Developing guidelines for school closure interventions to be used during a future influenza pandemic

A Retrospective Database Analysis of Before and After Social Distancing in Relation to Pediatric Infection Rate and Healthcare Services Usage During the Coronavirus Disease 2019 Pandemic

BACKGROUND

Social distancing policy was introduced in Israel in 2020 to reduce the spread of coronavirus disease 2019 (COVID-19). The aim of this study was to analyze the effect of social distancing on other infections in children, by comparing disease rate and healthcare utilization before and after social distancing.

METHODS

This was a before-and-after study. Within this retrospective database analysis of parallel periods in 2019 (periods 1 and 2) and 2020 (periods 3 [prelockdown period] and 4 [lockdown period]) we included all pediatric population registered in the electronic medical records of the Maccabi Healthcare Services, Israel, looking at the occurrence of non-COVID-19 infections, antibiotic purchasing, physician visits, ambulatory emergency care center visits, emergency department visits, and hospitalizations.

RESULTS

A total of 776 828 children were included from 2019, and 777 729 from 2020. We found a lower infection rate in 2020 versus 2019. We did not find a difference in infection rate between periods 1 and 2, while there was a significant difference between periods 3 and 4. We found a significant difference between periods 2 and 4, with a higher RR than for the comparison between periods 1 and 3. There was a modest decrease in ambulatory emergency care center visits in 2020, and lower increases in emergency department visits and hospital admissions. We found decreases in antibiotic purchasing between periods 1 and 3 and between periods 2 and 4, more pronounced in 2020 than in 2019.

CONCLUSIONS

Analysis of findings before and after social distancing and masking showed reduced prevalence of non-COVID-19 pediatric infections and reduced consumption of healthcare services and antibiotics related with the lockdown period.

Impact of school reopening on pandemic spread: A case study using an agent-based model for COVID-19

This article examines the impact of partial/full reopening of school/college campuses on the spread of a pandemic using COVID-19 as a case study. The study uses an agent-based simulation model that replicates community spread in an urban region of U.S.A. via daily social mixing of susceptible and infected individuals. Data representing population demographics, SARS-CoV-2 epidemiology, and social interventions guides the model's behavior, which is calibrated and validated using data reported by the government. The model indicates a modest but significant increase (8.15%) in the total number of reported cases in the region for a complete (100%) reopening compared to keeping schools and colleges fully virtual. For partial returns of 75% and 50%, the percent increases in the number of reported cases are shown to be small (2.87% and 1.26%, respectively) and statistically insignificant. The AB model also predicts that relaxing the stringency of the school safety protocol for sanitizing, use of mask, social distancing, testing, and quarantining and thus allowing the school transmission coefficient to double may result in a small increase in the number of reported infected cases (2.14%). Hence for pandemic outbreaks from viruses with similar characteristics as for SARS-CoV-2, keeping the schools and colleges open with a modest campus safety protocol and in-person attendance below a certain threshold may be advisable.

Projected geographic disparities in healthcare worker absenteeism from COVID-19 school closures and the economic feasibility of child care subsidies: a simulation study

BACKGROUND

School closures have been enacted as a measure of mitigation during the ongoing coronavirus disease 2019 (COVID-19) pandemic. It has been shown that school closures could cause absenteeism among healthcare workers with dependent children, but there remains a need for spatially granular analyses of the relationship between school closures and healthcare worker absenteeism to inform local community preparedness.

METHODS

We provide national- and county-level simulations of school closures and unmet child care needs across the USA. We develop individual simulations using county-level demographic and occupational data, and model school closure effectiveness with age-structured compartmental models. We perform multivariate quasi-Poisson ecological regressions to find associations between unmet child care needs and COVID-19 vulnerability factors.

RESULTS

At the national level, we estimate the projected rate of unmet child care needs for healthcare worker households to range from 7.4 to 8.7%, and the effectiveness of school closures as a 7.6% and 8.4% reduction in fewer hospital and intensive care unit (ICU) beds, respectively, at peak demand when varying across initial reproduction number estimates by state. At the county level, we find substantial variations of projected unmet child care needs and school closure effects, 9.5% (interquartile range (IQR) 8.2-10.9%) of healthcare worker households and 5.2% (IQR 4.1-6.5%) and 6.8% (IQR 4.8-8.8%) reduction in fewer hospital and ICU beds, respectively, at peak demand. We find significant positive associations between estimated levels of unmet child care needs and diabetes prevalence, county rurality, and race (p<0.05). We estimate costs of absenteeism and child care and observe from our models that an estimated 76.3 to 96.8% of counties would find it less expensive to provide child care to all healthcare workers with children than to bear the costs of healthcare worker absenteeism during school closures.

CONCLUSIONS

School closures are projected to reduce peak ICU and hospital demand, but could disrupt healthcare systems through absenteeism, especially in counties that are already particularly vulnerable to COVID-19. Child care subsidies could help circumvent the ostensible trade-off between school closures and healthcare worker absenteeism.

Projected geographic disparities in healthcare worker absenteeism from COVID-19 school closures and the economic feasibility of child care subsidies: a simulation study

Background

School closures have been enacted as a measure of mitigation during the ongoing COVID-19 pandemic. It has been shown that school closures could cause absenteeism amongst healthcare workers with dependent children, but there remains a need for spatially granular analyses of the relationship between school closures and healthcare worker absenteeism to inform local community preparedness.

Methods

We provide national- and county-level simulations of school closures and unmet child care needs across the United States. We develop individual simulations using county-level demographic and occupational data, and model school closure effectiveness with age-structured compartmental models. We perform multivariate quasi-Poisson ecological regressions to find associations between unmet child care needs and COVID-19 vulnerability factors.

Results

At the national level, we estimate the projected rate of unmet child care needs for healthcare worker households to range from 7.5% to 8.6%, and the effectiveness of school closures to range from 3.2% (R0 = 4) to 7.2% (R0 = 2) reduction in fewer ICU beds at peak demand. At the county-level, we find substantial variations of projected unmet child care needs and school closure effects, ranging from 1.9% to 18.3% of healthcare worker households and 5.7% to 8.8% reduction in fewer ICU beds at peak demand (R0 = 2). We find significant positive associations between estimated levels of unmet child care needs and diabetes prevalence, county rurality, and race (p < 0.05). We estimate costs of absenteeism and child care and observe from our models that an estimated 71.1% to 98.8% of counties would find it less expensive to provide child care to all healthcare workers with children than to bear the costs of healthcare worker absenteeism during school closures.

Conclusions

School closures are projected to reduce peak ICU bed demand, but could disrupt healthcare systems through absenteeism, especially in counties that are already particularly vulnerable to COVID-19. Child care subsidies could help circumvent the ostensible tradeoff between school closures and healthcare worker absenteeism.

Study design and protocol for investigating social network patterns in rural and urban schools and households in a coastal setting in Kenya using wearable proximity sensors

Background: Social contact patterns shape the transmission of respiratory infections spread via close interactions. There is a paucity of observational data from schools and households, particularly in developing countries. Portable wireless sensors can record unbiased proximity events between individuals facing each other, shedding light on pathways of infection transmission.

Design and methods: The aim is to characterize face-to-face contact patterns that may shape the transmission of respiratory infections in schools and households in Kilifi, Kenya. Two schools, one each from a rural and urban area, will be purposively selected. From each school, 350 students will be randomly selected proportional to class size and gender to participate. Nine index students from each school will be randomly selected and followed-up to their households. All index household residents will be recruited into the study. A further 3-5 neighbouring households will also be recruited to give a maximum of 350 participants per household setting. The sample size per site is limited by the number of sensors available for data collection. Each participant will wear a wireless proximity sensor lying on their chest area for 7 consecutive days. Data on proximal dyadic interactions will be collected automatically by the sensors only for participants who are face-to-face. Key characteristics of interest include the distribution of degree and the frequency and duration of contacts and their variation in rural and urban areas. These will be stratified by age, gender, role, and day of the week.

