Using Serology to Anticipate Measles Post-honeymoon Period Outbreaks.

Measles vaccination is a public health 'best buy', with the highest cost of illness averted of any vaccine-preventable disease (Ozawa et al., Bull. WHO 2017;95:629). In recent decades, substantial reductions have been made in the number of measles cases, with an estimated 20 million deaths averted from 2000 to 2017 (Dabbagh et al., MMWR 2018;67:1323). Yet, an important feature of epidemic dynamics is that large outbreaks can occur following years of apparently successful control (Mclean et al., Epidemiol. Infect. 1988;100:419-442). Such 'post-honeymoon period' outbreaks are a result of the nonlinear dynamics of epidemics (Mclean et al., Epidemiol. Infect. 1988;100:419-442). Anticipating post-honeymoon outbreaks could lead to substantial gains in public health, helping to guide the timing, age-range, and location of catch-up vaccination campaigns (Grais et al., J. Roy. Soc. Interface 2008003B6:67-74). Theoretical conditions for such outbreaks are well understood for measles, yet the information required to make these calculations policy-relevant is largely lacking. We propose that a major extension of serological studies to directly characterize measles susceptibility is a high priority.

Improved inference of time-varying reproduction numbers during infectious disease outbreaks.

Accurate estimation of the parameters characterising infectious disease transmission is vital for optimising control interventions during epidemics. A valuable metric for assessing the current threat posed by an outbreak is the time-dependent reproduction number, i.e. the expected number of secondary cases caused by each infected individual. This quantity can be estimated using data on the numbers of observed new cases at successive times during an epidemic and the distribution of the serial interval (the time between symptomatic cases in a transmission chain). Some methods for estimating the reproduction number rely on pre-existing estimates of the serial interval distribution and assume that the entire outbreak is driven by local transmission. Here we show that accurate inference of current transmissibility, and the uncertainty associated with this estimate, requires: (i) up-to-date observations of the serial interval to be included, and; (ii) cases arising from local transmission to be distinguished from those imported from elsewhere. We demonstrate how pathogen transmissibility can be inferred appropriately using datasets from outbreaks of H1N1 influenza, Ebola virus disease and Middle-East Respiratory Syndrome. We present a tool for estimating the reproduction number in real-time during infectious disease outbreaks accurately, which is available as an R software package (EpiEstim 2.2). It is also accessible as an interactive, user-friendly online interface (EpiEstim App), permitting its use by non-specialists. Our tool is easy to apply for assessing the transmission potential, and hence informing control, during future outbreaks of a wide range of invading pathogens.

Reconstruction and prediction of viral disease epidemics.

A growing number of infectious pathogens are spreading among geographic regions. Some pathogens that were previously not considered to pose a general threat to human health have emerged at regional and global scales, such as Zika and Ebola Virus Disease. Other pathogens, such as yellow fever virus, were previously thought to be under control but have recently re-emerged, causing new challenges to public health organisations. A wide array of new modelling techniques, aided by increased computing capabilities, novel diagnostic tools, and the increased speed and availability of genomic sequencing allow researchers to identify new pathogens more rapidly, assess the likelihood of geographic spread, and quantify the speed of human-to-human transmission. Despite some initial successes in predicting the spread of acute viral infections, the practicalities and sustainability of such approaches will need to be evaluated in the context of public health responses.

Establishment and cryptic transmission of Zika virus in Brazil and the Americas.

Transmission of Zika virus (ZIKV) in the Americas was first confirmed in May 2015 in northeast Brazil. Brazil has had the highest number of reported ZIKV cases worldwide (more than 200,000 by 24 December 2016) and the most cases associated with microcephaly and other birth defects (2,366 confirmed by 31 December 2016). Since the initial detection of ZIKV in Brazil, more than 45 countries in the Americas have reported local ZIKV transmission, with 24 of these reporting severe ZIKV-associated disease. However, the origin and epidemic history of ZIKV in Brazil and the Americas remain poorly understood, despite the value of this information for interpreting observed trends in reported microcephaly. Here we address this issue by generating 54 complete or partial ZIKV genomes, mostly from Brazil, and reporting data generated by a mobile genomics laboratory that travelled across northeast Brazil in 2016. One sequence represents the earliest confirmed ZIKV infection in Brazil. Analyses of viral genomes with ecological and epidemiological data yield an estimate that ZIKV was present in northeast Brazil by February 2014 and is likely to have disseminated from there, nationally and internationally, before the first detection of ZIKV in the Americas. Estimated dates for the international spread of ZIKV from Brazil indicate the duration of pre-detection cryptic transmission in recipient regions. The role of northeast Brazil in the establishment of ZIKV in the Americas is further supported by geographic analysis of ZIKV transmission potential and by estimates of the basic reproduction number of the virus.

Quantifying homologous and heterologous antibody titre rises after influenza virus infection.

