Your browser doesn't support javascript.
loading
Mostrar: 20 | 50 | 100
Resultados 1 - 20 de 3.820
Filtrar
1.
Artículo en Portugués | PAHO-IRIS | ID: phr-52524

RESUMEN

[RESUMO]. Objetivo. Determinar a existência de aglomerados de municípios (clusters) com alto risco para sífilis congênita (SC) no Brasil e descrever a tendência temporal da doença no país, comparando a população de crianças cujas mães realizaram o pré-natal com aquelas cujas mães não realizaram esse controle. Métodos. Este estudo ecológico utilizou dados do Sistema de Informação de Agravos de Notificação (SINAN) e do Sistema de Informações sobre Nascidos Vivos (SINASC). Para a análise de aglomerados, a estatística de varredura Kulldorff foi aplicada à população de risco. A significância estatística foi determinada pelo logaritmo da razão de verossimilhança utilizando a distribuição discreta de Poisson. Para a análise das tendências das taxas de detecção do agravo, utilizou-se a regressão de Prais-Winsten. A análise foi realizada com os programas SatScan 9.4 e Stata 14.0. Resultados. Clusters com taxas de detecção de 41,3, 44,4 e 188,1 casos/10 000 nascidos vivos foram identificados em 2001, 2009 e 2017, respectivamente. Em 2001, as taxas foram 8 vezes maiores nos clusters do que no restante do país; em 2009, foram 3,3 vezes maiores; e, em 2017, 2,5. Detectou-se uma tendência crescente na infecção por SC em todas as regiões e unidades da federação. As taxas foram 8,53 vezes maiores nos neonatos cujas mães não realizaram pré-natal (243,3 casos/1 000 nascidos vivos vs. 28,4 casos/1 000 nascidos vivos em mães com pré-natal). Conclusões. A identificação de aglomerados de municípios com alto risco para SC e de tendências crescentes de infecção por SC em todo o país, mesmo na presença de pré-natal, indicam a necessidade de melhoria nas ações de saúde pública para o combate dessa doença.


[ABSTRACT]. Objective. To determine the occurrence of high-risk clusters for congenital syphilis (CS) in Brazil and describe the temporal trends in the CS infection in the country, comparing children whose mothers received vs. those whose mothers did not receive prenatal care. Method. This ecological study used data from the National Disease Notification System (Sistema de Informação de Agravos de Notificação, SINAN) and the Live Birth Information System (Sistema de Informações sobre Nascidos Vivos, SINASC). For cluster analysis, the Kulldorff scan statistic was applied to the population at risk. Statistical significance was determined by the log-likelihood ratio based on Poisson discrete distribution. To analyze the temporal trends of disease detection rates, Prais-Winsten regression was used. The analysis was performed with SatScan 9.4 and Stata 14.0 software. Results. Clusters with detection rates of 41.3, 44.4 and 188.1 CS cases/10 000 live births were identified in 2001, 2009 and 2017 respectively. In 2001, the rates were 8 times higher in the clusters than in the remaining country; in 2009, the rates were 3.3 times higher; and in 2017, 2.5 times higher. An increasing trend in CS infection was detected in all regions and federation units. The rates were 8.53 times higher in the children of mothers without prenatal care (243.3 cases/1 000 live births vs. 28.3 cases/1 000 live births in the children of mothers with prenatal care). Conclusions. The identification of municipality clusters at high risk for CS and of increasing trends in CS infection across the country, even in the presence of prenatal care, suggests the need for improvement of public health actions to fight this disease.


Asunto(s)
Epidemiología , Sífilis Congénita , Análisis Espacial , Brasil , Epidemiología , Sífilis Congénita , Análisis Espacial , Brasil
2.
Mem Inst Oswaldo Cruz ; 115: e200043, 2020.
Artículo en Inglés | MEDLINE | ID: mdl-32667459

RESUMEN

BACKGROUND The number of malaria cases in Roraima nearly tripled from 2016 to 2018. The capital, Boa Vista, considered a low-risk area for malaria transmission, reported an increasing number of autochthonous and imported cases. OBJECTIVES This study describes a spatial analysis on malaria cases in an urban region of Boa Vista, which sought to identify the autochthonous and imported cases and associated them with Anopheles habitats and the potential risk of local transmission. METHODS In a cross-sectional study at the Polyclinic Cosme e Silva, 520 individuals were interviewed and diagnosed with malaria by microscopic examination. Using a global positional system, the locations of malaria cases by type and origin and the breeding sites of anopheline vectors were mapped and the risk of malaria transmission was evaluated by spatial point pattern analysis. FINDINGS Malaria was detected in 57.5% of the individuals and there was a disproportionate number of imported cases (90.6%) linked to Brazilian coming from gold mining sites in Venezuela and Guyana. MAIN CONCLUSIONS The increase in imported malaria cases circulating in the west region of Boa Vista, where there are positive breeding sites for the main vectors, may represent a potential condition for increased autochthonous malaria transmission in this space.


