1
|
Cavalcante Filho JB, Góes MADO, Araújo DDC, Peixoto MVDS, Nunes MAP. Association of socioeconomic indicators with COVID-19 mortality in Brazil: a population-based ecological study. Geospat Health 2023; 18. [PMID: 37449873 DOI: 10.4081/gh.2023.1206] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/18/2023] [Accepted: 07/01/2023] [Indexed: 07/18/2023]
Abstract
The article presents an analysis of the spatial distribution of mortality from COVID-19 and its association with socioeconomic indicators in the north-eastern region of Brazil - an area particularly vulnerable with regard to these indicators. This populationbased ecology study was carried out at the municipal level in the years 2020 and 2021, with analyses performed by spatial autocorrelation, multiple linear regression and spatial autoregressive models. The results showed that mortality from COVID-19 in this part of Brazil was higher in the most populous cities with better socioeconomic indicators. Factors such as the onset of the COVID-19 pandemic in large cities, the agglomerations existing within them, the pressure to maintain economic activities and mistakes in the management of the pandemic by the Brazilian federal Government were part of the complex scenario related to the spread of COVID-19 in the country and this study was undertaken in an attempt to understand this situation. Analysing the different scenarios is essential to face the challenges posed by the pandemic to the world's health systems.
Collapse
|
2
|
da Silva CC, de Souza KOC, da Paz WS, Santos APS, de Melo LRS, de Sousa ÁFL, Araújo DDC, dos Santos AD. Spatial modeling of homicide mortality in the Northeast region of Brazil. Rev Bras Enferm 2023; 76:e20220182. [PMID: 36753255 PMCID: PMC9901349 DOI: 10.1590/0034-7167-2022-0182] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2022] [Accepted: 10/05/2022] [Indexed: 02/09/2023] Open
Abstract
OBJECTIVE To analyze the spatiotemporal distribution of homicide mortality and association with social determinants of health in the Northeast Region of Brazil. METHODS Ecological study with spatiotemporal modeling of homicide deaths between 2000 and 2019. Temporal trends were analyzed by segmented linear regression. Crude mortality was calculated and adjusted by smoothing the local empirical Bayesian method and analyzed by the Global/Local Moran Index and spatiotemporal scan statistics. The association between social determinants of health and homicide mortality was performed using multiple linear regression and autoregressive spatial models. RESULTS 353,089 deaths were recorded. Mortality increased from 2000 to 2019, with an annual increase of 4.37 in males and 3.57 in females. High risk spatial and spatiotemporal clusters were identified in the coastal region of the states. The spatial regression model showed an association with socioeconomic inequalities. CONCLUSIONS High risk areas for homicides associated with socioeconomic inequality, which should be considered as a priority for designing and investing in public health policies were investigated.
Collapse
|
3
|
Almeida Andrade L, Silva da Paz W, Fontes Lima AGC, da Conceição Araújo D, Duque AM, Peixoto MVS, Góes MAO, Freire de Souza CD, Nunes Ribeiro CJ, Almeida Lima SVM, Bezerra-Santos M, Dantas Dos Santos A. Spatiotemporal Pattern of COVID-19-Related Mortality during the First Year of the Pandemic in Brazil: A Population-based Study in a Region of High Social Vulnerability. Am J Trop Med Hyg 2021; 106:132-141. [PMID: 34758451 PMCID: PMC8733529 DOI: 10.4269/ajtmh.21-0744] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2021] [Accepted: 10/03/2021] [Indexed: 11/07/2022] Open
Abstract
Currently, the world is facing a severe pandemic caused by the new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus. Although the WHO has recommended preventive measures to limit its spread, Brazil has neglected most of these recommendations, and consequently, our country has the second largest number of deaths from COVID-19 worldwide. In addition, recent studies have shown the relationship between socioeconomic inequalities and the risk of severe COVID-19 infection. Herein, we aimed to assess the spatiotemporal distribution of mortality and lethality rates of COVID-19 in a region of high social vulnerability in Brazil (Northeast region) during the first year of the pandemic. A segmented log-linear regression model was applied to assess temporal trends of mortality and case fatality rate (CFR) and according to the social vulnerability index (SVI). The Local Empirical Bayesian Estimator and Global Moran Index were used for spatial analysis. We conducted a retrospective space-time scan to map clusters at high risk of death from COVID-19. A total of 66,358 COVID-19-related deaths were reported during this period. The mortality rate was 116.2/100,000 inhabitants, and the CFR was 2.3%. Nevertheless, CFR was > 7.5% in 27 municipalities (1.5%). We observed an increasing trend of deaths in this region (AMCP = 18.2; P = 0.001). Also, increasing trends were observed in municipalities with high (N = 859) and very high SVI (N = 587). We identified two significant spatiotemporal clusters of deaths by COVID-19 in this Brazilian region (P = 0.001), and most high-risk municipalities were on the coastal strip of the region. Taken together, our analyses demonstrate that the pandemic has been responsible for several deaths in Northeast Brazil, with clusters at high risk of mortality mainly in municipalities on the coastline and those with high SVI.