Most influenza virus infections are associated with mild disease. One approach to estimate the occurrence of influenza virus infections in individuals is via repeated measurement of humoral antibody titres. We used baseline and convalescent antibody titres measured by haemagglutination inhibition (HI) and viral neutralization (VN) assays against influenza A(H1N1), A(H3N2) and B viruses to investigate the characteristics of antibody rises following virologically confirmed influenza virus infections in participants in a community-based study. Multivariate models were fitted in a Bayesian framework to characterize the distribution of changes in antibody titres following influenza A virus infections. In 122 participants with PCR-confirmed influenza A virus infection, homologous antibody titres rose by geometric means of 1·2- to 10·2-fold after infection with A(H1N1), A(H3N2) and A(H1N1)pdm09. Significant cross-reactions were observed between A(H1N1)pdm09 and seasonal A(H1N1). Antibody titre rises for some subtypes and assays varied by age, receipt of oseltamivir treatment, and recent receipt of influenza vaccination. In conclusion, we provided a quantitative description of the mean and variation in rises in influenza virus antibody titres following influenza virus infection. The multivariate patterns in boosting of antibody titres following influenza virus infection could be taken into account to improve estimates of cumulative incidence of infection in seroepidemiological studies.

Estimating the transmissibility of H5N1 and the effect of vaccination in Indonesia.

The spread of H5N1 avian influenza continues to pose an economic burden and a public health risk worldwide. Despite this, estimates of the transmissibility of infection exist in only a handful of settings and vary considerably. Using final size methods and flock-level infection data from a field trial of mass vaccination, we obtained the first estimates of the transmissibility of infection between and within flocks in Indonesia. We also found that outbreaks in areas designated as vaccination zones were less transmissible than in non-vaccination zones. However, this reduction is only comparable with a limited degree of protective vaccination coverage. Quantifying the overall effect of vaccination in these zones remains challenging. However, this result would appear to imply that, although the interventions applied in vaccination zones were not sufficient to completely prevent transmission in all areas, when outbreaks occur, they are less transmissible than those in areas where vaccination was not applied. This could be either a direct or an indirect effect of vaccination. Given the dynamism of small-scale poultry production in Indonesia, more regular vaccination may be required to ensure that infection is fully controlled in vaccination zones.

Local and regional spread of chikungunya fever in the Americas.

Chikungunya fever (CHIKV), a viral disease transmitted by mosquitoes, is currently affecting several areas in the Caribbean. The vector is found in the Americas from southern Florida to Brazil, and the Caribbean is a highly connected region in terms of population movements. There is therefore a significant risk for the epidemic to quickly expand to a wide area in the Americas. Here, we describe the spread of CHIKV in the first three areas to report cases and between areas in the region. Local transmission of CHIKV in the Caribbean is very effective, the mean number of cases generated by a human case ranging from two to four. There is a strong spatial signature in the regional epidemic, with the risk of transmission between areas estimated to be inversely proportional to the distance rather than driven by air transportation. So far, this simple distance-based model has successfully predicted observed patterns of spread. The spatial structure allows ranking areas according to their risk of invasion. This characterisation may help national and international agencies to optimise resource allocation for monitoring and control and encourage areas with elevated risks to act.

Transmission scenarios for Middle East Respiratory Syndrome Coronavirus (MERS-CoV) and how to tell them apart.

Detection of human cases of Middle East Respiratory Syndrome Coronavirus (MERS-CoV) infection internationally is a global public health concern. Rigorous risk assessment is particularly challenging in a context where surveillance may be subject to under-ascertainment and a selection bias towards more severe cases. We would like to assess whether the virus is capable of causing widespread human epidemics, and whether self-sustaining transmission is already under way. Here we review possible transmission scenarios for MERS-CoV and their implications for risk assessment and control. We discuss how existing data, future investigations and analyses may help in reducing uncertainty and refining the public health risk assessment and present analytical approaches that allow robust assessment of epidemiological characteristics, even from partial and biased surveillance data. Finally, we urge that adequate data be collected on future cases to permit rigorous assessment of the transmission characteristics and severity of MERS-CoV, and the public health threat it may pose. Going beyond minimal case reporting, open international collaboration, under the guidance of the World Health Organization and the International Health Regulations, will impact on how this potential epidemic unfolds and prospects for control.

Virus shedding and environmental deposition of novel A (H1N1) pandemic influenza virus: interim findings.

