Edition). Proximal secondary outcome include caregiver strategies measured by the sum of five items from the Joint Engagement Rating Inventory. We will describe key implementation determinants. Results: Participant enrolment started in April 2023. Estimated primary completion date is March 2027. Conclusion: The ACACIA trial will determine whether a cascaded task-sharing intervention delivered in an educational setting leads to meaningful improvements in communication abilities of autistic children, and identify implementation barriers and facilitators.

Generalizing the information content for stepped wedge designs: A marginal modeling approach.

Stepped wedge trials are increasingly adopted because practical constraints necessitate staggered roll-out. While a complete design requires clusters to collect data in all periods, resource and patient-centered considerations may call for an incomplete stepped wedge design to minimize data collection burden. To study incomplete designs, we expand the metric of information content to discrete outcomes. We operate under a marginal model with general link and variance functions, and derive information content expressions when data elements (cells, sequences, periods) are omitted. We show that the centrosymmetric patterns of information content can hold for discrete outcomes with the variance-stabilizing link function. We perform numerical studies under the canonical link function, and find that while the patterns of information content for cells are approximately centrosymmetric for all examined underlying secular trends, the patterns of information content for sequences or periods are more sensitive to the secular trend, and may be far from centrosymmetric.

Protocol for a pilot randomized controlled trial of a telehealth-delivered counseling intervention to reduce suicidality and improve HIV care engagement in Tanzania.

OBJECTIVE: Suicidal ideation is strikingly common among people living with HIV (PLWH) worldwide, leading to higher burden of disease, poor HIV care engagement, and loss of life. In low- and middle-income countries such as Tanzania, mental health resources are scarce, requiring innovative strategies for treatment. We describe the protocol for a clinical trial of a three-session telehealth counseling intervention to reduce suicidality and improve HIV care engagement in Tanzania. METHODS: In a pilot randomized controlled trial, we will assess the feasibility, acceptability, and potential efficacy of a new telehealth intervention, termed "IDEAS for Hope". A total of 60 PLWH will be enrolled from two HIV clinics in the Kilimanjaro region and connected to telehealth counsellors based at a large regional hospital. Participants will be ≥18 years old and speak either Kiswahili or English. Patient screening will occur during routine HIV clinical care to identify PLWH experiencing suicidal ideation. Baseline surveys will be administered upon enrollment and participants will be randomized 1:1 to receive either IDEAS for Hope or the comparison condition, a brief safety planning session. All participants will receive an additional referral for psychiatric treatment. Follow-up assessment will occur at three months. IDEAS for Hope is informed by a Motivational Interviewing-enhanced safety planning intervention (MI-SafeCope) and our formative work in Tanzania. The model consists of Four Pillars: living healthy with HIV, managing HIV stigma, seeking social support, and meeting basic needs. Together, these mechanisms serve as a foundation for developing a sense of safety and hope for the future. Outcome measures will include intervention feasibility, acceptability, participant suicidality, and HIV care engagement. SIGNIFICANCE: Innovative, telehealth-based counseling represents a promising treatment for suicidality among PLWH in low-resource settings. Results from this pilot trial will inform intervention refinement and parameter estimates for a future clinical trial powered to evaluate effectiveness.

The Day-in-the-Life method for assessing infant caregiving in rural Pakistan.

Objective: This manuscript describes the Day-in-the-Life (DIL) method for assessing child caregiving activities, its implementation, and findings regarding family members' roles and associations with maternal depression symptoms. Background: Infant caregiving activities are most commonly performed by the mother, although there is increasing acknowledgement of others' contribution. Few methods exist to measure the diverse caregiving activities that mothers and others perform. Method: Method development occurred within the Bachpan Cohort Study in rural Pakistan (N = 1,154 maternal-child dyads) when the child was 3 months old. The DIL was designed as a semi-structured interview in which the mother describes her child's day from their perspective. Regression analyses were then used to explore the correlation between the DIL and depression symptoms, using the Patient Health Questionnaire-9 (PHQ-9) measure. Results: The DIL method was easy to administer and displayed excellent interrater agreement. The findings indicated that instrumental caregiving was mostly provided by the mother alone, others in the household tended to contribute more to infant social interactions, and there was more support from others when the mother was less able to provide care (e.g., when ill). Depression symptoms were higher among women who experienced less contribution from family members when the mother was less able to provide care. Conclusions: The DIL can be deployed to measure infant caregiving activities and associations with maternal mental health. Implications: This method is promising for researchers interested in disentangling the contribution of multiple family members toward child caregiving and its impacts on maternal and child health.