Collapse
Affiliation(s)
- Lucas Almeida Andrade
- Nursing Graduate Program, Federal University of Sergipe, Aracaju, Brazil.,Collective Health Research Center, Federal University of Sergipe, Aracaju, Brazil
| | - Wandklebson Silva da Paz
- Parasitic Biology Graduate Program, Federal University of Sergipe, Aracaju, Brazil.,Tropical Medicine Graduate Program, Federal University of Pernambuco, Recife, Brazil
| | | | - Damião da Conceição Araújo
- Collective Health Research Center, Federal University of Sergipe, Aracaju, Brazil.,Health Sciences Graduate Program, Federal University of Sergipe, Aracaju, Brazil
| | - Andrezza M Duque
- Collective Health Research Center, Federal University of Sergipe, Aracaju, Brazil.,Department of Occupational Therapy, Federal University of Sergipe, Lagarto, Brazil
| | - Marcus Valerius S Peixoto
- Collective Health Research Center, Federal University of Sergipe, Aracaju, Brazil.,Department of Speech Therapy, Federal University of Sergipe, Aracaju, Brazil
| | - Marco Aurélio O Góes
- Collective Health Research Center, Federal University of Sergipe, Aracaju, Brazil.,Department of Medicine, Federal University of Sergipe, Aracaju, SE, Brazil.,Sergipe State Department of Health, Aracaju, Brazil
| | | | - Caíque J Nunes Ribeiro
- Nursing Graduate Program, Federal University of Sergipe, Aracaju, Brazil.,Collective Health Research Center, Federal University of Sergipe, Aracaju, Brazil.,Departament of Nursing, Federal University of Sergipe, Lagarto, Brazil
| | - Shirley V M Almeida Lima
- Nursing Graduate Program, Federal University of Sergipe, Aracaju, Brazil.,Collective Health Research Center, Federal University of Sergipe, Aracaju, Brazil.,Departament of Nursing, Federal University of Sergipe, Lagarto, Brazil
| | - Márcio Bezerra-Santos
- Collective Health Research Center, Federal University of Sergipe, Aracaju, Brazil.,Parasitic Biology Graduate Program, Federal University of Sergipe, Aracaju, Brazil.,Health Sciences Graduate Program, Federal University of Sergipe, Aracaju, Brazil.,Departament of Morphology, Federal University of Sergipe, Aracaju, Brazil
| | - Allan Dantas Dos Santos
- Nursing Graduate Program, Federal University of Sergipe, Aracaju, Brazil.,Collective Health Research Center, Federal University of Sergipe, Aracaju, Brazil.,Departament of Nursing, Federal University of Sergipe, Lagarto, Brazil
| |
Collapse
|
5
|
Lima SVMA, Cruz LZ, Araújo DDC, Santos ADD, Queiroz AAFLN, Araújo KCGMD, Mendes IAC. Quality of tuberculosis information systems after record linkage. Rev Bras Enferm 2020; 73:e20200536. [DOI: 10.1590/0034-7167-2020-0536] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2020] [Accepted: 09/03/2020] [Indexed: 11/21/2022] Open
Abstract
ABSTRACT Objective: to analyze the quality of a tuberculosis notification information system after record linkage and spatial and temporal distribution of tuberculosis in a Brazilian state. Method: an ecological study carried between 2006 and 2016 in Sergipe, Brazil. A deterministic linkage was performed with Notifiable Diseases Information System and Mortality Information System, recording 7,873 cases and 483 deaths. The temporal trend of tuberculosis incidence was calculated. Results: there was an increase among men (2.75%), > 60 years (6.29%), higher education (4.34%) and indigenous (4.76%). A total of 190 new cases (2.9%) was found. There was an increasing trend in tuberculosis incidence with a concentration of deaths in the metropolitan region. Conclusion: the quality of the information system showed fragility in identifying cases and deaths in Sergipe. Temporal distribution showed an increasing trend in tuberculosis incidence, and spatial distribution identified higher incidences in southeastern Brazil.
