Your browser doesn't support javascript.
loading
Mostrar: 20 | 50 | 100
Resultados 1 - 20 de 1.172
Filtrar
1.
Mayo Clin Proc ; 96(1): 92-104, 2021 01.
Artigo em Inglês | MEDLINE | ID: mdl-33413839

RESUMO

OBJECTIVE: To estimate the contribution of county-level contextual factors to differences in life expectancy in the United States. METHODS: We used a counterfactual approach to estimate the years of life expectancy lost associated with 45 potentially modifiable county-level contextual characteristics in the United States in the year 2016. Contextual data and life expectancy data were obtained from the County Health Ranking Project and the U.S. Small-Area Life Expectancy Estimates Project, respectively. RESULTS: Median census-tract-level life expectancy was 78.90 (interquartile range, 76.30-81.00) years, and the range across census tracts spanned 41.20 years. Large variations in life expectancy existed within and between states and within and between counties; the gap between counties was 20.30 years and gaps within counties ranged from 0 to 34.60 years. An array of 45 county-level factors was associated with 4.30 years of life expectancy loss. County-level adult smoking, food insecurity, adult obesity, physical inactivity, college education, and median household income were associated with 1.24-, 0.89-, 0.58-, 0.35-, 0.33-, and 0.14-year losses in life expectancy, respectively; and altogether were associated with a 3.53-year loss in life expectancy. The contribution of contextual factors to years of life expectancy lost varied among states and was more pronounced in states with lower life expectancy and in areas of increased socioeconomic deprivation and increased percentage of Black race. CONCLUSION: Substantial geographic variation in life expectancy was observed. Six county-level contextual factors were associated with a 3.53-year loss in life expectancy. The findings may inform and help prioritize approaches to reduce inequalities in life expectancy in the United States.


Assuntos
Disparidades nos Níveis de Saúde , Expectativa de Vida , Idoso , Idoso de 80 Anos ou mais , Grupos de Populações Continentais/estatística & dados numéricos , Geografia Médica , Humanos , Fatores de Risco , Fatores Socioeconômicos , Estados Unidos
2.
Commun Biol ; 4(1): 60, 2021 01 05.
Artigo em Inglês | MEDLINE | ID: mdl-33402722

RESUMO

The basic reproduction number, R0, determines the rate of spread of a communicable disease and therefore gives fundamental information needed to plan public health interventions. Using mortality records, we estimated the rate of spread of COVID-19 among 160 counties and county-aggregates in the USA at the start of the epidemic. We show that most of the high among-county variance is explained by four factors (R2 = 0.70): the timing of outbreak, population size, population density, and spatial location. For predictions of future spread, population density and spatial location are important, and for the latter we show that SARS-CoV-2 strains containing the G614 mutation to the spike gene are associated with higher rates of spread. Finally, the high predictability of R0 allows extending estimates to all 3109 counties in the conterminous 48 states. The high variation of R0 argues for public health policies enacted at the county level for controlling COVID-19.


Assuntos
/epidemiologia , Surtos de Doenças , Modelos Estatísticos , /virologia , Análise Fatorial , Geografia Médica , Humanos , Densidade Demográfica , Vigilância da População , Estados Unidos/epidemiologia
3.
Euro Surveill ; 25(50)2020 12.
Artigo em Inglês | MEDLINE | ID: mdl-33334400

RESUMO

BackgroundThe first wave of the coronavirus disease (COVID-19) pandemic spread rapidly in Spain, one of Europe's most affected countries. A national lockdown was implemented on 15 March 2020.AimTo describe reported cases and the impact of national lockdown, and to identify disease severity risk factors.MethodsNational surveillance data were used to describe PCR-confirmed cases as at 27 April 2020. We compared case characteristics by severity categories (hospitalisation, admission to intensive care unit (ICU), death) and identified severity risk factors using multivariable regression.ResultsThe epidemic peaked on 20 March. Of 218,652 COVID-19 cases, 45.4% were hospitalised, 4.6% were admitted to ICU and 11.9% died. Among those who died, 94.8% had at least one underlying disease. Healthcare workers (HCWs) represented 22.9% of cases. Males were more likely to have severe outcomes than females. Cardiovascular disease was a consistent risk factor. Patients with pneumonia had higher odds of hospitalisation (odds ratio (OR): 26.63; 95% confidence interval (CI): 25.03-28.33). The strongest predictor of death was age ≥ 80 years (OR: 28.4; 95% CI: 19.85-40.78). Among underlying diseases, chronic renal disease had highest odds of death (OR: 1.47; 95% CI: 1.29-1.68).ConclusionsCOVID-19 case numbers began declining 6 days after the national lockdown. The first wave of the COVID-19 pandemic in Spain had a severe impact on elderly people. Patients with cardiovascular or renal conditions were at higher risk for severe outcomes. A high proportion of cases were HCWs. Enhanced surveillance and control measures in these subgroups are crucial during future COVID-19 waves.


