ABSTRACT
BACKGROUND: Shigella sonnei is an emergent and major diarrheal pathogen for which there is currently no vaccine. We aimed to quantify duration of maternal antibody against S. sonnei and investigate transplacental IgG transfer in a birth cohort in southern Vietnam. METHODS AND RESULTS: Over 500-paired maternal/infant plasma samples were evaluated for presence of anti-S. sonnei-O IgG and IgM. Longitudinal plasma samples allowed for the estimation of the median half-life of maternal anti-S. sonnei-O IgG, which was 43 days (95% confidence interval: 41-45 days). Additionally, half of infants lacked a detectable titer by 19 weeks of age. Lower cord titers were associated with greater increases in S. sonnei IgG over the first year of life, and the incidence of S. sonnei seroconversion was estimated to be 4/100 infant years. Maternal IgG titer, the ratio of antibody transfer, the season of birth and gestational age were significantly associated with cord titer. CONCLUSIONS: Maternal anti-S. sonnei-O IgG is efficiently transferred across the placenta and anti-S. sonnei-O maternal IgG declines rapidly after birth and is undetectable after 5 months in the majority of children. Preterm neonates and children born to mothers with low IgG titers have lower cord titers and therefore may be at greater risk of seroconversion in infancy.
Subject(s)
Antibodies, Bacterial/blood , Immunity, Maternally-Acquired , Immunoglobulin G/blood , Shigella sonnei , Antibodies, Bacterial/chemistry , Enzyme-Linked Immunosorbent Assay , Female , Fetal Blood/immunology , Half-Life , Humans , Immunoglobulin G/chemistry , Infant , Infant, Newborn , Longitudinal Studies , Male , O Antigens/isolation & purification , Seroconversion , VietnamABSTRACT
It is predicted that the integration of climate-based early warning systems into existing action plans will facilitate the timely provision of interventions to diarrheal disease epidemics in resource-poor settings. Diarrhea remains a considerable public health problem in Ho Chi Minh City (HCMC), Vietnam and we aimed to quantify variation in the impact of environmental conditions on diarrheal disease risk across the city. Using all inpatient diarrheal admissions data from three large hospitals within HCMC, we developed a mixed effects regression model to differentiate district-level variation in risk due to environmental conditions from the overarching seasonality of diarrheal disease hospitalization in HCMC. We identified considerable spatial heterogeneity in the risk of all-cause diarrhea across districts of HCMC with low elevation and differential responses to flooding, air temperature, and humidity driving further spatial heterogeneity in diarrheal disease risk. The incorporation of these results into predictive forecasting algorithms will provide a powerful resource to aid diarrheal disease prevention and control practices in HCMC and other similar settings.