Asunto(s)
Anopheles/parasitología , Malaria/diagnóstico , Malaria/transmisión , Mineros/estadística & datos numéricos , Mosquitos Vectores/parasitología , Plasmodium/aislamiento & purificación , Viaje , Adulto , Animales , Anopheles/clasificación , Brasil/epidemiología , Estudios Transversales , Femenino , Sistemas de Información Geográfica , Oro , Guyana , Humanos , Malaria/epidemiología , Malaria/parasitología , Masculino , Persona de Mediana Edad , Plasmodium/clasificación , Análisis Espacial , Población Urbana , Venezuela
3.
Indian J Public Health ; 64(Supplement): S177-S182, 2020 Jun.
Artículo en Inglés | MEDLINE | ID: mdl-32496251

RESUMEN

Background: In March 2020, a healthcare professional from a renowned private hospital, in the textile city of Bhilwara, Rajasthan, reported clustering of cases of pneumonia amongst doctors and paramedical staff suspected to be due to COVID-19. The basis of suspicion was clinico-eco-epidemiologic-radiological findings as, by that time, about 20 COVID19 cases were reported from the state of Rajasthan including a big Italian group of tourists who travelled extensively in Rajasthan, including Udaipur city. Objectives: The current study presents the field experience of the Central and the State Rapid Response Teams (RRTs) in the cluster containment at Bhilwara. Methods: The information regarding the sociodemographic profile of the cases was provided by the Senior Medical Officer In-charge. The containment strategy was modeled under 6 pillars. Google Maps was used for preparing spot map. Results: Immediate public health actions of cluster containment including contact tracing, quarantine, and isolation were initiated using epidemiological approach of mapping the cluster and taking care of reservoir of infection by the District Public Health Team supported by Multidisciplinary Rapid Response Team. This was supplemented by strict enforcement of lock down in the District taking care of daily need of the community by the leadership of administration with very strong intersectoral co-ordination (locally called "ruthless containment"). Conclusion: The forthcoming challenge resides in re-establishment of inter-district and inter-state travel, which can become a risk of re-entry of the new cases, which needs to be taken care of, with the help of stringent administrative measures and screening at all points of entry. The team in Bhilwara needs to remain vigilant to pick up any imported cases early before local transmission establishes.


Asunto(s)
Control de Enfermedades Transmisibles/organización & administración , Infecciones por Coronavirus/epidemiología , Infecciones por Coronavirus/prevención & control , Pandemias/prevención & control , Neumonía Viral/epidemiología , Neumonía Viral/prevención & control , Adolescente , Adulto , Anciano , Betacoronavirus , Trazado de Contacto , Femenino , Humanos , India/epidemiología , Masculino , Persona de Mediana Edad , Cuarentena , Factores Socioeconómicos , Análisis Espacial , Adulto Joven
4.
Indian J Public Health ; 64(Supplement): S183-S187, 2020 Jun.
Artículo en Inglés | MEDLINE | ID: mdl-32496252

RESUMEN

Background: India has reported more than 70,000 cases and 2000 deaths. Pune is the second city in the Maharashtra state after Mumbai to breach the 1000 cases. Total deaths reported from Pune were 158 with a mortality of 5.7%. To plan health services, it is important to learn lessons from early stage of the outbreak on course of the disease in a hospital setting. Objectives: To describe the epidemiological characteristics of the outbreak of COVID-19 in India from a tertiary care hospital. Methods: This was a hospital-based cross-sectional study which included all admitted laboratory confirmed COVID19 cases from March 31, to April 24, 2020. The information was collected in a predesigned pro forma which included sociodemographic data, duration of stay, family background, outcome, etc., by trained staff after ethics approval. Epi Info7 was used for data analysis. Results: Out of the total 197 cases, majority cases were between the ages of 31-60 years with slight male preponderance. Majority of these cases were from the slums. Breathlessness was the main presenting symptom followed by fever and cough. More than 1/5th of patients were asymptomatic from exposure to admission. The case fatality rate among the admitted cases was 29.4%. Comorbidity was one of the significant risk factors for the progression of disease and death (odds ratio [OR] = 16.8, 95% confidence interval [CI] = 7.0 - 40.1, P < 0.0001). Conclusion: Mortality was higher than the national average of 3.2%; comorbidity was associated with bad prognosis.