Expected results: Resultant data will inform on social contact patterns in rural and urban areas of a previously unstudied population. Ensuing data will be used to parameterize mathematical simulation models of transmission of a range of respiratory viruses, including respiratory syncytial virus, and used to explore the impact of intervention measures such as vaccination and social distancing.

School dismissal as a pandemic influenza response: When, where and for how long?

We used individual-based computer simulation models at community, regional and national levels to evaluate the likely impact of coordinated pre-emptive school dismissal policies during an influenza pandemic. Such policies involve three key decisions: when, over what geographical scale, and how long to keep schools closed. Our evaluation includes uncertainty and sensitivity analyses, as well as model output uncertainties arising from variability in serial intervals and presumed modifications of social contacts during school dismissal periods. During the period before vaccines become widely available, school dismissals are particularly effective in delaying the epidemic peak, typically by 4–6 days for each additional week of dismissal. Assuming the surveillance is able to correctly and promptly diagnose at least 5–10% of symptomatic individuals within the jurisdiction, dismissals at the city or county level yield the greatest reduction in disease incidence for a given dismissal duration for all but the most severe pandemic scenarios considered here. Broader (multi-county) dismissals should be considered for the most severe and fast-spreading (1918-like) pandemics, in which multi-month closures may be necessary to delay the epidemic peak sufficiently to allow for vaccines to be implemented.

Study design and protocol for investigating social network patterns in rural and urban schools and households in a coastal setting in Kenya using wearable proximity sensors

Background: Social contact patterns shape the transmission of respiratory infections spread via close interactions. There is a paucity of observational data from schools and households, particularly in developing countries. Portable wireless sensors can record unbiased proximity events between individuals facing each other, shedding light on pathways of infection transmission. Design and methods: The aim is to characterize face-to-face contact patterns that may shape the transmission of respiratory infections in schools and households in Kilifi, Kenya. Two schools, one each from a rural and urban area, will be purposively selected. From each school, 350 students will be randomly selected proportional to class size and gender to participate. Nine index students from each school will be randomly selected and followed-up to their households. All index household residents will be recruited into the study. A further 3-5 neighbouring households will also be recruited to give a maximum of 350 participants per household setting. The sample size per site is limited by the number of sensors available for data collection. Each participant will wear a wireless proximity sensor lying on their chest area for 7 consecutive days. Data on proximal dyadic interactions will be collected automatically by the sensors only for participants who are face-to-face. Key characteristics of interest include the distribution of degree and the frequency and duration of contacts and their variation in rural and urban areas. These will be stratified by age, gender, role, and day of the week. Expected results: Resultant data will inform on social contact patterns in rural and urban areas of a previously unstudied population. Ensuing data will be used to parameterize mathematical simulation models of transmission of a range of respiratory viruses, including respiratory syncytial virus, and used to explore the impact of intervention measures such as vaccination and social distancing.

Lessons from a decade of individual-based models for infectious disease transmission: a systematic review (2006-2015)

Background

Individual-based models (IBMs) are useful to simulate events subject to stochasticity and/or heterogeneity, and have become well established to model the potential (re)emergence of pathogens (e.g., pandemic influenza, bioterrorism). Individual heterogeneity at the host and pathogen level is increasingly documented to influence transmission of endemic diseases and it is well understood that the final stages of elimination strategies for vaccine-preventable childhood diseases (e.g., polio, measles) are subject to stochasticity. Even so it appears IBMs for both these phenomena are not well established. We review a decade of IBM publications aiming to obtain insights in their advantages, pitfalls and rationale for use and to make recommendations facilitating knowledge transfer within and across disciplines.

Methods

We systematically identified publications in Web of Science and PubMed from 2006-2015 based on title/abstract/keywords screening (and full-text if necessary) to retrieve topics, modeling purposes and general specifications. We extracted detailed modeling features from papers on established vaccine-preventable childhood diseases based on full-text screening.

Results

We identified 698 papers, which applied an IBM for infectious disease transmission, and listed these in a reference database, describing their general characteristics. The diversity of disease-topics and overall publication frequency have increased over time (38 to 115 annual publications from 2006 to 2015). The inclusion of intervention strategies (8 to 52) and economic consequences (1 to 20) are increasing, to the detriment of purely theoretical explorations. Unfortunately, terminology used to describe IBMs is inconsistent and ambiguous. We retrieved 24 studies on a vaccine-preventable childhood disease (covering 7 different diseases), with publication frequency increasing from the first such study published in 2008. IBMs have been useful to explore heterogeneous between- and within-host interactions, but combined applications are still sparse. The amount of missing information on model characteristics and study design is remarkable.

Conclusions

IBMs are suited to combine heterogeneous within- and between-host interactions, which offers many opportunities, especially to analyze targeted interventions for endemic infections. We advocate the exchange of (open-source) platforms and stress the need for consistent “branding”. Using (existing) conventions and reporting protocols would stimulate cross-fertilization between research groups and fields, and ultimately policy making in decades to come.

Electronic supplementary material

The online version of this article (doi:10.1186/s12879-017-2699-8) contains supplementary material, which is available to authorized users.

Identifying cost-effective dynamic policies to control epidemics

We describe a mathematical decision model for identifying dynamic health policies for controlling epidemics. These dynamic policies aim to select the best current intervention based on accumulating epidemic data and the availability of resources at each decision point. We propose an algorithm to approximate dynamic policies that optimize the population's net health benefit, a performance measure which accounts for both health and monetary outcomes. We further illustrate how dynamic policies can be defined and optimized for the control of a novel viral pathogen, where a policy maker must decide (i) when to employ or lift a transmission-reducing intervention (e.g. school closure) and (ii) how to prioritize population members for vaccination when a limited quantity of vaccines first become available. Within the context of this application, we demonstrate that dynamic policies can produce higher net health benefit than more commonly described static policies that specify a pre-determined sequence of interventions to employ throughout epidemics. Copyright © 2016 John Wiley & Sons, Ltd.

Control Measures for Human Respiratory Viral Infection

New viral respiratory pathogens are emerging with increasing frequency and have potentially devastating impacts on the population worldwide. Recent examples of newly emerged threats include severe acute respiratory syndrome coronavirus, the 2009 H1N1 influenza pandemic, and Middle East respiratory syndrome coronavirus. Experiences with these pathogens have shown up major deficiencies in how we deal globally with emerging pathogens and taught us salient lessons in what needs to be addressed for future pandemics. This article reviews the lessons learnt from past experience and current knowledge on the range of measures required to limit the impact of emerging respiratory infections from public health responses down to individual patient management. Key areas of interest are surveillance programs, political limitations on our ability to respond quickly enough to emerging threats, media management, public information dissemination, infection control, prophylaxis, and individual patient management. Respiratory physicians have a crucial role to play in many of these areas and need to be aware of how to respond as new viral pathogens emerge.

A Tale of Many Cities: A Contemporary Historical Study of the Implementation of School Closures during the 2009 pA(H1N1) Influenza Pandemic

Applying qualitative historical methods, we examined the consideration and implementation of school closures as a nonpharmaceutical intervention (NPI) in thirty US cities during the spring 2009 wave of the pA(H1N1) influenza pandemic. We gathered and performed close textual readings of official federal, state, and municipal government documents; media coverage; and academic publications. Lastly, we conducted oral history interviews with public health and education officials in our selected cities. We found that several local health departments pursued school closure plans independent of CDC guidance, that uncertainty of action and the rapidly evolving understanding of pA(H1N1) contributed to tension and pushback from the public, that the media and public perception played a significant role in the response to school closure decisions, and that there were some notable instances of interdepartmental communication breakdown. We conclude that health departments should continue to develop and fine-tune their action plans while also working to develop better communication methods with the public, and work more closely with education officials to better understand the complexities involved in closing schools. Lastly, state and local governments should work to resolve lingering issues of legal authority for school closures in times of public health crises.

