212 research outputs found

    Theoretical basis to measure the impact of short-lasting control of an infectious disease on the epidemic peak

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    Background. While many pandemic preparedness plans have promoted disease control effort to lower and delay an epidemic peak, analytical methods for determining the required control effort and making statistical inferences have yet to be sought. As a first step to address this issue, we present a theoretical basis on which to assess the impact of an early intervention on the epidemic peak, employing a simple epidemic model. Methods. We focus on estimating the impact of an early control effort (e.g. unsuccessful containment), assuming that the transmission rate abruptly increases when control is discontinued. We provide analytical expressions for magnitude and time of the epidemic peak, employing approximate logistic and logarithmic-form solutions for the latter. Empirical influenza data (H1N1-2009) in Japan are analyzed to estimate the effect of the summer holiday period in lowering and delaying the peak in 2009. Results. Our model estimates that the epidemic peak of the 2009 pandemic was delayed for 21 days due to summer holiday. Decline in peak appears to be a nonlinear function of control-associated reduction in the reproduction number. Peak delay is shown to critically depend on the fraction of initially immune individuals. Conclusions. The proposed modeling approaches offer methodological avenues to assess empirical data and to objectively estimate required control effort to lower and delay an epidemic peak. Analytical findings support a critical need to conduct population-wide serological survey as a prior requirement for estimating the time of peak. © 2011 Omori and Nishiura; licensee BioMed Central Ltd.published_or_final_versio

    Spatial and Temporal Dynamics of Influenza

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    Despite the significant amount of research conducted on the epidemiology of seasonal influenza, the patterns in the annual oscillations of influenza epidemics have not been fully described or understood. Furthermore, the current understanding of the intrinsic properties of influenza epidemics is limited by the geographic scales used to evaluate the data. Analyses conducted at larger spatial scales may potentially conceal local trends in disease structure which may reveal the effect of population structure or environmental factors on disease spread. By using influenza incidence data from the Commonwealth of Pennsylvania and United States influenza mortality data, this dissertation characterizes seasonal influenza epidemics, evaluates factors that drive local influenza epidemics, and provides an initial assessment in how administrative borders influence surveillance for local and regional influenza epidemics.Evidence of spatial heterogeneity existed in the distribution of influenza epidemics for Pennsylvania counties resulting in a cluster of elevated incidence in the South Central region of the state that persisted during the entire study period (2003-2009). Lower monthly precipitation levels during the influenza season (OR = 0.52, p = 0.0319), fewer residents over age 64 (OR = 0.27, p = 0.01) and fewer residents with more than a high school education (OR = 0.76, p = 0.0148) were significantly associated with membership in this cluster. In addition, significant synchrony in the timing of epidemics existed across the entire state and decayed with distance (regional correlation r = 62%). Synchrony as a function of population size displayed evidence of hierarchical spread with more synchronized epidemics occurring among the most populated counties. A gravity model describing movement between two populations was the best predictor of influenza spread suggesting that non-routine and leisure travel drive local epidemics. Within the United States, clusters of epidemic synchronization existed, most notably in densely populated regions where connectivity is stronger. Observation of county and state epidemic clusters highlights the importance and necessity of correctly identifying the ontologic unit of epidemicity for influenza and other diseases. Recognition of the appropriate geographic unit to implement effective surveillance and prevention methods can strengthen the public health response and minimize inefficient mechanisms

    Highlighting the Compound Risk of COVID-19 and Environmental Pollutants Using Geospatial Technology

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    The new COVID-19 coronavirus disease has emerged as a global threat and not just to human health but also the global economy. Due to the pandemic, most countries affected have therefore imposed periods of full or partial lockdowns to restrict community transmission. This has had the welcome but unexpected side effect that existing levels of atmospheric pollutants, particularly in cities, have temporarily declined. As found by several authors, air quality can inherently exacerbate the risks linked to respiratory diseases, including COVID-19. In this study, we explore patterns of air pollution for ten of the most affected countries in the world, in the context of the 2020 development of the COVID-19 pandemic. We find that the concentrations of some of the principal atmospheric pollutants were temporarily reduced during the extensive lockdowns in the spring. Secondly, we show that the seasonality of the atmospheric pollutants is not significantly affected by these temporary changes, indicating that observed variations in COVID-19 conditions are likely to be linked to air quality. On this background, we confirm that air pollution may be a good predictor for the local and national severity of COVID-19 infections.The authors acknowledge financial support from the Spanish Government, Grant RTI2018-354 094336-B-I00 (MCIU/AEI/FEDER, UE), the Spanish Carlos III Health Institute, COV 20/01213, and the Basque Government, Grant IT1207-19