Asunto(s)
Infecciones por Coronavirus/epidemiología , Neumonía Viral/epidemiología , Centros de Atención Terciaria/estadística & datos numéricos , Adolescente , Adulto , Anciano , Betacoronavirus , Comorbilidad , Infecciones por Coronavirus/mortalidad , Infecciones por Coronavirus/fisiopatología , Estudios Transversales , Femenino , Hospitalización , Humanos , India/epidemiología , Tiempo de Internación , Masculino , Persona de Mediana Edad , Pandemias , Neumonía Viral/mortalidad , Neumonía Viral/fisiopatología , Factores de Riesgo , Factores Socioeconómicos , Análisis Espacial , Adulto Joven
5.
Epidemiol Serv Saude ; 29(3): e2020204, 2020.
Artículo en Inglés, Portugués | MEDLINE | ID: mdl-32520107

RESUMEN

OBJECTIVE: to describe the spatial distribution of the first confirmed COVID-19 cases and deaths in Rio de Janeiro. METHODS: this was an ecological study of confirmed SARS-CoV-2 cases and deaths between March 6thand April 10th, 2020. Incidence, mortality, lethality, excess risk and global and local Moran rates were calculated. RESULTS: 1,808 confirmed cases and 92 confirmed deaths were recorded. The COVID-19 incidence rate was 26.8/100,000 inhab., the mortality rate was 1.36/100,000 inhab. and lethality rate 5%. The incidence rate in eight neighborhoods was 4-12 times higher than the overall rate for the municipality: Joá, in the city's Western Zone; Cosme Velho, Gávea, Ipanema, Jardim Botânico, Lagoa, Leblon and São Conrado, in its Southern Zone. CONCLUSION: high risk of COVID-19 infection and deaths was found in neighborhoods in the Southern Zone of the city of Rio de Janeiro. Neighborhoods in the Northern Zone of the city also stand out in relation to high risk of death.


Asunto(s)
Infecciones por Coronavirus/epidemiología , Neumonía Viral/epidemiología , Adolescente , Adulto , Anciano , Anciano de 80 o más Años , Brasil/epidemiología , Causas de Muerte , Niño , Preescolar , Infecciones por Coronavirus/mortalidad , Femenino , Humanos , Incidencia , Lactante , Recién Nacido , Masculino , Persona de Mediana Edad , Pandemias , Neumonía Viral/mortalidad , Análisis Espacial , Adulto Joven
6.
Rev Bras Parasitol Vet ; 29(2): e000820, 2020.
Artículo en Inglés | MEDLINE | ID: mdl-32490893

RESUMEN

Toxoplasma gondii is one of the most important protozoa parasites worldwide. Although many seroprevalence studies have been performed in domestic and wild species, data on the cumulative incidence and the spatial distribution of T. gondii in animals are extremely scarce. In the present study, dogs from Botucatu municipality, São Paulo state, were followed for one year and their blood samples were collected on three moments: days 1, 180, and 360. The sera were submitted to the immunofluorescence antibody test (IFAT) to detect IgG antibodies to T. gondii. Age and sex were compared with IFAT results through statistical tests. Spatial analysis was used to detect clusters of seropositive dogs. Among the 350 dogs that were seronegative on day 1, 53 became seropositive in subsequent samplings; thus, cumulative incidence was 15.1% exposed dogs/year. Age and sex were not associated with serological results. The spatial analysis revealed that seropositive dogs were distributed in all the studied areas, with a significant cluster in a zone with poor sanitary conditions and low socioeconomic status. T. gondii is frequent and widely distributed in the urban area of Botucatu, and impoverished areas are possibly associated with high levels of environmental contamination by this parasite.


Asunto(s)
Anticuerpos Antiprotozoarios/sangre , Enfermedades de los Perros/epidemiología , Toxoplasmosis Animal/epidemiología , Animales , Brasil/epidemiología , Enfermedades de los Perros/diagnóstico , Enfermedades de los Perros/parasitología , Perros , Femenino , Técnica del Anticuerpo Fluorescente Indirecta/veterinaria , Incidencia , Estudios Longitudinales , Masculino , Estudios Seroepidemiológicos , Análisis Espacial , Toxoplasmosis Animal/diagnóstico
7.
Rev Bras Parasitol Vet ; 29(2): e001120, 2020.
Artículo en Inglés | MEDLINE | ID: mdl-32490894

