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1.
PLoS One ; 16(4): e0249133, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-33793611

RESUMO

BACKGROUND: Several research efforts have evaluated the impact of various factors including a) socio-demographics, (b) health indicators, (c) mobility trends, and (d) health care infrastructure attributes on COVID-19 transmission and mortality rate. However, earlier research focused only on a subset of variable groups (predominantly one or two) that can contribute to the COVID-19 transmission/mortality rate. The current study effort is designed to remedy this by analyzing COVID-19 transmission/mortality rates considering a comprehensive set of factors in a unified framework. METHODS AND FINDINGS: We study two per capita dependent variables: (1) daily COVID-19 transmission rates and (2) total COVID-19 mortality rates. The first variable is modeled using a linear mixed model while the later dimension is analyzed using a linear regression approach. The model results are augmented with a sensitivity analysis to predict the impact of mobility restrictions at a county level. Several county level factors including proportion of African-Americans, income inequality, health indicators associated with Asthma, Cancer, HIV and heart disease, percentage of stay at home individuals, testing infrastructure and Intensive Care Unit capacity impact transmission and/or mortality rates. From the policy analysis, we find that enforcing a stay at home order that can ensure a 50% stay at home rate can result in a potential reduction of about 33% in daily cases. CONCLUSIONS: The model framework developed can be employed by government agencies to evaluate the influence of reduced mobility on transmission rates at a county level while accommodating for various county specific factors. Based on our policy analysis, the study findings support a county level stay at home order for regions currently experiencing a surge in transmission. The model framework can also be employed to identify vulnerable counties that need to be prioritized based on health indicators for current support and/or preferential vaccination plans (when available).


Assuntos
Assistência à Saúde , Demografia/estatística & dados numéricos , Pandemias/estatística & dados numéricos , Fatores Socioeconômicos , /mortalidade , Assistência à Saúde/organização & administração , Assistência à Saúde/estatística & dados numéricos , Instalações de Saúde/estatística & dados numéricos , Política de Saúde , Humanos , Fatores de Risco , Estados Unidos
2.
PLoS One ; 16(1): e0244962, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-33465108

RESUMO

The coronavirus disease pandemic has brought a new urgency for the development and deployment of web-based applications which complement, and offer alternatives to, traditional one-on-one consultations and pencil-and-paper (PaP) based assessments that currently dominate clinical research. We have recently developed a web-based application that can be used for the self-administered collection of patient demographics, self-rated health, depression and anxiety, and cognition as part of a single platform. In this study we report the findings from a study with 155 cognitively healthy older adults who received established PaP versions, as well as our novel computerized measures of self-rated health, depression and anxiety, and cognition. Moderate to high correlations were observed between PaP and web- based measures of self-rated health (r = 0.77), depression and anxiety (r = 0.72), and preclinical Alzheimer's disease cognitive composite (PACC) (r = .61). Test-retest correlations were variable with high correlations for a measure of processing speed and a measure of delayed episodic memory. Taken together, these data support the feasibility and validity of utilization of this novel web-based platform as a new alternative for collecting patient demographics and the assessment of self-rated health, depression and anxiety, and cognition in the elderly.


Assuntos
Ansiedade/diagnóstico , Disfunção Cognitiva/diagnóstico , Depressão/diagnóstico , Autoavaliação Diagnóstica , Avaliação Geriátrica/métodos , Internet , Telemedicina/métodos , Idoso , Idoso de 80 Anos ou mais , Ansiedade/epidemiologia , Disfunção Cognitiva/epidemiologia , Demografia/estatística & dados numéricos , Depressão/epidemiologia , Feminino , Humanos , Vida Independente , Masculino , Pessoa de Meia-Idade
3.
PLoS One ; 16(1): e0244536, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-33465142

RESUMO

BACKGROUND: Since March 11, 2020 when the World Health Organization (WHO) declared the COVID-19 pandemic, the number of infected cases, the number of deaths, and the number of affected countries have climbed rapidly. To understand the impact of COVID-19 on public health, many studies have been conducted for various countries. To complement the available work, in this article we examine Canadian COVID-19 data for the period of March 18, 2020 to August 16, 2020 with the aim to forecast the dynamic trend in a short term. METHOD: We focus our attention on Canadian data and analyze the four provinces, Ontario, Alberta, British Columbia, and Quebec, which have the most severe situations in Canada. To build predictive models and conduct prediction, we employ three models, smooth transition autoregressive (STAR) models, neural network (NN) models, and susceptible-infected-removed (SIR) models, to fit time series data of confirmed cases in the four provinces separately. In comparison, we also analyze the data of daily infections in two states of USA, Texas and New York state, for the period of March 18, 2020 to August 16, 2020. We emphasize that different models make different assumptions which are basically difficult to validate. Yet invoking different models allows us to examine the data from different angles, thus, helping reveal the underlying trajectory of the development of COVID-19 in Canada. FINDING: The examinations of the data dated from March 18, 2020 to August 11, 2020 show that the STAR, NN, and SIR models may output different results, though the differences are small in some cases. Prediction over a short term period incurs smaller prediction variability than over a long term period, as expected. The NN method tends to outperform other two methods. All the methods forecast an upward trend in all the four Canadian provinces for the period of August 12, 2020 to August 23, 2020, though the degree varies from method to method. This research offers model-based insights into the pandemic evolvement in Canada.