Reactive School Closure During Increased Influenza-Like Illness (ILI) Activity in Western Kentucky, 2013: A Field Evaluation of Effect on ILI Incidence and Economic and Social Consequences for Families

A reactive school closure following high influenza-like illness-related student absenteeism in a Kentucky school district did not influence reported influenza-like illness transmission in student households.

Background. School closures are an important mitigation strategy during influenza pandemic: if implemented early in a local outbreak, they can slow the disease spread in the surrounding community. During seasonal influenza epidemics, school closures may occur reactively, after the disease is already widespread in the community. Such reactive closures are often too late to reduce influenza transmission. However, they can provide data to determine under which circumstances they might be effective in reducing influenza-like illness (ILI) transmission.

Methods. We conducted a household survey in a school district in Kentucky. District A closed after high student absenteeism due to influenza-like illness (ILI), whereas adjacent Districts B and C remained open. We collected data on self-reported ILI among household members in these 3 districts 2 weeks before the District A closure, during closure, and 2 weeks after reopening, and we evaluated economic and social consequences of school closure on student households in District A. The difference-in-differences method was applied to compare changes in ILI rates from before to after closure between districts.

Results. Estimated average daily ILI rate decreased less in District A than in District B or C for the entire sample and when stratified by age groups (0–5 years old, 6–18 years old, and above 18 years old). Twenty-five percent of District A households reported ≥1 closure-related economic or social difficulty.

Conclusions. Closing schools after a widespread ILI activity in District A did not reduce ILI transmission but caused difficulties for some households.

Economic Evaluation of Individual School Closure Strategies: The Hong Kong 2009 H1N1 Pandemic

BACKGROUND

School closures as a means of containing the spread of disease have received considerable attention from the public health community. Although they have been implemented during previous pandemics, the epidemiological and economic effects of the closure of individual schools remain unclear.

METHODOLOGY

This study used data from the 2009 H1N1 pandemic in Hong Kong to develop a simulation model of an influenza pandemic with a localised population structure to provide scientific justifications for and economic evaluations of individual-level school closure strategies.

FINDINGS

The estimated cost of the study's baseline scenario was USD330 million. We found that the individual school closure strategies that involved all types of schools and those that used a lower threshold to trigger school closures had the best performance. The best scenario resulted in an 80% decrease in the number of cases (i.e., prevention of about 830,000 cases), and the cost per case prevented by this intervention was USD1,145; thus, the total cost was USD1.28 billion.

CONCLUSION

This study predicts the effects of individual school closure strategies on the 2009 H1N1 pandemic in Hong Kong. Further research could determine optimal strategies that combine various system-wide and district-wide school closures with individual school triggers across types of schools. The effects of different closure triggers at different phases of a pandemic should also be examined.

Model-Based Comprehensive Analysis of School Closure Policies for Mitigating Influenza Epidemics and Pandemics

School closure policies are among the non-pharmaceutical measures taken into consideration to mitigate influenza epidemics and pandemics spread. However, a systematic review of the effectiveness of alternative closure policies has yet to emerge. Here we perform a model-based analysis of four types of school closure, ranging from the nationwide closure of all schools at the same time to reactive gradual closure, starting from class-by-class, then grades and finally the whole school. We consider policies based on triggers that are feasible to monitor, such as school absenteeism and national ILI surveillance system. We found that, under specific constraints on the average number of weeks lost per student, reactive school-by-school, gradual, and county-wide closure give comparable outcomes in terms of optimal infection attack rate reduction, peak incidence reduction or peak delay. Optimal implementations generally require short closures of one week each; this duration is long enough to break the transmission chain without leading to unnecessarily long periods of class interruption. Moreover, we found that gradual and county closures may be slightly more easily applicable in practice as they are less sensitive to the value of the excess absenteeism threshold triggering the start of the intervention. These findings suggest that policy makers could consider school closure policies more diffusely as response strategy to influenza epidemics and pandemics, and the fact that some countries already have some experience of gradual or regional closures for seasonal influenza outbreaks demonstrates that logistic and feasibility challenges of school closure strategies can be to some extent overcome.

Substantial Impact of School Closure on the Transmission Dynamics during the Pandemic Flu H1N1-2009 in Oita, Japan

Background

School closure is considered as an effective measure to prevent pandemic influenza. Although Japan has implemented many class, grade, and whole school closures during the early stage of the pandemic 2009, the effectiveness of such a school closure has not been analysed appropriately. In addition, analysis based on evidence or data from a large population has yet to be performed. We evaluated the preventive effect of school closure against the pandemic (H1N1) 2009 and examined efficient strategies of reactive school closure.

Materials and Methods

Data included daily reports of reactive school closures and the number of infected students in the pandemic in Oita City, Japan. We used a regression model that incorporated a time delay to analyse the daily data of school closure based on a time continuous susceptible-exposed-infected-removed model of infectious disease spread. The delay was due to the time-lag from transmission to case reporting. We simulated the number of students infected daily with and without school closure and evaluated the effectiveness.

Results

The model with a 3-day delay from transmission to reporting yielded the best fit using R² (the coefficient of determination). This result suggests that the recommended period of school closure is more than 4 days. Moreover, the effect of school closure in the simulation of school closure showed the following: the number of infected students decreased by about 24% at its peak, and the number of cumulative infected students decreased by about 8.0%.

Conclusions

School closure was an effective intervention for mitigating the spread of influenza and should be implemented for more than 4 days. School closure has a remarkable impact on decreasing the number of infected students at the peak, but it does not substantially decrease the total number of infected students.

An outbreak of influenza A(H1N1)pdm09 virus in a primary school in Vietnam

BACKGROUND

Despite school pupils being at greatest risk during the 2009 influenza pandemic there are limited data on outbreaks of influenza A(H1N1)pdm09 in primary schools in South-East Asia. This prospective cohort study describes an outbreak of influenza A(H1N1)pdm09 in a primary school in rural Vietnam.

FINDINGS

In total 103 cases of influenza-like illness were found among the 407 pupils in the primary school. Ten of these were laboratory confirmed cases of influenza A(H1N1)pdm09 virus. The overall attack rate (AR) was 25% (103/407), and was highest (41%) in grade 4 pupils, where the outbreak started. All cases in the outbreak presented with a mild and self-limiting illness, acute respiratory symptoms and fever. Public health interventions to contain the outbreak could explain the lower attack rates in other grades. Ill pupils were asked to stay at home. Oseltamivir was not given to pupils and the school did not close during the outbreak. The last detected case occurred 12 days following identification of the first case.

CONCLUSIONS

This is the first report of an outbreak of influenza A(H1N1)pdm09 among pupils in a primary school in Vietnam. High attack rates in Grade 4 pupils suggest shared activities contributed to transmission. The public health response using non-pharmaceutical measures may have played a role in ending the outbreak.

Improving public health policy through infection transmission modelling: Guidelines for creating a Community of Practice

Infection transmission models have been applied in the Canadian public health system to create modelling frameworks and knowledge translation methods that inform public health by linking theory, practice and policy. The Use of Mathematical Modelling in Public Health Decision Making for Infectious Diseases workshop was held by the Pandemic Influenza Outbreak Research Modelling team and the National Collaborating Centre for Infectious Diseases to establish the infrastructure, expertise and resources necessary for building a Community of Practice. The authors discuss the key presentations, as well as summarize the outcomes and action plans that emerged.