RESUMEN

This study aimed to determine the seroprevalence, factors associated with seropositivity to Leishmania infection in dogs and spatial analysis in six municipalities in the semiarid region of Pernambuco, Brazil. Blood samples were collected from 462 dogs, 77 in each municipality, and used for serological analysis [dual path platform (DPP®) and enzyme-linked immunosorbent assay (ELISA)]. Clinical signs of dogs were evaluated and associated factors for Leishmania infection were analyzed using robust Poisson regression model. A seroprevalence of 42.8% (198/462, IC: 95% = 38.6%-47.6%) was detected in dogs that tested positive in both tests, ranging from 29.8% to 55.8%, with higher prevalence in the municipality of Cabrobó (55.8%; P = 0.006). About 67% (132/198) of the seropositive dogs showed one or more clinical signs suggestive of canine leishmaniasis (CanL), such as lymphadenomegaly, skin lesions and conjunctivitis, which were associated with seropositivity. High seroprevalence levels were identified in urban and rural areas in all the municipalities, and the buffer for sand flies around cases covered almost these entire areas. Spatial analysis revealed a significant cluster, showing a relative risk of 1.88 in the urban area of Cabrobó. The higher density of seropositive dogs in urban areas indicates the need effective control measures against CanL to prevent the emergence of canine and human diseases.


Asunto(s)
Anticuerpos Antiprotozoarios/sangre , Enfermedades de los Perros/epidemiología , Leishmania infantum/inmunología , Leishmaniasis Visceral/veterinaria , Animales , Brasil/epidemiología , Enfermedades de los Perros/diagnóstico , Perros , Ensayo de Inmunoadsorción Enzimática/veterinaria , Femenino , Leishmaniasis Visceral/diagnóstico , Leishmaniasis Visceral/epidemiología , Masculino , Prevalencia , Factores de Riesgo , Estudios Seroepidemiológicos , Análisis Espacial
8.
Rev Assoc Med Bras (1992) ; 66(3): 370-374, 2020 Mar.
Artículo en Inglés | MEDLINE | ID: mdl-32520160

RESUMEN

The present study aimed to review the epidemiology, clinical manifestation, laboratory diagnosis, treatment, and future perspectives related to COVID-19 infections. The following electronic databases were used searched: MEDLINE, SCIELO, and LILACS. It became clear that COVID-19 infections occur through exposure to the virus, and both the immunosuppressed and healthy population appear susceptible. The clinical course of COVID-19 is still not clear, although the SARS-CoV-2 infection seems to develop with mild, influenza-like symptoms in the vast majority of subjects, i.e., 10%-15% of COVID-19 patients. Since rRT-PCR tests serve as the gold standard method to confirm a SARS-CoV-2 infection, false-negative results could hinder the prevention and control of the epidemic, particularly considering the test plays a key role in the decision for continued isolated medical observation or discharge. Our findings also indicate that a radical increase in the identification and isolation of currently undocumented infections would be needed to fully control SARS-CoV2.


Asunto(s)
Betacoronavirus , Infecciones por Coronavirus , Pandemias , Neumonía Viral , Infecciones por Coronavirus/diagnóstico , Infecciones por Coronavirus/epidemiología , Infecciones por Coronavirus/terapia , Humanos , Neumonía Viral/diagnóstico , Neumonía Viral/epidemiología , Neumonía Viral/terapia , Análisis Espacial
9.
Ying Yong Sheng Tai Xue Bao ; 31(5): 1660-1672, 2020 May.
Artículo en Chino | MEDLINE | ID: mdl-32530245

RESUMEN

Research on the spatial quantitative evaluation of land use and ecosystem service value in the source region of the Yellow River is of great significance for ensuring the ecological security of the river basin. Taking Maduo County in the source region of the Yellow River as an example, based on a 3 km × 3 km grid unit, the spatial autocorrelation method was applied to construct an evaluation model of ecosystem service value. The spatial autocorrelation pattern characteristics of Maduo County in 2015 was quantitatively evaluated, and the spatial information of ecosystem service value was visually expressed. The results showed that, at the examined grid scale, the area of grasslands with different coverages was large, and water grid area accounted for 42.9% of the total grids and was mainly distributed in the northwest of Maduo County. The construction land showed a "line-like" distribution from northeast to southwest, while the unutilized land was more distributed in southwest and less in northeast. In space, different land use type grids interacted with each other, with positive correlation and cluster distribution. The values of global Moran I and local Moran I of water area was the largest, with strongest spatial aggregation and high local connectivity. The global Moran I and local Moran I values of the construction land were 0.293 and 0.127, respectively, with the weakest spatial autocorrelation and clustering characteristics in a small range. In 2015, ecosystem service value (ESV) of Maduo County was 93.887 billion yuan, the mean ESV across all the grids was 3.20×107 yuan, with a maximum of 19.96×107 yuan. The water distribution grid had high ESV. On the whole, the ESV distribution pattern in Maduo County had a significant spatial positive correlation, with clustered ESV grids. The ESV grids of different land use types generally showed high-high cluster and low-low cluster, with the spatial pattern of high-low cluster and low-high cluster being sporadic. We proposed several possible strategies of land space planning and use control. First, the water and unused land should adopt a "centralized continuum" protection mode that emphasize the value of ecological spillovers. Second, grasslands with different coverage levels should adopt a "group-type" eco-governance model of primary and secondary division and zoning management. Third, construction land should adopt a small-scale intensive development and utilization model in a "corridor " distribution pattern.


