Assessment of intervention strategies against a novel influenza epidemic using an individual-based model

How Did the Dengue Fever Outbreak Progress in Yoyogi Park, Tokyo, in 2014?-Evaluation Based on a Mathematical Model

OBJECTIVES

In the summer of 2014, an outbreak of autochthonous dengue fever occurred in Yoyogi Park and its vicinity, Tokyo, Japan. In this study, we investigated how the dengue fever outbreak progressed in Yoyogi Park using a mathematical model.

METHODS

This study was limited to the transmission of the dengue virus in Yoyogi Park and its vicinity. We estimated the distributions of the intrinsic incubation period and infection dates on the basis of epidemiological information on the dengue outbreak in 2014. We searched for an assumption that satisfactorily explains the outbreak in 2014 using rough estimates of secondary and tertiary infection cases. We constructed a mathematical model for the transmission of the dengue virus between humans and Aedes albopictus.

RESULTS

We carried out 1,000-trial stochastic simulations for all combinations of three kinds of assumption about Ae. albopictus and asymptomatic infection with each of three levels. Simulation results showed that the scale of the outbreak was markedly affected by the daily survival rate of Ae. albopictus. The outbreak involved a small number of secondary infection cases, reached a peak at tertiary infection, and transformed to termination at the fourth infection. Under some assumptions, the daily progress of onset cases was within a range between the 1st-3rd quartiles of 1,000 trials for 87% of dates and within a range between the minimum and maximum for all dates.

CONCLUSIONS

It is important to execute plans to detect asymptomatic cases and reduce the survival rate of Ae. albopictus to prevent the spread of tertiary infections unless an outbreak is suppressed at the secondary infection stage.

Dynamic modelling of strategies for the control of acute haemorrhagic conjunctivitis outbreaks in schools in Changsha, China (2004–2015)

Outbreaks of acute haemorrhagic conjunctivitis (AHC) – a rapidly progressing and highly contagious infection – often occur in schools during summer and autumn. We used dynamic modelling to evaluate the efficacy of interventions to control AHC outbreaks in schools. A susceptible-infected-recovered (SIR) model was built to simulate AHC outbreaks in Chinese schools, with isolation or school closure added into the model. We used outbreak data from the period 2004–2015 in our models to estimate the effective reproduction number and assess the efficacy of interventions. The median effective reproduction number (uncontrolled) of AHC outbreaks was 7·00 (range 1·77–25·87). The median effective reproduction number (controlled) of AHC outbreaks was 0·16 (range 0·00–2·28). Intervention efficacy is affected by the timing of isolation; earlier isolation is associated with a lower morbidity peak and smaller total attack rate (TAR). School closures were not effective; TARs were almost 100% and did not change even when different school closure durations were adopted. Isolation and school closure as a combined intervention strategy was used to simulate outbreak control, but the efficacy was the same as isolation alone. An isolation programme could be an effective primary intervention during AHC outbreaks in schools. However, school closure is not recommended.

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.

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.

Simulations to compare efficacies of tetravalent dengue vaccines and mosquito vector control

SUMMARY

Infection with dengue, the most prevalent mosquito-borne virus, manifests as dengue fever (DF) or the more fatal dengue haemorrhagic fever (DHF). DHF occurs mainly when an individual who has acquired antibodies to one serotype is inoculated with another serotype. It was reported that mosquito control may have increased the incidence of DF and DHF due to age-dependency in manifesting these illnesses or an immunological mechanism. Tetravalent dengue vaccine is currently being tested in clinical trials. However, seroconversions to all four serotypes were achieved only after three doses. Therefore, vaccines may predispose vaccinees to the risk of developing DHF in future infections. This study employed an individual-based computer simulation, to emulate mosquito control and vaccination, incorporating seroconversion rates reported from actual clinical trials. It was found that mosquito control alone would have increased incidence of DF and DHF in areas of high mosquito density. A vaccination programme with very high coverage, even with a vaccine of suboptimal seroconversion rates, attenuated possible surges in the incidence of DF and DHF which would have been caused by insufficient reduction in mosquito abundance. DHF cases attributable to vaccine-derived enhancement were fewer than DHF cases prevented by a vaccine with considerably high (although not perfect) seroconversion rates. These predictions may justify vaccination programmes, at least in areas of high mosquito abundance. In such areas, mosquito control programmes should be conducted only after the vaccination programme with a high coverage has been initiated.

Trends in parameterization, economics and host behaviour in influenza pandemic modelling: a review and reporting protocol

BACKGROUND

The volume of influenza pandemic modelling studies has increased dramatically in the last decade. Many models incorporate now sophisticated parameterization and validation techniques, economic analyses and the behaviour of individuals.

METHODS

We reviewed trends in these aspects in models for influenza pandemic preparedness that aimed to generate policy insights for epidemic management and were published from 2000 to September 2011, i.e. before and after the 2009 pandemic.

RESULTS

We find that many influenza pandemics models rely on parameters from previous modelling studies, models are rarely validated using observed data and are seldom applied to low-income countries. Mechanisms for international data sharing would be necessary to facilitate a wider adoption of model validation. The variety of modelling decisions makes it difficult to compare and evaluate models systematically.

CONCLUSIONS

We propose a model Characteristics, Construction, Parameterization and Validation aspects protocol (CCPV protocol) to contribute to the systematisation of the reporting of models with an emphasis on the incorporation of economic aspects and host behaviour. Model reporting, as already exists in many other fields of modelling, would increase confidence in model results, and transparency in their assessment and comparison.

[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.

Evaluation of vaccination strategies to suppress a novel influenza pandemic using an individual-based model

OBJECTIVES

In this study, we aimed to evaluate vaccination strategies with regard to the impact of prioritization, coverage, and a delay in the vaccination program against a novel influenza pandemic with high-level fatality equivalent to Spanish flu using an individual-based model (IBM). Vaccination is one of the main measures to prevent infection, a serious condition, or death.

METHODS

We constructed an IBM for the transmission of a novel influenza virus utilizing personal information on the basis of demographic data from Sapporo City, thereby resulting in a more realistic model. We designed simulations for scenarios along the guidelines of the Ministry of Health, Labour and Welfare of Japan, which requests the prioritization of vaccination of pregnant women and persons with underlying diseases, among whom influenza would cause higher fatality than among healthy persons, infants, or their parents, as well as school-aged and old-aged persons.

RESULTS

A vaccination program fully taking into account the ordered priority groups would more effectively reduce the number of deaths in the priority groups and also the total number of deaths in comparison with a program shortening the transition time to the next priority or a non-priority group. A delay in the vaccination program would lower the effectiveness of reducing the numbers of patients and deaths.

CONCLUSIONS

According to the simulation-based results, when vaccination programs scheduled on the basis of priority groups start 90 and 150 days after outbreak, the total numbers of patients would be reduced to one-third-one-half, and two-thirds, respectively, in comparison with baseline of no vaccination, which leads to the necessity to conduct a vaccination program as soon as possible.