Assessing secondary attack rates among household contacts at the beginning of the influenza A (H1N1) pandemic in Ontario, Canada, April-June 2009: A prospective, observational study
Rachel SavageMichael WhelanIan JohnsonElizabeth ReaMarie LaFreniereLaura C. RosellaFreda LamTina BadianiAnne‐Luise WinterDeborah CarrCrystal FrenetteMaureen HornKathleen DoolingMonali VariaAnne‐Marie HoltVidya SunilCatherine GriftEleanor PagetMichael KingJ. F. BarbaroNatasha S. Crowcroft
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Abstract:
Understanding transmission dynamics of the pandemic influenza A (H1N1) virus in various exposure settings and determining whether transmissibility differed from seasonal influenza viruses was a priority for decision making on mitigation strategies at the beginning of the pandemic. The objective of this study was to estimate household secondary attack rates for pandemic influenza in a susceptible population where control measures had yet to be implemented.All Ontario local health units were invited to participate; seven health units volunteered. For all laboratory-confirmed cases reported between April 24 and June 18, 2009, participating health units performed contact tracing to detect secondary cases among household contacts. In total, 87 cases and 266 household contacts were included in this study. Secondary cases were defined as any household member with new onset of acute respiratory illness (fever or two or more respiratory symptoms) or influenza-like illness (fever plus one additional respiratory symptom). Attack rates were estimated using both case definitions.Secondary attack rates were estimated at 10.3% (95% CI 6.8-14.7) for secondary cases with influenza-like illness and 20.2% (95% CI 15.4-25.6) for secondary cases with acute respiratory illness. For both case definitions, attack rates were significantly higher in children under 16 years than adults (25.4% and 42.4% compared to 7.6% and 17.2%). The median time between symptom onset in the primary case and the secondary case was estimated at 3.0 days.Secondary attack rates for pandemic influenza A (H1N1) were comparable to seasonal influenza estimates suggesting similarities in transmission. High secondary attack rates in children provide additional support for increased susceptibility to infection.Keywords:
Pandemic
Attack rate
Biostatistics
Contact tracing
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MSc Student in Biostatistics, Department of Biostatistics, Faculty of Medicine, Tarbiat Modares University, Tehran, Iran. Professor in Biostatistics, Department of Biostatistics, Faculty of Medicine, Tarbiat Modares University, Tehran, Iran. Assistant Professor in Biostatistics, Faculty of Medicine, Ardabil University of Medical Science, Ardabil, Iran. ___________________________________________________________________________ Abstract
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Abstract Background: Contact tracing is one of the main public health tools in the control of coronavirus disease 2019 (COVID-19). A centralized contact tracing system was developed in Belgium in 2020. We aim to evaluate the performance and describe the results, between January 01, 2021, and September 30, 2021. The characteristics of COVID-19 cases and the impact of COVID-19 vaccination on testing and tracing are also described. Methods: We combined laboratory diagnostic test data (molecular and antigen test), vaccination data, and contact tracing data. A descriptive analysis was done to evaluate the performance of contact tracing and describe insights into the epidemiology of COVID-19 by contact tracing. Results: Between January and September 2021, 555.181 COVID-19 cases were reported to the central contact center and 91% were contacted. The average delay between symptom onset and contact tracing initiation was around 5 days, of which 4 days corresponded to pre-testing delay. High-Risk Contacts (HRC) were reported by 49% of the contacted index cases. The mean number of reported HRC was 2.7. In total, 666.869 HRC were reported of which 91% were successfully contacted and 89% of these were tested at least once following the interview. The estimated average secondary attack rate (SAR) among the contacts of the COVID-19 cases who reported at least one contact, was 27% and was significantly higher among household HRC. The proportion of COVID-19 cases who were previously identified as HRC within the central system was 24%. Conclusions: The contact-tracing system contacted more than 90% of the reported COVID-19 cases and their HRC. This proportion remained stable between January 1 2021 and September 30 2021 despite an increase in cases in March-April 2021. We report high SAR, indicating that through contact tracing a large number of infections were prospectively detected. The system can be further improved by (1) reducing the delay between onset of illness and medical consultation (2) having more exhaustive reporting of HRC by the COVID-19 case.
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The aim of this study was to assess the level of importance, adequacy and need of biostatistics and biostatistics education regarding health sciences in Turkey.Within the scope of the study a survey (questionnaire) was applied to a total of 237 academicians (academicians holding various titles employed by different departments) officiating at medical, veterinary medicine and health sciences faculties of six universities (Afyon Kocatepe, Gazi, Ankara, Hacettepe, Marmara ve Düzce) in Turkey. With this survey were taken views of academics on the status of the training they had received regarding biostatistics, their need for biostatistics education, the importance of biostatistics education and its level of adequacy, the source and adequacy of current information on biostatistics, the solutions to meet biostatistics needs and the statistical techniques which were required.According to the results, 27.8% of the participants have not received biostatistics education. It was determined that the importance of biostatistics education was emphasized as "very and exactly important" by 88.19% of the participants. 14.35% of the participants reported that biostatistics education was far from adequate for post graduate. They needed biostatistics knowledge mainly in the analysis of researches data (χ̄=4.01). On the other hand, they met biostatistics knowledge needs mostly by "help from friends".The study revealed that most of the academicians found biostatistics education important but claimed it had been inadequate. They emphasized the need for the organization of courses, seminars, etc. regarding biostatistics at sufficient intervals. As a consequence of that, this study reveals the importance of biostatistics and biostatistics education once again in the data analysis process in health sciences.
