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INTRODUCTION: There is a need to improve knowledge and understanding of the factors associated with mortality from COVID-19 so that managers and decision-makers can implement strategies to mitigate and control the severe forms of the disease. This study aimed to determine the factors associated with deaths from COVID-19 in the state of Maranhão, in northeastern Brazil. METHODOLOGY: This is a cross-sectional and analytical study with patients with a confirmed diagnosis of COVID-19 who died from March 2020 to January 2022. Simple and multiple logistic regression models were used to assess the association between clinical-epidemiological characteristics and death. The odds ratios were expressed using a 95% confidence interval and a 5% significance level. RESULTS: A total of 386,567 cases of COVID-19 were registered in the period, of which 10,986 died. Risk factors associated with deaths from COVID-19 were male sex, age over 30 years, positive reverse transcriptase-polymerase chain reaction (RT-PCR) result, positive CT scan, and having one or more associated comorbidities. The three comorbidities linked to the highest propensity to die were diabetes mellitus, neurological disease, and obesity. CONCLUSIONS: The study findings support the implementation of strategic actions by health care and surveillance professionals and managers towards reducing the incidence of the risk factors for mortality by COVID-19 in Maranhão.
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COVID-19 , Humanos , Masculino , Adulto , Femenino , SARS-CoV-2 , Brasil/epidemiología , Estudios Transversales , Factores de RiesgoRESUMEN
INTRODUCTION: The analysis of factors associated with multibacillary leprosy is important for the development of strategies to mitigate the disease, which persists as a public health problem in Brazil and the world. The objective of this study was to verify the associations between sociodemographic and clinical-epidemiological variables and multibacillary leprosy in the state of northeastern Brazil. METHODOLOGY: This is a cross-sectional, analytical, and retrospective study, with a quantitative approach, carried out in 16 municipalities in the southwest of Maranhão State, northeastern Brazil. All cases of leprosy reported between January 2008 and December 2017 were considered. Sociodemographic and clinical-epidemiological variables were analyzed using descriptive statistics. The identification of the risk factors associated with multibacillary leprosy was conducted using Poisson regression models. The prevalence ratios and respective 95% confidence intervals were estimated using regression coefficients at a 5% significance level. RESULTS: A total of 3,903 leprosy cases were analyzed. Individuals older than 15 years, males, with less than 8 years of education, with level I, II, or "not evaluated" disability, and with type 1 or 2 or both reactional states were more likely to have multibacillary leprosy. Therefore, these characteristics may be considered risk factors. No protective factors were identified. CONCLUSIONS: The investigation revealed important associations between risk factors and multibacillary leprosy. The findings can be considered during the creation of strategies to control and combat the disease.
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Lepra Multibacilar , Lepra , Humanos , Masculino , Brasil/epidemiología , Estudios Transversales , Lepra/epidemiología , Lepra Multibacilar/epidemiología , Estudios Retrospectivos , Adolescente , Femenino , AdultoRESUMEN
BACKGROUND: Coronavirus disease 2019 (COVID-19) has spread worldwide, causing a high burden of morbidity and mortality, and has affected the various health service systems in the world, demanding disease monitoring and control strategies. The objective of this study was to identify risk areas using spatiotemporal models and determine the COVID-19 time trend in a federative unit of northeastern Brazil. METHODS: An ecological study using spatial analysis techniques and time series was carried out in the state of Maranhão, Brazil. All new cases of COVID-19 registered in the state from March 2020 to August 2021 were included. Incidence rates were calculated and spatially distributed by area, while the spatiotemporal risk territories were identified using scan statistics. The COVID-19 time trend was determined using Prais-Winsten regressions. RESULTS: Four spatiotemporal clusters with high relative risks for the disease were identified in seven health regions located in the southwest/northwest, north and east of Maranhão. The COVID-19 time trend was stable during the analysed period, with higher rates in the regions of Santa Inês in the first and second waves and Balsas in the second wave. CONCLUSIONS: The heterogeneously distributed spatiotemporal risk areas and the stable COVID-19 time trend can assist in the management of health systems and services, facilitating the planning and implementation of actions toward the mitigation, surveillance and control of the disease.
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COVID-19 , Humanos , COVID-19/epidemiología , Brasil/epidemiología , Medición de Riesgo , Análisis Espacial , Factores de Tiempo , Análisis Espacio-TemporalRESUMEN
BACKGROUND: The detection of spatiotemporal clusters of deaths by coronavirus disease 2019 (COVID-19) is essential for health systems and services, as it contributes to the allocation of resources and helps in effective decision making aimed at disease control and surveillance. Thus we aim to analyse the spatiotemporal distribution and describe sociodemographic and clinical and operational characteristics of COVID-19-related deaths in a Brazilian state. METHODS: A descriptive and ecological study was carried out in the state of Maranhão. The study population consisted of deaths by COVID-19 in the period from 29 March to 31 July 2020. The detection of spatiotemporal clusters was performed by spatiotemporal scan analysis. RESULTS: A total of 3001 deaths were analysed with an average age of 69 y, predominantly in males, of brown ethnicity, with arterial hypertension and diabetes, diagnosed mainly by reverse transcription polymerase chain reaction in public laboratories. The crude mortality rates the municipalities ranged from 0.00 to 102.24 deaths per 100 000 inhabitants and three spatiotemporal clusters of high relative risk were detected, with a mortality rate ranging from 20.25 to 91.49 deaths per 100 000 inhabitants per month. The headquarters was the metropolitan region of São Luís and municipalities with better socio-economic and health development. CONCLUSIONS: The heterogeneous spatiotemporal distribution and the sociodemographic and clinical and operational characteristics of deaths by COVID-19 point to the need for interventions.