Assuntos
/epidemiologia , /mortalidade , Canadá/epidemiologia , Demografia/estatística & dados numéricos , Humanos , Modelos Estatísticos , Mortalidade/tendências , Redes Neurais de Computação
4.
PLoS One ; 16(1): e0244867, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-33449940

RESUMO

In light of the ongoing coronavirus disease (COVID-19) pandemic, this study aims to examine the relationship between the availability of public health resources and the mortality rate of this disease. We conducted empirical analyses using linear regression, a time-varying effect model, and a regression discontinuity design to investigate the association of medical resources with the mortality rate of the COVID-19 patients in Hubei, China. The results showed that the numbers of hospital beds, healthcare system beds, and medical staff per confirmed cases all had significant negative effects on the coronavirus disease mortality rate. Furthermore, in the context of the severe pandemic currently being experienced worldwide, the present study summarized the experience and implications in pandemic prevention and control in Hubei province from the perspective of medical resource integration as follows: First, hospitals' internal medical resources were integrated, breaking interdepartmental barriers. Second, joint pandemic control was realized by integrating regional healthcare system resources. Finally, an external medical resource allocation system was developed.


Assuntos
/mortalidade , /epidemiologia , China/epidemiologia , Demografia/estatística & dados numéricos , Recursos em Saúde/estatística & dados numéricos , Humanos , Mortalidade/tendências
5.
PLoS One ; 15(11): e0242654, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-33211748

RESUMO

BACKGROUND: Epidemiological studies during the early phase of the coronavirus (COVID-19) pandemics reported different level of people's risk perception in different countries. There is a paucity of data on perceived high risk of COVID-19 and associated factors in Ethiopia. We sought to assess the prevalence of community's perceived high risk about COVID-19 infections and associated factors among Gondar town community. METHODS: A cross-sectional study was carried out from April 20 to 27, 2020 in Gondar town community, Northwest Ethiopia. Multistage cluster sampling technique was used to recruit 635 participants. Structured and pre-tested questionnaire was used to collect the data. Descriptive statistics, bivariate and multivariable binary logistic regression were used to summarize the results. RESULTS: A total of 623 participants were considered in the analysis with a response rate of 98.1%. The prevalence of coronavirus high risk perceptions of the respondents was found to be 23.11% (95% CI; 19.80%-26.43%). Age above 45 years (AOR = 1.41, 95%CI; 1.19-2.66), college and above educational level (AOR = 0.28, 95%CI; 0.21-0.98), and poor knowledge towards COVID-19 virus (AOR = 1.57, 95%CI; 1.09-2.23) were significantly associated with perceived high risk about COVID-19. CONCLUSIONS: The prevalence of perceived high risk of COVID-19 was found to be low. Factors such as age, educational status, and knowledge about COVID-19 virus were found to be independent predictors of perceived high risk towards COVID-19. Government and non-government organizations should use formal and informal means of educating the community.


Assuntos
Infecções por Coronavirus/transmissão , Conhecimentos, Atitudes e Prática em Saúde , Pneumonia Viral/transmissão , Adolescente , Adulto , Idoso , Idoso de 80 Anos ou mais , Betacoronavirus , Estudos Transversais , Demografia/estatística & dados numéricos , Etiópia , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Pandemias , Fatores Sociológicos , Inquéritos e Questionários , Adulto Jovem
6.
Sci Rep ; 10(1): 18909, 2020 11 03.
Artigo em Inglês | MEDLINE | ID: mdl-33144595

RESUMO

While the epidemic of SARS-CoV-2 has spread worldwide, there is much concern over the mortality rate that the infection induces. Available data suggest that COVID-19 case fatality rate had varied temporally (as the epidemic has progressed) and spatially (among countries). Here, we attempted to identify key factors possibly explaining the variability in case fatality rate across countries. We used data on the temporal trajectory of case fatality rate provided by the European Center for Disease Prevention and Control, and country-specific data on different metrics describing the incidence of known comorbidity factors associated with an increased risk of COVID-19 mortality at the individual level. We also compiled data on demography, economy and political regimes for each country. We found that temporal trajectories of case fatality rate greatly vary among countries. We found several factors associated with temporal changes in case fatality rate both among variables describing comorbidity risk and demographic, economic and political variables. In particular, countries with the highest values of DALYs lost to cardiovascular, cancer and chronic respiratory diseases had the highest values of COVID-19 CFR. CFR was also positively associated with the death rate due to smoking in people over 70 years. Interestingly, CFR was negatively associated with share of death due to lower respiratory infections. Among the demographic, economic and political variables, CFR was positively associated with share of the population over 70, GDP per capita, and level of democracy, while it was negatively associated with number of hospital beds ×1000. Overall, these results emphasize the role of comorbidity and socio-economic factors as possible drivers of COVID-19 case fatality rate at the population level.


