Transmission Of Pandemic Influenza Research Articles

Feasibility, Acceptability, and Barriers to Implementing Select Non-Pharmaceutical Interventions to Reduce the Transmission of Pandemic Influenza - United States, 2019.

This study aimed to assess the feasibility and acceptability of implementing non-pharmaceutical interventions (NPIs) reserved for influenza pandemics (voluntary home quarantine, use of face masks by ill persons, childcare facility closures, school closures, and social distancing at schools, workplaces, and mass gatherings). Public health officials in all 50 states (including Washington, DC) and 8 territories, and a random sample of 822 local health departments (LHDs), were surveyed in 2019. The response rates for the states/ territories and LHDs were 75% (44/ 59) and 25% (206/ 822), respectively. Most of the state/ territorial respondents stated that the feasibility and acceptability of implementing NPIs were high, except for K-12 school closures lasting up to 6 weeks or 6 months. The LHD respondents also indicated that feasibility and acceptability were lowest for prolonged school closures. Compared to LHD respondents in suburban or urban areas, those in rural areas expressed lower feasibility and acceptability. Barriers to implementing NPIs included financial impact, compliance and difficulty in enforcement, perceived level of disease threat, and concerns regarding political implications. Proactive strategies to systematically address perceived barriers and promote disease prevention ahead of a new pandemic are needed to increase receptivity and consistent adoption of NPIs and other evidence-based countermeasures.

Adoption and impact of non-pharmaceutical interventions for COVID-19

Background: Several non-pharmaceutical interventions (NPIs) have been implemented across the world to control the coronavirus disease (COVID-19) pandemic. Social distancing (SD) interventions applied so far have included school closures, remote working and quarantine. These measures have been shown to have large impacts on pandemic influenza transmission. However, there has been comparatively little examination of such measures for COVID-19. Methods: We examined the existing literature, and collated data, on implementation of NPIs to examine their effects on the COVID-19 pandemic so far. Data on NPIs were collected from official government websites as well as from media sources. Results: Measures such as travel restrictions have been implemented in multiple countries and appears to have slowed the geographic spread of COVID-19 and reduced initial case numbers. We find that, due to the relatively sparse information on the differences with and without interventions, it is difficult to quantitatively assess the efficacy of many interventions. Similarly, whilst the comparison to other pandemic diseases such as influenza can be helpful, there are key differences that could affect the efficacy of similar NPIs. Conclusions: The timely implementation of control measures is key to their success and must strike a balance between early enough application to reduce the peak of the epidemic and ensuring that they can be feasibly maintained for an appropriate duration. Such measures can have large societal impacts and they need to be appropriately justified to the population. As the pandemic of COVID-19 progresses, quantifying the impact of interventions will be a vital consideration for the appropriate use of mitigation strategies.

Adoption and impact of non-pharmaceutical interventions for COVID-19.

Background: Several non-pharmaceutical interventions (NPIs) have been implemented across the world to control the coronavirus disease (COVID-19) pandemic. Social distancing (SD) interventions applied so far have included school closures, remote working and quarantine. These measures have been shown to have large impacts on pandemic influenza transmission. However, there has been comparatively little examination of such measures for COVID-19. Methods: We examined the existing literature, and collated data, on implementation of NPIs to examine their effects on the COVID-19 pandemic so far. Data on NPIs were collected from official government websites as well as from media sources. Results: Measures such as travel restrictions have been implemented in multiple countries and appears to have slowed the geographic spread of COVID-19 and reduced initial case numbers. We find that, due to the relatively sparse information on the differences with and without interventions, it is difficult to quantitatively assess the efficacy of many interventions. Similarly, whilst the comparison to other pandemic diseases such as influenza can be helpful, there are key differences that could affect the efficacy of similar NPIs. Conclusions: The timely implementation of control measures is key to their success and must strike a balance between early enough application to reduce the peak of the epidemic and ensuring that they can be feasibly maintained for an appropriate duration. Such measures can have large societal impacts and they need to be appropriately justified to the population. As the pandemic of COVID-19 progresses, quantifying the impact of interventions will be a vital consideration for the appropriate use of mitigation strategies.