Assuntos
/epidemiologia , Pandemias , Adolescente , Adulto , Idoso , Idoso de 80 Anos ou mais , Algoritmos , Criança , Pré-Escolar , Controle de Doenças Transmissíveis/métodos , Comorbidade , Coleta de Dados , Feminino , Geografia Médica , Pessoal de Saúde/estatística & dados numéricos , Humanos , Lactente , Masculino , Pessoa de Meia-Idade , Vigilância da População , Quarentena , Sistema de Registros , Fatores de Risco , Espanha/epidemiologia , Adulto Jovem
4.
PLoS One ; 15(11): e0242055, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-33166372

RESUMO

BACKGROUND: Novel approaches are required to better focus latent tuberculosis infection (LTBI) efforts in low-prevalence regions. Geographic information systems, used within large health systems, may provide one such approach. METHODS: A retrospective, cross-sectional design was used to integrate US Census and Duke Health System data between January 1, 2010 and October 31, 2017 and examine the relationships between LTBI screening and population tuberculosis risk (assessed using the surrogate measure of proportion of persons born in tuberculosis-endemic regions) by census tract. RESULTS: The median proportion of Duke patients screened per census tract was 0.01 (range 0-0.1, interquartile range 0.01-0.03). The proportion of Duke patients screened within a census tract significantly but weakly correlated with the population risk. Furthermore, patients residing in census tracts with higher population tuberculosis risk were more likely to be screened with TST than with an IGRA (p<0.001). CONCLUSION: The weak correlation between patient proportion screened for LTBI and our surrogate marker of population tuberculosis risk suggests that LTBI screening efforts should be better targeted. This type of geography-based analysis may serve as an easily obtainable benchmark for LTBI screening in health systems with low tuberculosis prevalence.


Assuntos
Tuberculose Latente/diagnóstico , Estudos Transversais , Doenças Endêmicas , Geografia Médica , Humanos , Tuberculose Latente/epidemiologia , Prevalência , Estudos Retrospectivos , Fatores de Risco
5.
Pan Afr Med J ; 35(Suppl 2): 131, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-33193946

RESUMO

Introduction: Nigeria is the most populous country in the African continent. The aim of this study was to analyze risk factors for COVID-19 prevalence and deaths in all 6 geopolitical regions and 37 States in Nigeria. Methods: we analyzed the data retrieved from various sources, including Nigeria CDC, Nigeria National Bureau of Statistics, Unicef-Nigeria multiple indicator cluster survey and the Institute of Health Metrics and Evaluation, University of Washington. We examined 4 clinical risk factors (prevalence of TB, HIV, smoking and BCG vaccination coverage) and 5 sociodemographic factors (age ≥65, population density, literacy rate, unemployment and GDP per capita). Multivariate modeling was conducted using generalized linear model. Results: our analysis showed that the incidence of confirmed COVID-19 cases differed widely across the 37 States, from 0.09 per 100,000 in Kogi to 83.7 in Lagos. However, more than 70% of confirmed cases were concentrated in just 7 States: Lagos, Abuja, Oyo, Kano, Edo, Rivers and Delta. Case mortality rate (CMR) also varied considerably, with Lagos, Abuja and Edo having CMR above 9 per million population. On bivariate analysis, higher CMR correlated positively with GDP (r=0.53) and to a lesser extent with TB (r=0.36) and population density (r=0.38). On multivariate analysis, which is more definitive, States with higher HIV prevalence and BCG coverage had lower CMR, while high GDP States had a greater CMR. Conclusion: this study indicates that COVID-19 has disproportionately affected certain States in Nigeria. Population susceptibility factors include higher economic development but not literacy or unemployment. Death rates were mildly lower in States with higher HIV prevalence and BCG vaccination coverage.


Assuntos
Betacoronavirus , Infecções por Coronavirus/mortalidade , Pandemias , Pneumonia Viral/mortalidade , Fatores Etários , Idoso , Vacina BCG , Feminino , Geografia Médica , Produto Interno Bruto/estatística & dados numéricos , Infecções por HIV/epidemiologia , Humanos , Alfabetização/estatística & dados numéricos , Masculino , Nigéria/epidemiologia , Densidade Demográfica , Prevalência , Utilização de Procedimentos e Técnicas , Fatores de Risco , Fumar/epidemiologia , Determinantes Sociais da Saúde , Tuberculose/epidemiologia , Desemprego/estatística & dados numéricos , Vacinação/estatística & dados numéricos
6.
Artigo em Inglês | MEDLINE | ID: mdl-33207598

RESUMO

Several studies on spatial patterns of COVID-19 show huge differences depending on the country or region under study, although there is some agreement that socioeconomic factors affect these phenomena. The aim of this paper is to increase the knowledge of the socio-spatial behavior of coronavirus and implementing a geospatial methodology and digital system called SITAR (Fast Action Territorial Information System, by its Spanish acronym). We analyze as a study case a region of Spain called Cantabria, geocoding a daily series of microdata coronavirus records provided by the health authorities (Government of Cantabria-Spain) with the permission of Medicines Ethics Committee from Cantabria (CEIm, June 2020). Geocoding allows us to provide a new point layer based on the microdata table that includes cases with a positive result in a COVID-19 test. Regarding general methodology, our research is based on Geographical Information Technologies using Environmental Systems Research Institute (ESRI) Technologies. This tool is a global reference for spatial COVID-19 research, probably due to the world-renowned COVID-19 dashboard implemented by the Johns Hopkins University team. In our analysis, we found that the spatial distribution of COVID-19 in urban locations presents a not random distribution with clustered patterns and density matters in the spread of the COVID-19 pandemic. As a result, large metropolitan areas or districts with a higher number of persons tightly linked together through economic, social, and commuting relationships are the most vulnerable to pandemic outbreaks, particularly in our case study. Furthermore, public health and geoprevention plans should avoid the idea of economic or territorial stigmatizations. We hold the idea that SITAR in particular and Geographic Information Technologies in general contribute to strategic spatial information and relevant results with a necessary multi-scalar perspective to control the pandemic.