Assuntos
Infecções por Coronavirus/mortalidade , Pneumonia Viral/mortalidade , Canadá , Infecções por Coronavirus/epidemiologia , Interpretação Estatística de Dados , Demografia/estatística & dados numéricos , Europa (Continente) , Humanos , Mortalidade/tendências , Pandemias , Pneumonia Viral/epidemiologia , Sistemas Políticos/estatística & dados numéricos , Fatores Socioeconômicos , Estados Unidos
7.
Buenos Aires; GCBA. Dirección General de Estadística y Censos; nov. 2020. a) f: 50 l:57 p. tab, graf.(Población de Buenos Aires, 17, 29).
Monografia em Espanhol | LILACS, InstitutionalDB, BINACIS, UNISALUD | ID: biblio-1146287

RESUMO

En un nuevo contexto de la migración en la Ciudad de Buenos Aires, el presente informe tiene como objetivo analizar las características sociodemográficas de los principales orígenes que integran el conjunto de inmigrantes externos y que, como se mencionó, presentan particularidades en su composición y antigüedad de residencia en la Ciudad, considerando asimismo desde una perspectiva comparativa a los residentes nacidos en el país. Para este informe se explotaron los datos de la última Encuesta Anual de Hogares disponible correspondiente a 2019 que releva la Dirección General de Estadística y Censos sobre la base de una muestra probabilística de viviendas y hogares residentes en CABA y que contiene preguntas específicas sobre el lugar de nacimiento y el año desde que la persona reside en forma continua, que permiten identificar la antigüedad y cohortes de inmigrantes. (AU)


Assuntos
População , Dinâmica Populacional/tendências , Dinâmica Populacional/estatística & dados numéricos , Demografia/tendências , Demografia/estatística & dados numéricos , Emigração e Imigração/tendências , Emigração e Imigração/estatística & dados numéricos , População Residente , Migração Humana/tendências , Migração Humana/estatística & dados numéricos
8.
Lancet ; 396(10258): 1160-1203, 2020 10 17.
Artigo em Inglês | MEDLINE | ID: mdl-33069325

RESUMO

BACKGROUND: Accurate and up-to-date assessment of demographic metrics is crucial for understanding a wide range of social, economic, and public health issues that affect populations worldwide. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 produced updated and comprehensive demographic assessments of the key indicators of fertility, mortality, migration, and population for 204 countries and territories and selected subnational locations from 1950 to 2019. METHODS: 8078 country-years of vital registration and sample registration data, 938 surveys, 349 censuses, and 238 other sources were identified and used to estimate age-specific fertility. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate age-specific fertility rates for 5-year age groups between ages 15 and 49 years. With extensions to age groups 10-14 and 50-54 years, the total fertility rate (TFR) was then aggregated using the estimated age-specific fertility between ages 10 and 54 years. 7417 sources were used for under-5 mortality estimation and 7355 for adult mortality. ST-GPR was used to synthesise data sources after correction for known biases. Adult mortality was measured as the probability of death between ages 15 and 60 years based on vital registration, sample registration, and sibling histories, and was also estimated using ST-GPR. HIV-free life tables were then estimated using estimates of under-5 and adult mortality rates using a relational model life table system created for GBD, which closely tracks observed age-specific mortality rates from complete vital registration when available. Independent estimates of HIV-specific mortality generated by an epidemiological analysis of HIV prevalence surveys and antenatal clinic serosurveillance and other sources were incorporated into the estimates in countries with large epidemics. Annual and single-year age estimates of net migration and population for each country and territory were generated using a Bayesian hierarchical cohort component model that analysed estimated age-specific fertility and mortality rates along with 1250 censuses and 747 population registry years. We classified location-years into seven categories on the basis of the natural rate of increase in population (calculated by subtracting the crude death rate from the crude birth rate) and the net migration rate. We computed healthy life expectancy (HALE) using years lived with disability (YLDs) per capita, life tables, and standard demographic methods. Uncertainty was propagated throughout the demographic estimation process, including fertility, mortality, and population, with 1000 draw-level estimates produced for each metric. FINDINGS: The global TFR decreased from 2·72 (95% uncertainty interval [UI] 2·66-2·79) in 2000 to 2·31 (2·17-2·46) in 2019. Global annual livebirths increased from 134·5 million (131·5-137·8) in 2000 to a peak of 139·6 million (133·0-146·9) in 2016. Global livebirths then declined to 135·3 million (127·2-144·1) in 2019. Of the 204 countries and territories included in this study, in 2019, 102 had a TFR lower than 2·1, which is considered a good approximation of replacement-level fertility. All countries in sub-Saharan Africa had TFRs above replacement level in 2019 and accounted for 27·1% (95% UI 26·4-27·8) of global livebirths. Global life expectancy at birth increased from 67·2 years (95% UI 66·8-67·6) in 2000 to 73·5 years (72·8-74·3) in 2019. The total number of deaths increased from 50·7 million (49·5-51·9) in 2000 to 56·5 million (53·7-59·2) in 2019. Under-5 deaths declined from 9·6 million (9·1-10·3) in 2000 to 5·0 million (4·3-6·0) in 2019. Global population increased by 25·7%, from 6·2 billion (6·0-6·3) in 2000 to 7·7 billion (7·5-8·0) in 2019. In 2019, 34 countries had negative natural rates of increase; in 17 of these, the population declined because immigration was not sufficient to counteract the negative rate of decline. Globally, HALE increased from 58·6 years (56·1-60·8) in 2000 to 63·5 years (60·8-66·1) in 2019. HALE increased in 202 of 204 countries and territories between 2000 and 2019. INTERPRETATION: Over the past 20 years, fertility rates have been dropping steadily and life expectancy has been increasing, with few exceptions. Much of this change follows historical patterns linking social and economic determinants, such as those captured by the GBD Socio-demographic Index, with demographic outcomes. More recently, several countries have experienced a combination of low fertility and stagnating improvement in mortality rates, pushing more populations into the late stages of the demographic transition. Tracking demographic change and the emergence of new patterns will be essential for global health monitoring. FUNDING: Bill & Melinda Gates Foundation.


