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BACKGROUND: US Centers for Disease Control and Prevention guidelines currently recommend triple-therapy antimicrobial treatment for anthrax meningitis. In the Kyrgyz Republic, a country with endemic anthrax, cutaneous anthrax patients are routinely hospitalized and treated successfully with only monotherapy or dual therapy. Clinical algorithms have been developed to identify patients with likely anthrax meningitis based on signs and symptoms alone. We sought to retrospectively identify likely meningitis patients in the Kyrgyz Republic using a clinical algorithm and evaluate risk factors and their outcomes by type of treatment. METHODS: We conducted a retrospective chart review of cutaneous anthrax patients in the Kyrgyz Republic from 2005 through 2012. Using previous methods, we developed a highly specific algorithm to categorize patients by meningitis status. We then evaluated patient risk factors, treatments, and outcomes by disease severity and meningitis status. RESULTS: We categorized 37 of 230 cutaneous anthrax patients as likely having meningitis. All 37 likely meningitis patients survived, receiving only mono- or dual-therapy antimicrobials. We identified underlying medical conditions, such as obesity, hypertension, and chronic obstructive pulmonary disease, and tobacco and alcohol use, as potential risk factors for severe anthrax and anthrax meningitis. CONCLUSIONS: Based on our analyses, treatment of anthrax meningitis may not require 3 antimicrobials, which could impact future anthrax treatment recommendations. In addition, chronic comorbidities may increase risk for severe anthrax and anthrax meningitis. Future research should further investigate potential risk factors for severe anthrax and their impact on laboratory-confirmed meningitis and evaluate mono- and dual-therapy antimicrobial regimens for anthrax meningitis.
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Antraz , Anti-Infecciosos , Meningites Bacterianas , Algoritmos , Antraz/diagnóstico , Antraz/tratamento farmacológico , Antraz/epidemiologia , Antibacterianos/uso terapêutico , Anti-Infecciosos/uso terapêutico , Humanos , Quirguistão/epidemiologia , Meningites Bacterianas/diagnóstico , Meningites Bacterianas/tratamento farmacológico , Meningites Bacterianas/epidemiologia , Estudos Retrospectivos , Fatores de Risco , Dermatopatias Bacterianas , Resultado do TratamentoRESUMO
In April 2020, during the peak of the coronavirus disease 2019 (COVID-19) pandemic in Europe, a cluster of children with hyperinflammatory shock with features similar to Kawasaki disease and toxic shock syndrome was reported in England* (1). The patients' signs and symptoms were temporally associated with COVID-19 but presumed to have developed 2-4 weeks after acute COVID-19; all children had serologic evidence of infection with SARS-CoV-2, the virus that causes COVID-19 (1). The clinical signs and symptoms present in this first cluster included fever, rash, conjunctivitis, peripheral edema, gastrointestinal symptoms, shock, and elevated markers of inflammation and cardiac damage (1). On May 14, 2020, CDC published an online Health Advisory that summarized the manifestations of reported multisystem inflammatory syndrome in children (MIS-C), outlined a case definition, and asked clinicians to report suspected U.S. cases to local and state health departments. As of July 29, a total of 570 U.S. MIS-C patients who met the case definition had been reported to CDC. A total of 203 (35.6%) of the patients had a clinical course consistent with previously published MIS-C reports, characterized predominantly by shock, cardiac dysfunction, abdominal pain, and markedly elevated inflammatory markers, and almost all had positive SARS-CoV-2 test results. The remaining 367 (64.4%) of MIS-C patients had manifestations that appeared to overlap with acute COVID-19 (2-4), had a less severe clinical course, or had features of Kawasaki disease.§ Median duration of hospitalization was 6 days; 364 patients (63.9%) required care in an intensive care unit (ICU), and 10 patients (1.8%) died. As the COVID-19 pandemic continues to expand in many jurisdictions, clinicians should be aware of the signs and symptoms of MIS-C and report suspected cases to their state or local health departments; analysis of reported cases can enhance understanding of MIS-C and improve characterization of the illness for early detection and treatment.