Feasibility of Social Distancing Practices in US Schools to Reduce Influenza Transmission During a Pandemic.

Background:Schools are socially dense environments, and school-based outbreaks often predate and fuel community-wide transmission of seasonal and pandemic influenza. While preemptive school closures can effectively reduce influenza transmission, they are disruptive and currently recommended only for pandemics. We assessed the feasibility of implementing other social distancing practices in K-12 schools as a first step in seeking an alternative to preemptive school closures.Methods:We conducted 36 focus groups with education and public health officials across the United States. We identified and characterized themes and compared feasibility of practices by primary versus secondary school and region of the United States.Results:Participants discussed 29 school practices (25 within-school practices implemented as part of the school day and 4 reduced-schedule practices that impact school hours). Participants reported that elementary schools commonly implement several within-school practices as part of routine operations such as homeroom stay, restriction of hall movement, and staggering of recess times. Because of routine implementation and limited use of individualized schedules within elementary schools, within-school practices were generally felt to be more feasible for elementary schools than secondary schools. Of reduced-schedule practices, shortening the school week and the school day was considered the most feasible; however, reduced-schedule practices were generally perceived to be less feasible than within-school practices for all grade levels.Conclusions:Our findings suggest that schools have many options to increase social distance other than closing. Future research should evaluate which of these seemingly feasible practices are effective in reducing influenza transmission in schools and surrounding communities.

Symbolic transfer entropy reveals the age structure of pandemic influenza transmission from high-volume influenza-like illness data.

Existing methods to infer the relative roles of age groups in epidemic transmission can normally only accommodate a few age classes, and/or require data that are highly specific for the disease being studied. Here, symbolic transfer entropy (STE), a measure developed to identify asymmetric transfer of information between stochastic processes, is presented as a way to reveal asymmetric transmission patterns between age groups in an epidemic. STE provides a ranking of which age groups may dominate transmission, rather than a reconstruction of the explicit between-age-group transmission matrix. Using simulations, we establish that STE can identify which age groups dominate transmission even when there are differences in reporting rates between age groups and even if the data are noisy. Then, the pairwise STE is calculated between time series of influenza-like illness for 12 age groups in 884 US cities during the autumn of 2009. Elevated STE from 5 to 19 year-olds indicates that school-aged children were likely the most important transmitters of infection during the autumn wave of the 2009 pandemic in the USA. The results may be partially confounded by higher rates of physician-seeking behaviour in children compared to adults, but it is unlikely that differences in reporting rates can explain the observed differences in STE.

Anticipation and response: pandemic influenza in Malawi, 2009

ABSTRACT Background: In 2006, Malawi developed a national influenza plan to mitigate, prevent and manage the burden of infection should an outbreak occur. In 2009, it translated its contingency plan to respond to the unfolding influenza pandemic. However, little is known of how Malawi translated its national influenza plan into response actions, or the success of these responses. Objective: To investigate how Malawi translated its preparedness plan and so broaden our understanding of the outcomes of the responses. Methods: We draw on data from 22 in-depth interviews with government policymakers and people working at a policy level in various non-governmental organisations, conducted to assess the level of preparedness and the challenges of translating this. Results: Through a number of public health initiatives, authorities developed communication strategies, strengthened influenza surveillance activities and updated overall goals in pandemic training and education. However, without influenza drills, exercises and simulations to test the plan, activating the pandemic plan, including coordinating and deploying generic infection control measures, was problematic. Responses during the pandemic were at times ‘weak and clumsy’ and failed to mirror the activities and processes highlighted in the preparedness plan. Conclusions: Participants stressed that in order to achieve a coordinated and successful response to mitigate and prevent the further transmission of pandemic influenza, good preparation was critical. The key elements which they identified as relevant for a rapid response included effective communications, robust evidence-based decision-making, strong and reliable surveillance systems and flexible public health responses. To effectively articulate a viable trajectory of pandemic responses, the potential value of simulation exercises could be given more consideration as a mean of sustaining good levels of preparedness and responses against future pandemics. These all demand a well-structured planning for and response to pandemic influenza strategy developed by a functioning scientific and policy advisory committee.

