Prevalence and Correlates of Stunting among a High-Risk Population of Kenyan Children Recently Hospitalized for Acute Illnesses.

Stunting (length/height-for-age z-score < -2) is associated with significant morbidity and mortality among children under 5 years of age in sub-Saharan Africa. Children who are stunted and recently hospitalized for acute illness may be at particularly elevated risk for post-discharge mortality. In this cross-sectional analysis, we measured the prevalence of stunting at hospital discharge and identified host, caregiver, and environmental correlates of stunting among children aged 1-59 months in Western Kenya enrolled in the Toto Bora Trial. Child age- and site-adjusted prevalence ratios were estimated using Poisson regression. Of the 1,394 children included in this analysis, 23% were stunted at hospital discharge. Older children (12-23 months and 24-59 months versus 0-5 months) had a higher prevalence of stunting (adjusted prevalence ratio [aPR]: 1.58; 95% CI: 1.04-2.36 and aPR: 1.59; 95% CI: 1.08-2.34, respectively). HIV-exposed, uninfected children (aPR: 1.94; 95% CI: 1.39-2.70), children with HIV infection (aPR: 2.73; 95% CI: 1.45-5.15), and those who were never exclusively breastfed in early life (aPR 2.51; 95% CI: 1.35-4.67) were more likely to be stunted. Caregiver education (primary school or less) and unimproved sanitation (pit latrine without slab floor or open defecation) were associated with increased risk of stunting (aPR: 1.94; 95% CI: 1.54-2.44; aPR: 1.99; 95% CI: 1.20-3.31; aPR: 3.57; 95% CI: 1.77-7.21, respectively). Hospital discharge represents an important opportunity for both identifying and delivering targeted interventions for nutrition-associated poor outcomes among a high-risk population of children.

Data Management in Multicountry Consortium Studies: The Enterics For Global Health (EFGH) Shigella Surveillance Study Example.

Background: Rigorous data management systems and planning are essential to successful research projects, especially for large, multicountry consortium studies involving partnerships across multiple institutions. Here we describe the development and implementation of data management systems and procedures for the Enterics For Global Health (EFGH) Shigella surveillance study-a 7-country diarrhea surveillance study that will conduct facility-based surveillance concurrent with population-based enumeration and a health care utilization survey to estimate the incidence of Shigella--associated diarrhea in children 6 to 35 months old. Methods: The goals of EFGH data management are to utilize the knowledge and experience of consortium members to collect high-quality data and ensure equity in access and decision-making. During the planning phase before study initiation, a working group of representatives from each EFGH country site, the coordination team, and other partners met regularly to develop the data management systems for the study. Results: This resulted in the Data Management Plan, which included selecting REDCap and SurveyCTO as the primary database systems. Consequently, we laid out procedures for data processing and storage, study monitoring and reporting, data quality control and assurance activities, and data access. The data management system and associated real-time visualizations allow for rapid data cleaning activities and progress monitoring and will enable quicker time to analysis. Conclusions: Experiences from this study will contribute toward enriching the sparse landscape of data management methods publications and serve as a case study for future studies seeking to collect and manage data consistently and rigorously while maintaining equitable access to and control of data.

Diarrhea Case Surveillance in the Enterics for Global Health Shigella Surveillance Study: Epidemiologic Methods.

Background: Shigella is a leading cause of acute watery diarrhea, dysentery, and diarrhea-attributed linear growth faltering, a precursor to stunting and lifelong morbidity. Several promising Shigella vaccines are in development and field efficacy trials will require a consortium of potential vaccine trial sites with up-to-date Shigella diarrhea incidence data. Methods: The Enterics for Global Health (EFGH) Shigella surveillance study will employ facility-based enrollment of diarrhea cases aged 6-35 months with 3 months of follow-up to establish incidence rates and document clinical, anthropometric, and financial consequences of Shigella diarrhea at 7 country sites (Mali, Kenya, The Gambia, Malawi, Bangladesh, Pakistan, and Peru). Over a 24-month period between 2022 and 2024, the EFGH study aims to enroll 9800 children (1400 per country site) between 6 and 35 months of age who present to local health facilities with diarrhea. Shigella species (spp.) will be identified and serotyped from rectal swabs by conventional microbiologic methods and quantitative polymerase chain reaction. Shigella spp. isolates will undergo serotyping and antimicrobial susceptibility testing. Incorporating population and healthcare utilization estimates from contemporaneous household sampling in the catchment areas of enrollment facilities, we will estimate Shigella diarrhea incidence rates. Conclusions: This multicountry surveillance network will provide key incidence data needed to design Shigella vaccine trials and strengthen readiness for potential trial implementation. Data collected in EFGH will inform policy makers about the relative importance of this vaccine-preventable disease, accelerating the time to vaccine availability and uptake among children in high-burden settings.

Microbiological Methods Used in the Enterics for Global Health Shigella Surveillance Study.

Background: Shigella is a major cause of diarrhea in young children worldwide. Multiple vaccines targeting Shigella are in development, and phase 3 clinical trials are imminent to determine efficacy against shigellosis. Methods: The Enterics for Global Health (EFGH) Shigella surveillance study is designed to determine the incidence of medically attended shigellosis in 6- to 35-month-old children in 7 resource-limited settings. Here, we describe the microbiological methods used to isolate and identify Shigella. We developed a standardized laboratory protocol for isolation and identification of Shigella by culture. This protocol was implemented across all 7 sites, ensuring consistency and comparability of results. Secondary objectives of the study are to determine the antibiotic resistance profiles of Shigella, compare isolation of Shigella from rectal swabs versus whole stool, and compare isolation of Shigella following transport of rectal swabs in Cary-Blair versus a modified buffered glycerol saline transport medium. Conclusions: Data generated from EFGH using culture methods described herein can potentially be used for microbiological endpoints in future phase 3 clinical trials to evaluate vaccines against shigellosis and for other clinical and public health studies focused on these organisms.