Telemedicine Referral to Improve Access to Specialty Care for Preschool Children in Rural Alaska: A Cluster-Randomized Controlled Trial.

OBJECTIVES: Preschool programs provide essential preventive services, such as hearing screening, but in rural regions, limited access to specialists and loss to follow-up compound rural health disparities. We conducted a parallel-arm cluster-randomized controlled trial to evaluate telemedicine specialty referral for preschool hearing screening. The goal of this trial was to improve timely identification and treatment of early childhood infection-related hearing loss, a preventable condition with lifelong implications. We hypothesized that telemedicine specialty referral would improve time to follow-up and the number of children receiving follow-up compared with the standard primary care referral. DESIGN: We conducted a cluster-randomized controlled trial in K-12 schools in 15 communities over two academic years. Community randomization occurred within four strata using location and school size. In the second academic year (2018-2019), an ancillary trial was performed in the 14 communities that had preschools to compare telemedicine specialty referral (intervention) to standard primary care referral (comparison) for preschool hearing screening. Randomization of communities from the main trial was used for this ancillary trial. All children enrolled in preschool were eligible. Masking was not possible because of timing in the second year of the main trial, but referral assignment was not openly disclosed. Study team members and school staff were masked throughout data collection, and statisticians were blinded to allocation during analysis. Preschool screening occurred once, and children who were referred for possible hearing loss or ear disease were monitored for follow-up for 9 months from the screening date. The primary outcome was time to ear/hearing-related follow-up from the date of screening. The secondary outcome was any ear/hearing follow-up from screening to 9 months. Analyses were conducted using an intention-to-treat approach. RESULTS: A total of 153 children were screened between September 2018 and March 2019. Of the 14 communities, 8 were assigned to the telemedicine specialty referral pathway (90 children), and 6 to the standard primary care referral pathway (63 children). Seventy-one children (46.4%) were referred for follow-up: 39 (43.3%) in the telemedicine specialty referral communities and 32 (50.8%) in the standard primary care referral communities. Of children referred, 30 (76.9%) children in telemedicine specialty referral communities and 16 (50.0%) children in standard primary care referral communities received follow-up within 9 months (Risk Ratio = 1.57; 95% confidence interval [CI], 1.22 to 2.01). Among children who received follow-up, median time to follow-up was 28 days (interquartile range [IQR]: 15 to 71) in telemedicine specialty referral communities compared with 85 days (IQR: 26 to 129) in standard primary care referral communities. Mean time to follow-up for all referred children was 4.5 (event time ratio = 4.5; 95% CI, 1.8 to 11.4; p = 0.045) times faster in telemedicine specialty referral communities compared with standard primary care referral communities in the 9-month follow-up time frame. CONCLUSIONS: Telemedicine specialty referral significantly improved follow-up and reduced time to follow-up after preschool hearing screening in rural Alaska. Telemedicine referrals could extend to other preventive school-based services to improve access to specialty care for rural preschool children.

ORTH.Ord: An R package for analyzing correlated ordinal outcomes using alternating logistic regressions with orthogonalized residuals.

BACKGROUND AND OBJECTIVES: Marginal models with generalized estimating equations (GEE) are usually recommended for analyzing correlated ordinal outcomes which are commonly seen in a longitudinal study or clustered randomized trial (CRT). Within-cluster association is often of interest in longitudinal studies or CRTs, and can be estimated with paired estimating equations. However, the estimators for within-cluster association parameters and variances may be subject to finite-sample biases when the number of clusters is small. The objective of this article is to introduce a newly developed R package ORTH.Ord for analyzing correlated ordinal outcomes using GEE models with finite-sample bias corrections. METHODS: The R package ORTH.Ord implements a modified version of alternating logistic regressions with estimation based on orthogonalized residuals (ORTH), which use paired estimating equations to jointly estimate parameters in marginal mean and association models. The within-cluster association between ordinal responses is modeled by global pairwise odds ratios (POR). The R package also provides a finite-sample bias correction to POR parameter estimates based on matrix multiplicative adjusted orthogonalized residuals (MMORTH) for correcting estimating equations, and bias-corrected sandwich estimators with different options for covariance estimation. RESULTS: A simulation study shows that MMORTH provides less biased global POR estimates and coverage of their 95% confidence intervals closer to the nominal level than uncorrected ORTH. An analysis of patient-reported outcomes from an orthognathic surgery clinical trial illustrates features of ORTH.Ord. CONCLUSIONS: This article provides an overview of the ORTH method with bias-correction on both estimating equations and sandwich estimators for analyzing correlated ordinal data, describes the features of the ORTH.Ord R package, evaluates the performance of the package using a simulation study, and finally illustrates its application in an analysis of a clinical trial.