Asunto(s)
Conservación de los Recursos Naturales , Ecosistema , China , Ríos , Análisis Espacial
10.
Artículo en Inglés | MEDLINE | ID: mdl-32520210

RESUMEN

Leptospirosis is a reemerging zoonosis caused by bacteria of the genus Leptospira sp. with global importance in the medical and veterinary fields, being responsible for about 59 thousand deaths each year in the world. The use of Geographic Information Systems (GIS) in the health sector is propitious and has been adopted by human and animal health professionals as an important tool in spatial analyses of health. The objective of this study was to conduct a systematic review on the geoprocessing and spatial analysis techniques adopted for mapping risk areas of human and animal leptospirosis. The articles were collected on scientific platforms by entering the following terms: SIG/GIS, leptospirose/leptospirosis, area de risco/risk area and distribuicao espacial/spatial distribution, and included in the study if they met the following criteria: a) publication in the period from 1998 to 2017; b) identification of risk areas and/or spatial distribution of leptospirosis as one of the research topics; and c) application of GIS in the methodology. As a result, we found 40 articles, published by 15 different countries, which adopted GIS for the spatial analysis and identification of risk areas of leptospirosis. Among these, only 45% (18) conducted an spatial statistical analysis. Brazil and USA had the highest numbers of publications, 16 and 7 articles, respectively. From 2007, the use of GIS and spatial analysis techniques, applied to the theme of this study, have been intensified and diversified, and 93% of the articles elected for this review were published from 2007 to 2017. The results point to a progressive interest of health professionals in applying these techniques for monitoring and conducting epidemiological analyses of leptospirosis, besides indicating a greater need for intersectoral integration between health professionals and others, in the use of spatial analysis and GIS techniques.


Asunto(s)
Leptospirosis/epidemiología , Sistemas de Información Geográfica , Humanos , Medición de Riesgo , Análisis Espacial
11.
Artículo en Inglés | MEDLINE | ID: mdl-32545581

RESUMEN

Prediction of the COVID-19 incidence rate is a matter of global importance, particularly in the United States. As of 4 June 2020, more than 1.8 million confirmed cases and over 108 thousand deaths have been reported in this country. Few studies have examined nationwide modeling of COVID-19 incidence in the United States particularly using machine-learning algorithms. Thus, we collected and prepared a database of 57 candidate explanatory variables to examine the performance of multilayer perceptron (MLP) neural network in predicting the cumulative COVID-19 incidence rates across the continental United States. Our results indicated that a single-hidden-layer MLP could explain almost 65% of the correlation with ground truth for the holdout samples. Sensitivity analysis conducted on this model showed that the age-adjusted mortality rates of ischemic heart disease, pancreatic cancer, and leukemia, together with two socioeconomic and environmental factors (median household income and total precipitation), are among the most substantial factors for predicting COVID-19 incidence rates. Moreover, results of the logistic regression model indicated that these variables could explain the presence/absence of the hotspots of disease incidence that were identified by Getis-Ord Gi* (p < 0.05) in a geographic information system environment. The findings may provide useful insights for public health decision makers regarding the influence of potential risk factors associated with the COVID-19 incidence at the county level.


Asunto(s)
Infecciones por Coronavirus/epidemiología , Redes Neurales de la Computación , Neumonía Viral/epidemiología , Algoritmos , Betacoronavirus , Sistemas de Información Geográfica , Humanos , Incidencia , Modelos Logísticos , Aprendizaje Automático , Modelos Estadísticos , Pandemias , Salud Pública , Factores de Riesgo , Análisis Espacial , Estados Unidos/epidemiología
12.
Ying Yong Sheng Tai Xue Bao ; 31(2): 599-607, 2020 Feb.
Artículo en Chino | MEDLINE | ID: mdl-32476354

RESUMEN

Understanding the spatial variability and agglomeration of soil salinity is of great significance for the sustainable development of estuarine wetland. Landsat 8 OLI remote sensing image, digital elevation mode and soil surface samples of Minjiang estuary wetland of Fuzhou were used as the data sources. The correlation analysis and principal component analysis were combined to select significant environmental variables and to reduce their dimensions. We analyzed the spatial variability of soil salinity with support vector regression ordinary kriging model (SVROK) and regression kri-ging model (RK), and quantified spatial agglomeration of soil salinity by the spatial autocorrelation analysis. The results showed that three principal components (PCs) extracted by the principal component analysis could explain at least 85% of the total variance in the original dataset and reflected the comprehensive information of vegetation cover, soil properties and topography. Both soil salinity and its residuals were affected by structural factors and random factors. The SVROK model based on principal component (PCs) as input variables can more accurately reflect the spatial variability of soil salinity, with a trend of "higher in the north and lower in the south". The Moran's I of soil salinity was more than 0.5, with significant positive spatial autocorrelation and a higher spatial aggregation degree, displaying the spatial agglomeration characteristics of "high value agglomeration, high value widespread, high value surrounded by low value".