Assuntos
Coeficiente de Natalidade , Carga Global da Doença , Expectativa de Vida , Mortalidade , Adolescente , Adulto , Idoso , Idoso de 80 Anos ou mais , Censos , Criança , Pré-Escolar , Demografia/estatística & dados numéricos , Feminino , Humanos , Lactente , Recém-Nascido , Nascimento Vivo/epidemiologia , Masculino , Pessoa de Meia-Idade , Fatores de Risco , Análise Espacial , Inquéritos e Questionários , Adulto Jovem
9.
PLoS One ; 15(10): e0239451, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-33048926

RESUMO

INTRODUCTION: Most communities, rural or urban, have taboos regarding foods to avoid during pregnancy, and most have local explanations for why certain foods should be avoided. Such taboos may have health benefits, but they also can have large nutritional and health costs to mothers and fetuses. As such, understanding local pregnancy food taboos is an important public health goal, especially in contexts where food resources are limited. Despite this, information regarding food taboos is limited in Ethiopia. Therefore, this study assessed food taboos, related misconceptions, and associated factors among pregnant women in Northern Ethiopia. METHODS: A cross-sectional study of 332 pregnant women in antenatal care (ANC) follow-up at selected private clinics in Mekelle city, Tigray, Ethiopa, recruited between April and May, 2017. Using a semi-structured questionnaire, we assessed whether respondents' observed food taboos, what types of foods they avoided, their perceived reasons for avoidance, diversity of respondents' diets during pregnancy, and respondents' socio-demographic characteristics. After reporting frequency statistics for categorical variables and central tendencies (mean and standard deviation) of continuous variables, bivariate and multivariable logistic regression analyses were conducted to identify the socio-demographic factors and diet diversity associated with food taboo practices. RESULTS: Around 12% of the pregnant women avoided at least one type of food during their current pregnancy for one or more reasons. These mothers avoided eating items such as yogurt, banana, legumes, honey, and "kollo" (roasted barley and wheat). The most common reasons given for the avoidances were that the foods were (mistakenly) believed to cause: abortion; abdominal cramps in the mother and newborn; prolonged labor; or coating of the fetus's body. Maternal education (diploma and above) (AOR: 4.55, 95% CI: 1.93, 10.31) and marital status (single) were found to be negatively associated (protective factors) with observances of pregnancy food taboos. Approximately 79% of respondents had pregnancy diets that were insufficiently diverse, although we did not find any statistical evidence that this was associated with adhering to food taboos. CONCLUSION: The misconceptions related to pregnancy food taboos should be discouraged insofar as they may restrict women's consumption of nutritious foods which could support maternal health and healthy fetal development. Health providers should counsel pregnant women and their husbands about appropriate pregnancy nutrition during ANC visits.