BACKGROUND:

Despite significant research efforts in Canada, real application of modelling in public health decision making and practice has not yet met its full potential. There is still room to better address the diversity of the Canadian population and ensure that research outcomes are translated for use within their relevant contexts.

OBJECTIVES:

To strengthen connections to public health practice and to broaden its scope, the Pandemic Influenza Outbreak Research Modelling team partnered with the National Collaborating Centre for Infectious Diseases to hold a national workshop. Its objectives were to: understand areas where modelling terms, methods and results are unclear; share information on how modelling can best be used in informing policy and improving practice, particularly regarding the ways to integrate a focus on health equity considerations; and sustain and advance collaborative work in the development and application of modelling in public health.

METHOD:

The Use of Mathematical Modelling in Public Health Decision Making for Infectious Diseases workshop brought together research modellers, public health professionals, policymakers and other experts from across the country. Invited presentations set the context for topical discussions in three sessions. A final session generated reflections and recommendations for new opportunities and tasks.

CONCLUSIONS:

Gaps in content and research include the lack of standard frameworks and a glossary for infectious disease modelling. Consistency in terminology, clear articulation of model parameters and assumptions, and sustained collaboration will help to bridge the divide between research and practice.

Mitigation of infectious disease at school: targeted class closure vs school closure

Background

School environments are thought to play an important role in the community spread of infectious diseases such as influenza because of the high mixing rates of school children. The closure of schools has therefore been proposed as an efficient mitigation strategy. Such measures come however with high associated social and economic costs, making alternative, less disruptive interventions highly desirable. The recent availability of high-resolution contact network data from school environments provides an opportunity to design models of micro-interventions and compare the outcomes of alternative mitigation measures.

Methods and results

We model mitigation measures that involve the targeted closure of school classes or grades based on readily available information such as the number of symptomatic infectious children in a class. We focus on the specific case of a primary school for which we have high-resolution data on the close-range interactions of children and teachers. We simulate the spread of an influenza-like illness in this population by using an SEIR model with asymptomatics, and compare the outcomes of different mitigation strategies. We find that targeted class closure affords strong mitigation effects: closing a class for a fixed period of time – equal to the sum of the average infectious and latent durations – whenever two infectious individuals are detected in that class decreases the attack rate by almost 70% and significantly decreases the probability of a severe outbreak. The closure of all classes of the same grade mitigates the spread almost as much as closing the whole school.

Conclusions

Our model of targeted class closure strategies based on readily available information on symptomatic subjects and on limited information on mixing patterns, such as the grade structure of the school, shows that these strategies might be almost as effective as whole-school closure, at a much lower cost. This may inform public health policies for the management and mitigation of influenza-like outbreaks in the community.

Electronic supplementary material

The online version of this article (doi:10.1186/s12879-014-0695-9) contains supplementary material, which is available to authorized users.

A model-based economic analysis of pre-pandemic influenza vaccination cost-effectiveness

Background

A vaccine matched to a newly emerged pandemic influenza virus would require a production time of at least 6 months with current proven techniques, and so could only be used reactively after the peak of the pandemic. A pre-pandemic vaccine, although probably having lower efficacy, could be produced and used pre-emptively. While several previous studies have investigated the cost effectiveness of pre-emptive vaccination strategies, they have not been directly compared to realistic reactive vaccination strategies.

Methods

An individual-based simulation model of ~30,000 people was used to examine a pre-emptive vaccination strategy, assuming vaccination conducted prior to a pandemic using a low-efficacy vaccine. A reactive vaccination strategy, assuming a 6-month delay between pandemic emergence and availability of a high-efficacy vaccine, was also modelled. Social distancing and antiviral interventions were examined in combination with these alternative vaccination strategies. Moderate and severe pandemics were examined, based on estimates of transmissibility and clinical severity of the 1957 and 1918 pandemics respectively, and the cost effectiveness of each strategy was evaluated.

Results

Provided that a pre-pandemic vaccine achieved at least 30% efficacy, pre-emptive vaccination strategies were found to be more cost effective when compared to reactive vaccination strategies. Reactive vaccination coupled with sustained social distancing and antiviral interventions was found to be as effective at saving lives as pre-emptive vaccination coupled with limited duration social distancing and antiviral use, with both strategies saving approximately 420 life-years per 10,000 population for a moderate pandemic with a basic reproduction number of 1.9 and case fatality rate of 0.25%. Reactive vaccination was however more costly due to larger productivity losses incurred by sustained social distancing, costing $8 million per 10,000 population ($19,074/LYS) versus $6.8 million per 10,000 population ($15,897/LYS) for a pre-emptive vaccination strategy. Similar trends were observed for severe pandemics.

Conclusions

Compared to reactive vaccination, pre-emptive strategies would be more effective and more cost effective, conditional on the pre-pandemic vaccine being able to achieve a certain level of coverage and efficacy. Reactive vaccination strategies exist which are as effective at mortality reduction as pre-emptive strategies, though they are less cost effective.

The effects of school closures on influenza outbreaks and pandemics: systematic review of simulation studies

BACKGROUND

School closure is a potential intervention during an influenza pandemic and has been investigated in many modelling studies.

OBJECTIVES

To systematically review the effects of school closure on influenza outbreaks as predicted by simulation studies.

METHODS

We searched Medline and Embase for relevant modelling studies published by the end of October 2012, and handsearched key journals. We summarised the predicted effects of school closure on the peak and cumulative attack rates and the duration of the epidemic. We investigated how these predictions depended on the basic reproduction number, the timing and duration of closure and the assumed effects of school closures on contact patterns.

RESULTS

School closures were usually predicted to be most effective if they caused large reductions in contact, if transmissibility was low (e.g. a basic reproduction number <2), and if attack rates were higher in children than in adults. The cumulative attack rate was expected to change less than the peak, but quantitative predictions varied (e.g. reductions in the peak were frequently 20-60% but some studies predicted >90% reductions or even increases under certain assumptions). This partly reflected differences in model assumptions, such as those regarding population contact patterns.

CONCLUSIONS

Simulation studies suggest that school closure can be a useful control measure during an influenza pandemic, particularly for reducing peak demand on health services. However, it is difficult to accurately quantify the likely benefits. Further studies of the effects of reactive school closures on contact patterns are needed to improve the accuracy of model predictions.

An operational epidemiological model for calibrating agent-based simulations of pandemic influenza outbreaks

Uncertainty of pandemic influenza viruses continue to cause major preparedness challenges for public health policymakers. Decisions to mitigate influenza outbreaks often involve tradeoff between the social costs of interventions (e.g., school closure) and the cost of uncontrolled spread of the virus. To achieve a balance, policymakers must assess the impact of mitigation strategies once an outbreak begins and the virus characteristics are known. Agent-based (AB) simulation is a useful tool for building highly granular disease spread models incorporating the epidemiological features of the virus as well as the demographic and social behavioral attributes of tens of millions of affected people. Such disease spread models provide excellent basis on which various mitigation strategies can be tested, before they are adopted and implemented by the policymakers. However, to serve as a testbed for the mitigation strategies, the AB simulation models must be operational. A critical requirement for operational AB models is that they are amenable for quick and simple calibration. The calibration process works as follows: the AB model accepts information available from the field and uses those to update its parameters such that some of its outputs in turn replicate the field data. In this paper, we present our epidemiological model based calibration methodology that has a low computational complexity and is easy to interpret. Our model accepts a field estimate of the basic reproduction number, and then uses it to update (calibrate) the infection probabilities in a way that its effect combined with the effects of the given virus epidemiology, demographics, and social behavior results in an infection pattern yielding a similar value of the basic reproduction number. We evaluate the accuracy of the calibration methodology by applying it for an AB simulation model mimicking a regional outbreak in the US. The calibrated model is shown to yield infection patterns closely replicating the input estimates of the basic reproduction number. The calibration method is also tested to replicate an initial infection incidence trend for a H1N1 outbreak like that of 2009.