Assuntos
Infecções por Coronavirus/epidemiologia , Infecções por Coronavirus/prevenção & controle , Geografia Médica , Pandemias/prevenção & controle , Pneumonia Viral/epidemiologia , Pneumonia Viral/prevenção & controle , Betacoronavirus , Mapeamento Geográfico , Humanos , Saúde Pública , Espanha
7.
Biomedica ; 40(Supl. 2): 131-138, 2020 10 30.
Artigo em Inglês, Espanhol | MEDLINE | ID: mdl-33152196

RESUMO

Introduction: Public health surveillance together with good sanitary decisions is essential for the proper management of the SARS-CoV-2 pandemic. Objective: To compare the performance of Colombian departments based on the quality of the data and to build the national ranking. Materials and methods: We analyzed the accumulated cases published between March 6 and September 1, 2020, by the Instituto Nacional de Salud. To achieve comparability, the analyses considered the day the first case was diagnosed as the first analysis date for each department. The fulfillment of Benford's law was assessed with p-values in the log-likelihood ratio or chi-square tests. The analysis was completed with the lethality observed in each department and then the performance ranking was established. Results: Bogotá and Valle del Cauca had optimal public health surveillance performance all along. The data suggest that Antioquia, Nariño, and Tolima had good containment and adequate public health surveillance after the economic opening beginning on June 1, 2020. Conclusion: We obtained the ranking of the departments regarding the quality of public health surveillance data. The best five departments can be case studies to identify the elements associated with good performance.


Assuntos
Betacoronavirus , Infecções por Coronavirus/epidemiologia , Pandemias , Pneumonia Viral/epidemiologia , Vigilância da População , Benchmarking , Colômbia/epidemiologia , Notificação de Doenças , Geografia Médica , Humanos , População Rural/estatística & dados numéricos , Distribuições Estatísticas , Análise de Sobrevida , População Urbana/estatística & dados numéricos
8.
JAMA ; 324(14): 1429-1438, 2020 10 13.
Artigo em Inglês | MEDLINE | ID: mdl-33048153

RESUMO

Importance: The prevalence of leading risk factors for morbidity and mortality in the US significantly varies across regions, states, and neighborhoods, but the extent these differences are associated with a person's place of residence vs the characteristics of the people who live in different places remains unclear. Objective: To estimate the degree to which geographic differences in leading risk factors are associated with a person's place of residence by comparing trends in health outcomes among individuals who moved to different areas or did not move. Design, Setting, and Participants: This retrospective cohort study estimated the association between the differences in the prevalence of uncontrolled chronic conditions across movers' destination and origin zip codes and changes in individuals' likelihood of uncontrolled chronic conditions after moving, adjusting for person-specific fixed effects, the duration of time since the move, and secular trends among movers and those who did not move. Electronic health records from the Veterans Health Administration were analyzed. The primary analysis included 5 342 207 individuals with at least 1 Veterans Health Administration outpatient encounter between 2008 and 2018 who moved zip codes exactly once or never moved. Exposures: The difference in the prevalence of uncontrolled chronic conditions between a person's origin zip code and destination zip code (excluding the individual mover's outcomes). Main Outcomes and Measures: Prevalence of uncontrolled blood pressure (systolic blood pressure level >140 mm Hg or diastolic blood pressure level >90 mm Hg), uncontrolled diabetes (hemoglobin A1c level >8%), obesity (body mass index >30), and depressive symptoms (2-item Patient Health Questionnaire score ≥2) per quarter-year during the 3 years before and the 3 years after individuals moved. Results: The study population included 5 342 207 individuals (mean age, 57.6 [SD, 17.4] years, 93.9% men, 72.5% White individuals, and 12.7% Black individuals), of whom 1 095 608 moved exactly once and 4 246 599 never moved during the study period. Among the movers, the change after moving in the prevalence of uncontrolled blood pressure was 27.5% (95% CI, 23.8%-31.3%) of the between-area difference in the prevalence of uncontrolled blood pressure. Similarly, the change after moving in the prevalence of uncontrolled diabetes was 5.0% (95% CI, 2.7%-7.2%) of the between-area difference in the prevalence of uncontrolled diabetes; the change after moving in the prevalence of obesity was 3.1% (95% CI, 2.0%-4.2%) of the between-area difference in the prevalence of obesity; and the change after moving in the prevalence of depressive symptoms was 15.2% (95% CI, 13.1%-17.2%) of the between-area difference in the prevalence of depressive symptoms. Conclusions and Relevance: In this retrospective cohort study of individuals receiving care at Veterans Health Administration facilities, geographic differences in prevalence were associated with a substantial percentage of the change in individuals' likelihood of poor blood pressure control or depressive symptoms, and a smaller percentage of the change in individuals' likelihood of poor diabetes control and obesity. Further research is needed to understand the source of these associations with a person's place of residence.