Collapse
|
6
|
Lima SVMA, dos Santos AD, Duque AM, de Oliveira Goes MA, da Silva Peixoto MV, da Conceição Araújo D, Ribeiro CJN, Santos MB, de Araújo KCGM, Nunes MAP. Spatial and temporal analysis of tuberculosis in an area of social inequality in Northeast Brazil. BMC Public Health 2019; 19:873. [PMID: 31272437 PMCID: PMC6610860 DOI: 10.1186/s12889-019-7224-0] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2018] [Accepted: 06/21/2019] [Indexed: 01/28/2023] Open
Abstract
BACKGROUND Tuberculosis is an infectious disease caused by Mycobacterium tuberculosis. It is a disease known worldwide for its vulnerability factors, magnitude and mortality. The objective of the study was to analyze the spatial and temporal dynamics of TB in the area of social inequality in northeast Brazil between the years 2001 and 2016. METHODS An ecological time series study with the use of spatial analysis techniques was carried out from 2001 to 2016. The units of analysis were the 75 municipalities in the state of Sergipe. Data from the Notification of Injury Information System were used. For the construction of the maps, the cartographic base of the state of Sergipe, obtained at the Instituto Brasileiro de Geografia e Estatística, was used. Georeferenced data were analysed using TerraView 4.2.2 software (Instituto Nacional de Pesquisas Espaciais) and QGis 2.18.2 (Open Source Geospatial Foundation). Spatial analyses included the empirical Bayesian model and the global and local Moran indices. The time trend analyses were performed by the software Joinpoint Regression, Version 4.5.0.1, with the variables of sex, age, cure and abandonment. RESULTS There was an increasing trend of tuberculosis cases in patients under 20 years old and 20-39 years old, especially in males. Cured cases showed a decreasing trend, and cases of treatment withdrawal were stationary. A spatial dependence was observed in almost all analysed territories but with different concentrations. Significant spatial correlations with the formation of clusters in the southeast and northeast of the state were observed. The probability of illness among municipalities was determined not to occur in a random way. CONCLUSION The identification of risk areas and priority groups can help health planning by refining the focus of attention to tuberculosis control. Understanding the epidemiological, spatial and temporal dynamics of tuberculosis can allow for improved targeting of strategies for disease prevention and control.
Collapse
Affiliation(s)
| | - Allan Dantas dos Santos
- Nursing Department, Federal University of Sergipe, Avenida Universitária Marcelo Deda Chagas, 330, Lagarto, SE 49.400-000 Brazil
| | - Andrezza Marques Duque
- Program in Health Sciences, Federal University of Sergipe, Brazil Cláudio Batista, s/n, Cidade Nova, Aracaju, SE 49060-108 Brazil
| | - Marco Aurélio de Oliveira Goes
- Program in Health Sciences, Federal University of Sergipe, Brazil Cláudio Batista, s/n, Cidade Nova, Aracaju, SE 49060-108 Brazil
| | - Marcus Valerius da Silva Peixoto
- Program in Health Sciences, Federal University of Sergipe, Brazil Cláudio Batista, s/n, Cidade Nova, Aracaju, SE 49060-108 Brazil
| | - Damião da Conceição Araújo
- Program in Health Sciences, Federal University of Sergipe, Brazil Cláudio Batista, s/n, Cidade Nova, Aracaju, SE 49060-108 Brazil
| | - Caíque Jordan Nunes Ribeiro
- Program in Health Sciences, Federal University of Sergipe, Brazil Cláudio Batista, s/n, Cidade Nova, Aracaju, SE 49060-108 Brazil
| | - Márcio Bezerra Santos
- Department of Health education, Federal University of Sergipe, Avenida Universitária Marcelo Deda Chagas 330, Lagarto, SE 49.400-000 Brazil
| | | | - Marco Antônio Prado Nunes
- Program in Health Sciences, Federal University of Sergipe, Brazil Cláudio Batista, s/n, Cidade Nova, Aracaju, SE 49060-108 Brazil
| |
Collapse
|