Assuntos
Cidades , Dieta/psicologia , Tabu , Adulto , Demografia/estatística & dados numéricos , Etiópia , Feminino , Humanos , Avaliação Nutricional , Gravidez
10.
PLoS One ; 15(10): e0239678, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-33052918

RESUMO

We generalize the Susceptible-Infected-Removed (SIR) model for epidemics to take into account generic effects of heterogeneity in the degree of susceptibility to infection in the population. We introduce a single new parameter corresponding to a power-law exponent of the susceptibility distribution at small susceptibilities. We find that for this class of distributions the gamma distribution is the attractor of the dynamics. This allows us to identify generic effects of population heterogeneity in a model as simple as the original SIR model which is contained as a limiting case. Because of this simplicity, numerical solutions can be generated easily and key properties of the epidemic wave can still be obtained exactly. In particular, we present exact expressions for the herd immunity level, the final size of the epidemic, as well as for the shape of the wave and for observables that can be quantified during an epidemic. In strongly heterogeneous populations, the herd immunity level can be much lower than in models with homogeneous populations as commonly used for example to discuss effects of mitigation. Using our model to analyze data for the SARS-CoV-2 epidemic in Germany shows that the reported time course is consistent with several scenarios characterized by different levels of immunity. These scenarios differ in population heterogeneity and in the time course of the infection rate, for example due to mitigation efforts or seasonality. Our analysis reveals that quantifying the effects of mitigation requires knowledge on the degree of heterogeneity in the population. Our work shows that key effects of population heterogeneity can be captured without increasing the complexity of the model. We show that information about population heterogeneity will be key to understand how far an epidemic has progressed and what can be expected for its future course.


Assuntos
Infecções por Coronavirus/epidemiologia , Demografia/estatística & dados numéricos , Modelos Teóricos , Pneumonia Viral/epidemiologia , Infecções por Coronavirus/imunologia , Alemanha , Humanos , Imunidade Coletiva , Pandemias , Pneumonia Viral/imunologia
11.
PLoS One ; 15(10): e0240151, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-33052932

RESUMO

As of August 2020, the United States is the global epicenter of the COVID-19 pandemic. Emerging data suggests that "essential" workers, who are disproportionately more likely to be racial/ethnic minorities and immigrants, bear a disproportionate degree of risk. We used publicly available data to build a series of spatial autoregressive models assessing county level associations between COVID-19 mortality and (1) percentage of individuals engaged in farm work, (2) percentage of households without a fluent, adult English-speaker, (3) percentage of uninsured individuals under the age of 65, and (4) percentage of individuals living at or below the federal poverty line. We further adjusted these models for total population, population density, and number of days since the first reported case in a given county. We found that across all counties that had reported a case of COVID-19 as of July 12, 2020 (n = 3024), a higher percentage of farmworkers, a higher percentage of residents living in poverty, higher density, higher population, and a higher percentage of residents over the age of 65 were all independently and significantly associated with a higher number of deaths in a county. In urban counties (n = 115), a higher percentage of farmworkers, higher density, and larger population were all associated with a higher number of deaths, while lower rates of insurance coverage in a county was independently associated with fewer deaths. In non-urban counties (n = 2909), these same patterns held true, with higher percentages of residents living in poverty and senior residents also significantly associated with more deaths. Taken together, our findings suggest that farm workers may face unique risks of contracting and dying from COVID-19, and that these risks are independent of poverty, insurance, or linguistic accessibility of COVID-19 health campaigns.


Assuntos
Infecções por Coronavirus/epidemiologia , Pneumonia Viral/epidemiologia , Fatores Socioeconômicos , Infecções por Coronavirus/mortalidade , Demografia/estatística & dados numéricos , Emigrantes e Imigrantes/estatística & dados numéricos , Fazendeiros/estatística & dados numéricos , Humanos , Cobertura do Seguro/estatística & dados numéricos , Pandemias , Pneumonia Viral/mortalidade , Estados Unidos
12.
PLoS One ; 15(10): e0240346, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-33052960

RESUMO

BACKGROUND: Given the severity and scope of the current COVID-19 pandemic, it is critical to determine predictive features of COVID-19 mortality and medical resource usage to effectively inform health, risk-based physical distancing, and work accommodation policies. Non-clinical sociodemographic features are important explanatory variables of COVID-19 outcomes, revealing existing disparities in large health care systems. METHODS AND FINDINGS: We use nation-wide multicenter data of COVID-19 patients in Brazil to predict mortality and ventilator usage. The dataset contains hospitalized patients who tested positive for COVID-19 and had either recovered or were deceased between March 1 and June 30, 2020. A total of 113,214 patients with 50,387 deceased, were included. Both interpretable (sparse versions of Logistic Regression and Support Vector Machines) and state-of-the-art non-interpretable (Gradient Boosted Decision Trees and Random Forest) classification methods are employed. Death from COVID-19 was strongly associated with demographics, socioeconomic factors, and comorbidities. Variables highly predictive of mortality included geographic location of the hospital (OR = 2.2 for Northeast region, OR = 2.1 for North region); renal (OR = 2.0) and liver (OR = 1.7) chronic disease; immunosuppression (OR = 1.7); obesity (OR = 1.7); neurological (OR = 1.6), cardiovascular (OR = 1.5), and hematologic (OR = 1.2) disease; diabetes (OR = 1.4); chronic pneumopathy (OR = 1.4); immunosuppression (OR = 1.3); respiratory symptoms, ranging from respiratory discomfort (OR = 1.4) and dyspnea (OR = 1.3) to oxygen saturation less than 95% (OR = 1.7); hospitalization in a public hospital (OR = 1.2); and self-reported patient illiteracy (OR = 1.1). Validation accuracies (AUC) for predicting mortality and ventilation need reach 79% and 70%, respectively, when using only pre-admission variables. Models that use post-admission disease progression information reach accuracies (AUC) of 86% and 87% for predicting mortality and ventilation use, respectively. CONCLUSIONS: The results highlight the predictive power of socioeconomic information in assessing COVID-19 mortality and medical resource allocation, and shed light on existing disparities in the Brazilian health care system during the COVID-19 pandemic.


