330 research outputs found

    Accounting for Underreporting in Mathematical Modeling of Transmission and Control of COVID-19 in Iran

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    Iran has been the country most affected by the outbreak of SARS-CoV-2 in the Middle East. With a relatively high case fatality ratio and limited testing capacity, the number of confirmed cases reported is suspected to suffer from significant underreporting. Therefore, understanding the transmission dynamics of COVID-19 and assessing the effectiveness of the interventions that have taken place in Iran while accounting for the uncertain level of underreporting is of critical importance. In this paper, we developed a compartmental transmission model to estimate the time-dependent effective reproduction number since the beginning of the outbreak in Iran. We associate the variations in the effective reproduction number with a timeline of interventions and national events. The estimation method accounts for the underreporting due to low case ascertainment. Our estimates of the effective reproduction number ranged from 0.66 to 1.73 between February and April 2020, with a median of 1.16. We estimate a reduction in the effective reproduction number during this period, from 1.73 (95% CI 1.60–1.87) on 1 March 2020 to 0.69 (95% CI 0.68–0.70) on 15 April 2020, due to various non-pharmaceutical interventions. The series of non-pharmaceutical interventions and the public compliance that took place in Iran are found to be effective in slowing down the speed of the spread of COVID-19. However, we argue that if the impact of underreporting is overlooked, the estimated transmission and control dynamics could mislead public health decisions, policy makers, and the general public

    Accounting for Underreporting in Mathematical Modeling of Transmission and Control of COVID-19 in Iran

    Get PDF
    Iran has been the country most affected by the outbreak of SARS-CoV-2 in the Middle East. With a relatively high case fatality ratio and limited testing capacity, the number of confirmed cases reported is suspected to suffer from significant underreporting. Therefore, understanding the transmission dynamics of COVID-19 and assessing the effectiveness of the interventions that have taken place in Iran while accounting for the uncertain level of underreporting is of critical importance. In this paper, we developed a compartmental transmission model to estimate the time-dependent effective reproduction number since the beginning of the outbreak in Iran. We associate the variations in the effective reproduction number with a timeline of interventions and national events. The estimation method accounts for the underreporting due to low case ascertainment. Our estimates of the effective reproduction number ranged from 0.66 to 1.73 between February and April 2020, with a median of 1.16. We estimate a reduction in the effective reproduction number during this period, from 1.73 (95% CI 1.60–1.87) on 1 March 2020 to 0.69 (95% CI 0.68–0.70) on 15 April 2020, due to various non-pharmaceutical interventions. The series of non-pharmaceutical interventions and the public compliance that took place in Iran are found to be effective in slowing down the speed of the spread of COVID-19. However, we argue that if the impact of underreporting is overlooked, the estimated transmission and control dynamics could mislead public health decisions, policy makers, and the general public

    Actual versus 'ideal' antibiotic prescribing for common conditions in English primary care

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    Previous work based on guidelines and expert opinion identified 'ideal' prescribing proportions-the overall proportion of consultations that should result in an antibiotic prescription-for common infectious conditions. Here, actual condition-specific prescribing proportions in primary care in England were compared with ideal prescribing proportions identified by experts. All recorded consultations for common infectious conditions (cough, bronchitis, exacerbations of asthma or chronic obstructive pulmonary disease, sore throat, rhinosinusitis, otitis media, lower respiratory tract infection, upper respiratory tract infection, influenza-like illness, urinary tract infection, impetigo, acne, gastroenteritis) for 2013-15 were extracted from The Health Improvement Network (THIN) database. The proportions of consultations resulting in an antibiotic prescription were established, concentrating on acute presentations in patients without relevant comorbidities. These actual prescribing proportions were then compared with previously established 'ideal' proportions by condition. For most conditions, substantially higher proportions of consultations resulted in an antibiotic prescription than was deemed appropriate according to expert opinion. An antibiotic was prescribed in 41% of all acute cough consultations when experts advocated 10%. For other conditions the proportions were: bronchitis (actual 82% versus ideal 13%); sore throat (actual 59% versus ideal 13%); rhinosinusitis (actual 88% versus ideal 11%); and acute otitis media in 2- to 18-year-olds (actual 92% versus ideal 17%). Substantial variation between practices was found. This work has identified substantial overprescribing of antibiotics in English primary care, and highlights conditions where this is most pronounced, particularly in respiratory tract conditions

    Explaining variation in antibiotic prescribing between general practices in the UK