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Infecções por Coronavirus/complicações , Pneumonia Viral/complicações , Síndrome de Resposta Inflamatória Sistêmica/epidemiologia , Síndrome de Resposta Inflamatória Sistêmica/virologia , Adolescente , COVID-19 , Criança , Pré-Escolar , Infecções por Coronavirus/epidemiologia , Feminino , Humanos , Masculino , Pandemias , Pneumonia Viral/epidemiologia , Estados Unidos/epidemiologiaRESUMO
BACKGROUND: Estimates of influenza-associated mortality are important for national and international decision making on public health priorities. Previous estimates of 250â000-500â000 annual influenza deaths are outdated. We updated the estimated number of global annual influenza-associated respiratory deaths using country-specific influenza-associated excess respiratory mortality estimates from 1999-2015. METHODS: We estimated country-specific influenza-associated respiratory excess mortality rates (EMR) for 33 countries using time series log-linear regression models with vital death records and influenza surveillance data. To extrapolate estimates to countries without data, we divided countries into three analytic divisions for three age groups (<65 years, 65-74 years, and ≥75 years) using WHO Global Health Estimate (GHE) respiratory infection mortality rates. We calculated mortality rate ratios (MRR) to account for differences in risk of influenza death across countries by comparing GHE respiratory infection mortality rates from countries without EMR estimates with those with estimates. To calculate death estimates for individual countries within each age-specific analytic division, we multiplied randomly selected mean annual EMRs by the country's MRR and population. Global 95% credible interval (CrI) estimates were obtained from the posterior distribution of the sum of country-specific estimates to represent the range of possible influenza-associated deaths in a season or year. We calculated influenza-associated deaths for children younger than 5 years for 92 countries with high rates of mortality due to respiratory infection using the same methods. FINDINGS: EMR-contributing countries represented 57% of the global population. The estimated mean annual influenza-associated respiratory EMR ranged from 0·1 to 6·4 per 100â000 individuals for people younger than 65 years, 2·9 to 44·0 per 100â000 individuals for people aged between 65 and 74 years, and 17·9 to 223·5 per 100â000 for people older than 75 years. We estimated that 291â243-645â832 seasonal influenza-associated respiratory deaths (4·0-8·8 per 100â000 individuals) occur annually. The highest mortality rates were estimated in sub-Saharan Africa (2·8-16·5 per 100â000 individuals), southeast Asia (3·5-9·2 per 100â000 individuals), and among people aged 75 years or older (51·3-99·4 per 100â000 individuals). For 92 countries, we estimated that among children younger than 5 years, 9243-105â690 influenza-associated respiratory deaths occur annually. INTERPRETATION: These global influenza-associated respiratory mortality estimates are higher than previously reported, suggesting that previous estimates might have underestimated disease burden. The contribution of non-respiratory causes of death to global influenza-associated mortality should be investigated. FUNDING: None.
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Saúde Global/estatística & dados numéricos , Influenza Humana/mortalidade , Estações do Ano , Adolescente , Adulto , Idoso , Criança , Pré-Escolar , Feminino , Humanos , Lactente , Recém-Nascido , Influenza Humana/complicações , Modelos Lineares , Masculino , Pessoa de Meia-Idade , Fatores Socioeconômicos , Adulto JovemRESUMO
CDC, the Food and Drug Administration (FDA), state and local health departments, and public health and clinical stakeholders are investigating a nationwide outbreak of e-cigarette, or vaping, product use-associated lung injury (EVALI) (1). As of November 13, 2019, 49 states, the District of Columbia, and two U.S. territories (Puerto Rico and U.S. Virgin Islands) have reported 2,172 EVALI cases to CDC, including 42 (1.9%) EVALI-associated deaths. To inform EVALI surveillance, including during the 2019-20 influenza season, case report information supplied by states for hospitalized and nonhospitalized patients with EVALI were analyzed using data collected as of November 5, 2019. Among 2,016 EVALI patients with available data on hospitalization status, 1,906 (95%) were hospitalized, and 110 (5%) were not hospitalized. Demographic characteristics of hospitalized and nonhospitalized patients were similar; most were male (68% of hospitalized versus 65% of nonhospitalized patients), and most were aged <35 years (78% of hospitalized versus 74% of nonhospitalized patients). These patients also reported similar use of tetrahydrocannabinol (THC)-containing products (83% of hospitalized versus 84% of nonhospitalized patients). Given the similarity between hospitalized and nonhospitalized EVALI patients, the potential for large numbers of respiratory infections during the emerging 2019-20 influenza season, and the potential difficulty in distinguishing EVALI from respiratory infections, CDC will no longer collect national data on nonhospitalized EVALI patients. Further collection of data on nonhospitalized patients will be at the discretion of individual state, local, and territorial health departments. Candidates for outpatient management of EVALI should have normal oxygen saturation (≥95% while breathing room air), no respiratory distress, no comorbidities that might compromise pulmonary reserve, reliable access to care, strong social support systems, and should be able to ensure follow-up within 24-48 hours of initial evaluation and to seek medical care promptly if respiratory symptoms worsen. Health care providers should emphasize the importance of annual influenza vaccination for all persons aged ≥6 months, including persons who use e-cigarette, or vaping, products (2,3).