Assessing the State of Knowledge Regarding the Effectiveness of Interventions to Contain Pandemic Influenza Transmission: A Systematic Review and Narrative Synthesis.

BackgroundInfluenza pandemics occur when a novel influenza strain, to which humans are immunologically naïve, emerges to cause infection and illness on a global scale. Differences in the viral properties of pandemic strains, relative to seasonal ones, can alter the effectiveness of interventions typically implemented to control seasonal influenza burden. As a result, annual control activities may not be sufficient to contain an influenza pandemic.PurposeThis study seeks to inform pandemic policy and planning initiatives by reviewing the effectiveness of previous interventions to reduce pandemic influenza transmission and infection. Results will inform the planning and design of more focused in-depth systematic reviews for specific types of interventions, thus providing the most comprehensive and current understanding of the potential for alternative interventions to mitigate the burden of pandemic influenza.MethodsA systematic review and narrative synthesis of existing systematic reviews and meta-analyses examining intervention effectiveness in containing pandemic influenza transmission was conducted using information collected from five databases (PubMed, Medline, Cochrane, Embase, and Cinahl/EBSCO). Two independent reviewers conducted study screening and quality assessment, extracting data related to intervention impact and effectiveness.Results and DiscussionMost included reviews were of moderate to high quality. Although the degree of statistical heterogeneity precluded meta-analysis, the present systematic review examines the wide variety of interventions that can impact influenza transmission in different ways. While it appears that pandemic influenza vaccination provides significant protection against infection, there was insufficient evidence to conclude that antiviral prophylaxis, seasonal influenza cross-protection, or a range of non-pharmaceutical strategies would provide appreciable protection when implemented in isolation. It is likely that an optimal intervention strategy will employ a combination of interventions in a layered approach, though more research is needed to substantiate this proposition.Trial RegistrationPROSPERO 42016039803

Siaα2-3Galβ1- Receptor Genetic Variants Are Associated with Influenza A(H1N1)pdm09 Severity.

Different host genetic variants may be related to the virulence and transmissibility of pandemic Influenza A(H1N1)pdm09, influencing events such as binding of the virus to the entry receptor on the cell of infected individuals and the host immune response. In the present study, two genetic variants of the ST3GAL1 gene, which encodes the Siaα2-3Galβ1- receptor to which influenza A(H1N1)pdm09 virus binds for entry into the host cell, were investigated in an admixed Brazilian population. First, the six exons encoding the ST3GAL1 gene were sequenced in 68 patients infected with strain A(H1N1)pdm09. In a second phase of the study, the rs113350588 and rs1048479 polymorphisms identified in this sample were genotyped in a sample of 356 subjects from the northern and northeastern regions of Brazil with a diagnosis of pandemic influenza. Functional analysis of the polymorphisms was performed in silico and the influence of these variants on the severity of infection was evaluated. The results suggest that rs113350588 and rs1048479 may alter the function of ST3GAL1 either directly through splicing regulation alteration and/or indirectly through LD with SNP with regulatory function. In the study the rs113350588 and rs1048479 polymorphisms were in linkage disequilibrium in the population studied (D’ = 0.65). The GC haplotype was associated with an increased risk of death in subjects with influenza (OR = 4.632, 95% CI = 2.10;1.21). The AT haplotype was associated with an increased risk of severe disease and death (OR = 1.993, 95% CI = 1.09;3.61 and OR 4.476, 95% CI = 2.37;8.44, respectively). This study demonstrated for the first time the association of ST3GAL1 gene haplotypes on the risk of more severe disease and death in patients infected with Influenza A(H1N1)pdm09 virus.

Early Characterization of the Severity and Transmissibility of Pandemic Influenza Using Clinical Episode Data from Multiple Populations.