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    Objectives:Primary care practices in England differ in antibiotic prescribing rates, and, anecdotally, prescribers justify high prescribing rates based on their individual case mix. The aim of this paper was to explore to what extent factors such as patient comorbidities explain this variation in antibiotic prescribing. Methods:Primary care consultation and prescribing data recorded in The Health Improvement Network (THIN) database in 2013 were used. Boosted regression trees (BRTs) and negative binomial regression (NBR) models were used to evaluate associations between predictors and antibiotic prescribing rates. The following variables were considered as potential predictors: various infection-related consultation rates, proportions of patients with comorbidities, proportion of patients with inhaled/systemic corticosteroids or immunosuppressive drugs, and demographic traits. Results:The median antibiotic prescribing rate was 65.6 (IQR 57.4-74.0) per 100 registered patients among 348 English practices. In the BRT model, consultation rates had the largest total relative influence on antibiotic prescribing rate (53.5%), followed by steroid and immunosuppressive drugs (31.6%) and comorbidities (12.2%). Only 21% of the deviance could be explained by an NBR model considering only comorbidities and age and gender, whereas 57% of the deviance could be explained by the model considering all variables. Conclusions:The majority of practice-level variation in antibiotic prescribing cannot be explained by variation in prevalence of comorbidities. Factors such as high consultation rates for respiratory tract infections and high prescribing rates for corticosteroids could explain much of the variation, and as such may be considered in determining a practice's potential to reduce prescribing

    Understanding the gender gap in antibiotic prescribing:a cross-sectional analysis of English primary care

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    OBJECTIVES:To explore the causes of the gender gap in antibiotic prescribing, and to determine whether women are more likely than men to receive an antibiotic prescription per consultation. DESIGN:Cross-sectional analysis of routinely collected electronic medical records from The Health Improvement Network (THIN). SETTING:English primary care. PARTICIPANTS:Patients who consulted general practices registered with THIN between 2013 and 2015. PRIMARY AND SECONDARY OUTCOME MEASURES:Total antibiotic prescribing was measured in children (<19 years), adults (19-64 years) and the elderly (65+ years). For 12 common conditions, the number of adult consultations was measured, and the relative risk (RR) of being prescribed antibiotics when consulting as female or with comorbidity was estimated. RESULTS:Among 4.57 million antibiotic prescriptions observed in the data, female patients received 67% more prescriptions than male patients, and 43% more when excluding antibiotics used to treat urinary tract infection (UTI). These gaps were more pronounced in adult women (99% more prescriptions than men; 69% more when excluding UTI) than in children (9%; 0%) or the elderly (67%; 38%). Among adults, women accounted for 64% of consultations (62% among patients with comorbidity), but were not substantially more likely than men to receive an antibiotic prescription when consulting with common conditions such as cough (RR 1.01; 95% CI 1.00 to 1.02), sore throat (RR 1.01, 95% CI 1.00 to 1.01) and lower respiratory tract infection (RR 1.00, 95% CI 1.00 to 1.01). Exceptions were skin conditions: women were less likely to be prescribed antibiotics when consulting with acne (RR 0.67, 95% CI 0.66 to 0.69) or impetigo (RR 0.85, 95% CI 0.81 to 0.88). CONCLUSIONS:The gender gap in antibiotic prescribing can largely be explained by consultation behaviour. Although in most cases adult men and women are equally likely to be prescribed an antibiotic when consulting primary care, it is unclear whether or not they are equally indicated for antibiotic therapy

    Cost-Effectiveness of Pediatric Influenza Vaccination in The Netherlands

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    Objective: This study evaluates the cost-effectiveness of extending the Dutch influenza vaccination program for elderly and medical high-risk groups to include pediatric influenza vaccination, taking indirect protection into account. Methods: An age-structured dynamic transmission model was used that was calibrated to influenza-associated GP visits over 4 seasons (2010-2011 to 2013-2014). The clinical and economic impact of different pediatric vaccination strategies were compared over 20 years, varying the targeted age range, the vaccine type for children or elderly and high-risk groups. Outcome measures include averted symptomatic infections and deaths, societal costs and quality-adjusted life-years (QALYs), and incremental cost-effectiveness ratios. Costs and QALYs were discounted at 4% and 1.5% annually. Results: At an assumed coverage of 50%, adding pediatric vaccination for 2to 17-year-olds with quadrivalent live-attenuated vaccine to the current vaccination program for elderly and medical high-groups with quadrivalent inactivated vaccine was estimated to avert, on average, 401 820 symptomatic cases and 72 deaths per year. Approximately half of averted symptomatic cases and 99% of averted deaths were prevented in other age groups than 2to 17-year-olds due to herd immunity. The cumulative discounted 20-year economic impact was 35 068 QALYs gained and V1687 million saved, that is, the intervention was cost-saving. This vaccination strategy had the highest probability of being the most cost-effective strategy considered, dominating pediatric strategies targeting 2to 6-year-olds or 2to 12-year-olds or strategies with trivalent inactivated vaccine. Conclusion: Modeling indicates that introducing pediatric influenza vaccination in The Netherlands is cost-saving, reducing the influenza-related disease burden substantially

    Intrauterine exposure to carbamazepine and specific congenital malformations: systematic review and case-control study.

