Banca de DEFESA: MARIA DA LUZ GOIS CAMPOS

Uma banca de DEFESA de DOUTORADO foi cadastrada pelo programa.
STUDENT : MARIA DA LUZ GOIS CAMPOS
DATE: 27/09/2024
TIME: 14:00
LOCAL: Videoconferência via Gerência de Redes do CCET/UFRN
TITLE:

ANALYSIS OF THE TIME-SPATIAL DIFFUSION OF COVID-19 IN TWO BRAZILIAN STATES

KEY WORDS:

Coronavirus 2 (COVID-19); Socioeconomic and demographic factors; Mixed Model Geographically Weighted Autoregressive Regression (MGWRSAR); Dynamical Systems; Behavioral epidemiological model.

PAGES: 179
BIG AREA: Ciências Sociais Aplicadas
AREA: Demografia
SUBÁREA: Componentes da Dinâmica Demográfica
SUMMARY:

The SARS-CoV-2 pandemic has had considerable effects on the global economy and demographics, as well as affecting regions with more vulnerable populations, both socially and in terms of health and sanitation conditions. It is in this context that this study aims to study the spread of COVID-19 infection to the states of Rio Grande do Norte (RN) and Amazonas (AM). Thus, using data from the Public Health Department (SESAP) of the state of Rio Grande do Norte and the IBGE – 2010 Census, we analyzed the incidence of COVID-19 for the period of epidemiological week SE49 (11/23/2020 to 11/29/2020). This is a descriptive, cross-sectional exploratory study, whose empirical basis is to analyze global and local spatial models to model the incidence of COVID-19 in the 167 municipalities of Rio Grande do Norte and their main socioeconomic and demographic determinants. Methodologically, we describe the presence of spatial autocorrelation and cluster formation, using Exploratory Analysis of Spatial Data (AEDE). The presence of spatial heterogeneity for the incidence of COVID-19 in the municipalities of RN was observed, which allows adjusting for the indicators of identification of social vulnerability a Mixed Model of Geographically Weighted Spatial Autoregressive Regression (MGWRSAR). According to the results, it is demonstrated that the coefficients of the study variables presented patterns of associations with socioeconomic and demographic factors, therefore, the Gini index (Gini) and urban concentration (Gurb) are the most relevant factors to explain the spread of the disease to the state of RN. To study the extensive spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in the state of Amazonas, we used data from MonitoraCovid-19/Fiocruz and the Amazonas Health Surveillance Foundation (FVS-AM) from March 9, 2020 to April 25, 2021. From a methodological point of view, we used a descriptive experimental and ecological study, using continuous dynamic simulation modeling through dynamic systems, with an emphasis on the behavioral epidemiological model, susceptible, infected, recovered and deaths (SIRD-AM), in addition to statistical analysis. This analysis procedure aims to estimate alternative scenarios, based on the social distancing measures imposed by the state government of Amazonas, as well as hospital capacity, at the population level, to predict deaths and cases by COVID-19. From the perspective of the results, we simulated 5 times more deaths for Amazonas; when we consider hospital capacity, we estimate an excess mortality rate 411% higher than the Brazilian rate for 2021 and the flows I(t), R(t) and D(t) decreased at an average rate of 2.5, in favor of pandemic control policies.

COMMITTEE MEMBERS:
Externa à Instituição - 0 - - nullExterno à Instituição - JOSIVAN RIBEIRO JUSTINO - UNIR
Presidente - 1688188 - MOISES ALBERTO CALLE AGUIRRE
Interna - ***.649.538-** - SILVANA NUNES DE QUEIROZ - URCA
Externo à Instituição - WEBER SOARES - UFMG