BACKGROUND: The relative importance of different routes of influenza transmission, including the role of bioaerosols, and ability of masks and/or hand hygiene to prevent transmission, remains poorly understood. Current evidence suggests that infectious virus is not typically released from adults after 5 days of illness, however, little is known about the extent to which virus is deposited by infected individuals into the environment and whether deposited virus has the ability to infect new hosts. Further information about the deposition of viable influenza virus in the immediate vicinity of patients with pandemic influenza is fundamental to our understanding of the routes and mechanisms of transmission. OBJECTIVES: To collect data on patients infected with pandemic H1N1 2009 (swine flu). Primary objectives were to correlate the amount of virus detected in a patient's nose with that recovered from his/her immediate environment, and with symptom duration and severity. Secondary objectives were to describe virus shedding and duration according to major patient characteristics: adults versus children, and those with mild illness (community patients) versus those with more severe disease (hospitalised patients). METHODS: Adults and children, both in hospital and from the community, who had symptoms of pandemic H1N1 infection, were enrolled and visited every day during follow-up for a maximum of 12 days. Symptom data was collected and samples were taken, including nose swabs and swabs from surfaces and objects around patients. Samples of air were obtained using validated sampling equipment. The samples were tested for the presence of pandemic H1N1 virus, using polymerase chain reaction (PCR) to detect virus genome and an immunofluorescence technique to detect viable virus. RESULTS: Forty-three subjects were followed up, and 19 of them were subsequently proven to be infected with pandemic H1N1 virus. The median duration of virus shedding from the 19 infected cases was 6 days when detection was performed by PCR, and 3 days when detection was performed by a culture technique. Over 30% of cases remained potentially infectious for at least 5 days. Only 0.5% of all community and none of the hospital swabs taken revealed virus on surfaces. Five subjects had samples of the air around them collected and virus was detected by PCR from four; some of the air particles in which virus was detected were small enough to be inhaled and deposited deep in the lungs. LIMITATION: Small number of subjects recruited. CONCLUSIONS: The finding that over 30% of infected individuals have infectious virus in their noses for 5 days or more has infection control implications. The data suggest that contact transmission of pandemic influenza via fomites may be less important than previously thought, but transmission via bioaerosols at short range may be possible, meaning that high-level personal protective equipment may be needed by health-care workers when attending patients with pandemic influenza. Further work is being undertaken to consolidate these findings, as they have important potential implications for the protection of health-care workers and the formulation of advice to households, nationally and internationally.

Repeated influenza vaccination of healthy children and adults: borrow now, pay later?

A growing number of publications are recommending annual influenza vaccination of healthy children and adults. However, the long-term consequences of repeated influenza vaccination are unknown. We used a simple model of recurrent influenza infection to assess the likely impact of various repeated influenza vaccination scenarios. The model was based on a Markovian framework and was fitted on annual incidence rates of influenza infection by age. We found that natural influenza infection reduced the risk of being re-infected by 15.4% (95% confidence interval 7.1-23.0). Various scenarios of repeated influenza vaccination were then simulated and compared with a reference scenario where vaccination is given from age 65 years onwards. We show that repeated vaccination at a young age substantially increases the risk of influenza in older age, by a factor ranging between 1.2 (vaccination after 50 years) to 2.4 (vaccination from birth). These findings have important implications for influenza vaccination policies.

A Bayesian MCMC approach to study transmission of influenza: application to household longitudinal data.

We propose a transmission model to estimate the main characteristics of influenza transmission in households. The model details the risks of infection in the household and in the community at the individual scale. Heterogeneity among subjects is investigated considering both individual susceptibility and infectiousness. The model was applied to a data set consisting of the follow-up of influenza symptoms in 334 households during 15 days after an index case visited a general practitioner with virologically confirmed influenza. Estimating the parameters of the transmission model was challenging because a large part of the infectious process was not observed: only the dates when new cases were detected were observed. For each case, the data were augmented with the unobserved dates of the start and the end of the infectious period. The transmission model was included in a 3-levels hierarchical structure: (i) the observation level ensured that the augmented data were consistent with the observed data, (ii) the transmission level described the underlying epidemic process, (iii) the prior level specified the distribution of the parameters. From a Bayesian perspective, the joint posterior distribution of model parameters and augmented data was explored by Markov chain Monte Carlo (MCMC) sampling. The mean duration of influenza infectious period was estimated at 3.8 days (95 per cent credible interval, 95 per cent CI [3.1,4.6]) with a standard deviation of 2.0 days (95 per cent CI [1.1,2.8]). The instantaneous risk of influenza transmission between an infective and a susceptible within a household was found to decrease with the size of the household, and established at 0.32 person day(-1) (95 per cent CI [0.26,0.39]); the instantaneous risk of infection from the community was 0.0056 day(-1) (95 per cent CI [0.0029,0.0087]). Focusing on the differences in transmission between children (less than 15 years old) and adults, we estimated that the former were more likely to transmit than adults (posterior probability larger than 99 per cent), but that the mean duration of the infectious period was similar in children (3.6 days, 95 per cent CI [2.3,5.2]) and adults (3.9 days, 95 per cent CI [3.2,4.9]). The posterior probability that children had a larger community risk was 76 per cent and the posterior probability that they were more susceptible than adults was 79 per cent.