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Surtos de Doenças , Hospitalização/estatística & dados numéricos , Lesão Pulmonar/epidemiologia , Vaping/efeitos adversos , Adolescente , Adulto , Idoso , Centers for Disease Control and Prevention, U.S. , Feminino , Humanos , Lesão Pulmonar/terapia , Masculino , Pessoa de Meia-Idade , Estados Unidos/epidemiologia , Adulto JovemRESUMO
During March 2013-February 24, 2017, annual epidemics of avian influenza A(H7N9) in China resulted in 1,258 avian influenza A(H7N9) virus infections in humans being reported to the World Health Organization (WHO) by the National Health and Family Planning Commission of China and other regional sources (1). During the first four epidemics, 88% of patients developed pneumonia, 68% were admitted to an intensive care unit, and 41% died (2). Candidate vaccine viruses (CVVs) were developed, and vaccine was manufactured based on representative viruses detected after the emergence of A(H7N9) virus in humans in 2013. During the ongoing fifth epidemic (beginning October 1, 2016),* 460 human infections with A(H7N9) virus have been reported, including 453 in mainland China, six associated with travel to mainland China from Hong Kong (four cases), Macao (one) and Taiwan (one), and one in an asymptomatic poultry worker in Macao (1). Although the clinical characteristics and risk factors for human infections do not appear to have changed (2,3), the reported human infections during the fifth epidemic represent a significant increase compared with the first four epidemics, which resulted in 135 (first epidemic), 320 (second), 226 (third), and 119 (fourth epidemic) human infections (2). Most human infections continue to result in severe respiratory illness and have been associated with poultry exposure. Although some limited human-to-human spread continues to be identified, no sustained human-to-human A(H7N9) transmission has been observed (2,3).
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Epidemias/estatística & dados numéricos , Subtipo H7N9 do Vírus da Influenza A/isolamento & purificação , Influenza Humana/epidemiologia , Influenza Humana/virologia , Animais , China/epidemiologia , Humanos , Influenza Aviária/transmissão , Influenza Humana/transmissão , Doenças Profissionais , Aves Domésticas , Fatores de Risco , ViagemRESUMO
During May 21-September 23, 2017,* the United States experienced low-level seasonal influenza virus activity; however, beginning in early September, CDC received reports of a small number of localized influenza outbreaks caused by influenza A(H3N2) viruses. In addition to influenza A(H3N2) viruses, influenza A(H1N1)pdm09 and influenza B viruses were detected during May-September worldwide and in the United States. Influenza B viruses predominated in the United States from late May through late June, and influenza A viruses predominated beginning in early July. The majority of the influenza viruses collected and received from the United States and other countries during that time have been characterized genetically or antigenically as being similar to the 2017 Southern Hemisphere and 2017-18 Northern Hemisphere cell-grown vaccine reference viruses; however, a smaller proportion of the circulating A(H3N2) viruses showed similarity to the egg-grown A(H3N2) vaccine reference virus which represents the A(H3N2) viruses used for the majority of vaccine production in the United States. Also, during May 21-September 23, 2017, CDC confirmed a total of 33 influenza variant virus infections; two were influenza A(H1N2) variant (H1N2v) viruses (Ohio) and 31 were influenza A(H3N2) variant (H3N2v) viruses (Delaware [1], Maryland [13], North Dakota [1], Pennsylvania [1], and Ohio [15]). An additional 18 specimens from Maryland have tested presumptive positive for H3v and further analysis is being conducted at CDC.
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Surtos de Doenças , Saúde Global/estatística & dados numéricos , Vírus da Influenza A Subtipo H1N1/isolamento & purificação , Vírus da Influenza A Subtipo H3N2/isolamento & purificação , Vírus da Influenza B/isolamento & purificação , Influenza Humana/epidemiologia , Vigilância da População , Centers for Disease Control and Prevention, U.S. , Humanos , Vírus da Influenza A Subtipo H1N1/genética , Vírus da Influenza A Subtipo H3N2/genética , Vírus da Influenza B/genética , Estações do Ano , Estados Unidos/epidemiologiaRESUMO
Among all influenza viruses assessed using CDC's Influenza Risk Assessment Tool (IRAT), the Asian lineage avian influenza A(H7N9) virus (Asian H7N9), first reported in China in March 2013,* is ranked as the influenza virus with the highest potential pandemic risk (1). During October 1, 2016-August 7, 2017, the National Health and Family Planning Commission of China; CDC, Taiwan; the Hong Kong Centre for Health Protection; and the Macao CDC reported 759 human infections with Asian H7N9 viruses, including 281 deaths, to the World Health Organization (WHO), making this the largest of the five epidemics of Asian H7N9 infections that have occurred since 2013 (Figure 1). This report summarizes new viral and epidemiologic features identified during the fifth epidemic of Asian H7N9 in China and summarizes ongoing measures to enhance pandemic preparedness. Infections in humans and poultry were reported from most areas of China, including provinces bordering other countries, indicating extensive, ongoing geographic spread. The risk to the general public is very low and most human infections were, and continue to be, associated with poultry exposure, especially at live bird markets in mainland China. Throughout the first four epidemics of Asian H7N9 infections, only low pathogenic avian influenza (LPAI) viruses were detected among human, poultry, and environmental specimens and samples. During the fifth epidemic, mutations were detected among some Asian H7N9 viruses, identifying the emergence of high pathogenic avian influenza (HPAI) viruses as well as viruses with reduced susceptibility to influenza antiviral medications recommended for treatment. Furthermore, the fifth-epidemic viruses diverged genetically into two separate lineages (Pearl River Delta lineage and Yangtze River Delta lineage), with Yangtze River Delta lineage viruses emerging as antigenically different compared with those from earlier epidemics. Because of its pandemic potential, candidate vaccine viruses (CVV) were produced in 2013 that have been used to make vaccines against Asian H7N9 viruses circulating at that time. CDC is working with partners to enhance surveillance for Asian H7N9 viruses in humans and poultry, to improve laboratory capability to detect and characterize H7N9 viruses, and to develop, test and distribute new CVV that could be used for vaccine production if a vaccine is needed.
