Abstract
Improving maternal, newborn, and child health is central to Sustainable Development Goal targets for 2030, requiring acceleration especially to prevent 5.6 million deaths around the time of birth. Infections contribute to this burden, but etiological data are limited. Group B Streptococcus (GBS) is an important perinatal pathogen, although previously focus has been primarily on liveborn children, especially early-onset disease. In this first of an 11-article supplement, we discuss the following: (1) Why estimate the worldwide burden of GBS disease? (2) What outcomes of GBS in pregnancy should be included? (3) What data and epidemiological parameters are required? (4) What methods and models can be used to transparently estimate this burden of GBS? (5) What are the challenges with available data? and (6) How can estimates address data gaps to better inform GBS interventions including maternal immunization? We review all available GBS data worldwide, including maternal GBS colonization, risk of neonatal disease (with/without intrapartum antibiotic prophylaxis), maternal GBS disease, neonatal/infant GBS disease, and subsequent impairment, plus GBS-associated stillbirth, preterm birth, and neonatal encephalopathy. We summarize our methods for searches, meta-analyses, and modeling including a compartmental model. Our approach is consistent with the World Health Organization (WHO) Guidelines for Accurate and Transparent Health Estimates Reporting (GATHER), published in The Lancet and the Public Library of Science (PLoS). We aim to address priority epidemiological gaps highlighted by WHO to inform potential maternal vaccination.
Highlights
A Promise RenewedGlobal Strategy for Women’s, Children’s and Adolescents’ Global Strategy for Women’s, Health [62]
The first of 11 covering the most comprehensive assessment to date of data regarding disease burden of Group B Streptococcus (GBS), we address 6 questions that guide the methodological approach taken throughout the supplement (Table 2)
For epidemiological exposures around the time of birth, which are either noninfections or where the infection is mainly passed from mother to child, the main factors affecting cases are the risk at birth and demographic factors affecting births
Summary
Global Strategy for Women’s, Children’s and Adolescents’ Global Strategy for Women’s, Health [62]. While the poorest and most vulnerable populations have the highest risk of most diseases, they have the least data—the “inverse data law.” This applies to the estimated 600 000 child deaths due to neonatal infections, which is more than that for malaria and AIDS combined (Figure 1). For epidemiological exposures around the time of birth, which are either noninfections (eg, hypoxia) or where the infection is mainly passed from mother to child (including GBS), the main factors affecting cases are the risk at birth and demographic factors affecting births In this case, a stable compartment model is appropriate and has been used for other estimates of perinatal outcomes [52] and operates in 4 steps as follows: Step 1. What is the exposure prevalence at the population level (eg, an infection among pregnant women, or a blood group type such as rhesus negative)?
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