Infection, sepsis and antibiotics resistance
This research group is a multidisciplinary team of:
These specialists address highly-lethal infections and infections which are global public health concerns.
The main objectives include improving diagnosis and therapy of highly-lethal infections and helping to better identify vulnerable populations and novel health policies for transmissible diseases.
The group researches on how to:
- Prevent exposure to the infectious agent;
- Making otherwise susceptible individuals or population, immune to the infectious agent;
- Better understand the pathophysiology of infectious diseases, exploring the interaction between infectious agent and host;
- Improving the diagnosis of infected individuals and develop prognostic markers of poor outcomes;
- Treating infected individuals to prevent illness and transmission of the agent to others;
- Epidemiology of neonatal infection, providing knowledge about antibiotics prescription and strategies to improve antibiotics prescription;
- Improving the timeless and appropriateness of care for symptomatic individuals to minimize morbidity and mortality and, in some instances, to reduce the likelihood of transmission to others.
In general, in terms of methodology, quantitative methods are more often used than qualitative ones. Depending on the purpose, different study designs can be used. For example, longitudinal observational studies (prospective or retrospective) or experimental studies, which allow establishing causal relationships, can be useful to understand the pathophysiology, causes, risk factors, and evolution of a given disease. Studies that aim to test the diagnostic and/or prognostic acuity of certain clinical variables and/or biomarkers are common and follow the STARD/ TRIPOD guidelines of the EQUATOR network. The data sources, both qualitative and quantitative, are specifically built databases, and also, quite often, pre-existing clinical files or databases, national and international, assembled in the context of epidemiological surveillance or pharmacovigilance. The statistical methodology is based on descriptive analysis of the study population, followed by the use of statistical inference tests adequate to meet the study objectives. The most commonly used tools are Excel, SPSS and STATA.
Research in tuberculosis and COVID-19 is epidemiological, retrospective or prospective, either using surveillance databases such as the tuberculosis surveillance system (SVIG-TB) or by collecting data, either by conducting case-control studies or ambidirectional cohorts. R is the most commonly used language for data analysis, together with the SPSS program. Descriptive, univariate and multivariate analyses are performed, using regression for binary outcomes, counts and survival time, or time series. The objective of the work is to estimate the effect of a given exposure or to identify the effect of variables of interest, adjusting for confounding factors.