Assuntos
Transtorno Depressivo/epidemiologia , Diabetes Mellitus/epidemiologia , Migração Humana/estatística & dados numéricos , Hipertensão/epidemiologia , Obesidade/epidemiologia , Características de Residência/estatística & dados numéricos , Doença Crônica/epidemiologia , Doença Crônica/etnologia , Transtorno Depressivo/etnologia , Diabetes Mellitus/etnologia , Registros Eletrônicos de Saúde/estatística & dados numéricos , Feminino , Geografia Médica , Migração Humana/tendências , Humanos , Hipertensão/etnologia , Masculino , Pessoa de Meia-Idade , Obesidade/etnologia , Prevalência , Estudos Retrospectivos , Fatores de Risco , Fatores de Tempo , Incerteza , Estados Unidos/epidemiologia , Estados Unidos/etnologia , Serviços de Saúde para Veteranos Militares/estatística & dados numéricos
9.
Health Place ; 66: 102446, 2020 11.
Artigo em Inglês | MEDLINE | ID: mdl-33045672

RESUMO

This paper explores neighbourhood-level correlates of the Covid-19 deaths in London during the initial rise and peak of the pandemic within the UK - the period March 1 to April 17, 2020. It asks whether the person-level predictors of Covid-19 that are identified in reports by Public Health England and by the Office of National Statistics also hold at a neighbourhood scale, remaining evident in the differences between neighbours. In examining this, the paper focuses on localised differences in the number of deaths, putting forward an innovative method of analysis that looks at the differences between places that share a border. Specifically, a difference across spatial boundaries method is employed to consider whether a higher number of deaths in one neighbourhood, when compared to its neighbours, is related to other differences between those contiguous locations. It is also used to map localised 'hot spots' and to look for spatial variation in the regression coefficients. The results are compared to those for a later period, April 18 - May 31. The findings show that despite some spatial diffusion of the disease, a greater number of deaths continues to be associated with Asian and Black ethnic groups, socio-economic disadvantage, very large households (likely indicative of residential overcrowding), and fewer from younger age groups. The analysis adds to the evidence showing that age, wealth/deprivation, and ethnicity are key risk factors associated with higher mortality rates from Covid-19.


Assuntos
/mortalidade , Grupos Étnicos/estatística & dados numéricos , Geografia Médica/estatística & dados numéricos , Características de Residência/estatística & dados numéricos , Adulto , Idoso , Idoso de 80 Anos ou mais , Feminino , Humanos , Londres/epidemiologia , Masculino , Mapas como Assunto , Pessoa de Meia-Idade , Pandemias , Análise Espacial , Adulto Jovem
10.
Euro Surveill ; 25(42)2020 10.
Artigo em Inglês | MEDLINE | ID: mdl-33094713

RESUMO

BackgroundThe progression and geographical distribution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in the United Kingdom (UK) and elsewhere is unknown because typically only symptomatic individuals are diagnosed. We performed a serological study of blood donors in Scotland in the spring of 2020 to detect neutralising antibodies to SARS-CoV-2 as a marker of past infection and epidemic progression.AimOur objective was to determine if sera from blood bank donors can be used to track the emergence and progression of the SARS-CoV-2 epidemic.MethodsA pseudotyped SARS-CoV-2 virus microneutralisation assay was used to detect neutralising antibodies to SARS-CoV-2. The study comprised samples from 3,500 blood donors collected in Scotland between 17 March and 18 May 2020. Controls were collected from 100 donors in Scotland during 2019.ResultsAll samples collected on 17 March 2020 (n = 500) were negative in the pseudotyped SARS-CoV-2 virus microneutralisation assay. Neutralising antibodies were detected in six of 500 donors from 23 to 26 March. The number of samples containing neutralising antibodies did not significantly rise after 5-6 April until the end of the study on 18 May. We found that infections were concentrated in certain postcodes, indicating that outbreaks of infection were extremely localised. In contrast, other areas remained comparatively untouched by the epidemic.ConclusionAlthough blood donors are not representative of the overall population, we demonstrated that serosurveys of blood banks can serve as a useful tool for tracking the emergence and progression of an epidemic such as the SARS-CoV-2 outbreak.


Assuntos
Anticorpos Neutralizantes/sangue , Anticorpos Antivirais/sangue , Betacoronavirus/imunologia , Doadores de Sangue , Infecções por Coronavirus/epidemiologia , Pandemias , Pneumonia Viral/epidemiologia , Vigilância da População , Adulto , Análise por Conglomerados , Infecções por Coronavirus/sangue , Ensaio de Imunoadsorção Enzimática , Feminino , Geografia Médica , Humanos , Concentração Inibidora 50 , Masculino , Modelos Imunológicos , Testes de Neutralização , Pneumonia Viral/sangue , Prevalência , Escócia/epidemiologia , Sensibilidade e Especificidade , Estudos Soroepidemiológicos , População Urbana
11.
PLoS One ; 15(10): e0241330, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-33112922

RESUMO

OBJECTIVES: According to current reporting, the number of active coronavirus disease 2019 (COVID-19) infections is not evenly distributed, both spatially and temporally. Reported COVID-19 infections may not have properly conveyed the full extent of attention to the pandemic. Furthermore, infection metrics are unlikely to illustrate the full scope of negative consequences of the pandemic and its associated risk to communities. METHODS: In an effort to better understand the impacts of COVID-19, we concurrently assessed the geospatial and longitudinal distributions of Twitter messages about COVID-19 which were posted between March 3rd and April 13th and compared these results with the number of confirmed cases reported for sub-national levels of the United States. Geospatial hot spot analysis was also conducted to detect geographic areas that might be at elevated risk of spread based on both volume of tweets and number of reported cases. RESULTS: Statistically significant aberrations of high numbers of tweets were detected in approximately one-third of US states, most of which had relatively high proportions of rural inhabitants. Geospatial trends toward becoming hotspots for tweets related to COVID-19 were observed for specific rural states in the United States. DISCUSSION: Population-adjusted results indicate that rural areas in the U.S. may not have engaged with the COVID-19 topic until later stages of an outbreak. Future studies should explore how this dynamic can inform future outbreak communication and health promotion.


