Spatial clusters, social determinants of health and risk of COVID-19 mortality in Brazilian children and adolescents: A nationwide population-based ecological study

Santos, Victor Santana; Siqueira, Thayane Santos; Atienzar, Ana I Cubas; Santos, Maria Augusta Ricardo da Rocha; Vieira, Sarah Cristina Fontes; Lopes, Aline de Siqueira Alves; Martins-Filho, Paulo Ricardo; Cuevas, Luís E.; Gurgel, Ricardo Queiróz

doi:10.1016/j.lana.2022.100311

Cited by 9 publications

(10 citation statements)

References 29 publications

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“…In the country, the difficult access to health services and ICU beds can influence the severity of COVID-19 in this age group due to the greater need for hospitalizations and intensive care 17 , especially in the North and Northeast regions, which have the worst socioeconomic conditions and health indicators and the lowest proportions of pediatric ICU beds 3 . In this context, besides the deleterious effects of the disease, the worsening of the condition should be considered a consequence of the deficient care provided.…”

Section: Discussionmentioning

confidence: 99%

“…Newborns (NBs) are considered a risk group due to the immaturity of their immune system and other conditions — such as prematurity — responsible for important changes in the respiratory system 3 . Thus, this research aimed to describe the clinical characteristics of cases of COVID-19 severe acute respiratory syndrome (SARS) in the age group from 0 to 28 days in Brazil in 2020 and 2021.…”

Section: Introductionmentioning

confidence: 99%

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COVID-19 severe acute respiratory syndrome in Brazilian newborns in 2020-2021

Pereira

Branco

Costa

et al. 2023

Rev. bras. epidemiol.

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Objective: To describe the clinical characteristics of cases of COVID-19 severe acute respiratory syndrome (SARS) in Brazilian newborns (NBs) in 2020 and 2021, recorded in the Influenza Epidemiological Surveillance Information System (Sistema de Informação da Vigilância Epidemiológica da Gripe — SIVEP-Gripe). Methods: The variables analyzed were gender, race/skin color, hospitalization, intensive care unit (ICU) admission, use of ventilatory support, signs and symptoms (fever, cough, O2 saturation<95%, dyspnea, respiratory distress, diarrhea, and vomiting), progress (death or cure), risk factors/comorbidities. Categorical variables were expressed as absolute and relative frequencies. Results: We found 1,649 records of COVID-19 SARS in NBs, with a predominance of multiracial babies in both years. The most frequent symptoms in 2020 and 2021 were, respectively: respiratory distress (67.0 and 69.7%), fever (46.3 and 46.2%), and cough (37.0 and 46.3%). In 2020, 30.5% of patients received invasive ventilatory support; in 2021, this number was 41.6%. In addition, more than 55% of cases required ICU admission, and over 16% died. Conclusion: We emphasize the high proportion of cases that required intensive care and progressed to death.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

COVID-19 severe acute respiratory syndrome in Brazilian newborns in 2020-2021

Pereira

Branco

Costa

et al. 2023

Rev. bras. epidemiol.

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“…Another significant cluster discovered in November 2020, was the Teratai cluster which involved Klang, Kuala Selangor, Petaling and Hulu Langat. This cluster was linked to Top Glove Corp Bhd and resulted in over 6000 cases (Birruntha, 2021) Several research have investigated the spatial clustering analysis of COVID-19 and its associated variables utilising GIS techniques (Liu et al, 2021;Ullah et al, 2020;Fonseca-Rodríguez et al, 2021;Santos et al, 2022). The results of the investigations indicated that the COVID-19 transmission was significantly influenced by the population outflow.…”

Section: Introductionmentioning

confidence: 99%

“…The results of the investigations indicated that the COVID-19 transmission was significantly influenced by the population outflow. (Liu et al, 2021;Fonseca-Rodríguez et al, 2021) such as population in with higher social socioeconomic inequality (Santos et al, 2022) and the proportion of immigrants senior citizens (Fonseca-Rodríguez et al, 2021). SARS-CoV-2 may also disseminate in environment with high levels of inbound movement or travel, poor ventilation, high humidity or heavy rains, low temperatures, and high levels of air pollution.…”

Section: Introductionmentioning

confidence: 99%

“…SARS-CoV-2 may also disseminate in environment with high levels of inbound movement or travel, poor ventilation, high humidity or heavy rains, low temperatures, and high levels of air pollution. (Liu et al, 2021) Therefore, by identifying the spatial clustering of the disease, it can be beneficial to guide control authorities on prioritizing locations for targeted interventions or mass immunisation programme and other the disease control activities (Ullah et al, 2020;Santos et al, 2022). For example, for the control and prevention of COVID-19, it may be beneficial to implement the proper lockdown procedures and travel restrictions, improve the ventilation of living and working spaces, manage air pollution, and make adequate preparations for a potential second wave in the relatively cold autumn and winter months (Liu et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

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Spatial Clustering Phenomena of Covid-19 Cases in Selangor: A Hotspot Analysis and Ordinary Least Squares Method

Mohammad

Rasam²,

Ghazali³

et al. 2023

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. An increase in number of Coronavirus disease 2019 (COVID-19) cases will lead to more cluster discovery in Malaysia. Furthermore, with the increasing population, city growth, workplace income needs, high-risk groups, and other relevant factors can contribute to the formation of the new clusters. The cluster distribution of the disease could be seen by mapping and spatial analysis to understand their spatial phenomena of the disease dynamics. The purpose of the study is to analyse the spatial distribution of COVID-19 cluster cases in Selangor for year 2020. Two objectives of the study are i) to determine the hotspot location of the COVID- 19 cluster, and ii)to examine the spatial distribution of the factors affecting the COVID-19 cluster. The data processing was conducted using hotspot analysis and ordinary least squares (OLS) in ArcGIS Pro and Microsoft Excel to explore the local disease phenomena. TheCOVID-19 cases was most prevalent in the Petaling district, followed by Hulu Langat and Klang. The virus had the least impact in Sabak Bernam, Hulu Selangor, Kuala Selangor, Sepang, Kuala Langat, and Gombak. Three environmental factors of population density, the effects of urbanisation, and workplace cases were influential variables at the local clusters. These findings could help the local agencies to facilitate and control the spread mode of the virus in a spatial human environment.

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