Age-dependent estimates of the epidemiological impact of pandemic influenza (H1N1-2009) in Japan

Age-dependent final size equation to anticipate mortality impact of COVID-19 in China

Before reopening society in December 2022, China had not achieved sufficiently high vaccination coverage among people aged 80 years and older, who are vulnerable to severe infection and death owing to COVID-19. Suddenly ending the zero-COVID policy was anticipated to lead to substantial mortality. To investigate the mortality impact of COVID-19, we devised an age-dependent transmission model to derive a final size equation, permitting calculation of the expected cumulative incidence. Using an age-specific contact matrix and published estimates of vaccine effectiveness, final size was computed as a function of the basic reproduction number, R0. We also examined hypothetical scenarios in which third-dose vaccination coverage was increased in advance of the epidemic, and also in which mRNA vaccine was used instead of inactivated vaccines. Without additional vaccination, the final size model indicated that a total of 1.4 million deaths (half of which were among people aged 80 years and older) were anticipated with an assumed R0 of 3.4. A 10% increase in third-dose coverage would prevent 30,948, 24,106, and 16,367 deaths, with an assumed second-dose effectiveness of 0%, 10%, and 20%, respectively. With mRNA vaccine, the mortality impact would have been reduced to 1.1 million deaths. The experience of reopening in China indicates the critical importance of balancing pharmaceutical and non-pharmaceutical interventions. Ensuring sufficiently high vaccination coverage is vital in advance of policy changes.

Adult influenza epidemic is associated with out-of-hospital cardiac arrest: From the All-Japan Utstein Registry, a prospective, nationwide, population-based, observational registry

It has been reported that influenza infection is associated with out-of-hospital cardiac arrest of cardiac origin (OHCA-CA). However, the association between OHCA-CA and influenza epidemics in adults has not been well investigated.We analyzed data from the All-Japan Utstein Registry, a prospective, nationwide, population-based, observational study, regarding OHCA-CA cases and the Infectious Diseases Weekly Report for influenza cases: 17,710 OHCA-CA cases and 764,808 influenza cases were recorded between 2005 and 2015 in Fukuoka, Japan. The weekly average number of OHCA-CA cases was positively associated with the number of patients with influenza infection (r = 0.70, P < .0001). To eliminate the effects of season and age, we investigated only adults in winter. The weekly number of OHCA-CA cases was positively associated with the number of patients with influenza infection in weeks when there was a high frequency of influenza infection in adults (r = 0.36, P = .006), but not in weeks with a medium (r = 0.26, P = .05) or low frequency of influenza infection (r = 0.003, P = 1.0). In weeks during which there was a high frequency of influenza infection, the weekly number of OHCA-CA cases was positively associated with the number of influenza infections in males (r = 0.37, P = .006), but not females (r = 0.18, P = .2).The number of OHCA-CA cases was positively associated with the number of influenza infections in adult males during weeks in which there was a high frequency of influenza infections. To help prevent OHCA-CA in males, it might be beneficial to announce influenza epidemics specifically in adults, in addition to all ages.

Rate of diagnosed seasonal influenza in children with influenza-like illness: A cross-sectional study

Introduction

Although influenza surveillance systems have been used to monitor influenza epidemics, these systems generally evaluate diagnostic information obtained from medical institutions and they do not include patients who have not been examined. In contrast, community based epidemiological studies target people with influenza-like illness (ILI) that self-reported influenza-like symptoms whether they have medical examinations or not. Because the criteria for influenza surveillance systems and ILI differ, there is a gap between them. The purpose of this study was to clarify this gap using school-based survey data.

Methods

Questionnaires about both ILI and the influenza diagnosis history during the 2018/19 season were administered to the guardians of 11,684 elementary schoolchildren in a single city in Japan. Based on their responses, a Bayesian model was constructed to estimate the probability of infection, ILI onset, and diagnosis at medical institutions.

Results

Responses were obtained from guardians of 10,309 children (88.2%). Of these, 3,380 children (32.8%) had experienced ILI, with 2,380 (23.1%) diagnosed as influenza at a medical institution. Bayesian estimation showed that the probability of influenza cases being diagnosed among ILI symptomatic children was 70% (95% credible interval, 69–71%). Of the infected children, 5% were without ILI symptoms, with 11% of these patients diagnosed with influenza.

Conclusions

This epidemiological study clarified the proportion gap between ILI and influenza diagnosis among schoolchildren. These results may help to establish epidemic control measures and secure sufficient medical resources.