Cost-effective length and timing of school closure during an influenza pandemic depend on the severity

BACKGROUND

There has been a variation in published opinions toward the effectiveness of school closure which is implemented reactively when substantial influenza transmissions are seen at schools. Parameterizing an age-structured epidemic model using published estimates of the pandemic H1N1-2009 and accounting for the cost effectiveness, we examined if the timing and length of school closure could be optimized.

METHODS

Age-structured renewal equation was employed to describe the epidemic dynamics of an influenza pandemic. School closure was assumed to take place only once during the course of the pandemic, abruptly reducing child-to-child transmission for a fixed length of time and also influencing the transmission between children and adults. Public health effectiveness was measured by reduction in the cumulative incidence, and cost effectiveness was also examined by calculating the incremental cost effectiveness ratio and adopting a threshold of 1.0 × 10⁷ Japanese Yen/life-year.

RESULTS

School closure at the epidemic peak appeared to yield the largest reduction in the final size, while the time of epidemic peak was shown to depend on the transmissibility. As the length of school closure was extended, we observed larger reduction in the cumulative incidence. Nevertheless, the cost effectiveness analysis showed that the cost of our school closure scenario with the parameters derived from H1N1-2009 was not justifiable. If the risk of death is three times or greater than that of H1N1-2009, the school closure could be regarded as cost effective.

CONCLUSIONS

There is no fixed timing and duration of school closure that can be recommended as universal guideline for different types of influenza viruses. The effectiveness of school closure depends on the transmission dynamics of a particular influenza virus strain, especially the virulence (i.e. the infection fatality risk).

Challenges and lessons learned from implementing a risk-based approach to school advice and closure during the containment phase of the 2009 influenza pandemic in the West Midlands, England

OBJECTIVE

School closure as a social distancing measure was used in some countries during the initial phases of the influenza A(H1N1)pdm09 pandemic. The objective of this paper is to describe the use of a risk-based approach to public health interventions for schools during the 'containment phase' of the pandemic and to describe lessons learnt.

METHODS

The development of a framework for risk assessment and decision-making to determine school closures in the West Midlands, England, during the 'containment phase' of influenza A(H1N1)pdm09 pandemic is described.

RESULTS

Using the framework developed during the 'containment phase', assessments were conducted for 344 educational institutions who reported confirmed cases or 'particularly high absenteeism'. Of these, 209 (60%) had confirmed cases and 65 were closed, mainly for public health or operational reasons. Schools were closed on an individual basis, during the most intense period of the pandemic and for an average period of six days (maximum 11 days). The risk-based approach evolved as experience and knowledge of influenza A(H1N1)pdm09 pandemic virus increased, however some decisions were difficult to communicate to parents, schools and stakeholders particularly when the number of schools affected escalated and the pandemic response phases changed.

CONCLUSION

The management of school closures is an 'uncertain art'. Numerous challenges and lessons were identified in attempting, during the containment phase of the influenza A(H1N1)pdm09 pandemic, to ensure consistency and transparency in an increasingly complex process. The overall approach described could be further developed to improve decision-making for infectious diseases in schools.

Understanding the school community's response to school closures during the H1N1 2009 influenza pandemic

Background

During the 2009 H1N1 influenza pandemic, Australian public health officials closed schools as a strategy to mitigate the spread of the infection. This article examines school communities’ understanding of, and participation in, school closures and the beliefs and values which underpinned school responses to the closures.

Methods

We interviewed four school principals, 25 staff, 14 parents and 13 students in five schools in one Australian city which were either fully or partially closed during the 2009 H1N1 pandemic.

Results

Drawing on Thompson et al’s ethical framework for pandemic planning, we show that considerable variation existed between and within schools in their attention to ethical processes and values. In all schools, health officials and school leaders were strongly committed to providing high quality care for members of the school community. There was variation in the extent to which information was shared openly and transparently, the degree to which school community members considered themselves participants in decision-making, and the responsiveness of decision-makers to the changing situation. Reservations were expressed about the need for closures and quarantine and there was a lack of understanding of the rationale for the closures. All schools displayed a strong duty of care toward those in need, although school communities had a broader view of care than that of the public health officials. Similarly, there was a clear understanding of and commitment to protect the public from harm and to demonstrate responsible stewardship.

Conclusions

We conclude that school closures during an influenza pandemic represent both a challenge for public health officials and a litmus test for the level of trust in public officials, government and the school as institution. In our study, trust was the foundation upon which effective responses to the school closure were built. Trust relations within the school were the basis on which different values and beliefs were used to develop and justify the practices and strategies in response to the pandemic.

The cost effectiveness of pandemic influenza interventions: a pandemic severity based analysis

BACKGROUND

The impact of a newly emerged influenza pandemic will depend on its transmissibility and severity. Understanding how these pandemic features impact on the effectiveness and cost effectiveness of alternative intervention strategies is important for pandemic planning.

METHODS

A cost effectiveness analysis of a comprehensive range of social distancing and antiviral drug strategies intended to mitigate a future pandemic was conducted using a simulation model of a community of ∼30,000 in Australia. Six pandemic severity categories were defined based on case fatality ratio (CFR), using data from the 2009/2010 pandemic to relate hospitalisation rates to CFR.

RESULTS

Intervention strategies combining school closure with antiviral treatment and prophylaxis are the most cost effective strategies in terms of cost per life year saved (LYS) for all severity categories. The cost component in the cost per LYS ratio varies depending on pandemic severity: for a severe pandemic (CFR of 2.5%) the cost is ∼$9 k per LYS; for a low severity pandemic (CFR of 0.1%) this strategy costs ∼$58 k per LYS; for a pandemic with very low severity similar to the 2009 pandemic (CFR of 0.03%) the cost is ∼$155 per LYS. With high severity pandemics (CFR >0.75%) the most effective attack rate reduction strategies are also the most cost effective. During low severity pandemics costs are dominated by productivity losses due to illness and social distancing interventions, while for high severity pandemics costs are dominated by hospitalisation costs and productivity losses due to death.

CONCLUSIONS

The most cost effective strategies for mitigating an influenza pandemic involve combining sustained social distancing with the use of antiviral agents. For low severity pandemics the most cost effective strategies involve antiviral treatment, prophylaxis and short durations of school closure; while these are cost effective they are less effective than other strategies in reducing the infection rate.

Pandemic influenza in Papua New Guinea: a modelling study comparison with pandemic spread in a developed country

OBJECTIVES

The possible occurrence of a highly pathogenic influenza strain is of concern to health authorities worldwide. It is known that during past influenza pandemics developing countries have experienced considerably higher death rates compared with developed countries. Furthermore, many developing countries lack appropriate pandemic preparedness plans. Mathematical modelling studies to guide the development of such plans are largely focused on predicting pandemic influenza spread in developed nations. However, intervention strategies shown by modelling studies to be highly effective for developed countries give limited guidance as to the impact which an influenza pandemic may have on low-income countries given different demographics and resource constraints. To address this, an individual-based model of a Papua New Guinean (PNG) community was created and used to simulate the spread of a novel influenza strain. The results were compared with those obtained from a comparable Australian model.

DESIGN

A modelling study.

SETTING

The towns of Madang in PNG (population ∼35 000) and Albany (population ∼30 000) in Australia.