The potential rapid availability of large-scale clinical episode data during the next influenza pandemic suggests an opportunity for increasing the speed with which novel respiratory pathogens can be characterized. Key intervention decisions will be determined by both the transmissibility of the novel strain (measured by the basic reproductive number R 0) and its individual-level severity. The 2009 pandemic illustrated that estimating individual-level severity, as described by the proportion p C of infections that result in clinical cases, can remain uncertain for a prolonged period of time. Here, we use 50 distinct US military populations during 2009 as a retrospective cohort to test the hypothesis that real-time encounter data combined with disease dynamic models can be used to bridge this uncertainty gap. Effectively, we estimated the total number of infections in multiple early-affected communities using the model and divided that number by the known number of clinical cases. Joint estimates of severity and transmissibility clustered within a relatively small region of parameter space, with 40 of the 50 populations bounded by: p C, 0.0133–0.150 and R 0, 1.09–2.16. These fits were obtained despite widely varying incidence profiles: some with spring waves, some with fall waves and some with both. To illustrate the benefit of specific pairing of rapidly available data and infectious disease models, we simulated a future moderate pandemic strain with p C approximately ×10 that of 2009; the results demonstrating that even before the peak had passed in the first affected population, R 0 and p C could be well estimated. This study provides a clear reference in this two-dimensional space against which future novel respiratory pathogens can be rapidly assessed and compared with previous pandemics.

Inference of seasonal and pandemic influenza transmission dynamics

The inference of key infectious disease epidemiological parameters is critical for characterizing disease spread and devising prevention and containment measures. The recent emergence of surveillance records mined from big data such as health-related online queries and social media, as well as model inference methods, permits the development of new methodologies for more comprehensive estimation of these parameters. We use such data in conjunction with Bayesian inference methods to study the transmission dynamics of influenza. We simultaneously estimate key epidemiological parameters, including population susceptibility, the basic reproductive number, attack rate, and infectious period, for 115 cities during the 2003-2004 through 2012-2013 seasons, including the 2009 pandemic. These estimates discriminate key differences in the epidemiological characteristics of these outbreaks across 10 y, as well as spatial variations of influenza transmission dynamics among subpopulations in the United States. In addition, the inference methods appear to compensate for observational biases and underreporting inherent in the surveillance data.

Behavioural response in educated young adults towards influenza A(H1N1)pdm09.

The purpose of this paper was to determine how contact behaviour change influences the indoor transmission of influenza A(H1N1)pdm09 among school children. We incorporated transmission rate matrices constructed from questionnaire responses into an epidemiological model to simulate contact behaviour change during an influenza epidemic. We constructed a dose-response model describing the relationships between contact rate, viral load, and respiratory symptom scores using published experimental human infection data for A(H1N1)pdm09. Findings showed that that mean numbers of contacts were 5.66 ± 6.23 and 1.96 ± 2.76 d-1 in the 13-19 and 40-59 years age groups, respectively. We found that the basic reproduction number (R 0) was <1 during weekends in pandemic periods, implying that school closures or class suspensions are probably an effective social distancing policy to control pandemic influenza transmission. We conclude that human contact behaviour change is a potentially influential factor on influenza infection rates. For substantiation of this effect, we recommend a future study with more comprehensive control measures.

Determinants of influenza transmission in South East Asia: insights from a household cohort study in Vietnam.

To guide control policies, it is important that the determinants of influenza transmission are fully characterized. Such assessment is complex because the risk of influenza infection is multifaceted and depends both on immunity acquired naturally or via vaccination and on the individual level of exposure to influenza in the community or in the household. Here, we analyse a large household cohort study conducted in 2007–2010 in Vietnam using innovative statistical methods to ascertain in an integrative framework the relative contribution of variables that influence the transmission of seasonal (H1N1, H3N2, B) and pandemic H1N1pdm09 influenza. Influenza infection was diagnosed by haemagglutination-inhibition (HI) antibody assay of paired serum samples. We used a Bayesian data augmentation Markov chain Monte Carlo strategy based on digraphs to reconstruct unobserved chains of transmission in households and estimate transmission parameters. The probability of transmission from an infected individual to another household member was 8% (95% CI, 6%, 10%) on average, and varied with pre-season titers, age and household size. Within households of size 3, the probability of transmission from an infected member to a child with low pre-season HI antibody titers was 27% (95% CI 21%–35%). High pre-season HI titers were protective against infection, with a reduction in the hazard of infection of 59% (95% CI, 44%–71%) and 87% (95% CI, 70%–96%) for intermediate (1∶20–1∶40) and high (≥1∶80) HI titers, respectively. Even after correcting for pre-season HI titers, adults had half the infection risk of children. Twenty six percent (95% CI: 21%, 30%) of infections may be attributed to household transmission. Our results highlight the importance of integrated analysis by influenza sub-type, age and pre-season HI titers in order to infer influenza transmission risks in and outside of the household.