A method for estimating the transmissibility of influenza using serial cross-sectional seroepidemiological data

BACKGROUND

Seroepidemiological surveillance data has been demonstrated to be useful for estimating the cumulative incidence of influenza, and measures the difference between pre- and post-epidemic seropositive fractions. Despite this, such studies relied on a chosen cut-off value for seropositivity. The aim of the present study is to develop a method to analyze distributions of serial cross-sectional seroepidemiological surveillance datasets using an epidemiological model so that the transmission potential can be estimated without imposing a cut-off value.

METHODS

A mathematical model of influenza transmission with a discrete antibody titer level was constructed. The final size equation for pre- and post-epidemic titer levels was derived. Subsequently, using the estimated distribution of the dilution increase caused by infection and the measurement error distribution, the model parameters were optimized using the maximum likelihood method. A bootstrap-based confidence interval calculation and sensitivity analysis were also performed.

RESULTS

Without imposing a cut-off value, the cumulative incidence was quantified, thereby yielding an estimate of the basic reproduction number. For the purpose of exposition, the proposed method was applied to influenza A/Victoria/3/75(H3N2) data, and serological data between 1975 and 1976 were compared. The estimated reproduction number was greater than that using the cut-off value of the hemagglutination inhibition level with titer level 20 (dilution 1:20) or above to define positives.

CONCLUSION

The proposed method without a cut-off value offers an unbiased approach to estimating the cumulative incidence along with the reproduction number. If a cut-off value is required, the results imply that titer level 20 or above may better represent a reasonable cut-off value for calculating the incidence, but it could underestimate the basic reproduction number.

Accounting for cross-immunity can improve forecast accuracy during influenza epidemics

Previous exposure to influenza viruses confers cross-immunity against future infections with related strains. However, this is not always accounted for explicitly in mathematical models used for forecasting during influenza outbreaks. We show that, if an influenza outbreak is due to a strain that is similar to one that has emerged previously, then accounting for cross-immunity explicitly can improve the accuracy of real-time forecasts. To do this, we consider two infectious disease outbreak forecasting models. In the first (the "1-group model"), all individuals are assumed to be identical and cross-immunity is not accounted for. In the second (the "2-group model"), individuals who have previously been infected by a related strain are assumed to be less likely to experience severe disease, and therefore recover more quickly, than immunologically naive individuals. We fit both models to estimated case notification data (including symptomatic individuals as well as laboratory-confirmed cases) from Japan from the 2009 H1N1 influenza pandemic, and then generate synthetic data for a future outbreak by assuming that the 2-group model represents the epidemiology of influenza infections more accurately. We use the 1-group model (as well as the 2-group model for comparison) to generate forecasts that would be obtained in real-time as the future outbreak is ongoing, using parameter values estimated from the 2009 epidemic as informative priors, motivated by the fact that without using prior information from 2009, the forecasts are highly uncertain. In the scenario that we consider, the 1-group model only produces accurate outbreak forecasts once the peak of the epidemic has passed, even when the values of important epidemiological parameters such as the lengths of the mean incubation and infectious periods are known exactly. As a result, it is necessary to use the more epidemiologically realistic 2-group model to generate accurate forecasts. Accounting for cross-immunity driven by exposures in previous outbreaks explicitly is expected to improve the accuracy of epidemiological modelling forecasts during influenza outbreaks.

Quantifying the causal impact of funding bedside antigen testing on the incidence of respiratory syncytial virus infection in Japan: a difference-in-differences study

BACKGROUND

To estimate the causal impact of a change in the national health insurance policy to cover the cost of respiratory syncytial virus (RSV) antigen testing on the incidence of RSV infection by age-groups, we analyzed the sentinel datasets of RSV infection in Japan from 2009-2017.

METHODS

The causal effect of introducing RSV antigen testing on increasing the reported incidence of RSV infection was quantified using a quasi-experimental difference-in-differences (DID) design and influenza as a control group.

RESULTS

Examining sentinel and virus surveillance datasets, only clinically mild cases have selectively increased from 2012/13. The median estimated incidences of influenza and RSV infection among children aged 0-4 years, the age group that dominates cases of both diseases, were estimated at 5,607 and 1,761 per 100,000 individuals, respectively. Exploring sentinel datasets, only the incidence of RSV infection abruptly increased from 2012/13. Using an age-dependent model, the estimated causal effect on the increase in RSV annual incidence was greatest among children aged 5-9 years, with an estimated additional 1,912 cases per 100,000 individuals (95% CI: 418-3,406).

CONCLUSIONS

Owing to financial support of bedside RSV antigen testing from 2012/13, the incidence of RSV infection has been elevated. The recent increasing trend in RSV infection incidence should not be directly perceived as an increase in natural infections with RSV.