Assuntos
Infecções por Coronavirus/epidemiologia , Utilização de Instalações e Serviços/estatística & dados numéricos , Modelos Estatísticos , Pneumonia Viral/epidemiologia , Fatores Socioeconômicos , Brasil , Comorbidade , Infecções por Coronavirus/mortalidade , Demografia/estatística & dados numéricos , Disparidades em Assistência à Saúde/estatística & dados numéricos , Humanos , Pandemias , Pneumonia Viral/mortalidade
13.
PLoS One ; 15(10): e0240500, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-33052976

RESUMO

BACKGROUND: The COVID-19 pandemic has led to disruptive changes worldwide, with different implications across countries. The evolution of citizens' concerns and behaviours over time is a central piece to support public policies. OBJECTIVE: To unveil perceptions and behaviours of the Portuguese population regarding social and economic impacts of the COVID-19 pandemic, allowing for more informed public policies. METHODS: Online panel survey distributed in three waves between March 13th and May 6th 2020. Data collected from a non-representative sample of 7,448 respondents includes socio-demographic characteristics and self-reported measures on levels of concern and behaviours related to COVID-19. We performed descriptive analysis and probit regressions to understand relationships between the different variables. RESULTS: Most participants (85%) report being at least very concerned with the consequences of the COVID-19 pandemic and social isolation reached a high level of adherence during the state of emergency. Around 36% of the sample anticipated consumption decisions, stockpiling ahead of the state of emergency declaration. Medical appointments suffered severe consequences, being re-rescheduled or cancelled. We find important variation in concerns with the economic impact across activity sectors. CONCLUSION: We show that high level of concern and behaviour adaptation in our sample preceded the implementation of lockdown measures in Portugal around mid-March. One month later, a large share of individuals had suffered disruption in their routine health care and negative impacts in their financial status.


Assuntos
Adaptação Psicológica , Comportamento do Consumidor , Infecções por Coronavirus/psicologia , Pneumonia Viral/psicologia , Comportamento Social , Adolescente , Adulto , Idoso , Idoso de 80 Anos ou mais , Atitude , Infecções por Coronavirus/epidemiologia , Demografia/estatística & dados numéricos , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Pandemias , Pneumonia Viral/epidemiologia , Portugal , Fatores Socioeconômicos
14.
PLoS One ; 15(9): e0239334, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32976484

RESUMO

BACKGROUND: Botswana is currently undergoing rapid epidemiological transition indicated by a decline in infectious diseases and an increase in chronic non-communicable diseases and their associated risk factors. The main aim of this study was to assess prevalence and correlates of multimorbidity among the adult population in Botswana. METHODS: A cross-sectional study called Chronic Non-Communicable Diseases Study (NCDs study) was conducted in March, 2016. Using multistage cross sectional sampling design, 1178 male and female respondents aged 15 years and above were interviewed across 3 cities and towns, 15 urban villages and 15 rural villages. Participants were interviewed face-to-face using a structured questionnaire. Adjusted multinomial logistic regression analysis was used to assess covariates of multimorbidity. The statistical significant level was fixed at p <0 .05. RESULTS: Prevalence of multimorbidity in the sampled population was estimated at 5.4%. Multivariate results indicate that the odds of multimobridty were significantly high among women (AOR = 3.34, 95% C.I. = 1.22-21.3) than men. On the other hand, the odds of multimorbidity were significantly low among young people aged below 24 years (AOR = 0.01, 95% C.I. = 0.00-0.07), currently married people (AOR = 0.24, 95% C.I. = 0.07-0.80) and individuals in the 2nd wealth quintile (AOR = 0.20, 95% C.I. = 0.05-0.75) compared to their counterparts. For behavioural risk factors, alcohol consumption (AOR = 4.80, 95% C.I. = 1.16-19.8) and overweight/obesity (AOR = 1.44, 95% CI = 1.12-2.61) were significantly associated with high multimorbidity prevalence. CONCLUSION: Multimorbidity was found to be more prevalent among women, alcohol consumers and overweight/obese people. There is need to strengthen interventions encouraging healthy lifestyles such as non-consumption of alcohol, physical activity and healthy diets. Moreover, there is need for a holistic approach of health care services to meet the needs of those suffering from multimorbidity.