OUTCOME MEASURES

Daily and cumulative illness attack rates in both models following introduction of a novel influenza strain into a naive population, for an unmitigated scenario and two social distancing intervention scenarios.

RESULTS

The unmitigated scenario indicated an approximately 50% higher attack rate in PNG compared with the Australian model. The two social distancing-based interventions strategies were 60-70% less effective in a PNG setting compared with an Australian setting.

CONCLUSIONS

This study provides further evidence that an influenza pandemic occurring in a low-income country such as PNG may have a greater impact than one occurring in a developed country, and that PNG-feasible interventions may be substantially less effective. The larger average household size in PNG, the larger proportion of the population under 18 and greater community-wide contact all contribute to this feature.

Economic analysis of pandemic influenza mitigation strategies for five pandemic severity categories

BACKGROUND

The threat of emergence of a human-to-human transmissible strain of highly pathogenic influenza A(H5N1) is very real, and is reinforced by recent results showing that genetically modified A(H5N1) may be readily transmitted between ferrets. Public health authorities are hesitant in introducing social distancing interventions due to societal disruption and productivity losses. This study estimates the effectiveness and total cost (from a societal perspective, with a lifespan time horizon) of a comprehensive range of social distancing and antiviral drug strategies, under a range of pandemic severity categories.

METHODS

An economic analysis was conducted using a simulation model of a community of ~30,000 in Australia. Data from the 2009 pandemic was used to derive relationships between the Case Fatality Rate (CFR) and hospitalization rates for each of five pandemic severity categories, with CFR ranging from 0.1% to 2.5%.

RESULTS

For a pandemic with basic reproduction number R0 = 1.8, adopting no interventions resulted in total costs ranging from $441 per person for a pandemic at category 1 (CFR 0.1%) to $8,550 per person at category 5 (CFR 2.5%). For severe pandemics of category 3 (CFR 0.75%) and greater, a strategy combining antiviral treatment and prophylaxis, extended school closure and community contact reduction resulted in the lowest total cost of any strategy, costing $1,584 per person at category 5. This strategy was highly effective, reducing the attack rate to 5%. With low severity pandemics costs are dominated by productivity losses due to illness and social distancing interventions, whereas higher severity pandemic costs are dominated by healthcare costs and costs arising from productivity losses due to death.

CONCLUSIONS

For pandemics in high severity categories the strategies with the lowest total cost to society involve rigorous, sustained social distancing, which are considered unacceptable for low severity pandemics due to societal disruption and cost.

Vaccination strategies for future influenza pandemics: a severity-based cost effectiveness analysis

Background

A critical issue in planning pandemic influenza mitigation strategies is the delay between the arrival of the pandemic in a community and the availability of an effective vaccine. The likely scenario, born out in the 2009 pandemic, is that a newly emerged influenza pandemic will have spread to most parts of the world before a vaccine matched to the pandemic strain is produced. For a severe pandemic, additional rapidly activated intervention measures will be required if high mortality rates are to be avoided.

Methods

A simulation modelling study was conducted to examine the effectiveness and cost effectiveness of plausible combinations of social distancing, antiviral and vaccination interventions, assuming a delay of 6-months between arrival of an influenza pandemic and first availability of a vaccine. Three different pandemic scenarios were examined; mild, moderate and extreme, based on estimates of transmissibility and pathogenicity of the 2009, 1957 and 1918 influenza pandemics respectively. A range of different durations of social distancing were examined, and the sensitivity of the results to variation in the vaccination delay, ranging from 2 to 6 months, was analysed.

Results

Vaccination-only strategies were not cost effective for any pandemic scenario, saving few lives and incurring substantial vaccination costs. Vaccination coupled with long duration social distancing, antiviral treatment and antiviral prophylaxis was cost effective for moderate pandemics and extreme pandemics, where it saved lives while simultaneously reducing the total pandemic cost. Combined social distancing and antiviral interventions without vaccination were significantly less effective, since without vaccination a resurgence in case numbers occurred as soon as social distancing interventions were relaxed. When social distancing interventions were continued until at least the start of the vaccination campaign, attack rates and total costs were significantly lower, and increased rates of vaccination further improved effectiveness and cost effectiveness.

Conclusions

The effectiveness and cost effectiveness consequences of the time-critical interplay of pandemic dynamics, vaccine availability and intervention timing has been quantified. For moderate and extreme pandemics, vaccination combined with rapidly activated antiviral and social distancing interventions of sufficient duration is cost effective from the perspective of life years saved.

[Effects of school closure during influenza A/H1N1 pandemic in 2009 in Japan]

Schools were closed worldwide during the 2009 influenza A/H1N1 pandemic to prevent the viral spread; however, to date, there has been insufficient evidence to conclude that the closures were beneficial. Therefore, in the present review, we evaluated the effects of school closure during the 2009 influenza A/H1N1 pandemic in Japan. A search of PubMed and Japanese journals identified 24 articles that evaluated the effects of school closure using the following methods: descriptive epidemiology, changes in absenteeism rate, a simulation model, and reproductive number. Almost all of the retrieved studies showed that school closure effectively reduced the number of new infections and thus subsequently suppressed the epidemic. On the other hand, two major sets of confounding variables were identified. First, the effect of school closure was confounded by the methods used to measure, viral infectivity, subject characteristics, increased immunization rates, nonpharmaceutical interventions, antiviral administration, student contact patterns during school closure, and individual household environments. Secondly, school closure implementation was affected by differences between proactive and reactive closures, differences between seasonal and pandemic influenza, decision factors regarding school closure, socioeconomic cost, and ethics of imposing restrictions on individuals. Therefore, a comprehensive, longitudinal study is necessary to clarify the effects of school closure during viral pandemics.

Attack rates assessment of the 2009 pandemic H1N1 influenza A in children and their contacts: a systematic review and meta-analysis

BACKGROUND

The recent H1N1 influenza A pandemic was marked by multiple reports of illness and hospitalization in children, suggesting that children may have played a major role in the propagation of the virus. A comprehensive detailed analysis of the attack rates among children as compared with their contacts in various settings is of great importance for understanding their unique role in influenza pandemics.

METHODOLOGY/PRINCIPAL FINDINGS

We searched MEDLINE (PubMed) and Embase for published studies reporting outbreak investigations with direct measurements of attack rates of the 2009 pandemic H1N1 influenza A among children, and quantified how these compare with those of their contacts. We identified 50 articles suitable for review, which reported school, household, travel and social events. The selected reports and our meta-analysis indicated that children had significantly higher attack rates as compared to adults, and that this phenomenon was observed for both virologically confirmed and clinical cases, in various settings and locations around the world. The review also provided insight into some characteristics of transmission between children and their contacts in the various settings.

CONCLUSION/SIGNIFICANCE

The consistently higher attack rates of the 2009 pandemic H1N1 influenza A among children, as compared to adults, as well as the magnitude of the difference is important for understanding the contribution of children to disease burden, for implementation of mitigation strategies directed towards children, as well as more precise mathematical modeling and simulation of future influenza pandemics.

School closure as an influenza mitigation strategy: how variations in legal authority and plan criteria can alter the impact

Background

States’ pandemic influenza plans and school closure statutes are intended to guide state and local officials, but most faced a great deal of uncertainty during the 2009 influenza H1N1 epidemic. Questions remained about whether, when, and for how long to close schools and about which agencies and officials had legal authority over school closures.

Methods

This study began with analysis of states’ school-closure statutes and pandemic influenza plans to identify the variations among them. An agent-based model of one state was used to represent as constants a population’s demographics, commuting patterns, work and school attendance, and community mixing patterns while repeated simulations explored the effects of variations in school closure authority, duration, closure thresholds, and reopening criteria.