Fine-scale family structure shapes influenza transmission risk in households: Insights from primary schools in Matsumoto city, 2014/15

Households are important settings for the transmission of seasonal influenza. Previous studies found that the per-person risk of within-household transmission decreases with household size. However, more detailed heterogeneities driven by household composition and contact patterns have not been studied. We employed a mathematical model that accounts for infections both from outside and within the household. The model was applied to citywide primary school seasonal influenza surveillance and household surveys from 10,486 students during the 2014/15 season in Matsumoto city, Japan. We compared a range of models to estimate the structure of household transmission and found that familial relationship and household composition strongly influenced the transmission patterns of seasonal influenza in households. Children had a substantially high risk of infection from outside the household (up to 20%) compared with adults (1–3%). Intense transmission was observed within-generation (between children/parents/grandparents) and also between mother and child, with transmission risks typically ranging from 5–20% depending on the transmission route and household composition. Children were identified as the largest source of secondary transmission, with family structure influencing infection risk.

We characterised detailed heterogeneity in household transmission patterns of influenza by applying a mathematical model to citywide primary school influenza survey data from 10,486 students in Matsumoto city, Japan, one of the largest-scale household surveys on seasonal influenza. Children were identified as the largest source of secondary transmission, with family structure influencing infection risk. This suggests that vaccinating children would have stronger secondary effects on transmission than would be assumed without taking into account transmission patterns within the household.

Modelling the optimal target age group for seasonal influenza vaccination in Japan

BACKGROUND

In Japan, the current influenza vaccination programme is targeting older individuals. On the other hand, epidemics of influenza are likely to be mainly driven by children. In this study, we consider the most cost-effective target age group for a seasonal influenza vaccination programme in Japan.

METHODS

We constructed a deterministic compartmental Susceptible-Exposed-Infectious-Recovered (SEIR) model with data from the 2012/13 to 2014/15 influenza seasons in Japan. Bayesian inference with Markov Chain Monte Carlo method was used for parameter estimation. Cost-effectiveness analyses were conducted from public health care payer's perspective.

RESULTS

A scenario targeting children under 15 was expected to reduce the number of cases 6,382,345 compared to the current strategy. A scenario targeting elderly population (age over 49 years) was expected to reduce the number of cases 693,206. The children targeted scenario demonstrated negative ICER (incremental cost-effectiveness ratio) value. On the other hand, elderly targeted scenario demonstrated higher ICER value than the willingness to pay (50,000 USD/QALY).

CONCLUSIONS

A vaccination programme which targets children under 15 is predicted to have much larger epidemiological impact than those targeting elderly.

Modelling a Supplementary Vaccination Program of Rubella Using the 2012⁻2013 Epidemic Data in Japan

From 2012-2013, Japan experienced a major epidemic of rubella, involving a total of 12,614 rubella cases and 45 confirmed cases of congenital rubella syndrome (CRS). One of the contributory factors in this outbreak may have been that the majority of adult males remained unvaccinated. To plan for a supplementary immunization program (SIP) to elevate the herd immunity level, it is critical to determine the required amount of vaccine and identify the target age groups among males for the SIP. The present study aimed to answer these policy questions, employing a mathematical model and analyzing epidemiological datasets from 2012-2013. Our model allowed us to reconstruct the age- and sex-dependent transmission patterns, and the effective reproduction number during the exponential growth phase in 2013 was estimated to be 1.5. The computed next-generation matrix indicated that vaccinating adult males aged from 20-49 years in 2013, using at least 17 million doses, was considered essential to prevent a major epidemic in the future. The proposed model also indicated that, even with smaller doses of vaccine, the SIP in adult males could lead to a substantial reduction in the incidence of rubella, as well as CRS. Importantly, the present study endorses a substantial background risk of observing another major epidemic from 2018-2019, in which cases may be dominated by adult males aged from 25-54 years, that is, our identified age groups plus a five-year time lag from 2013 to 2018.

Quantifying heterogeneous contact patterns in Japan: a social contact survey

BACKGROUND

Social contact surveys can greatly help in quantifying the heterogeneous patterns of infectious disease transmission. The present study aimed to conduct a contact survey in Japan, offering estimates of contact by age and location and validating a social contact matrix using a seroepidemiological dataset of influenza.

METHODS

An internet-based questionnaire survey was conducted, covering all 47 prefectures in Japan and including a total of 1476 households. The social contact matrix was quantified assuming reciprocity and using the maximum likelihood method. By imposing several parametric assumptions for the next-generation matrix, the empirical seroepidemiological data of influenza A (H1N1) 2009 was analysed and we estimated the basic reproduction number, R0.