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Epidemias/estatística & dados numéricos , Subtipo H7N9 do Vírus da Influenza A/isolamento & purificação , Influenza Humana/epidemiologia , Influenza Humana/virologia , Vigilância da População , Animais , China/epidemiologia , Humanos , Influenza Aviária/transmissão , Influenza Aviária/virologia , Pandemias/prevenção & controle , Aves DomésticasRESUMO
During November 2014-April 2015, a total of 165 case-patients with influenza virus A(H5N1) infection, including 6 clusters and 51 deaths, were identified in Egypt. Among infected persons, 99% reported poultry exposure: 19% to ill poultry and 35% to dead poultry. Only 1 person reported wearing personal protective equipment while working with poultry.
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Virus da Influenza A Subtipo H5N1/patogenicidade , Influenza Humana/epidemiologia , Animais , Egito/epidemiologia , Epidemias/estatística & dados numéricos , Humanos , Virus da Influenza A Subtipo H5N1/genética , Influenza Aviária/transmissão , Influenza Humana/patologia , Influenza Humana/transmissão , Filogenia , Aves Domésticas/genética , Aves Domésticas/virologiaRESUMO
BACKGROUND: Global estimates showed an estimate of up to 650,000 seasonal influenza-associated respiratory deaths annually. However, the mortality rate of seasonal influenza is unknown for most countries in the WHO Eastern Mediterranean Region, including Iran. We aimed to estimate the excess mortality attributable to seasonal influenza in Kerman province, southeast Iran for the influenza seasons 2006/2007-2011/2012. METHODS: We applied a Serfling model to the weekly total pneumonia and influenza (PI) mortality rate during winter to define the epidemic periods and to the weekly age-specific PI, respiratory, circulatory, and all-cause deaths during non-epidemic periods to estimate baseline mortality. The excess mortality was calculated as the difference between observed and predicted mortality. Country estimates were obtained by multiplying the estimated annual excess death rates by the populations of Iran. RESULTS: We estimated an annual average excess of 40 PI, 100 respiratory, 94 circulatory, and 306 all-cause deaths attributable to seasonal influenza in Kerman; corresponding to annual rates of 1.4 (95% confidence interval [CI] 1.1-1.8) PI, 3.6 (95% CI 2.6-4.8) respiratory, 3.4 (95% CI 2.1-5.2) circulatory, and 11.0 (95% CI 7.3-15.6) all-cause deaths per 100,000 population. Adults ≥75 years accounted for 56% and 53% of all excess respiratory and circulatory deaths, respectively. At country level, we would expect an annual of 1119 PI to 8792 all-cause deaths attributable to seasonal influenza. CONCLUSIONS: Our findings help to define the mortality burden of seasonal influenza, most of which affects adults aged ≥75 years. This study supports influenza prevention and vaccination programs in older adults.
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Epidemias , Influenza Humana , Humanos , Idoso , Influenza Humana/epidemiologia , Estações do Ano , Irã (Geográfico)/epidemiologia , Taxa RespiratóriaRESUMO
BACKGROUND: Using country-specific surveillance data to describe influenza epidemic activity could inform decisions on the timing of influenza vaccination. We analysed surveillance data from African countries to characterise the timing of seasonal influenza epidemics to inform national vaccination strategies. METHODS: We used publicly available sentinel data from African countries reporting to the WHO Global Influenza Surveillance and Response FluNet platform that had 3-10 years of data collected during 2010-19. We calculated a 3-week moving proportion of samples positive for influenza virus and assessed epidemic timing using an aggregate average method. The start and end of each epidemic were defined as the first week when the proportion of positive samples exceeded or went below the annual mean, respectively, for at least 3 consecutive weeks. We categorised countries into five epidemic patterns: northern hemisphere-dominant, with epidemics occurring in October-March; southern hemisphere-dominant, with epidemics occurring in April-September; primarily northern hemisphere with some epidemic activity in southern hemisphere months; primarily southern hemisphere with some epidemic activity in northern hemisphere months; and year-round influenza transmission without a discernible northern hemisphere or southern hemisphere predominance (no clear pattern). FINDINGS: Of the 34 countries reporting data to FluNet, 25 had at least 3 years of data, representing 46% of the countries in Africa and 89% of Africa's population. Study countries reported RT-PCR respiratory virus results for a total of 503â609 specimens (median 12â971 [IQR 9607-20â960] per country-year), of which 74â001 (15%; median 2078 [IQR 1087-3008] per country-year) were positive for influenza viruses. 248 epidemics occurred across 236 country-years of data (median 10 [range 7-10] per country). Six (24%) countries had a northern hemisphere pattern (Algeria, Burkina Faso, Egypt, Morocco, Niger, and Tunisia). Eight (32%) had a primarily northern hemisphere pattern with some southern hemisphere epidemics (Cameroon, Ethiopia, Mali, Mozambique, Nigeria, Senegal, Tanzania, and Togo). Three (12%) had a primarily southern hemisphere pattern with some northern hemisphere epidemics (Ghana, Kenya, and Uganda). Three (12%) had a southern hemisphere pattern (Central African Republic, South Africa, and Zambia). Five (20%) had no clear pattern (Côte d'Ivoire, DR Congo, Madagascar, Mauritius, and Rwanda). INTERPRETATION: Most countries had identifiable influenza epidemic periods that could be used to inform authorities of non-seasonal and seasonal influenza activity, guide vaccine timing, and promote timely interventions. FUNDING: None. TRANSLATIONS: For the Berber, Luganda, Xhosa, Chewa, Yoruba, Igbo, Hausa and Afan Oromo translations of the abstract see Supplementary Materials section.