    Influenza epidemiology and vaccine effectiveness following the 2009 pandemic

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    Influenza A(H1N1)pdm09 was identified in April 2009 and spread rapidly around the globe. The public health response in Victoria was undertaken in accordance with the Australian Health Management Plan for Pandemic Influenza (AHMPPI) and included intensive case follow up, school closure, antiviral distribution and a vaccination program. However, evidence soon emerged that most cases were relatively mild compared to previous pandemics. This thesis sought to assess how the epidemiology of influenza A(H1N1)pdm09 differed from expectations in pandemic planning and how the control measures of school closure and antiviral distribution within the AHMPPI were applied and performed, and to investigate the role of infection severity in driving the initial spread of influenza A(H1N1)pdm09. It also sought to examine how the epidemiology of seasonal influenza in Victoria changed following the emergence of influenza A(H1N1)pdm09, and measure the effectiveness of influenza vaccine in prevention of laboratory confirmed influenza infection prior to, during and following the emergence of influenza A(H1N1)pdm09. Investigation of these questions utilised a variety of methodological approaches, including: analysis of influenza-like illness (ILI) and laboratory confirmed influenza surveillance datasets in general practice, locum service, hospital, notifiable disease and reference laboratory settings; systematic review of the literature on influenza A(H1N1)pdm09 viral shedding; deterministic mathematical modelling; and application of sentinel surveillance influenza laboratory testing data to a novel variant of the traditional case control study design to measure vaccine effectiveness. Although it spread rapidly and primarily affected younger age groups, influenza A(H1N1)pdm09 morbidity and mortality were mild compared with previous pandemics. However, the intensity of the public health response was not commensurate with the severity and magnitude of the disease. Transmission of influenza A(H1N1)pdm09 was largely driven by those effectively invisible to the health system and the virus was therefore well-established by the time it was detected. The delay in detection and high proportion of relatively mild infections meant that school closures and antiviral distribution to notified cases and their contacts were ineffective. Pandemic plans need to be revised to accommodate such a scenario and ensure trust from public and professionals in future pandemic responses. Influenza A(H1N1)pdm09 replaced the previously circulating seasonal A(H1N1) and remained dominant in Victoria in 2010. Higher proportions of A(H3N2) and type B influenza were observed in 2011 before dominance of A(H3N2) in 2012, accompanied by an increase in severe infections in older people especially. Whilst ILI surveillance suggested influenza seasons of moderate magnitude from 2010-2012, notifiable disease surveillance indicated a considerable increase in influenza testing by medical practitioners. Influenza vaccine effectiveness (VE) in Victoria varied considerably in the years preceding, during and following the 2009 pandemic. With the exceptions of high influenza A(H1N1)pdm09-specific seasonal VE in 2010 and 2011, and no protective effect of seasonal vaccine against influenza A(H1N1)pdm09 in 2009, type and subtype-specific VE were inconsistent across seasons, and had little correlation with the percentage match between circulating and vaccine strains. Further investigation of the role of previous immunity and antigenic similarity by phylogenetic analysis is needed to better understand the determinants of influenza VE