Asunto(s)
Suelo , Humedales , China , Estuarios , Salinidad , Análisis Espacial
13.
Indian J Public Health ; 64(Supplement): S188-S191, 2020 Jun.
Artículo en Inglés | MEDLINE | ID: mdl-32496253

RESUMEN

Background: Most of the countries are affected with the pandemic outbreak of the coronavirus infection. Understanding the severity and distribution in various regions will help in planning the controlling measures. Objectives: The objective was to assess the distribution and growth rate of COVID-19 infection in Tamil Nadu, India. Methods: The data on the number of infections of COVID-19 have been obtained from the media reports released by the Government of Tamil Nadu. The data contain information on the incidence of the disease for the first 41 days of the outbreak started on March 7, 2020. Log-linear model has been used to estimate the progression of the COVID-19 infection in Tamil Nadu. Separate models were employed to model the growth rate and decay rate of the disease. Spatial Poisson regression was used to identify the high-risk areas in the state. Results: : The models estimated the doubling time for the number of cases in growth phase as 3.96 (95% confidence interval [CI]: 2.70, 9.42) days and halving time in the decay phase as 12.08 (95% CI: 6.79, 54.78) days. The estimated median reproduction numbers were 1.88 (min = 1.09, max = 2.51) and 0.76 (min = 0.56, max = 0.99) in the growth and decay phases, respectively. The spatial Poisson regression identified 11 districts as high risk. Conclusion: The results indicate that the outbreak is showing decay in the number of infections of the disease which highlights the effectiveness of controlling measures.


Asunto(s)
Infecciones por Coronavirus/epidemiología , Neumonía Viral/epidemiología , Betacoronavirus , Interpretación Estadística de Datos , Humanos , Incidencia , India/epidemiología , Modelos Lineales , Pandemias , Análisis Espacial
14.
Rev Bras Epidemiol ; 23: e200057, 2020.
Artículo en Portugués, Inglés | MEDLINE | ID: mdl-32578812

RESUMEN

OBJECTIVE: To analyze the spatial distribution of the incidence of COVID-19 and its correlation with the municipal human development index (MHDI) of the municipalities of Ceará. METHODS: This is an ecological study with data recovered from the 15th epidemiological week and the 19th one of the year 2020 using the MHDI and the COVID-19 incidence coefficient for each municipality as variables. The univariate spatial correlation and the bivariate one were analyzed using the TerraView and GeoDa softwares. RESULTS: The incidence of COVID-19 has spatial dependence with moderate positive correlation and the formation of high-high clusters located in the metropolitan region of Fortaleza and municipalities in the north region. The lowest incidence was a low-low cluster in the south and west regions. There was a positive bivariate correlation between MHDI and the incidence of COVID-19 with the formation of a cluster in the metropolitan region of Fortaleza. CONCLUSION: The uneven mapping of COVID-19 and its relationship with MHDI in Ceará can contribute to actions to regional combat the pandemic.


Asunto(s)
Infecciones por Coronavirus/epidemiología , Neumonía Viral/epidemiología , Cambio Social , Análisis Espacial , Betacoronavirus , Brasil/epidemiología , Ciudades/epidemiología , Ciudades/estadística & datos numéricos , Análisis por Conglomerados , Humanos , Incidencia , Pandemias , Factores Socioeconómicos
15.
J Rural Health ; 36(3): 433-445, 2020 06.
Artículo en Inglés | MEDLINE | ID: mdl-32543763