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Epidemias , Vacinas contra Influenza , Influenza Humana , Humanos , Influenza Humana/epidemiologia , Influenza Humana/prevenção & controle , Estudos Retrospectivos , Burkina Faso , Estações do AnoRESUMO
Dynamic buffer conditions are present in many electrophoretically driven separations. Polyelectrolyte multilayer coatings have been employed in CE because of their chemical and physical stability as well as their ease of application. The goal of this study is to measure the effect of dynamic changes in buffer pH on flow using a real-time method for measuring EOF. Polyelectrolyte multilayers (PEMs) were composed of pairs of strong or completely ionized polyelectrolytes including poly(diallyldimethylammonium) chloride and poly(styrene sulfonate) and weak or ionizable polyelectrolytes including poly(allylamine) and poly(methacrylic acid). Polyelectrolyte multilayers of varying thicknesses (3, 4, 7, 8, 15, or 16 layers) were also studied. While the magnitude of the EOF was monitored every 2 s, the buffer pH was exchanged from a relatively basic pH (7.1) to increasingly acidic pHs (6.6, 6.1, 5.5, and 5.1). Strong polyelectrolytes responded minimally to changes in buffer pH (<1%), whereas substantial (>10%) and sometimes irreversible changes were measured with weak polyelectrolytes. Thicker coatings resulted in a similar magnitude of response but were more likely to degrade in response to buffer pH changes. The most stable coatings were formed from thinner layers of strong polyelectrolytes.
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BACKGROUND: Influenza causes substantial morbidity and mortality worldwide, however, reliable burden estimates from developing countries are limited, including India. We aimed to quantify influenza-associated mortality for India utilizing 2010-2013 nationally representative data sources for influenza virus circulation and deaths. METHODS: Virological data were obtained from the influenza surveillance network of 10 laboratories led by National Institute of Virology, Pune covering eight states from 2010-2013. Death data were obtained from the nationally representative Sample Registration System for the same time period. Generalized linear regression with negative binomial distribution was used to model weekly respiratory and circulatory deaths by age group and proportion of specimens positive for influenza by subtype; excess deaths above the seasonal baseline were taken as an estimate of influenza-associated mortality counts and rates. Annual excess death rates and the 2011 India Census data were used to estimate national influenza-associated deaths. RESULTS: Estimated annual influenza-associated respiratory mortality rates were highest for those ≥65 years (51.1, 95% confidence interval (CI) = 9.2-93.0 deaths/100 000 population) followed by those <5 years (9.8, 95% CI = 0-21.8/100 000). Influenza-associated circulatory death rates were also higher among those ≥65 years (71.8, 95% CI = 7.9-135.8/100 000) as compared to those aged <65 years (1.9, 95% CI = 0-4.6/100 000). Across all age groups, a mean of 127 092 (95% CI = 64 046-190,139) annual influenza-associated respiratory and circulatory deaths may occur in India. CONCLUSIONS: Estimated influenza-associated mortality in India was high among children <5 years and adults ≥65 years. These estimates may inform strategies for influenza prevention and control in India, such as possible vaccine introduction.