Assuntos
Betacoronavirus , Infecções por Coronavirus , Geografia Médica , Pandemias , Pneumonia Viral , Mídias Sociais , Atitude Frente a Saúde , Participação da Comunidade , Infecções por Coronavirus/epidemiologia , Infecções por Coronavirus/psicologia , Humanos , Pneumonia Viral/epidemiologia , Pneumonia Viral/psicologia , Estudos Prospectivos , Saúde Pública , População Rural/estatística & dados numéricos , Mídias Sociais/estatística & dados numéricos , Fatores de Tempo , Estados Unidos/epidemiologia , População Urbana/estatística & dados numéricos
12.
Medicine (Baltimore) ; 99(36): e21982, 2020 Sep 04.
Artigo em Inglês | MEDLINE | ID: mdl-32899041

RESUMO

In the past 30 years, dengue has undergone dramatic changes in China every year. This study explores the epidemiological trend of dengue in China during this period to identify high-risk seasons, regions, ages, susceptible populations, and provide information for dengue prevention and control activities.Dengue data from 1990 to 2019 were derived from the Public Health Science Data Center, Web of Science, China National Knowledge Infrastructure, PubMed, and Centers for Disease Control and Prevention of the corresponding province. GraphPad Prism 7 was conducted to generate disease evolution maps, occupational heat maps, and monthly heat maps of dengue cases and deaths in mainland China and Guangdong Province. Excel 2016 was used to create a cyclone map of age and gender distribution. Powerpoint 2016 was performed to create geographic maps.From 1990 to 2019, the annual number of dengue cases showed an increasing trend and reaching a peak in 2014, with 46,864 dengue cases (incidence rate: 3.4582/100,000), mainly contributed by Guangdong Province (45,189 cases, accounting for 96.43%). Dengue pandemics occurred every 4 to 6 years. The prevalence of dengue fever was Autumn, which was generally prevalent from June to December and reached its peak from September to November. The provinces reporting dengue cases each year have expanded from the southeastern coastal region to the southwest, central, northeast, and northwest regions, and the provinces with a high incidence were Guangdong, Guangxi, Yunnan, Fujian, and Zhejiang. People aged 25 to 44 years were more susceptible to dengue virus infection. And most of them were male patients. Dengue mainly occurs in the following groups: students, business service staffs, workers, farmers, retired staffs, housewives, and the unemployed. Four provinces reported deaths from dengue, namely Guangdong Province, Zhejiang Province, Henan Province, and Hunan Province.The dengue fever epidemic occurred every 4 to 6 years, mostly in autumn. The endemic areas were Guangdong, Guangxi, Yunnan, Fujian, and Zhejiang provinces. People aged 25 to 44 years, men, students, business service staffs, workers, farmers, retired staffs, housewives, and the unemployed were more susceptible to dengue fever. These findings help to develop targeted public health prevention and control measures.


Assuntos
Dengue/epidemiologia , Adolescente , Adulto , Idoso , Idoso de 80 Anos ou mais , Criança , Pré-Escolar , China/epidemiologia , Bases de Dados Factuais , Feminino , Geografia Médica , Humanos , Lactente , Masculino , Pessoa de Meia-Idade , Adulto Jovem
13.
Transfus Clin Biol ; 27(4): 253-258, 2020 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-32987167

RESUMO

BACKGROUND: Novel coronavirus disease-19 (COVID-19) has spread worldwide, and to date presence of the virus has been recorded in 215 countries contributing 0.43 million of death. The role of blood groups in susceptibility/resistance to various infectious diseases has been reported. However, the association of blood groups with susceptibility to COVID-19 infections or related death are limited. In the present report, we performed an epidemiological investigation in the Indian population to decipher the importance of blood groups concerning susceptibility or mortality in COVID-19 infection. MATERIALS AND METHODS: Data on COVID-19 infection and mortality was obtained from the website of the Government of India. Prevalence of ABO blood groups in different states and union territories of India were searched using different databases such as PubMed and Google Scholar. Relevant articles were downloaded, and data were extracted. Spearman's rank coefficient analysis was employed to study the correlation between blood group frequencies and COVID-19 infection or mortality rate. RESULTS: A significant inverse correlation was observed between the frequency of O blood group and the COVID-19 mortality rate (Spearman r=-0.36, P=0.03), indicating a possible protective role of O blood group against COVID-19 related death. In contrast, the prevalence of blood group B was positively correlated with COVID-19 death/million (Spearman r=0.67, P<0.0001), suggesting B blood type as a deleterious factor in COVID-19 infection. CONCLUSIONS: ABO blood group system is associated with poor prognosis of COVID-19 infection. Blood group O may protects, and subjects with blood type B could be susceptible to COVID-19 mortality. However, further studies on COVID-19 infected patients in different population are required to validate our findings.


Assuntos
Sistema ABO de Grupos Sanguíneos/genética , Betacoronavirus , Infecções por Coronavirus/genética , Pneumonia Viral/genética , Infecções por Coronavirus/sangue , Infecções por Coronavirus/etnologia , Infecções por Coronavirus/mortalidade , Grupos Étnicos/genética , Frequência do Gene , Predisposição Genética para Doença , Geografia Médica , Humanos , Índia/epidemiologia , Modelos Imunológicos , Pandemias , Pneumonia Viral/sangue , Pneumonia Viral/etnologia , Pneumonia Viral/mortalidade , Prognóstico , Seleção Genética
14.
Lancet HIV ; 7(10): e699-e710, 2020 10.
Artigo em Inglês | MEDLINE | ID: mdl-32888413