Assuntos
Multimorbidade , Adulto , Idoso , Comportamento , Botsuana/epidemiologia , Estudos Transversais , Demografia/estatística & dados numéricos , Feminino , Inquéritos Epidemiológicos , Humanos , Masculino , Pessoa de Meia-Idade , Prevalência , Adulto Jovem
15.
PLoS One ; 15(9): e0239855, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32976494

RESUMO

INTRODUCTION: Antenatal care (ANC) is a vital mechanism for women to obtain close attention during pregnancy and prevent death-related issues. Moreover, it improves the involvement of women in the continuum of health care and to survive high-risk pregnancies. This study was conducted to determine the prevalence of and identify the associated factors of eight or more ANC contacts in Nigeria. METHODS: We used a nationally representative cross-sectional data from Nigeria Demographic and Health Survey-2018. A total sample of 7,936 women were included in this study. Prevalence was measured in percentages and the factors for eight or more ANC contacts were examined using multilevel multivariable binary logistic regression model. The level of significance was set at P<0.05. RESULTS: The prevalence of eight or more ANC contacts in Nigeria was approximately 17.4% (95% CI: 16.1%-18.7%). Women with at least secondary education were 2.46 times as likely to have eight or more ANC contacts, when compared with women with no formal education. Women who use media were 2.37 times as likely to have eight or more ANC contacts, when compared with women who do not use media. For every unit increase in the time (month) of ANC initiation, there was 53% reduction in the odds of eight or more ANC contacts. Rural women had 60% reduction in the odds of eight or more ANC contacts, when compared with their urban counterparts. Women from North East and North West had 74% and 79% reduction respectively in the odds of eight or more ANC contacts, whereas women from South East, South South and South West were 2.68, 5.00 and 14.22 times respectively as likely to have eight or more ANC contacts when compared with women from North Central. CONCLUSION: The coverage of eight or more ANC contacts was low and can be influenced by individual-, household-, and community-level factors. There should be concerted efforts to improve maternal socioeconomic status, as well as create awareness among key population for optimal utilization of ANC.


Assuntos
Utilização de Instalações e Serviços/estatística & dados numéricos , Cuidado Pré-Natal/estatística & dados numéricos , Adolescente , Adulto , Demografia/estatística & dados numéricos , Escolaridade , Feminino , Inquéritos Epidemiológicos/estatística & dados numéricos , Humanos , Pessoa de Meia-Idade , Nigéria , Características de Residência/estatística & dados numéricos , População Rural/estatística & dados numéricos , População Urbana/estatística & dados numéricos
16.
PLoS One ; 15(9): e0239722, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32976544

RESUMO

BACKGROUND: Pakistan and other developing countries need to address disparities in maternal health care and factors associated with it. This justifies tracking the progress on two important indicators 'spousal violence' and 'maternal health care utilization' to improve maternal health and achieve Sustainable Development Goals (SDGs) for these nations. OBJECTIVE: The objective of this study is to compare the data from the latest two Demographic Health Surveys of Pakistan to identify trends in prevalence of various forms of spousal violence and maternal healthcare utilization and to determine the predictive role of spousal violence in poor maternal health. METHODS: We conducted a retrospective analysis of nationally representative data from the 2012-13 and 2017-18 PDHS. The data used in this analysis is from the domestic violence module and core women's questionnaire. Spousal violence and sociodemographic background were predictor variables. Terminated pregnancy, number of pregnancy losses, number of antenatal visits for last birth and institutional delivery for last birth were taken as indicators of maternal health. Logistic regression analysis was conducted to test for association between maternal health indicators and various forms of spousal violence after controlling for sociodemographic variables. RESULTS: Almost one quarter of women experienced physical and emotional violence as revealed by both surveys. Binary analysis revealed that all forms of spousal violence significantly associate with maternal health variables in both surveys. The comparison of results on logistic regression analysis showed that odd ratios were relatively higher for 2012-13 as compared to 2017-18 PDHS. Logistic regression analysis from 2017-18 data showed that experience of less severe physical violence (OR = 1.26; 95% CI, 1.08-1.47), severe physical violence (OR = 1.41; 95% CI, 1.09-1.83), sexual violence (OR = 1.39; 95% CI, 1.02-1.89), physical violence during pregnancy (OR = 1.37; 95% CI, 1.07-1.76) augment the risk of terminated pregnancy. Emotional violence decreases the likelihood for institutional delivery (OR = 0.64; 95% CI, 0.45-0.93) and above than four antenatal visits (OR = 0.54; 95% CI, 0.37-0.79). CONCLUSIONS: Strategies to prevent spousal violence should be at the core of maternal health programs because health sector provides a platform to challenge social norms and promote attitudes that disapprove spousal violence which are essential for promoting gender equality, women empowerment (SDG 3) and improve maternal health (SDG 5).