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Sistema Cardiovascular/fisiopatologia , Influenza Humana , Doenças Respiratórias , Adolescente , Adulto , Fatores Etários , Idoso , Causas de Morte , Criança , Pré-Escolar , Feminino , Humanos , Índia/epidemiologia , Lactente , Influenza Humana/epidemiologia , Influenza Humana/mortalidade , Masculino , Pessoa de Meia-Idade , Doenças Respiratórias/complicações , Doenças Respiratórias/mortalidade , Estações do Ano , Adulto JovemRESUMO
Inadequate sanitation can lead to exposure to fecal contamination through multiple environmental pathways and can result in adverse health outcomes. By understanding the relative importance of multiple exposure pathways, sanitation interventions can be tailored to those pathways with greatest potential public health impact. The SaniPath Exposure Assessment Tool allows users to identify and quantify human exposure to fecal contamination in low-resource urban settings through a systematic yet customizable process. The Tool includes: a project management platform; mobile data collection and a data repository; protocols for primary data collection; and automated exposure assessment analysis. The data collection protocols detail the process of conducting behavioral surveys with households, school children, and community groups to quantify contact with fecal exposure pathways and of collecting and analyzing environmental samples for E. coli as an indicator of fecal contamination. Bayesian analyses are used to estimate the percentage of the population exposed and the mean dose of fecal exposure from microbiological and behavioral data. Fecal exposure from nine pathways (drinking water, bathing water, surface water, ocean water, open drains, floodwater, raw produce, street food, and public or shared toilets) can be compared through a common metric-estimated ingestion of E. coli units (MPN or CFU) per month. The Tool generates data visualizations and recommendations for interventions designed for both scientific and lay audiences. When piloted in Accra, Ghana, the results of the Tool were comparable with that of an in-depth study conducted in the same neighborhoods and highlighted consumption of raw produce as a dominant exposure pathway. The Tool has been deployed in nine cities to date, and the results are being used by local authorities to design and prioritize programming and policy. The SaniPath Tool is a novel approach to support public-health evidence-based decision-making for urban sanitation policies and investments.
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Microbiologia Ambiental , Monitoramento Ambiental/métodos , Fezes/microbiologia , Saneamento/estatística & dados numéricos , Software , Cidades , Tomada de Decisões , Exposição Ambiental , Monitoramento Ambiental/estatística & dados numéricos , Escherichia coli/isolamento & purificação , Contaminação de Alimentos , Gana , Humanos , Projetos Piloto , Formulação de Políticas , Pobreza , Saúde Pública , Saúde da População Urbana , Microbiologia da ÁguaRESUMO
BACKGROUND: Influenza burden estimates help provide evidence to support influenza prevention and control programs at local and international levels. METHODS: Through a systematic review, we aimed to identify all published articles estimating rates of influenza-associated hospitalizations, describe methods and data sources used, and identify regions of the world where estimates are still lacking. We evaluated study heterogeneity to determine if we could pool published rates to generate global estimates of influenza-associated hospitalization. RESULTS: We identified 98 published articles estimating influenza-associated hospitalization rates from 2007-2018. Most articles (65%) identified were from high-income countries, with 34 of those (53%) presenting estimates from the United States. While we identified fewer publications (18%) from low- and lower-middle-income countries, 50% of those were published from 2015-2018, suggesting an increase in publications from lower-income countries in recent years. Eighty percent (n = 78) used a multiplier approach. Regression modelling techniques were only used with data from upper-middle or high-income countries where hospital administrative data was available. We identified variability in the methods, case definitions, and data sources used, including 91 different age groups and 11 different categories of case definitions. Due to the high observed heterogeneity across articles (I2 >99%), we were unable to pool published estimates. CONCLUSIONS: The variety of methods, data sources, and case definitions adapted locally suggests that the current literature cannot be synthesized to generate global estimates of influenza-associated hospitalization burden.
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Bibliometria , Hospitalização/estatística & dados numéricos , Influenza Humana , Humanos , Influenza Humana/epidemiologia , Análise de RegressãoRESUMO
IMPORTANCE: Reported cases of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection likely underestimate the prevalence of infection in affected communities. Large-scale seroprevalence studies provide better estimates of the proportion of the population previously infected. OBJECTIVE: To estimate prevalence of SARS-CoV-2 antibodies in convenience samples from several geographic sites in the US. DESIGN, SETTING, AND PARTICIPANTS: This cross-sectional study performed serologic testing on a convenience sample of residual sera obtained from persons of all ages. The serum was collected from March 23 through May 12, 2020, for routine clinical testing by 2 commercial laboratory companies. Sites of collection were San Francisco Bay area, California; Connecticut; south Florida; Louisiana; Minneapolis-St Paul-St Cloud metro area, Minnesota; Missouri; New York City metro area, New York; Philadelphia metro area, Pennsylvania; Utah; and western Washington State. EXPOSURES: Infection with SARS-CoV-2. MAIN OUTCOMES AND MEASURES: The presence of antibodies to SARS-CoV-2 spike protein was estimated using an enzyme-linked immunosorbent assay, and estimates were standardized to the site populations by age and sex. Estimates were adjusted for test performance characteristics (96.0% sensitivity and 99.3% specificity). The number of infections in each site was estimated by extrapolating seroprevalence to site populations; estimated infections were compared with the number of reported coronavirus disease 2019 (COVID-19) cases as of last specimen collection date. RESULTS: Serum samples were tested from 16â¯025 persons, 8853 (55.2%) of whom were women; 1205 (7.5%) were 18 years or younger and 5845 (36.2%) were 65 years or older. Most specimens from each site had no evidence of antibodies to SARS-CoV-2. Adjusted estimates of the proportion of persons seroreactive to the SARS-CoV-2 spike protein antibodies ranged from 1.0% in the San Francisco Bay area (collected April 23-27) to 6.9% of persons in New York City (collected March 23-April 1). The estimated number of infections ranged from 6 to 24 times the number of reported cases; for 7 sites (Connecticut, Florida, Louisiana, Missouri, New York City metro area, Utah, and western Washington State), an estimated greater than 10 times more SARS-CoV-2 infections occurred than the number of reported cases. CONCLUSIONS AND RELEVANCE: During March to early May 2020, most persons in 10 diverse geographic sites in the US had not been infected with SARS-CoV-2 virus. The estimated number of infections, however, was much greater than the number of reported cases in all sites. The findings may reflect the number of persons who had mild or no illness or who did not seek medical care or undergo testing but who still may have contributed to ongoing virus transmission in the population.