    Role of Influenza among Adult Respiratory Hospitalizations: a Systemic Review

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    With the threat of avian influenza, influenza laboratory testing and surveillance capacity has increased globally. Data from global surveillance activities have been used to identify circulating influenza strains for vaccine policy decisions, and have provided evidence of influenza disease among various populations. A recent meta-analysis, which includes findings from these surveillance efforts, has shown that influenza contributes to 10% of pediatric respiratory hospitalizations. Although statistical models indicate a high burden of influenza-associated morbidity among older adults and pandemic studies reveal an increase in hospitalizations among young adults, the global burden of seasonal influenza among adults remains unknown. In order to estimate the global burden of seasonal influenza among adult respiratory hospitalizations, we conducted a systematic review of the published literature, and identified 48 eligible articles published between January 1996 and June 2012 that met our inclusion criteria. We combined these published datasets with 29 eligible, unique datasets from year-round, influenza hospital-based surveillance. These combined data covered 50 countries with varying income and vaccine policies. Extracting numbers tested and positive for influenza, we calculated crude median positive proportions and evaluated potential differences in crude proportions among variables using Kruskal-Wallis non-parametric tests. We observed differences by data source and country development status when we included the 2009 pandemic year. With the exclusion of the 2009 pandemic year, we then generated adjusted pooled estimates using the log binomial model. We found 11% of cases from adult respiratory hospitalizations worldwide were laboratory-confirmed for influenza. This pooled estimate was independent of age but increased as country development or income level decreased. Our findings suggest that influenza is an important contributor to severe acute respiratory illness among both young and older adult populations. For countries without reliable influenza data, we provide an estimate that they may use in planning and allocating resources for the control and prevention of influenza

    Principles and practice of public health surveillance

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    Public health surveillance is the systematic, ongoing assessment of the health of a community including the timely collection, analysis, interpretation, dissemination and subsequent use of data. The book presents an organized approach to planning, developing, implementing, and evaluating public health surveillance systems. Chapters include: planning; data sources; system management and data quality control; analyzing surveillance data; special statistical issues; communication; evaluation; ethical issues; legal issues; use of computers; state and local issues; and surveillance in developing countries. The book is intended to serve as a desk reference for public health practitioners and as a text for students in public health.PB9 3-10 1129I: Introduction -- II: Planning a surveillance system -- III: Sources of routinely collected data for surveillance -- IV: Management of the surveillance system and quality control of data -- V: Analyzing and interpreting surveillance data -- VI: Special analytic issues -- VII: Communicating information for action -- VIII: Evaluating public health surveillance -- IX: Ethical issues -- X:Public health surveillance and the law -- XI: Computerizing public health surveillance systems -- XII: State and local issues in surveillance -- XIII: Important surveillance issues in developing countries -- Tables and figures.1992874

    Estimating the impact of influenza vaccination and antigenic drift on influenza-related morbidity and mortality in England & Wales using hidden Markov models

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    Influenza causes substantial morbidity and mortality in some influenza sea- sons, especially among the elderly. Influenza seasons dominated by circula- tion of influenza A/H3N2 virus tend to result in more morbidity and mor- tality than seasons dominated by influenza A/H1N1 or influenza B viruses. Influenza viruses undergo constant mutation, called antigenic drift, which is largely driven by host immunity. It has been shown that antigenic drift in influenza A/H3N2 virus proceeds in a punctuated, as opposed to contin- uous, fashion. A cluster of antigenically similar influenza A/H3N2 viruses appears to remain dominant for between 1 and 8 influenza seasons before being supplanted by a new cluster. Influenza seasons when a new cluster becomes dominant may result in higher morbidity and mortality than other seasons. Influenza vaccine effectiveness varies between influenza seasons be- cause of the different subtypes in circulation and the degree of antigenic match between vaccine and circulating variants. In each influenza season in recent years, over 70% of the population of England & Wales aged > 65 has been vaccinated, though the impact of this high coverage on population level morbidity and mortality is unknown. Multivariate time series models were fitted to reports of laboratory confirmed influenza, sentinel general practi- tioner (GP) consultations for influenza-like-illness, and all deaths registered to underlying pneumonia or influenza in England & Wales from 1975/76 to 2004/05. The models successfully distinguish influenza - attributable GP consultations and deaths from GP consultations and deaths that would be expected in the absence of influenza. This distinction is made jointly by the laboratory reports and the non-laboratory confirmed surveillance data. It is not possible to use the multivariate time series models to quantify the average effect of the appearance of a new cluster of influenza A/H3N2 virus variants, or vaccine impact, on influenza - attributable morbidity or mortality in the data analyzed. Reasons for this are discu
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