RESULTS

In total, the reported number of contacts on weekdays was 10,682 whereas that on weekend days was 8867. Strong age-dependent assortativity was identified. Forty percent of weekday contacts took place at schools or workplaces, but that declined to 14% on weekends. Accounting for the age-dependent heterogeneity with the known social contact matrix, the minimum value of the Akaike information criterion was obtained and R0 was estimated at 1.45 (95% confidence interval: 1.42, 1.49).

CONCLUSIONS

Survey datasets will be useful for parameterizing the heterogeneous transmission model of various directly transmitted infectious diseases in Japan. Age-dependent assortativity, especially among children, along with numerous contacts in school settings on weekdays implies the potential effectiveness of school closure.

Real-time quantification of the next-generation matrix and age-dependent forecasting of pandemic influenza H1N1 2009 in Japan

PURPOSE

To quantify the age-dependent next-generation matrix (NGM) for the 2009 H1N1 influenza pandemic and forecast the age-stratified cumulative incidence in Japan.

METHODS

Using a renewal equation model that describes the time evolution of the 2009 H1N1 influenza pandemic, we derive the likelihood function to estimate parameters of the NGM and reporting coverage. Comparing the Akaike Information Criterion of models using empirically observed data from the 2009 pandemic in Gifu, Japan, we excluded redundant parameters and identified the three best models that were parameterized in different ways.

RESULTS

The initial proportions of susceptible populations were suggested as redundant information to be inferred. The three models selected successfully captured the order of the age-dependent cumulative incidence. We found that the time required for reliable estimation of age-dependent cumulative incidence was at least 180 days.

CONCLUSIONS

To forecast the age-dependent cumulative incidence reliably following the estimation of the NGM and reporting coverage, we need empirically observed data for more than 5 months from the start of the epidemic, which is likely to be after the peak. To increase the practical efficacy in forecasting the cumulative incidence, additional data and approaches are required.

Investigating the immunizing effect of the rubella epidemic in Japan, 2012-14

OBJECTIVES

A rubella epidemic occurred in Japan from 2012-14, involving more than 15,000 cases. The present study aimed to estimate the immunizing effect of the epidemic, analyzing seroepidemiological data that were collected over time and age.

METHODS

Annual nationwide cross-sectional surveys were conducted from July to September, collecting serum from at least 5,400 individuals. The proportions seropositive were estimated before (2012), during (2013) and after (2014) the epidemic.

RESULTS

While the cases were mainly seen among men aged from 30-49 years, no significant increase was observed in the proportion seropositive in the corresponding age group. Even after the epidemic, age-standardized proportion seropositive of the total population remained 79.3% (95% confidence interval (CI): 75.2, 83.4) and that among males was as small as 76.7% (95% CI: 73.8, 79.6).

CONCLUSIONS

Susceptible pockets remain in Japan, exposing the country to risk of additional rubella epidemics.

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).

Modeling the obesity epidemic: social contagion and its implications for control

Background

As an obesity epidemic has grown worldwide, a variety of intervention programs have been considered, but a scientific approach to comparatively assessing the control programs has still to be considered. The present study aims to describe an obesity epidemic by employing a simple mathematical model that accounts for both social contagion and non-contagious hazards of obesity, thereby comparing the effectiveness of different types of interventions.

Methods

An epidemiological model is devised to describe the time- and age-dependent risk of obesity, the hazard of which is dealt with as both dependent on and independent of obesity prevalence, and parameterizing the model using empirically observed data. The equilibrium prevalence is investigated as our epidemiological outcome, assessing its sensitivity to different parameters that regulate the impact of intervention programs and qualitatively comparing the effectiveness. We compare the effectiveness of different types of interventions, including those directed to never-obese individuals (i.e. primary prevention) and toward obese and ex-obese individuals (i.e. secondary prevention).

Results

The optimal choice of intervention programs considerably varies with the transmission coefficient of obesity, and a limited transmissibility led us to favour preventing weight gain among never-obese individuals. An abrupt decline in the prevalence is expected when the hazards of obesity through contagious and non-contagious routes fall into a particular parameter space, with a high sensitivity to the transmission potential of obesity from person to person. When a combination of two control strategies can be selected, primary and secondary preventions yielded similar population impacts and the superiority of the effectiveness depends on the strength of the interventions at an individual level.

Conclusions

The optimality of intervention programs depends on the contagiousness of obesity. Filling associated data gaps of obesity transmission would help systematically understand the epidemiological dynamics and consider required control programs.