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BACKGROUND: Influenza burden estimates help provide evidence to support influenza prevention and control programs. In this study, we estimated influenza-associated respiratory hospitalization rates in Bhutan, a country considering influenza vaccine introduction. METHODS: Using real-time reverse transcription-polymerase chain reaction laboratory results from severe acute respiratory infection (SARI) surveillance, we estimated the proportion of respiratory hospitalizations attributable to influenza each month among patients aged <5, 5-49, and ≥50 years in six Bhutanese districts for 2015 and 2016. We divided the sum of the monthly influenza-attributed hospitalizations by the total of the six district populations to generate age-specific rates for each year. RESULTS: In 2015, 10% of SARI patients tested positive for influenza (64/659) and 18% tested positive (129/736) in 2016. The incidence of influenza-associated hospitalizations among all age groups was 50/100 000 persons (95% confidence interval [CI]: 45-55) in 2015 and 118/100 000 persons (95% CI: 110-127) in 2016. The highest rates were among children <5 years: 182/100 000 (95% CI: 153-210) in 2015 and 532/100 000 (95% CI: 473-591) in 2016. The second highest influenza-associated hospitalization rates were among adults ≥50 years: 110/100 000 (95% CI: 91-130) in 2015 and 193/100 000 (95% CI: 165-221) in 2016. CONCLUSIONS: Influenza viruses were associated with a substantial burden of severe illness requiring hospitalization especially among children and older adults. These findings can be used to understand the potential impact of seasonal influenza vaccination in these age groups.
Assuntos
Efeitos Psicossociais da Doença , Hospitalização/estatística & dados numéricos , Influenza Humana/epidemiologia , Infecções Respiratórias/epidemiologia , Vigilância de Evento Sentinela , Adolescente , Adulto , Butão/epidemiologia , Criança , Pré-Escolar , Feminino , Humanos , Incidência , Lactente , Masculino , Pessoa de Meia-Idade , Infecções Respiratórias/virologia , Fatores de Risco , Índice de Gravidade de Doença , Adulto JovemRESUMO
Schoolchildren are commonly linked to influenza transmission. Handwashing with soap has been shown to decrease infections; however, improving handwashing practices using soap and water is difficult in low-resource settings. In these settings, alternative hygiene options, such as hand sanitizer, could improve handwashing promotion to reduce influenza virus infections. We conducted a cluster randomized control trial in 24 primary schools in Dhaka to assess the effectiveness of hand sanitizer and a respiratory hygiene education intervention in reducing influenza-like illness (ILI) and laboratory-confirmed influenza during June-September 2015. Twelve schools were randomly selected to receive hand sanitizer and respiratory hygiene education, and 12 schools received no intervention. Field staff actively followed children daily to monitor for new ILI episodes (cough with fever) through school visits and by phone if a child was absent. When an illness episode was identified, medical technologists collected nasal swabs to test for influenza viruses. During the 10-week follow-up period, the incidence of ILI per 1,000 student-weeks was 22 in the intervention group versus 27 in the control group (P-value = 0.4). The incidence of laboratory-confirmed influenza was 53% lower in the intervention schools (3/1,000 person-weeks) than in the control schools (6/1,000 person-weeks) (P-value = 0.01). Hand sanitizer and respiratory hygiene education can help to reduce the risk of influenza virus transmission in schools.