RESUMO

BACKGROUND: Community randomised trials have had mixed success in implementing combination prevention strategies that diagnose 90% of people living with HIV, initiate and retain on antiretroviral therapy (ART) 90% of those diagnosed, and achieve viral load suppression in 90% of those on ART (90-90-90). The Bukoba Combination Prevention Evaluation (BCPE) aimed to achieve 90-90-90 in Bukoba Municipal Council, Tanzania, by scaling up new HIV testing, linkage, and retention interventions. METHOD: We did population-based, cross-sectional surveys before and after our community-wide intervention in Bukoba-a mixed urban and rural council of approximately 150 000 residents located on the western shore of Lake Victoria in Tanzania. BCPE interventions were implemented in 11 government-supported health-care facilities throughout Bukoba from Oct 1, 2014, to March 31, 2017, when national ART-eligibility guidelines expanded from CD4 counts of less than 350 cells per µL (Oct 1, 2014-Dec 31, 2015) and 500 or less cells per µL (Jan 1, 2016-Sept 30, 2016) to any CD4 cell count (test and treat, Oct 1, 2016-March 31, 2017). We used pre-intervention (Nov 4, 2013-Jan 25, 2014) and post-intervention (June 21, 2017-Sept 20, 2017) population-based household surveys to assess population prevalence of undiagnosed HIV infection and ART coverage, and progress towards 90-90-90, among residents aged 18-49 years. FINDINGS: During the 2·5-year intervention, BCPE did 133 695 HIV tests, diagnosed and linked 3918 people living with HIV to HIV care at 11 Bukoba facilities, and returned to HIV care 604 patients who had stopped care. 4795 and 5067 residents aged 18-49 years participated in pre-intervention and post-intervention surveys. HIV prevalence before and after the intervention was similar: pre-intervention 8·9% (95% CI 7·5-10·4); post-intervention 8·4% (6·9-9·9). Prevalence of undiagnosed HIV infection decreased from 4·7% to 2·0% (prevalence ratio 0·42, 95% CI 0·31-0·57), and current ART use among all people living with HIV increased from 32·2% to 70·9% (2·20, 1·82-2·66) overall, 23·0% to 62·1% among men (2·70, 1·84-3·96), and 16·7% to 64·4% among people aged 18-29 years (3·87, 2·54-5·89). Of 436 and 435 people living with HIV aged 18-49 years who participated in pre-intervention and post-intervention surveys, previous HIV diagnosis increased from 47·4% (41·3-53·4) to 76·2% (71·8-80·6), ART use among diagnosed people living with HIV increased from 68·0% (60·9-75·2) to 93·1% (90·2-96·0), and viral load suppression of those on ART increased from 88·7% (83·6-93·8) to 91·3% (88·6-94·1). INTERPRETATION: BCPE findings suggest scaling up recommended HIV testing, linkage, and retention interventions can help reduce prevalence of undiagnosed HIV infection, increase ART use among all people living with HIV, and make substantial progress towards achieving 90-90-90 in a relatively short period. BCPE facility-based testing and linkage interventions are undergoing national scale up to help achieve 90-90-90 in Tanzania. FUNDING: US Presidents' Emergency Plan for AIDS Relief.


Assuntos
Infecções por HIV/epidemiologia , Adolescente , Adulto , Contagem de Linfócito CD4 , Administração de Caso , Estudos Transversais , Testes Diagnósticos de Rotina , Feminino , Geografia Médica , Infecções por HIV/diagnóstico , Infecções por HIV/terapia , Infecções por HIV/virologia , Humanos , Masculino , Programas de Rastreamento , Vigilância da População , Prevalência , População Rural , Tanzânia/epidemiologia , População Urbana , Carga Viral , Adulto Jovem
15.
J Infect Dis ; 222(12): 1951-1954, 2020 Nov 13.
Artigo em Inglês | MEDLINE | ID: mdl-32942299

RESUMO

The coronavirus disease 2019 (COVID-19) pandemic in the United States has revealed major disparities in the access to testing and messaging about the pandemic based on the geographic location of individuals, particularly in communities of color, rural areas, and areas of low income. This geographic disparity, in addition to deeply rooted structural inequities, have posed additional challenges to adequately diagnose and provide care for individuals of all ages living in these settings. We describe the impact that COVID-19 has had on geographically disparate populations in the United States and share our recommendations on what might be done to ameliorate the current situation.


Assuntos
/tendências , Grupos Étnicos , Geografia Médica , Disparidades em Assistência à Saúde/etnologia , /etnologia , Acesso aos Serviços de Saúde , Disparidades nos Níveis de Saúde , Humanos , Pobreza , Determinantes Sociais da Saúde/etnologia , Estados Unidos/epidemiologia
16.
PLoS One ; 15(9): e0239026, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32936811

RESUMO

The Government of India in-network with the state governments has implemented the epidemic curtailment strategies inclusive of case-isolation, quarantine and lockdown in response to ongoing novel coronavirus (COVID-19) outbreak. In this manuscript, we attempt to estimate the impact of these steps across ten selected Indian states using crowd-sourced data. The trajectory of the outbreak was parameterized by the reproduction number (R0), doubling time, and growth rate. These parameters were estimated at two time-periods after the enforcement of the lockdown on 24th March 2020, i.e. 15 days into lockdown and 30 days into lockdown. The authors used a crowd sourced database which is available in the public domain. After preparing the data for analysis, R0 was estimated using maximum likelihood (ML) method which is based on the expectation minimum algorithm where the distribution probability of secondary cases is maximized using the serial interval discretization. The doubling time and growth rate were estimated by the natural log transformation of the exponential growth equation. The overall analysis shows decreasing trends in time-varying reproduction numbers (R(t)) and growth rate (with a few exceptions) and increasing trends in doubling time. The curtailment strategies employed by the Indian government seem to be effective in reducing the transmission parameters of the COVID-19 epidemic. The estimated R(t) are still above the threshold of 1, and the resultant absolute case numbers show an increase with time. Future curtailment and mitigation strategies thus may take into account these findings while formulating further course of action.