Improving access to early intervention for autism: findings from a proof-of-principle cascaded task-sharing naturalistic developmental behavioural intervention in South Africa.

BACKGROUND: Despite the high number of children living with neurodevelopmental disabilities in sub-Saharan Africa, access to early intervention is almost non-existent. It is therefore important to develop feasible, scalable early autism intervention that can be integrated into systems of care. While Naturalistic Developmental Behavioural Intervention (NDBI) has emerged as an evidence-based intervention approach, implementation gaps exist globally, and task-sharing approaches may address access gaps. In this South African proof-of-principle pilot study, we set out to answer two questions about a 12-session cascaded task-sharing NDBI-whether the approach could be delivered with fidelity, and whether we could identify signals of change in child and caregiver outcomes. METHODS: We utilized a single-arm pre-post design. Fidelity (non-specialists, caregivers), caregiver outcomes (stress, sense of competence), and child outcomes (developmental, adaptive) were measured at baseline (T1) and follow-up (T2). Ten caregiver-child dyads and four non-specialists participated. Pre-to-post summary statistics were presented alongside individual trajectories. Non-parametric Wilcoxon signed rank test for paired samples was used to compare group medians between T1 and T2. RESULTS: Caregiver implementation fidelity increased in 10/10 participants. Non-specialists demonstrated a significant increase in coaching fidelity (increases in 7/10 dyads). Significant gains were seen on two Griffiths-III subscales (Language/Communication-9/10 improved, Foundations of Learning-10/10 improved) and on the General Developmental Quotient (9/10 improved). Significant gains were also seen on two Vineland Adaptive Behaviour Scales (Third Edition) subscales (Communication-9/10 improved, Socialization-6/10 improved) and in the Adaptive Behaviour Standard Score (9/10 improved). Caregiver sense of competence improved in 7/10 caregivers and caregiver stress in 6/10 caregivers. CONCLUSIONS: This proof-of-principle pilot study of the first cascaded task-sharing NDBI in Sub-Saharan Africa provided fidelity and intervention outcome data which supported the potential of such approaches in low-resource contexts. Larger studies are needed to expand on the evidence-base and answer questions on intervention effectiveness and implementation outcomes.

Improving access to early intervention for autism - findings from a proof-of-principle cascaded task-sharing naturalistic developmental behavioural intervention in South Africa.

Background Despite the high number of children living with neurodevelopmental disabilities in sub-Saharan Africa, access to early intervention is almost non-existent. It is therefore important to develop feasible, scalable early autism intervention that can be integrated into systems of care. While Naturalistic Developmental Behavioural Intervention (NDBI) has emerged as an evidence-based intervention approach, implementation gaps exist globally, and task-sharing approaches may address access gaps. In this South African proof-of-principle pilot study, we set out to answer two questions about a 12-session cascaded task-sharing NDBI - whether the approach could be delivered with fidelity, and whether we could identify signals of change in child and caregiver outcomes. Methods We utilized a single-arm pre-post design. Fidelity (non-specialists, caregivers), caregiver outcomes (stress, sense of competence), and child outcomes (developmental, adaptive) were measured at baseline (T1) and follow-up (T2). Ten caregiver-child dyads and four non-specialists participated. Pre-to-post summary statistics were presented alongside individual trajectories. Non-parametric Wilcoxon signed rank test for paired samples was used to compare group medians between T1 and T2. Results Caregiver implementation fidelity increased in 10/10 participants. Non-specialists demonstrated a significant increase in coaching fidelity (increases in 7/10 dyads). Significant gains were seen on two Griffiths-III subscales (Language/Communication - 9/10 improved, Foundations of Learning - 10/10 improved) and on the General Developmental Quotient (9/10 improved). Significant gains were also seen on two Vineland Adaptive Behaviour Scales (Third Edition) subscales (Communication - 9/10 improved, Socialization - 6/10 improved) and in the Adaptive Behaviour Standard Score (9/10 improved). Caregiver sense of competence improved in 7/10 caregivers and caregiver stress in 6/10 caregivers. Conclusions This proof-of-principle pilot study of the first cascaded task-sharing NDBI in Sub-Saharan Africa provided fidelity and intervention outcome data which supported the potential of such approaches in low-resource contexts. Larger studies are needed to expand on the evidence-base and answer questions on intervention effectiveness and implementation outcomes.