Assuntos
Utilização de Instalações e Serviços/tendências , Serviços de Saúde Materna/estatística & dados numéricos , Maus-Tratos Conjugais/estatística & dados numéricos , Adolescente , Adulto , Demografia/estatística & dados numéricos , Feminino , Humanos , Pessoa de Meia-Idade , Paquistão , Fatores Socioeconômicos
17.
PLoS One ; 15(9): e0239654, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32970748

RESUMO

Socioeconomic status (SES), living in poverty, and other social determinants of health contribute to health disparities in the United States. African American (AA) men living below poverty in Baltimore City have a higher incidence of mortality when compared to either white males or AA females living below poverty. Previous studies in our laboratory and elsewhere suggest that environmental conditions are associated with differential gene expression (DGE) patterns in peripheral blood mononuclear cells (PBMCs). DGE have also been associated with hypertension and cardiovascular disease (CVD) and correlate with race and sex. However, no studies have investigated how poverty status associates with DGE between male and female AAs and whites living in Baltimore City. We examined DGE in 52 AA and white participants of the Healthy Aging in Neighborhoods of Diversity across the Life Span (HANDLS) cohort, who were living above or below 125% of the 2004 federal poverty line at time of sample collection. We performed a microarray to assess DGE patterns in PBMCs from these participants. AA males and females living in poverty had the most genes differentially-expressed compared with above poverty controls. Gene ontology (GO) analysis identified unique and overlapping pathways related to the endosome, single-stranded RNA binding, long-chain fatty-acyl-CoA biosynthesis, toll-like receptor signaling, and others within AA males and females living in poverty and compared with their above poverty controls. We performed RT-qPCR to validate top differentially-expressed genes in AA males. We found that KLF6, DUSP2, RBM34, and CD19 are expressed at significantly lower levels in AA males in poverty and KCTD12 is higher compared to above poverty controls. This study serves as an additional link to better understand the gene expression response in peripheral blood mononuclear cells in those living in poverty.


Assuntos
Monócitos/metabolismo , Pobreza/estatística & dados numéricos , Transcriptoma , Adulto , Demografia/estatística & dados numéricos , Feminino , Perfilação da Expressão Gênica , Humanos , Longevidade , Masculino , Redes e Vias Metabólicas/genética , Pessoa de Meia-Idade , População Urbana/estatística & dados numéricos
18.
Surg Clin North Am ; 100(5): 823-833, 2020 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-32882165

RESUMO

This article reviews key population trends affecting rural American health. The article explains the role of demography in defining and studying rural health using example data from the 2014 to 2018 American Community Survey. Specific trends, including depopulation, aging, racial/ethnic diversification, socioeconomic status, and health characteristics found in rural areas, are highlighted. Insights are offered into how population trends, changing age and sex structures, and socioeconomic distributions have implications for rural health care practitioners and surgeons. Several areas and opportunities to address current and future rural health needs are identified.


Assuntos
Demografia/estatística & dados numéricos , Saúde da População Rural/estatística & dados numéricos , População Rural/estatística & dados numéricos , Humanos , Estados Unidos
19.
PLoS One ; 15(9): e0238508, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32898144

RESUMO

Strictly relying on publicly available data, this study depicts and quantifies the spatial pattern of England's military families with dependent children. England's Service Pupil Premium for the financial years between 2011 and 2019 is used as a proxy variable to estimate the density of service children at the parliamentary constituency level. Methodologically, the approach allows an assessment of spatial movements of a population or a cohort. The results inform policy makers by providing evidence-based findings about the location of England's military families and how the distribution has changed between 2011 and 2019. The results show empirical evidence supporting the hypothesis that, at a macro scale, beyond commuting distance, England's military families are becoming increasingly dispersed. We argue that the findings unveil spatial dynamics that have practical issues of housing, employment, and education regarding military families.


Assuntos
Família Militar , Criança , Demografia/estatística & dados numéricos , Inglaterra , Habitação , Humanos , Família Militar/estatística & dados numéricos
20.
Z Naturforsch C J Biosci ; 75(11-12): 389-396, 2020 Nov 26.
Artigo em Inglês | MEDLINE | ID: mdl-32920544

RESUMO

The coronavirus is currently extremely contagious for humankind, which is a zoonotic tropical disease. The pandemic is the largest in history, affecting almost the whole world. What makes the condition the worst of all is no specific effective treatment available. In this article, we present an extended and modified form of SIR and SEIR model, respectively. We begin by investigating a simple mathematical model that describes the pandemic. Then we apply different safety measures to control the pandemic situation. The mathematical model with and without control is solved by using homotopy perturbation method. Obtained solutions have been presented graphically. Finally, we develop another mathematical model, including quarantine and hospitalization.


Assuntos
Infecções por Coronavirus/epidemiologia , Demografia/estatística & dados numéricos , Modelos Teóricos , Pneumonia Viral/epidemiologia , Infecções por Coronavirus/prevenção & controle , Hospitalização/estatística & dados numéricos , Humanos , Pandemias/prevenção & controle , Pneumonia Viral/prevenção & controle , Quarentena/estatística & dados numéricos
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