Assuntos
Betacoronavirus , Controle de Doenças Transmissíveis/métodos , Infecções por Coronavirus/prevenção & controle , Pandemias/prevenção & controle , Pneumonia Viral/prevenção & controle , Número Básico de Reprodução , Betacoronavirus/fisiologia , Técnicas de Laboratório Clínico/estatística & dados numéricos , Infecções por Coronavirus/diagnóstico , Infecções por Coronavirus/epidemiologia , Infecções por Coronavirus/transmissão , Crowdsourcing , Bases de Dados Factuais , Geografia Médica , Órgãos Governamentais , Política de Saúde , Humanos , Incidência , Índia/epidemiologia , Modelos Biológicos , Pneumonia Viral/epidemiologia , Pneumonia Viral/transmissão , Quarentena
17.
PLoS One ; 15(9): e0239175, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32941485

RESUMO

The COVID-19 outbreak has forced most of the global population to lock-down and has put in check the health services all over the world. Current predictive models are complex, region-dependent, and might not be generalized to other countries. However, a 150-year old epidemics law promulgated by William Farr might be useful as a simple arithmetical model (percent increase [R1] and acceleration [R2] of new cases and deaths) to provide a first sight of the epidemic behavior and to detect regions with high predicted dynamics. Thus, this study tested Farr's Law assumptions by modeling COVID-19 data of new cases and deaths. COVID-19 data until April 10, 2020, was extracted from available countries, including income, urban index, and population characteristics. Farr's law first (R1) and second ratio (R2) were calculated. We constructed epidemic curves and predictive models for the available countries and performed ecological correlation analysis between R1 and R2 with demographic data. We extracted data from 210 countries, and it was possible to estimate the ratios of 170 of them. Around 42·94% of the countries were in an initial acceleration phase, while 23·5% already crossed the peak. We predicted a reduction close to zero with wide confidence intervals for 56 countries until June 10 (high-income countries from Asia and Oceania, with strict political actions). There was a significant association between high R1 of deaths and high urban index. Farr's law seems to be a useful model to give an overview of COVID-19 pandemic dynamics. The countries with high dynamics are from Africa and Latin America. Thus, this is a call to urgently prioritize actions in those countries to intensify surveillance, to re-allocate resources, and to build healthcare capacities based on multi-nation collaboration to limit onward transmission and to reduce the future impact on these regions in an eventual second wave.


Assuntos
Betacoronavirus , Infecções por Coronavirus/prevenção & controle , Modelos Biológicos , Pandemias/legislação & jurisprudência , Pneumonia Viral/prevenção & controle , África/epidemiologia , Ásia/epidemiologia , Infecções por Coronavirus/epidemiologia , Previsões , Geografia Médica , Humanos , Incidência , América Latina/epidemiologia , Morbidade/tendências , Mortalidade/tendências , Pandemias/prevenção & controle , Pneumonia Viral/epidemiologia , Dinâmica Populacional , Saúde da População Urbana
18.
PLoS One ; 15(9): e0239252, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32941512

RESUMO

Until treatment and vaccine for coronavirus disease-2019 (COVID-19) becomes widely available, other methods of reducing infection rates should be explored. This study used a retrospective, observational analysis of deidentified tests performed at a national clinical laboratory to determine if circulating 25-hydroxyvitamin D (25(OH)D) levels are associated with severe acute respiratory disease coronavirus 2 (SARS-CoV-2) positivity rates. Over 190,000 patients from all 50 states with SARS-CoV-2 results performed mid-March through mid-June, 2020 and matching 25(OH)D results from the preceding 12 months were included. Residential zip code data was required to match with US Census data and perform analyses of race/ethnicity proportions and latitude. A total of 191,779 patients were included (median age, 54 years [interquartile range 40.4-64.7]; 68% female. The SARS-CoV-2 positivity rate was 9.3% (95% C.I. 9.2-9.5%) and the mean seasonally adjusted 25(OH)D was 31.7 (SD 11.7). The SARS-CoV-2 positivity rate was higher in the 39,190 patients with "deficient" 25(OH)D values (<20 ng/mL) (12.5%, 95% C.I. 12.2-12.8%) than in the 27,870 patients with "adequate" values (30-34 ng/mL) (8.1%, 95% C.I. 7.8-8.4%) and the 12,321 patients with values ≥55 ng/mL (5.9%, 95% C.I. 5.5-6.4%). The association between 25(OH)D levels and SARS-CoV-2 positivity was best fitted by the weighted second-order polynomial regression, which indicated strong correlation in the total population (R2 = 0.96) and in analyses stratified by all studied demographic factors. The association between lower SARS-CoV-2 positivity rates and higher circulating 25(OH)D levels remained significant in a multivariable logistic model adjusting for all included demographic factors (adjusted odds ratio 0.984 per ng/mL increment, 95% C.I. 0.983-0.986; p<0.001). SARS-CoV-2 positivity is strongly and inversely associated with circulating 25(OH)D levels, a relationship that persists across latitudes, races/ethnicities, both sexes, and age ranges. Our findings provide impetus to explore the role of vitamin D supplementation in reducing the risk for SARS-CoV-2 infection and COVID-19 disease.