Effect of an Educational Program on Students' Knowledge Regarding Prevention and Control of Pandemic Influenza Transmission

Effect of an Educational Program on Students' Knowledge Regarding Prevention and Control of Pandemic Influenza Transmission

Patterns of spread of influenza A in Canada

Understanding spatial patterns of influenza transmission is important for designing control measures. We investigate spatial patterns of laboratory-confirmed influenza A across Canada from October 1999 to August 2012. A statistical analysis (generalized linear model) of the seasonal epidemics in this time period establishes a clear spatio-temporal pattern, with influenza emerging earlier in western provinces. Early emergence is also correlated with low temperature and low absolute humidity in the autumn. For the richer data from the 2009 pandemic, a mechanistic mathematical analysis, based on a transmission model, shows that both school terms and weather had important effects on pandemic influenza transmission.

International flight-related transmission of pandemic influenza A(H1N1)pdm09: an historical cohort study of the first identified cases in the United Kingdom

BackgroundTransporting over two billion passengers per year, global airline travel has the potential to spread emerging infectious diseases, both via transportation of infectious cases and through in-flight transmission. Current World Health Organization (WHO) guidance recommends contact tracing of passengers seated within two rows of a case of influenza during air travel.ObjectivesThe objectives of this study were to describe flight-related transmission of influenza A(H1N1)pdm09 during a commercial flight carrying the first cases reported in the United Kingdom and to test the specific hypothesis that passengers seated within two rows of an infectious case are at greater risk of infection.MethodsAn historical cohort study, supplemented by contact tracing, enhanced surveillance data and laboratory testing, was used to establish a case status for passengers on board the flight.ResultsData were available for 239 of 278 (86·0%) of passengers on the flight, of whom six were considered infectious in-flight and one immune. The attack rate (AR) was 10 of 232 (4·3%; 95% CI 1·7–6·9%). There was no evidence that the AR for those seated within two rows of an infectious case was different from those who were not (relative risk 0·9; 95% CI 0·2–3·1; P = 1·00). Laboratory testing using PCR and/or serology, available for 118 of 239 (49·4%) of the passengers, was largely consistent with clinically defined case status.ConclusionsThis study of A(H1N1)pdm09 does not support current WHO guidance regarding the contact tracing of passengers seated within two rows of an infectious case of influenza during air travel.

Detection and isolation of Influenza A virus subtype H1N1 from a small backyard swine herd in Colorado

Influenza A virus subtype H1N1 A(H1N1)pdm09 was first confirmed in pigs in the United States in October 2009. In November 2010, lungs and intestines from 2 York piglets from a small, privately owned herd were submitted to the Colorado State University Veterinary Diagnostic Laboratory. The submitting veterinarian reported rapid weight loss and signs of pneumonia in the piglets. Gross lesions included caudoventral pneumonia in both piglets, and histologic lesions in the lungs showed characteristics consistent with influenza virus and bacterial infection. Ribonucleic acid extracted from fresh lung homogenates from both piglets was positive for influenza A(H1N1)pdm09 by a real-time reverse transcription polymerase chain reaction. Virus was isolated from lung homogenates from both piglets in Madin-Darby canine kidney cells, as well as in 10-day-old specific pathogen-free embryonated chicken eggs. Sequence analysis showed 98% homology with 2009 H1N1 human isolates from across the United States and 98% homology against two 2009 and 2010 swine isolates from Nebraska and Minnesota. The current report documents the possible transmission of pandemic influenza A(H1N1)2009 virus [A(H1N1)pdm09] from a human being to a small, privately owned backyard swine herd. The owner was employed as a pharmacist, making occupational exposure to the pandemic influenza A(H1N1)pdm09 a possibility.