RESUMEN

PURPOSE: This ecological analysis investigates the spatial patterns of the COVID-19 epidemic in the United States in relation to socioeconomic variables that characterize US counties. METHODS: Data on confirmed cases and deaths from COVID-19 for 2,814 US counties were obtained from Johns Hopkins University. We used Geographic Information Systems (GIS) to map the spatial aspects of this pandemic and investigate the disparities between metropolitan and nonmetropolitan communities. Multiple regression models were used to explore the contextual risk factors of infections and death across US counties. We included population density, percent of population aged 65+, percent population in poverty, percent minority population, and percent of the uninsured as independent variables. A state-level measure of the percent of the population that has been tested for COVID-19 was used to control for the impact of testing. FINDINGS: The impact of COVID-19 in the United States has been extremely uneven. Although densely populated large cities and their surrounding metropolitan areas are hotspots of the pandemic, it is counterintuitive that incidence and mortality rates in some small cities and nonmetropolitan counties approximate those in epicenters such as New York City. Regression analyses support the hypotheses of positive correlations between COVID-19 incidence and mortality rates and socioeconomic factors including population density, proportions of elderly residents, poverty, and percent population tested. CONCLUSIONS: Knowledge about the spatial aspects of the COVID-19 epidemic and its socioeconomic correlates can inform first responders and government efforts. Directives for social distancing and to "shelter-in-place" should continue to stem the spread of COVID-19.


Asunto(s)
Infecciones por Coronavirus/epidemiología , Neumonía Viral/epidemiología , Características de la Residencia/estadística & datos numéricos , Factores de Edad , Betacoronavirus , Infecciones por Coronavirus/mortalidad , Sistemas de Información Geográfica , Humanos , Ciudad de Nueva York/epidemiología , Pandemias , Neumonía Viral/mortalidad , Factores de Riesgo , Factores Socioeconómicos , Análisis Espacial , Estados Unidos/epidemiología
16.
Rev Soc Bras Med Trop ; 53: e20190291, 2020.
Artículo en Inglés | MEDLINE | ID: mdl-32491100

RESUMEN

Cutaneous leishmaniasis (CL) is a zoonotic disease with complex transmission cycle. Some environmental and socioeconomic factors are known to be the major determinants of the transmission process, which are involved in configuring the spatiotemporal patterns and thus can be delimiting. However, the relevance of these socioeconomic and environmental determinants is still not well understood. In this study, we aimed to identify the major environmental and socioeconomic determinants of CL in Brazil by articulating a systematic literature review of studies that are based on this subject. The methodology included a search for studies according to a structured protocol using the scientific platforms, such as Scielo and PubMed. The references of each identified article were who referred to CL determinants were further screened, and so on. We extracted information from 41 articles and the determinants were grouped accordingly. Two measures were evaluated as follows: a) the frequency of citations of the determinants; and b) the proportion of determinants identified as having "significant association in analytical studies" with respect to the total number of determinants analyzed in other analytical studies using the same concept. The analyzed articles covered most of the regions of Brazil and 7 other countries bordering Brazil. We found 43 concepts of determinants. However, the final selection resulted in the identification of 14 major determinants. These results therefore contribute in the identification of major CL determinants and this information can be used to establish strategies for identifying risk prone areas for disease surveillance.


Asunto(s)
Leishmaniasis Cutánea/epidemiología , Brasil/epidemiología , Ambiente , Humanos , Factores de Riesgo , Factores Socioeconómicos , Análisis Espacial
17.
Artículo en Inglés | MEDLINE | ID: mdl-32485854

RESUMEN

The aim of this rapid analysis was to investigate the spatial patterns of COVID-19 emergence across counties in Colorado. In the U.S. West, Colorado has the second highest number of cases and deaths, second only to California. Colorado is also reporting, like other states, that communities of color and low-income persons are disproportionately affected by COVID-19. Using GIS and correlation analysis, this study explored COVID-19 incidence and deaths from March 14 to April 8, 2020, with social determinants and chronic conditions. Preliminary results demonstrate that COVID-19 incidence intensified in mountain communities west of Denver and along the Urban Front Range, and evolved into new centers of risk in eastern Colorado. Overall, the greatest increase in COVID-19 incidence was in northern Colorado, i.e., Weld County, which reported the highest rates in the Urban Front Range. Social and health determinants associated with higher COVID-19-related deaths were population density and asthma, indicative of urban areas, and poverty and unemployment, suggestive of rural areas. Furthermore, a spatial overlap of high rates of chronic diseases with high rates of COVID-19 may suggest a broader syndemic health burden, where comorbidities intersect with inequality of social determinants of health.


Asunto(s)
Betacoronavirus , Infecciones por Coronavirus/epidemiología , Neumonía Viral/epidemiología , Enfermedad Crónica , Colorado/epidemiología , Comorbilidad , Humanos , Incidencia , Pandemias , Densidad de Población , Análisis Espacial
18.
Artículo en Inglés | MEDLINE | ID: mdl-32408602

RESUMEN

Air travel has a decisive role in the spread of infectious diseases at the global level. We present a methodology applied during the early stages of the COVID-19 pandemic that uses detailed aviation data at the final destination level in order to measure the risk of the disease spreading outside China. The approach proved to be successful in terms of identifying countries with a high risk of infected travellers and as a tool to monitor the evolution of the pandemic in different countries. The high number of undetected or asymptomatic cases of COVID-19, however, limits the capacity of the approach to model the full dynamics. As a result, the risk for countries with a low number of passengers from Hubei province appeared as low. Globalization and international aviation connectivity allow travel times that are much shorter than the incubation period of infectious diseases, a fact that raises the question of how to react in a potential new pandemic.