Assuntos
Betacoronavirus/isolamento & purificação , Infecções por Coronavirus/sangue , Pandemias , Pneumonia Viral/sangue , RNA Viral/sangue , Deficiência de Vitamina D/sangue , Vitamina D/análogos & derivados , Adulto , Comorbidade , Grupos de Populações Continentais , Infecções por Coronavirus/epidemiologia , Infecções por Coronavirus/virologia , Grupos Étnicos , Feminino , Geografia Médica , Saúde Global , Humanos , Masculino , Pessoa de Meia-Idade , Técnicas de Amplificação de Ácido Nucleico , Razão de Chances , Pneumonia Viral/epidemiologia , Pneumonia Viral/virologia , Análise de Regressão , Estudos Retrospectivos , Estações do Ano , Vitamina D/sangue , Deficiência de Vitamina D/epidemiologia
19.
N Engl J Med ; 383(6): 537-545, 2020 08 06.
Artigo em Inglês | MEDLINE | ID: mdl-32757522

RESUMO

BACKGROUND: In 2015 and 2016, Colombia had a widespread outbreak of Zika virus. Data from two national population-based surveillance systems for symptomatic Zika virus disease (ZVD) and birth defects provided complementary information on the effect of the Zika virus outbreak on pregnancies and infant outcomes. METHODS: We collected national surveillance data regarding cases of pregnant women with ZVD that were reported during the period from June 2015 through July 2016. The presence of Zika virus RNA was identified in a subgroup of these women on real-time reverse-transcriptase-polymerase-chain-reaction (rRT-PCR) assay. Brain or eye defects in infants and fetuses and other adverse pregnancy outcomes were identified among the women who had laboratory-confirmed ZVD and for whom data were available regarding pregnancy outcomes. We compared the nationwide prevalence of brain and eye defects during the outbreak with the prevalence both before and after the outbreak period. RESULTS: Of 18,117 pregnant women with ZVD, the presence of Zika virus was confirmed in 5926 (33%) on rRT-PCR. Of the 5673 pregnancies with laboratory-confirmed ZVD for which outcomes had been reported, 93 infants or fetuses (2%) had brain or eye defects. The incidence of brain or eye defects was higher among pregnancies in which the mother had an onset of ZVD symptoms in the first trimester than in those with an onset during the second or third trimester (3% vs. 1%). A total of 172 of 5673 pregnancies (3%) resulted in pregnancy loss; after the exclusion of pregnancies affected by birth defects, 409 of 5426 (8%) resulted in preterm birth and 333 of 5426 (6%) in low birth weight. The prevalence of brain or eye defects during the outbreak was 13 per 10,000 live births, as compared with a prevalence of 8 per 10,000 live births before the outbreak and 11 per 10,000 live births after the outbreak. CONCLUSIONS: In pregnant women with laboratory-confirmed ZVD, brain or eye defects in infants or fetuses were more common during the Zika virus outbreak than during the periods immediately before and after the outbreak. The frequency of such defects was increased among women with a symptom onset early in pregnancy. (Funded by the Colombian Instituto Nacional de Salud and the Centers for Disease Control and Prevention.).


Assuntos
Encéfalo/anormalidades , Surtos de Doenças , Anormalidades do Olho/epidemiologia , Complicações Infecciosas na Gravidez , Infecção por Zika virus/complicações , Zika virus/isolamento & purificação , Adolescente , Adulto , Colômbia/epidemiologia , Feminino , Doenças Fetais/epidemiologia , Feto/anormalidades , Geografia Médica , Humanos , Incidência , Recém-Nascido , Masculino , Microcefalia/epidemiologia , Distribuição de Poisson , Gravidez , Complicações Infecciosas na Gravidez/epidemiologia , Resultado da Gravidez , Prevalência , RNA Viral/sangue , Reação em Cadeia da Polimerase em Tempo Real , Adulto Jovem , Zika virus/genética , Infecção por Zika virus/epidemiologia
20.
PLoS One ; 15(8): e0238280, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32853285

RESUMO

In December 2019, the novel coronavirus pneumonia (COVID-19) occurred in Wuhan, Hubei Province, China. The epidemic quickly broke out and spread throughout the country. Now it becomes a pandemic that affects the whole world. In this study, three models were used to fit and predict the epidemic situation in China: a modified SEIRD (Susceptible-Exposed-Infected-Recovered-Dead) dynamic model, a neural network method LSTM (Long Short-Term Memory), and a GWR (Geographically Weighted Regression) model reflecting spatial heterogeneity. Overall, all the three models performed well with great accuracy. The dynamic SEIRD prediction APE (absolute percent error) of China had been ≤ 1.0% since Mid-February. The LSTM model showed comparable accuracy. The GWR model took into account the influence of geographical differences, with R2 = 99.98% in fitting and 97.95% in prediction. Wilcoxon test showed that none of the three models outperformed the other two at the significance level of 0.05. The parametric analysis of the infectious rate and recovery rate demonstrated that China's national policies had effectively slowed down the spread of the epidemic. Furthermore, the models in this study provided a wide range of implications for other countries to predict the short-term and long-term trend of COVID-19, and to evaluate the intensity and effect of their interventions.


Assuntos
Infecções por Coronavirus/epidemiologia , Modelos Estatísticos , Pneumonia Viral/epidemiologia , Betacoronavirus , China/epidemiologia , Geografia Médica , Humanos , Pandemias
SELEÇÃO DE REFERÊNCIAS
DETALHE DA PESQUISA