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    OBJECTIVE: To identify specific major congenital malformations associated with use of carbamazepine in the first trimester of pregnancy. DESIGN: A review of all published cohort studies to identify key indications and a population based case-control study to test these indications. SETTING: Review of PubMed, Web of Science, and Embase for papers about carbamazepine exposure in the first trimester of pregnancy and specific malformations, and the EUROCAT Antiepileptic Study Database, including data from 19 European population based congenital anomaly registries, 1995-2005. PARTICIPANTS: The literature review covered eight cohort studies of 2680 pregnancies with carbamazepine monotherapy exposure, and the EUROCAT dataset included 98 075 registrations of malformations covering over 3.8 million births. MAIN OUTCOME MEASURES: Overall prevalence for a major congenital malformation after exposure to carbamazepine monotherapy in the first trimester. Odds ratios for malformations with exposure to carbamazepine among cases (five types of malformation identified in the literature review) compared with two groups of controls: other non-chromosomal registrations of malformations and chromosomal syndromes. RESULTS: The literature review yielded an overall prevalence for a major congenital malformation of 3.3% (95% confidence interval 2.7 to 4.2) after exposure to carbamazepine monotherapy in the first trimester. In 131 registrations of malformations, the fetus had been exposed to carbamazepine monotherapy. Spina bifida was the only specific major congenital malformation significantly associated with exposure to carbamazepine monotherapy (odds ratio 2.6 (95% confidence interval 1.2 to 5.3) compared with no antiepileptic drug), but the risk was smaller for carbamazepine than for valproic acid (0.2, 0.1 to 0.6). There was no evidence for an association with total anomalous pulmonary venous return (no cases with carbamazepine exposure), cleft lip (with or without palate) (0.2, 0.0 to 1.3), diaphragmatic hernia (0.9, 0.1 to 6.6), or hypospadias (0.7, 0.3 to 1.6) compared with no exposure to antiepileptic drugs. Further exploratory analysis suggested a higher risk of single ventricle and atrioventricular septal defect. CONCLUSION: Carbamazepine teratogenicity is relatively specific to spina bifida, though the risk is less than with valproic acid. Despite the large dataset, there was not enough power to detect moderate risks for some rare major congenital malformations

    Recent trends in molecular diagnostics of yeast infections : from PCR to NGS

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    The incidence of opportunistic yeast infections in humans has been increasing over recent years. These infections are difficult to treat and diagnose, in part due to the large number and broad diversity of species that can underlie the infection. In addition, resistance to one or several antifungal drugs in infecting strains is increasingly being reported, severely limiting therapeutic options and showcasing the need for rapid detection of the infecting agent and its drug susceptibility profile. Current methods for species and resistance identification lack satisfactory sensitivity and specificity, and often require prior culturing of the infecting agent, which delays diagnosis. Recently developed high-throughput technologies such as next generation sequencing or proteomics are opening completely new avenues for more sensitive, accurate and fast diagnosis of yeast pathogens. These approaches are the focus of intensive research, but translation into the clinics requires overcoming important challenges. In this review, we provide an overview of existing and recently emerged approaches that can be used in the identification of yeast pathogens and their drug resistance profiles. Throughout the text we highlight the advantages and disadvantages of each methodology and discuss the most promising developments in their path from bench to bedside

    Integration of decision support systems to improve decision support performance

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    Decision support system (DSS) is a well-established research and development area. Traditional isolated, stand-alone DSS has been recently facing new challenges. In order to improve the performance of DSS to meet the challenges, research has been actively carried out to develop integrated decision support systems (IDSS). This paper reviews the current research efforts with regard to the development of IDSS. The focus of the paper is on the integration aspect for IDSS through multiple perspectives, and the technologies that support this integration. More than 100 papers and software systems are discussed. Current research efforts and the development status of IDSS are explained, compared and classified. In addition, future trends and challenges in integration are outlined. The paper concludes that by addressing integration, better support will be provided to decision makers, with the expectation of both better decisions and improved decision making processes
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