Evaluation of Fecal Inflammatory Biomarkers to Identify Bacterial Diarrhea Episodes: Systematic Review and Protocol for the Enterics for Global Health Shigella Surveillance Study.

Background: The measurement of fecal inflammatory biomarkers among individuals presenting to care with diarrhea could improve the identification of bacterial diarrheal episodes that would benefit from antibiotic therapy. We reviewed prior literature in this area and describe our proposed methods to evaluate 4 biomarkers in the Enterics for Global Health (EFGH) Shigella surveillance study. Methods: We systematically reviewed studies since 1970 from PubMed and Embase that assessed the diagnostic characteristics of inflammatory biomarkers to identify bacterial diarrhea episodes. We extracted sensitivity and specificity and summarized the evidence by biomarker and diarrhea etiology. In EFGH, we propose using commercial enzyme-linked immunosorbent assays to test for myeloperoxidase, calprotectin, lipocalin-2, and hemoglobin in stored whole stool samples collected within 24 hours of enrollment from participants in the Bangladesh, Kenya, Malawi, Pakistan, Peru, and The Gambia sites. We will develop clinical prediction scores that incorporate the inflammatory biomarkers and evaluate their ability to identify Shigella and other bacterial etiologies of diarrhea as determined by quantitative polymerase chain reaction (qPCR). Results: Forty-nine studies that assessed fecal leukocytes (n = 39), red blood cells (n = 26), lactoferrin (n = 13), calprotectin (n = 8), and myeloperoxidase (n = 1) were included in the systematic review. Sensitivities were high for identifying Shigella, moderate for identifying any bacteria, and comparable across biomarkers. Specificities varied depending on the outcomes assessed. Prior studies were generally small, identified red and white blood cells by microscopy, and used insensitive gold standard diagnostics, such as conventional bacteriological culture for pathogen detection. Conclusions: Our evaluation of inflammatory biomarkers to distinguish diarrhea etiologies as determined by qPCR will provide an important addition to the prior literature, which was likely biased by the limited sensitivity of the gold standard diagnostics used. We will determine whether point-of-care biomarker tests could be a viable strategy to inform treatment decision making and increase appropriate targeting of antibiotic treatment to bacterial diarrhea episodes.

Quantifying the Cost of Shigella Diarrhea in the Enterics for Global Health (EFGH) Shigella Surveillance Study.

Background: Comparative costs of public health interventions provide valuable data for decision making. However, the availability of comprehensive and context-specific costs is often limited. The Enterics for Global Health (EFGH) Shigella surveillance study-a facility-based diarrhea surveillance study across 7 countries-aims to generate evidence on health system and household costs associated with medically attended Shigella diarrhea in children. Methods: EFGH working groups comprising representatives from each country (Bangladesh, Kenya, Malawi, Mali, Pakistan, Peru, and The Gambia) developed the study methods. Over a 24-month surveillance period, facility-based surveys will collect data on resource use for the medical treatment of an estimated 9800 children aged 6-35 months with diarrhea. Through these surveys, we will describe and quantify medical resources used in the treatment of diarrhea (eg, medication, supplies, and provider salaries), nonmedical resources (eg, travel costs to the facility), and the amount of caregiver time lost from work to care for their sick child. To assign costs to each identified resource, we will use a combination of caregiver interviews, national medical price lists, and databases from the World Health Organization and the International Labor Organization. Our primary outcome will be the estimated cost per inpatient and outpatient episode of medically attended Shigella diarrhea treatment across countries, levels of care, and illness severity. We will conduct sensitivity and scenario analysis to determine how unit costs vary across scenarios. Conclusions: Results from this study will contribute to the existing body of literature on diarrhea costing and inform future policy decisions related to investments in preventive strategies for Shigella.

Population Enumeration and Household Utilization Survey Methods in the Enterics for Global Health (EFGH): Shigella Surveillance Study.

Background: Accurate estimation of diarrhea incidence from facility-based surveillance requires estimating the population at risk and accounting for case patients who do not seek care. The Enterics for Global Health (EFGH) Shigella surveillance study will characterize population denominators and healthcare-seeking behavior proportions to calculate incidence rates of Shigella diarrhea in children aged 6-35 months across 7 sites in Africa, Asia, and Latin America. Methods: The Enterics for Global Health (EFGH) Shigella surveillance study will use a hybrid surveillance design, supplementing facility-based surveillance with population-based surveys to estimate population size and the proportion of children with diarrhea brought for care at EFGH health facilities. Continuous data collection over a 24 month period captures seasonality and ensures representative sampling of the population at risk during the period of facility-based enrollments. Study catchment areas are broken into randomized clusters, each sized to be feasibly enumerated by individual field teams. Conclusions: The methods presented herein aim to minimize the challenges associated with hybrid surveillance, such as poor parity between survey area coverage and facility coverage, population fluctuations, seasonal variability, and adjustments to care-seeking behavior.