Results

The results show no basis on which to justify statewide rather than school-specific or community-specific authority for school closures. Nor do these simulations offer evidence to require school closures promptly at the earliest stage of an epidemic. More important are criteria based on monitoring of local case incidence and on authority to sustain closure periods sufficiently to achieve epidemic mitigation.

Conclusions

This agent-based simulation suggests several ways to improve statutes and influenza plans. First, school closure should remain available to state and local authorities as an influenza mitigation strategy. Second, influenza plans need not necessarily specify the threshold for school closures but should clearly define provisions for early and ongoing local monitoring. Finally, school closure authority may be exercised at the statewide or local level, so long as decisions are informed by monitoring incidence in local communities and schools.

Dynamic modelling of costs and health consequences of school closure during an influenza pandemic

Background

The purpose of this article is to evaluate the cost-effectiveness of school closure during a potential influenza pandemic and to examine the trade-off between costs and health benefits for school closure involving different target groups and different closure durations.

Methods

We developed two models: a dynamic disease model capturing the spread of influenza and an economic model capturing the costs and benefits of school closure. Decisions were based on quality-adjusted life years gained using incremental cost-effectiveness ratios. The disease model is an age-structured SEIR compartmental model based on the population of Oslo. We studied the costs and benefits of school closure by varying the age targets (kindergarten, primary school, secondary school) and closure durations (1–10 weeks), given pandemics with basic reproductive number of 1.5, 2.0 or 2.5.

Results

The cost-effectiveness of school closure varies depending on the target group, duration and whether indirect costs are considered. Using a case fatality rate (CFR) of 0.1-0.2% and with current cost-effectiveness threshold for Norway, closing secondary school is the only cost-effective strategy, when indirect costs are included. The most cost-effective strategies would be closing secondary schools for 8 weeks if R₀=1.5, 6 weeks if R₀=2.0, and 4 weeks if R₀= 2.5. For severe pandemics with case fatality rates of 1-2%, similar to the Spanish flu, or when indirect costs are disregarded, the optimal strategy is closing kindergarten, primary and secondary school for extended periods of time. For a pandemic with 2009 H1N1 characteristics (mild severity and low transmissibility), closing schools would not be cost-effective, regardless of the age target of school children.

Conclusions

School closure has moderate impact on the epidemic’s scope, but the resulting disruption to society imposes a potentially great cost in terms of lost productivity from parents’ work absenteeism.

Simulating school closure policies for cost effective pandemic decision making

BACKGROUND

Around the globe, school closures were used sporadically to mitigate the 2009 H1N1 influenza pandemic. However, such closures can detrimentally impact economic and social life.

METHODS

Here, we couple a decision analytic approach with a mathematical model of influenza transmission to estimate the impact of school closures in terms of epidemiological and cost effectiveness. Our method assumes that the transmissibility and the severity of the disease are uncertain, and evaluates several closure and reopening strategies that cover a range of thresholds in school-aged prevalence (SAP) and closure durations.

RESULTS

Assuming a willingness to pay per quality adjusted life-year (QALY) threshold equal to the US per capita GDP ($46,000), we found that the cost effectiveness of these strategies is highly dependent on the severity and on a willingness to pay per QALY. For severe pandemics, the preferred strategy couples the earliest closure trigger (0.5% SAP) with the longest duration closure (24 weeks) considered. For milder pandemics, the preferred strategies also involve the earliest closure trigger, but are shorter duration (12 weeks for low transmission rates and variable length for high transmission rates).

CONCLUSIONS

These findings highlight the importance of obtaining early estimates of pandemic severity and provide guidance to public health decision-makers for effectively tailoring school closures strategies in response to a newly emergent influenza pandemic.

How the H1N1 influenza epidemic spread among university students in Japan: experience from Shinshu University

BACKGROUND

A worldwide outbreak of influenza A/H1N1 occurred in 2009. Little information is available regarding how the epidemic spread among young people, who composed the majority of individuals infected with this virus. We assessed the route of transmission of H1N1 among university students at Shinshu University, Japan.

METHODS

A total of 11,424 students were monitored between August 2009 and March 2010, and those who were diagnosed with confirmed, probable, or suspected H1N1 at a hospital or clinic were registered based on self-report to the university. Data including date of onset and suspected infection route were collected from the affected patients.

RESULTS

Of the 11,424 students, 1,016 (8.9%) were infected with H1N1. In most infected students, the suspected transmission route was associated with club activity, followed by close contact with friends and through lectures or laboratory work. After suspension of activity by clubs with more than 2 infected members, the number of infected individuals decreased.

CONCLUSION

H1N1 influenza spread in the university through specific routes, including club activity, close contact with friends, and lectures or laboratory work. During future outbreaks of influenza, interventions to reduce transmission through these routes may be effective infection control strategies in university students.

Two years after pandemic influenza A/2009/H1N1: what have we learned?

The world had been anticipating another influenza pandemic since the last one in 1968. The pandemic influenza A H1N1 2009 virus (A/2009/H1N1) finally arrived, causing the first pandemic influenza of the new millennium, which has affected over 214 countries and caused over 18,449 deaths. Because of the persistent threat from the A/H5N1 virus since 1997 and the outbreak of the severe acute respiratory syndrome (SARS) coronavirus in 2003, medical and scientific communities have been more prepared in mindset and infrastructure. This preparedness has allowed for rapid and effective research on the epidemiological, clinical, pathological, immunological, virological, and other basic scientific aspects of the disease, with impacts on its control. A PubMed search using the keywords "pandemic influenza virus H1N1 2009" yielded over 2,500 publications, which markedly exceeded the number published on previous pandemics. Only representative works with relevance to clinical microbiology and infectious diseases are reviewed in this article. A significant increase in the understanding of this virus and the disease within such a short amount of time has allowed for the timely development of diagnostic tests, treatments, and preventive measures. These findings could prove useful for future randomized controlled clinical trials and the epidemiological control of future pandemics.

School absenteeism as an adjunct surveillance indicator: experience during the second wave of the 2009 H1N1 pandemic in Quebec, Canada

Background

A school absenteeism surveillance system was implemented in the province of Quebec, Canada during the second wave of the 2009 H1N1pandemic. This paper compares this surveillance approach with other available indicators.

Method

All (3432) elementary and high schools from Quebec were included. Each school was required to report through a web-based system any day where the proportion of students absent for influenza-like illness (ILI) exceeded 10% of current school enrolment.

Results

Between October 18 and December 12 2009, 35.6% of all schools met the 10% absenteeism threshold. This proportion was greater in elementary compared to high schools (40% vs 19%) and in smaller compared to larger schools (44% vs 22%). The maximum absenteeism rate was reached the first day of reporting or within the next two days in 55% and 31% of schools respectively. The first reports and subsequent peak in school absenteeism provincially preceded the peak in paediatric hospitalization by two and one weeks, respectively. Trends in school surveillance otherwise mirrored other indicators.

Conclusion

During a pandemic, school outbreak surveillance based on a 10% threshold appears insufficient to trigger timely intervention within a given affected school. However, school surveillance appears well-correlated and slightly anticipatory compared to other population indicators. As such, school absenteeism warrants further evaluation as an adjunct surveillance indicator whose overall utility will depend upon specified objectives, and other existing capacity for monitoring and response.

The effect of school dismissal on rates of influenza-like illness in New York City schools during the spring 2009 novel H1N1 outbreak

BACKGROUND

The effects of individual school dismissal on influenza transmission have not been well studied. During the spring 2009 novel H1N1 outbreak, New York City implemented an individual school dismissal policy intended to limit influenza transmission at schools with high rates of influenza-like illness (ILI).