Assuntos
Desinfecção das Mãos , Comportamentos Relacionados com a Saúde , Influenza Humana/prevenção & controle , Influenza Humana/transmissão , Estudantes/estatística & dados numéricos , Bangladesh , Criança , Pré-Escolar , Feminino , Higienizadores de Mão/farmacologia , Humanos , Incidência , Influenza Humana/diagnóstico , Masculino , Instituições Acadêmicas , Sabões/farmacologiaRESUMO
BACKGROUND: No estimates of influenza-associated mortality exist for India. OBJECTIVE: To evaluate national mortality and viral surveillance data from India for assessing their appropriateness in estimating influenza-associated mortality using varied analytic approaches. METHODS: We reviewed influenza virus surveillance data from a national influenza surveillance network. We also reviewed national mortality data from Civil Registration System (CRS), Medical Certification of Cause of Death (MCCD) and the Sample Registration System (SRS). We compared and scored the different sources of mortality data using specific criteria, including the process of cause of death assignment, sample size, proportion of ill-defined deaths, representativeness and availability of time series data. Each of these 5 parameters was scored on a scale from 1 to 5. To evaluate how to generate an influenza-associated mortality estimate for India, we also reviewed 4 methodologic approaches to assess the appropriateness of their assumptions and requirements for these data sets. RESULTS: The influenza virus surveillance data included year-round sample testing for influenza virus and was found to be suitable for influenza mortality estimation modelling. Based on scoring for the 5 mortality data criteria, the SRS data had the highest score with 20 of 25 possible score, whereas MCCD and CRS scored 16 and 12, respectively. The SRS which used verbal autopsy survey methods was determined to be nationally representative and thus adequate for estimating influenza-associated mortality. Evaluation of the modelling methods demonstrated that Poisson regression, risk difference and mortality multiplier methods could be applied to the Indian setting. CONCLUSION: Despite significant challenges, it is possible to estimate influenza-associated mortality in India.
Assuntos
Influenza Humana/epidemiologia , Influenza Humana/mortalidade , Notificação de Doenças , Humanos , Índia/epidemiologia , Vigilância da População , Sistema de Registros , Análise de Regressão , Fatores de RiscoRESUMO
BACKGROUND: Seasonal influenza-associated mortality estimates help identify the burden of disease and assess the value of public health interventions such as annual influenza immunization. Vital registration is limited in Bangladesh making it difficult to estimate seasonal influenza mortality. OBJECTIVES: Our study aimed to estimate seasonal influenza-associated mortality rates for 2010-2012 in Bangladesh. METHODS: We conducted surveillance among hospitalized patients with severe acute respiratory illness (SARI) for persons aged ≥5 years and severe pneumonia for children <5 years in 11 sites across Bangladesh. We defined the catchment areas of these sites and conducted a community survey in 22 randomly selected unions (administrative units) within the catchment areas to identify respiratory deaths. We multiplied the proportion of influenza-positive patients at our surveillance sites by the age-specific number of respiratory deaths identified to estimate seasonal influenza-associated mortality. RESULTS: Among 4221 surveillance case-patients, 553 (13%) were positive for influenza viruses. Concurrently, we identified 1191 persons who died within 2 weeks of developing an acute respiratory illness within the catchment areas of the surveillance hospitals. In 2010-2011, the estimated influenza-associated mortality rate was 6 (95% CI 4-9) per 100 000 for children <5 years and 41 (95% CI 35-47) per 100 000 for persons >60 years. During 2011-2012, the estimated influenza-associated mortality rate was 13 (95% CI 10-16) per 100 000 among children <5 years and 88 (95% CI 79-98) per 100 000 among persons aged >60 years. CONCLUSIONS: We identified a substantial burden of influenza-associated deaths in Bangladesh suggesting that the introduction of prevention and control measures including seasonal vaccination should be considered by local public health decision-makers.
Assuntos
Influenza Humana/epidemiologia , Influenza Humana/mortalidade , Bangladesh/epidemiologia , Efeitos Psicossociais da Doença , Humanos , Modelos Biológicos , Estações do Ano , Vigilância de Evento SentinelaRESUMO
BACKGROUND: Understanding the burden of influenza-associated severe acute respiratory infection (SARI) is important for setting national influenza surveillance and vaccine priorities. Estimating influenza-associated SARI rates requires hospital-based surveillance data and a population-based denominator, which can be challenging to determine. OBJECTIVES: We present an application of the World Health Organization's recently developed manual (WHO Manual) including hospital admission survey (HAS) methods for estimating the burden of influenza-associated SARI, with lessons learned to help others calculate similar estimates. METHODS: Using an existing SARI surveillance platform in Cambodia, we counted influenza-associated SARI cases during 2015 at one sentinel surveillance site in Svay Rieng Province. We applied WHO Manual-derived methods to count respiratory hospitalizations at all hospitals within the catchment area, where 95% of the sentinel site case-patients resided. We used HAS methods to adjust the district-level population denominator for the sentinel site and calculated the incidence rate of influenza-associated SARI by dividing the number of influenza-positive SARI infections by the adjusted population denominator and multiplying by 100 000. We extrapolated the rate to the provincial population to derive a case count for 2015. We evaluated data sources, detailed steps of implementation, and identified lessons learned. RESULTS: We estimated an adjusted influenza-associated 2015 SARI rate of 13.5/100 000 persons for the catchment area of Svay Rieng Hospital and 77 influenza-associated SARI cases in Svay Rieng Province after extrapolation. CONCLUSIONS: Methods detailed in the WHO Manual and operationalized successfully in Cambodia can be used in other settings to estimate rates of influenza-associated SARI.