Knowledge Generation

Seeks to understand the impacts of the Bolsa Família conditional cash transfer on birth outcomes (e.g., birth weight, gestational weeks, etc). The proposed design will disentangle the measured effects into two components: one that is associated to the cash transfer; and another related to prenatal care assistance. Moreover, this strategy will allow the researchers to determine the window of opportunity where CCT interventions exhibit highest impacts on birth outcomes, recognizing heterogeneous impacts according to how early in the pregnancy the CCT intervention starts.

The main goal of the project is to develop and explore an innovative measure of gestational age - "potential pregnancy days lost" (PPDL) - to produce evidence of its association with maternal and child health, morbidity and mortality in the short, medium and long term. The indicator also aims to convince women and policy makers about the need to promote less interventions and "harm-free care" during pregnancy.

Bacterial plasmids are genetic elements that can carry genes for antibiotic resistance from one bacteria to another acting as "messengers". Plasmid transfers contribute to the appearance of multidrug resistant bacteria. This project aims to use a "kill the messenger, not the bacteria" approach to tackle the problem of increasing antibiotic resistance. The goal is to test the elimination of plasmids carrying genes for antimicrobial resistance.

The project proposes to characterize the resistant determinants of microbial communities from key sources in hospitals, environment and farms to model the dynamics of the flow of antibiotic resistant microorganisms. The goal is to understand how the hospital environment and animal farming affect the ecology of antibiotic resistance movement. The project will rely on a methodology that allows the analysis of genes related to antibiotic resistance in a complex microbial community derived from specific samples instead of culture based methods for AMR identification.

The researcher will use machine learning techniques and a linked database to analyze mortality from drug-resistant tuberculosis. The goal is to better understand how the flow of patients through the health services network have influenced, or not, the occurrence of resistance.

The project will study the genetic material from environmental samples from humans (healthy and ill), cattle and their meat to estimate the proportion of E. coli and K. pneumoniae in the microbiome. The main objective is to better understand the distribution of bacteria and its resistance genes, Escherichia coli and Klebsiella pneumoniae bacteria and extended spectrum beta-lactamase (EsβL) and carbapenemases encoding genes in distinct ecological sources.

The project will use molecular approaches, including genomics and phylogenomics, to find biomarkers that could indicate the location in the genetic code driving bacterial adaptation. In addition, these biomarkers could be used as a rapid method for screening predominant and high-virulency MRSA clones in hospitals, and thus quickly provide infection control committees with key data on MRSA spread and its antimicrobial resistance profile.

William Fifer of Columbia University in the U.S. is developing a non-invasive method to measure heart rate and heart rate variability in the fetus during pregnancy as a window into brain function to help warn of emerging brain abnormalities. They aim to produce charts of brain development beginning during pregnancy and continuing into early childhood that can be used in limited-resource settings for monitoring child health.