Asunto(s)
Viaje en Avión , Aviación/estadística & datos numéricos , Infecciones por Coronavirus/epidemiología , Coronavirus , Pandemias , Neumonía Viral/epidemiología , Betacoronavirus , Infecciones por Coronavirus/transmisión , Salud Global , Humanos , Neumonía Viral/transmisión , Medición de Riesgo , Análisis Espacial , Incertidumbre
19.
J Environ Manage ; 268: 110667, 2020 Aug 15.
Artículo en Inglés | MEDLINE | ID: mdl-32383661

RESUMEN

The research on SO2 pollution in China has been hotly debated over the past decades. Different from the existing studies, this work employs satellite observed SO2 columns from 2005 to 2016 and applies a spatial econometric approach to investigate the socio-economic influencing factors of SO2 pollution of 270 prefecture-level cities in China. The findings are as follows. (1) SO2 pollution over China exhibits a significant and positive spatial autocorrelation. (2) The most polluted area is concentrated on the North China Plain. However, SO2 pollution over China has been reduced gradually during the sample period, implying that overall environmental quality in China has been substantially improved. (3) Besides, the results of spatial econometric models are not in support of "pollution haven hypothesis". On the contrary, the pollution halo effect of foreign direct investment works well and contributes to reducing SO2 pollution in China. Moreover, we find that urban economic levels and innovative capability are negatively correlated with SO2 pollution, indicating that economic growth and an increase in innovation can help improve environmental quality. On contrast, the share of the secondary industry, urbanization and transportation are found to have positive impacts, indicating that they are three main contributors to SO2 pollution in China.


Asunto(s)
Contaminantes Atmosféricos , Contaminación del Aire , China , Ciudades , Monitoreo del Ambiente , Contaminación Ambiental , Material Particulado , Factores Socioeconómicos , Análisis Espacial
20.
Med Care ; 58(6): 497-503, 2020 06.
Artículo en Inglés | MEDLINE | ID: mdl-32412941

RESUMEN

BACKGROUND: Rates of low birthweight and prematurity vary 2-fold across states in the United States, with increased rates among states with higher concentrations of racial minorities. Medicaid expansion may serve as a mechanism to reduce geographic variation within states that expanded, by improving health and access to care for vulnerable populations. OBJECTIVE: The objective of this study was to identify the association of Medicaid expansion with changes in county-level geographic variation in rates of low birthweight and preterm births, overall and stratified by race/ethnicity. RESEARCH DESIGN: We compared changes in the coefficient of variation and the ratio of the 80th-to-20th percentiles using bootstrap samples (n=1000) of counties drawn separately for all births and for white, black, and Hispanic births, separately. MEASURES: County-level rates of low birthweight and preterm birth. RESULTS: Before Medicaid expansion, counties in expansion states were concentrated among quintiles with lower rates of adverse birth outcomes and counties in nonexpansion states were concentrated among quintiles with higher rates. In expansion states, county-level variation, measured by the coefficient of variation, declined for both outcomes among all racial/ethnic categories. In nonexpansion states, geographic variation reduced for both outcomes among Hispanic births and for low birthweight among white births, but increased for both outcomes among black births. CONCLUSIONS: The decrease in county-level variation in adverse birth outcomes among expansion states suggests improved equity in these states. Further reduction in geographic variation will depend largely on policies or interventions that reduce racial disparities in states that did and did not expand Medicaid.


Asunto(s)
Grupos de Población Continentales/estadística & datos numéricos , Recién Nacido de Bajo Peso , Medicaid/estadística & datos numéricos , Patient Protection and Affordable Care Act/legislación & jurisprudencia , Nacimiento Prematuro/etnología , Afroamericanos/estadística & datos numéricos , Grupo de Ascendencia Continental Europea/estadística & datos numéricos , Accesibilidad a los Servicios de Salud/estadística & datos numéricos , Encuestas Epidemiológicas , Hispanoamericanos/estadística & datos numéricos , Humanos , Recién Nacido , Cobertura del Seguro/estadística & datos numéricos , Seguro de Salud/estadística & datos numéricos , Análisis Espacial , Estados Unidos/epidemiología
SELECCIÓN DE REFERENCIAS
DETALLE DE LA BÚSQUEDA