Effect of Winter School Breaks on Influenza-like Illness, Argentina, 2005–2008

School closures are used to reduce seasonal and pandemic influenza transmission, yet evidence of their effectiveness is sparse. In Argentina, annual winter school breaks occur during the influenza season, providing an opportunity to study this intervention. We used 2005–2008 national weekly surveillance data of visits to a health care provider for influenza-like illness (ILI) from all provinces. Using Serfling-specified Poisson regressions and population-based census denominators, we developed incidence rate ratios (IRRs) for the 3 weeks before, 2 weeks during, and 3 weeks after the break. For persons 5–64 years of age, IRRs were <1 for at least 1 week after the break. Observed rates returned to expected by the third week after the break; overall decrease among persons of all ages was 14%. The largest decrease was among children 5–14 years of age during the week after the break (37% lower IRR). Among adults, effects were weaker and delayed. Two-week winter school breaks significantly decreased visits to a health care provider for ILI among school-aged children and nonelderly adults.

Worldwide transmission and seasonal variation of pandemic influenza A(H1N1)2009 virus activity during the 2009–2010 pandemic

Seasonal influenza activity varies with geography and time of year. To describe how pandemic influenza A(H1N1)2009 [A(H1N1)pdm09] activity varied during the 2009-2010 pandemic. We analyzed influenza virological data compiled by the World Health Organization from June 2009-August 2010. We calculated weekly proportions of A(H1N1)pdm09-positive specimens out of all A(H1N1)pdm09-positive specimens detected during the study period for each country. We compared parameters of pandemic activity (e.g., peak A[H1N1]pdm09 weekly proportion [peak activity], number of weeks between the 5th and 95th percentiles of A(H1N1)pdm09 cumulative weekly proportion [duration of activity]) between countries in temperate and tropical-subtropical regions. We quantified the proportion of A(H1N1)pdm09 out of all influenza A specimens by country and correlated it with countries' central latitudes. We analyzed data from 80 countries (47 temperate, 33 tropical-subtropical). The median proportion of cases identified during the peak week was higher in temperate (0·12) than in tropical-subtropical (0·09) regions (P<0·01). The median duration of activity was longer in tropical-subtropical (27 weeks) than in temperate countries (20 weeks) (P < 0·01). In most temperate countries (98%), peak pandemic activity occurred during the fall-winter period. There was a positive correlation between country central latitude and proportion of A(H1N1)pdm09 out of all influenza A specimens (r: 0·76; P<0·01). The transmission of A(H1N1)pdm09 exhibited similarities with seasonal influenza transmission in that activity varied between temperate and tropical-subtropical countries and by time of year. Our findings suggest the potential utility of accounting for these factors during future pandemic planning.

Toward unbiased assessment of treatment and prevention: modeling household transmission of pandemic influenza

Providing valid and reliable estimates of the transmissibility and severity of pandemic influenza in real time is key to guide public health policymaking. In particular, early estimates of the transmissibility are indispensable for determining the type and intensity of interventions. A recent study by House and colleagues in BMC Medicine devised a stochastic transmission model to estimate the unbiased risk of transmission within households, applying the method to datasets of the 2009 A/H1N1 influenza pandemic. Here, we discuss future challenges in household transmission studies and underscore the need to systematically collect epidemiological data to decipher the household transmission dynamics. We emphasize the need to consider three critical issues for future improvements: (i) capturing age-dependent heterogeneity within households calls for intensive modeling efforts, (ii) the timeline of observation during the course of an epidemic and the length of follow-up should be aligned with study objectives, and (iii) the use of laboratory methods, especially molecular techniques, is encouraged to distinguish household transmissions from those arising in the community.See related article: http://www.biomedcentral.com/1741-7015/10/117

Usefulness of School Absenteeism Data for Predicting Influenza Outbreaks, United States

Usefulness of School Absenteeism Data for Predicting Influenza Outbreaks, United States