Stroke and activity limitation in Chinese adults 65 Years or older.

BACKGROUND: Differences in activity limitations between stroke survivors and people with other chronic conditions and how their levels of activity limitation vary by sociodemographic characteristics have not been well quantified. OBJECTIVE: To quantify activity limitations experienced by Chinese older adult stroke survivors and explore stroke effects in specific subgroups. METHODS: We used Chinese Longitudinal Healthy Longevity Survey 2017-2018 data (N = 11,743) to produce population-weighted estimates of activity limitations using the Activities of Daily Living (ADL) and the Instrumental ADL (IADL) scales for older adults (age 65 and older) stroke survivors compared to those with non-stroke chronic conditions and those without chronic conditions. Multinomial logistic regressions were run with outcomes "no activity limitation," "IADL only limitation," and "ADL limitation." RESULTS: The weighted marginal prevalence of ADL limitation was higher in the stroke group (14.8%) than in those with non-stroke chronic condition (4.8%) or no chronic conditions (3.6%) (p < 0.01). The corresponding prevalence of IADL limitation for the three groups was 36.0%, 31.4%, and 22.2%, respectively (p < 0.01). Stroke survivors aged ≥ 80 years had a higher prevalence of ADL/IADL limitation than those aged 65-79 years (p < 0.01). Formal education was associated with a lower prevalence of ADL/IADL limitation in each chronic condition group (p < 0.01). CONCLUSIONS: Prevalence and severity of activity limitation among Chinese older adult stroke survivors were several times higher than those without chronic conditions and those with non-stroke chronic conditions. Stroke survivors, particularly those aged ≥80 years and those without formal education, might be predisposed to more severe activity limitation and require more support to compensate.

GEEMAEE: A SAS macro for the analysis of correlated outcomes based on GEE and finite-sample adjustments with application to cluster randomized trials.

BACKGROUND AND OBJECTIVES: Generalized estimating equations (GEE) are used to analyze correlated outcomes in marginal regression models with population-averaged interpretations of exposure effects. Limitations of popular software for GEE include: (i) user choice is restricted to a small set of within-cluster pairwise correlation (intra-class correlation; ICC) structures; and (ii) inference on ICC parameters is usually not possible because the precision of their estimates is not quantified. This is important because ICC values inform the design of cluster randomized trials. Beyond the standard GEE implementation, use of paired estimating equations (Prentice 1988) provides: (i) flexible specification of models for pairwise correlations and (ii) standard errors for ICC estimates. However, most GEEs give biased estimates of standard errors and correlations when the number of clusters is small (roughly, ≤40). Consequently, there is a need for software to provide GEE analysis with finite-sample bias-corrections. METHODS: The SAS macro GEEMAEE implements paired estimating equations to simultaneously estimate parameters in marginal mean and ICC models. It provides bias-corrected standard errors and uses matrix-adjusted estimating equations (MAEE) for bias-corrected estimation of correlations. Several built-in correlation matrix options, rarely found in software, are offered for multi-period, cluster randomized trials and similarly structured longitudinal observational data structures. Additional options include user-specified correlation structures and deletion diagnostics, namely Cooks' Distance and DBETA statistics that estimate the influence of observations, cluster-periods (when applicable) and clusters. RESULTS: GEEMAEE is illustrated for a binary and a count outcome in two stepped wedge cluster randomized trials and a binary outcome in a longitudinal study of disease surveillance. Use of MAEE resulted in larger values of correlation estimates compared to uncorrected estimating equations. Use of bias-corrected variance estimators resulted in (appropriately) larger values of standard errors compared to the usual sandwich estimators. Deletion diagnostics identified the clusters and cluster-periods having the most influence. CONCLUSIONS: The SAS macro GEEMAEE provides regression analysis for clustered or longitudinal responses, and is particularly useful when the number of clusters is small. Flexible specification and bias-corrected estimation of pairwise correlation parameters and standard errors are key features of the software to provide valid inference in real-world settings.