METHODS

Active disease surveillance data collected by the New York City Health Department on rates of ILI in schools were used to evaluate the impact. Sixty-four schools that met the Health Department's criteria for considering dismissal were included in the analysis. Twenty-four schools that met criteria subsequently dismissed all classes for approximately 1 school week. A regression model was fit to these data, estimating the effect of school dismissal on rates of in-school ILI following reconvening, adjusting for potential confounders.

RESULTS

The model estimated that, on average, school dismissal reduced the rate of ILI by 7.1% over the entire average outbreak period. However, a large proportion of in-school ILI occurred before dismissal criteria were met. A separate model estimated that school absenteeism rates were not significantly affected by dismissal.

CONCLUSION

Results suggest that individual school dismissal could be considered in situations where schools have a disproportionate number of high-risk students or may be unable to implement recommended preventive or infection control measures. Future work should focus on developing more sensitive indicators of early outbreak detection in schools and evaluating the impact of school dismissal on community transmission.

Controlling the spread of disease in schools

Pandemic and seasonal infectious diseases such as influenza may have serious negative health and economic consequences. Certain non-pharmaceutical intervention strategies--including school closures--can be implemented rapidly as a first line of defense against spread. Such interventions attempt to reduce the effective number of contacts between individuals within a community; yet the efficacy of closing schools to reduce disease transmission is unclear, and closures certainly result in significant economic impacts for caregivers who must stay at home to care for their children. Using individual-based computer simulation models to trace contacts among schoolchildren within a stereotypical school setting, we show how alternative school-based disease interventions have great potential to be as effective as traditional school closures without the corresponding loss of workforce and economic impacts.

Cost-effective strategies for mitigating a future influenza pandemic with H1N1 2009 characteristics

BACKGROUND

We performed an analysis of the cost-effectiveness of pandemic intervention strategies using a detailed, individual-based simulation model of a community in Australia together with health outcome data of infected individuals gathered during 2009-2010. The aim was to examine the cost-effectiveness of a range of interventions to determine the most cost-effective strategies suitable for a future pandemic with H1N1 2009 characteristics.

METHODOLOGY/PRINCIPAL FINDINGS

Using transmissibility, age-stratified attack rates and health outcomes determined from H1N1 2009 data, we determined that the most cost-effective strategies involved treatment and household prophylaxis using antiviral drugs combined with limited duration school closure, with costs ranging from $632 to $777 per case prevented. When school closure was used as a sole intervention we found the use of limited duration school closure to be significantly more cost-effective compared to continuous school closure, a result with applicability to countries with limited access to antiviral drugs. Other social distancing strategies, such as reduced workplace attendance, were found to be costly due to productivity losses.

CONCLUSION

The mild severity (low hospitalisation and case fatality rates) and low transmissibility of H1N1 2009 meant that health treatment costs were dominated by the higher productivity losses arising from workplace absence due to illness and childcare requirements following school closure. Further analysis for higher transmissibility but with the same, mild severity had no effect on the overall findings.

Spatial and temporal characteristics of the 2009 A/H1N1 influenza pandemic in Peru

BACKGROUND

Highly refined surveillance data on the 2009 A/H1N1 influenza pandemic are crucial to quantify the spatial and temporal characteristics of the pandemic. There is little information about the spatial-temporal dynamics of pandemic influenza in South America. Here we provide a quantitative description of the age-specific morbidity pandemic patterns across administrative areas of Peru.

METHODS

We used daily cases of influenza-like-illness, tests for A/H1N1 influenza virus infections, and laboratory-confirmed A/H1N1 influenza cases reported to the epidemiological surveillance system of Peru's Ministry of Health from May 1 to December 31, 2009. We analyzed the geographic spread of the pandemic waves and their association with the winter school vacation period, demographic factors, and absolute humidity. We also estimated the reproduction number and quantified the association between the winter school vacation period and the age distribution of cases.

RESULTS

The national pandemic curve revealed a bimodal winter pandemic wave, with the first peak limited to school age children in the Lima metropolitan area, and the second peak more geographically widespread. The reproduction number was estimated at 1.6-2.2 for the Lima metropolitan area and 1.3-1.5 in the rest of Peru. We found a significant association between the timing of the school vacation period and changes in the age distribution of cases, while earlier pandemic onset was correlated with large population size. By contrast there was no association between pandemic dynamics and absolute humidity.

CONCLUSIONS

Our results indicate substantial spatial variation in pandemic patterns across Peru, with two pandemic waves of varying timing and impact by age and region. Moreover, the Peru data suggest a hierarchical transmission pattern of pandemic influenza A/H1N1 driven by large population centers. The higher reproduction number of the first pandemic wave could be explained by high contact rates among school-age children, the age group most affected during this early wave.

Controlling epidemic viral infection

PURPOSE OF THE REVIEW

Due to their different virulence and infectivity, both severe acute respiratory syndrome (SARS) and H1N1 09 revealed different strengths and weaknesses in our ability to contain new viral threats over the past decade. This review focuses on recent literature around attempts to contain the impact of these two viral epidemics that have refined our approach for the future.

RECENT FINDINGS

Attempts to contain emerging epidemics at the site of origin have so far failed, in part due to resourcing of surveillance. H1N1 09 revealed major problems with rigid pandemic planning and the need for much greater flexibility. Popular attempts to prevent international spread of pandemics have minimal efficacy. Availability of rapid diagnostic tests is critical to optimally managing epidemics and was a major problem with H1N1 09. Healthcare institutions have emerged as a major source of infection.

SUMMARY

The experience with H1N1 09 and SARS has been very useful in informing us of the strengths and weaknesses of our current approach to emerging epidemics. Key messages are a need for improved surveillance, more flexible planning, improved diagnostic testing and retaining a focus on basic hygiene measures.

The impact of case diagnosis coverage and diagnosis delays on the effectiveness of antiviral strategies in mitigating pandemic influenza A/H1N1 2009

BACKGROUND

Neuraminidase inhibitors were used to reduce the transmission of pandemic influenza A/H1N1 2009 at the early stages of the 2009/2010 pandemic. Policies for diagnosis of influenza for the purposes of antiviral intervention differed markedly between and within countries, leading to differences in the timing and scale of antiviral usage.

METHODOLOGY/PRINCIPAL FINDINGS

The impact of the percentage of symptomatic infected individuals who were diagnosed, and of delays to diagnosis, for three antiviral intervention strategies (each with and without school closure) were determined using a simulation model of an Australian community. Epidemic characteristics were based on actual data from the A/H1N1 2009 pandemic including reproduction number, serial interval and age-specific infection rate profile. In the absence of intervention an illness attack rate (AR) of 24.5% was determined from an estimated R(0) of 1.5; this was reduced to 21%, 16.5% or 13% by treatment-only, treatment plus household prophylaxis, or treatment plus household plus extended prophylaxis antiviral interventions respectively, assuming that diagnosis occurred 24 hours after symptoms arose and that 50% of symptomatic cases were diagnosed. If diagnosis occurred without delay, ARs decreased to 17%, 12.2% or 8.8% respectively. If 90% of symptomatic cases were diagnosed (with a 24 hour delay), ARs decreased to 17.8%, 11.1% and 7.6%, respectively.

CONCLUSION

The ability to rapidly diagnose symptomatic cases and to diagnose a high proportion of cases was shown to improve the effectiveness of all three antiviral strategies. For epidemics with R(0)< = 1.5 our results suggest that when the case diagnosis coverage exceeds ∼70% the size of the antiviral stockpile required to implement the extended prophylactic strategy decreases. The addition of at least four weeks of school closure was found to further reduce cumulative and peak attack rates and the size of the required antiviral stockpile.