ORCID Profile
0000-0002-1406-0122
Current Organisation
Fundação Oswaldo Cruz
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Publisher: Elsevier BV
Date: 2018
Publisher: Universidad Nacional de Lanus
Date: 27-09-2020
Abstract: This study analyzes the spatial dynamics of drug users’ recruitment chains in the context of a respondent-driven s ling (RDS) study in the city of Recife, Brazil. The purpose is to understand the geographic bottlenecks, influenced by social geography, which have been a major challenge for RDS-based studies. Temporo-spatial analysis was used. Sequential maps depicted the dynamics of the recruiting process, considering neighborhood of residence and/or places of drug use. Poisson regression was fitted to model the recruiting rate by neighborhood of residence and/or places of drug use, and the different neighborhoods’ demographics. The distance between neighborhood of residence and/or places of drug use and the assessment center was negatively associated with recruitment. There was a positive association between the proportion of the population living in informal settings and the recruiting rate per neighborhood of residence and/or places of drug use. Recruitment chains depend on the social geography and demographics of the population. Studies should incorporate seeds from as many neighborhoods as possible, and more than one assessment center should be utilized.
Publisher: Ovid Technologies (Wolters Kluwer Health)
Date: 05-2018
Publisher: Informa UK Limited
Date: 05-02-2023
Publisher: Springer Science and Business Media LLC
Date: 07-2022
Publisher: Springer Science and Business Media LLC
Date: 13-06-2023
DOI: 10.1186/S12879-023-08300-1
Abstract: Acute encephalitis syndrome (AES) differs in its spatio-temporal distribution in Vietnam with the highest incidence seen during the summer months in the northern provinces. AES has multiple aetiologies, and the cause remains unknown in many cases. While vector-borne disease such as Japanese encephalitis and dengue virus and non-vector-borne diseases such as influenza and enterovirus show evidence of seasonality, associations with climate variables and the spatio-temporal distribution in Vietnam differs between these. The aim of this study was therefore to understand the spatio-temporal distribution of, and risk factors for AES in Vietnam to help hypothesise the aetiology. The number of monthly cases per province for AES, meningitis and diseases including dengue fever influenza-like-illness (ILI) hand, foot, and mouth disease (HFMD) and Streptococcus suis were obtained from the General Department for Preventive Medicine (GDPM) from 1998–2016. Covariates including climate, normalized difference vegetation index (NDVI), elevation, the number of pigs, socio-demographics, JEV vaccination coverage and the number of hospitals were also collected. Spatio-temporal multivariable mixed-effects negative binomial Bayesian models with an outcome of the number of cases of AES, a combination of the covariates and harmonic terms to determine the magnitude of seasonality were developed. The national monthly incidence of AES declined by 63.3% over the study period. However, incidence increased in some provinces, particularly in the Northwest region. In northern Vietnam, the incidence peaked in the summer months in contrast to the southern provinces where incidence remained relatively constant throughout the year. The incidence of meningitis, ILI and S. suis infection temperature, relative humidity with no lag, NDVI at a lag of one month, and the number of pigs per 100,000 population were positively associated with the number of cases of AES in all models in which these covariates were included. The positive correlation of AES with temperature and humidity suggest that a number of cases may be due to vector-borne diseases, suggesting a need to focus on vaccination c aigns. However, further surveillance and research are recommended to investigate other possible aetiologies such as S. suis or Orientia tsutsugamushi .
Publisher: Springer Science and Business Media LLC
Date: 10-05-2022
DOI: 10.1038/S41591-022-01807-1
Abstract: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Gamma variant of concern has spread rapidly across Brazil since late 2020, causing substantial infection and death waves. Here we used in idual-level patient records after hospitalization with suspected or confirmed coronavirus disease 2019 (COVID-19) between 20 January 2020 and 26 July 2021 to document temporary, sweeping shocks in hospital fatality rates that followed the spread of Gamma across 14 state capitals, during which typically more than half of hospitalized patients aged 70 years and older died. We show that such extensive shocks in COVID-19 in-hospital fatality rates also existed before the detection of Gamma. Using a Bayesian fatality rate model, we found that the geographic and temporal fluctuations in Brazil’s COVID-19 in-hospital fatality rates were primarily associated with geographic inequities and shortages in healthcare capacity. We estimate that approximately half of the COVID-19 deaths in hospitals in the 14 cities could have been avoided without pre-pandemic geographic inequities and without pandemic healthcare pressure. Our results suggest that investments in healthcare resources, healthcare optimization and pandemic preparedness are critical to minimize population-wide mortality and morbidity caused by highly transmissible and deadly pathogens such as SARS-CoV-2, especially in low- and middle-income countries.
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for Leonardo Bastos.