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Abstract A survey of medical schools in the United States and Canada was undertaken to learn the topics in biostatistics that are being taught to medical students and how the biostatistics instruction is organized. Results indicate that more schools are requiring course work in biostatistics than were doing so 10 years ago and that instruction is integrated within courses in epidemiology or public health/community medicine at half of the schools. Although some basic concepts are taught at 90% of the responding schools, there is wide variation in the topics being covered and in the number of hours devoted to the instruction. The results of the survey are followed by descriptions of the biostatistics curriculum at three medical schools.
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Introduction: Biostatistics is a discipline concerned with how we ought to make decisions when analysing biomedical data. As statistics is desirable at every stage of research to obtain scientifically important information and reliable results, the importance of biostatistics should definitely be informed to the researchers in health sciences. Aim: To evaluate the knowledge, attitude and perception of dental professionals towards biostatistics. Materials and Methods: A cross-sectional study was conducted to assess the knowledge, attitude and perception regarding biostatistics among 721 postgraduate students in dental institutions of Andhra Pradesh. All the participants were provided with a pre-structured questionnaire comprising 21 questions, and answering was completely self-paced. Results: Among the respondents, 86% were aware of the importance of biostatistics in research. Forty-five percent of the respondents attempted to perform statistical analysis on their own. Of all the students, 53% were unable to identify the commonly used parametric tests in clinical trials. Conclusion: Majority of the participants were aware of the importance of biostatistics, but only a few of them attempted to perform statistical analysis. Therefore, dental institutions should take initiatives in organising workshops and training programmes for learning and application of biostatistics, concomitantly encourage research activity to conduct valuable research and add up evidence to literature.
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Abstract Background: Transmission risk of coronavirus disease 2019 (COVID-19) to close contacts and at different exposure settings are yet to be fully understood for the evaluation of effective control measures. Methods: We traced 1171 close contact cases who were linked to 291 index cases between July 3, 2020 and September 3, 2020. Clinical and epidemiological characteristics of all index cases, close contacts, and secondary contact cases were collected and analyzed the secondary attack rate and risk of transmission at different exposure settings. Results: Median age of 291 index cases were 43.0 years (range 18.5-82.3) including 213 male and 78 females. Among all 1171 close contact cases, 39(3.3%) cases were identified as secondary infected cases. Among 39 secondary cases, 33(84.62%) cases were symptomatic and 3 (7.69%) cases were asymptomatic. Of the 33 symptomatic cases, 31(86.1%) male and 5(13.9%) female. Of these 36 symptomatic cases, 24(66.7%) cases between age 20-59 and remaining 12(33.3%) cases were age 60 and over. Of the 36 symptomatic cases, 11(30.6%) cases were identified as severe, 19(52.8%) as moderate and 6(16.7%) as mild. The overall secondary clinical attack rate was 3.07% (95% CI 2.49-3.64). The attack rate was higher among those aged between 50 to 69 years and shows higher risk of transmission than age below 50 years. The attack rate was higher among household contact (6.17%(95%CI 4.7-7.6; risk ratio 2.44[95%CI1.5-3.4]), and lower in hospital facility (2.29%,95%CI0.58-3.40; [risk ratio 0.91,95%CI 0.17-1.9]), funeral ceremony (2.53%,95%CI 0.32-4.73), work places (3.95%,95% CI2.5-5.42 [risk ratio 1.56,95%CI 0.63-2.5]), family contacts (3.87%,95%CI 2.4-5.3; risk ratio 1.53,95%CI 0.61-2.45]). Conclusions : Among all exposure settings analyzed, household contact exposure setting remained the highest transmission probability and risk of transmission of COVID-19 with the increase of age and disease severity.
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Objectives:
To assess the knowledge and attitudes of resident physicians toward biostatistics and research methodology concepts.Methods:
We conducted a cross-sectional study between November 2014 and October 2014 at King Abdulaziz University Hospital, Jeddah, Kingdom of Saudi Arabia. A self-administered questionnaire was distributed to all participants. The response rate was 90%.Results:
One hundred sixty-two resident completed the questionnaire. Most residents were well-informed in basic concepts, such as, "P" values, study power, and case control studies; more than half had confidence in interpreting the results of scientific papers. Conversely, more than 67% of the residents were not knowledgeable on more sophisticated terms in biostatistics. Residents with previous training in evidence-based medicine (EBM) (p=0.05) and non-specialist residents (p=0.003) were more likely to have better knowledge scores. Females (p=0.003), and those with previous training in biostatistics and epidemiology had positive attitude toward biostatistics (p<0.001 in both cases). Residents who read medical journals scored lower than those who never read journals (p=0.001).Conclusion:
Prior courses in EBM, as well as male gender were associated with knowledge scores. Reinforcing training after graduation from medical school with special focus on integrating biostatistics with epidemiology and research methods is needed.Biostatistics
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Biostatistics classes can cause many medical students to feel frustrated and frantic. Why is biostatistics part of the body of knowledge that is deemed essential and fundamental for the medical student and eventual practitioner? This is a question that many perplexed (because of trying to comprehend biostatistics) medical students ask. To reiterate, not perceiving the practical role (not just the test-taking role) of biostatistics may didn’t better motivate medical students to learn–and avoid want to learn–the language, purpose and practicality of biostatistics.
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