Improving sandwich variance estimation for marginal Cox analysis of cluster randomized trials.

Cluster randomized trials (CRTs) frequently recruit a small number of clusters, therefore necessitating the application of small-sample corrections for valid inference. A recent systematic review indicated that CRTs reporting right-censored, time-to-event outcomes are not uncommon and that the marginal Cox proportional hazards model is one of the common approaches used for primary analysis. While small-sample corrections have been studied under marginal models with continuous, binary, and count outcomes, no prior research has been devoted to the development and evaluation of bias-corrected sandwich variance estimators when clustered time-to-event outcomes are analyzed by the marginal Cox model. To improve current practice, we propose nine bias-corrected sandwich variance estimators for the analysis of CRTs using the marginal Cox model and report on a simulation study to evaluate their small-sample properties. Our results indicate that the optimal choice of bias-corrected sandwich variance estimator for CRTs with survival outcomes can depend on the variability of cluster sizes and can also slightly differ whether it is evaluated according to relative bias or type I error rate. Finally, we illustrate the new variance estimators in a real-world CRT where the conclusion about intervention effectiveness differs depending on the use of small-sample bias corrections. The proposed sandwich variance estimators are implemented in an R package CoxBcv.

A general method for calculating power for GEE analysis of complete and incomplete stepped wedge cluster randomized trials.

Stepped wedge designs have uni-directional crossovers at randomly assigned time points (steps) where clusters switch from control to intervention condition. Incomplete stepped wedge designs are increasingly used in cluster randomized trials of health care interventions and have periods without data collection due to logistical, resource and patient-centered considerations. The development of sample size formulae for stepped wedge trials has primarily focused on complete designs and continuous responses. Addressing this gap, a general, fast, non-simulation based power procedure is proposed for generalized estimating equations analysis of complete and incomplete stepped wedge designs and its predicted power is compared to simulated power for binary and continuous responses. An extensive set of simulations for six and twelve clusters is based upon the Connect-Home trial with an incomplete stepped wedge design. Results show that empirical test size is well controlled using a t-test with bias-corrected sandwich variance estimator for as few as six clusters. Analytical power agrees well with a simulated power in scenarios with twelve clusters. For six clusters, analytical power is similar to simulated power with estimation using the correctly specified model-based variance estimator. To explore the impact of study design choice on power, the proposed fast GEE power method is applied to the Connect-Home trial design, four alternative incomplete stepped wedge designs and one complete design.

Facility-based disease surveillance and Bayesian hierarchical modeling to estimate endemic typhoid fever incidence, Kilimanjaro Region, Tanzania, 2007-2018.

Growing evidence suggests considerable variation in endemic typhoid fever incidence at some locations over time, yet few settings have multi-year incidence estimates to inform typhoid control measures. We sought to describe a decade of typhoid fever incidence in the Kilimanjaro Region of Tanzania. Cases of blood culture confirmed typhoid were identified among febrile patients at two sentinel hospitals during three study periods: 2007-08, 2011-14, and 2016-18. To account for under-ascertainment at sentinel facilities, we derived adjustment multipliers from healthcare utilization surveys done in the hospital catchment area. Incidence estimates and credible intervals (CrI) were derived using a Bayesian hierarchical incidence model that incorporated uncertainty of our observed typhoid fever prevalence, of healthcare seeking adjustment multipliers, and of blood culture diagnostic sensitivity. Among 3,556 total participants, 50 typhoid fever cases were identified. Of typhoid cases, 26 (52%) were male and the median (range) age was 22 (<1-60) years; 4 (8%) were aged <5 years and 10 (20%) were aged 5 to 14 years. Annual typhoid fever incidence was estimated as 61.5 (95% CrI 14.9-181.9), 6.5 (95% CrI 1.4-20.4), and 4.0 (95% CrI 0.6-13.9) per 100,000 persons in 2007-08, 2011-14, and 2016-18, respectively. There were no deaths among typhoid cases. We estimated moderate typhoid incidence (≥10 per 100 000) in 2007-08 and low (<10 per 100 000) incidence during later surveillance periods, but with overlapping credible intervals across study periods. Although consistent with falling typhoid incidence, we interpret this as showing substantial variation over the study periods. Given potential variation, multi-year surveillance may be warranted in locations making decisions about typhoid conjugate vaccine introduction and other control measures.