Influenza A (H1N1) 2009 reinfection in Thailand

Epidemiology of repeat influenza infection in Queensland, Australia, 2005-2017

Natural infection with the influenza virus is believed to generate cross-protective immunity across both types and subtypes. However, less is known about the persistence of this immunity and thus the susceptibility of individuals to repeat infection. We used 13 years (2005–2017) of surveillance data from Queensland, Australia, to describe the incidence and distribution of repeat influenza infections. Consecutive infections that occurred within 14 days of prior infection were considered a mixed infection; those that occurred more than 14 days later were considered separate (repeat) infections. Kaplan-Meier plots were used to investigate the probability of reinfection over time and the Prentice, Williams and Peterson extension of the Cox proportional hazards model was used to assess the association of age and gender with reinfection. Among the 188 392 notifications received during 2005–2017, 6165 were consecutively notified for the same individual (3.3% of notifications), and 2958 were mixed infections (1.6%). Overall, the probability of reinfection was low: the cumulative incidence was <1% after one year, 4.6% after five years, and 9.6% after ten years. The majority of consecutive infections were the result of two type A infections (43%) and were most common among females (adjusted hazard ratio (aHR): 1.15, 95% confidence interval (CI) 1.09–1.21), children aged less than 5 years (relative to adults aged 18–64 years aHR: 1.58, 95% CI 1.47–1.70) and older adults aged at least 65 years (aHR: 1.35; 95% CI 1.24–1.47). Our study suggests consecutive infections are possible but rare. These findings have implications for our understanding of population immunity to influenza.

Epidemiology of influenza virus reinfection in Guangxi, China: a retrospective analysis of a nine-year influenza surveillance data

BACKGROUND

Epidemiological characteristics profile of the reinfection of the influenza virus has not been well described.

METHODS

Included all influenza cases of Guangxi, China from January 2011 to December 2019 recorded in National Notifiable Infectious Disease Reporting Information System (NIDRIS) within 24 hours after diagnosis.

RESULTS

A total of 53,605.6 person-months and the median time of 8.7 months were observed for reinfection. The median age at the first influenza virus infection was 4.5 (IQR=2.0-7.5) years. The cumulative reinfection incidence was 2% at 6-month, 4% at 12-month, 5% at 24-month, and 7% after 59-month. Living in the rural area (HR=1.37 [95%CI, 1.29-1.45]), age ≤6 years (HR=11.43 [95%CI, 9.47-13.80]) were independent risk factors associated with influenza reinfection. Among 49 patients experiencing twice laboratory tests, 32 patients (65.3%) were with different virus types. The interval between two consecutive laboratory-confirmed episodes of the four groups differed (p=0.148), as the maximum was 72.9 months, and the minimum was 1.2 months.

CONCLUSIONS

The reinfection of the influenza virus in Guangxi independently and positively associated with the rural area and younger age. The unusually high frequency of reinfection points to a need for further prospective longitudinal studies to better investigate sufficient impact on different subtypes.

Epidemiology of Recurrent Hand, Foot and Mouth Disease, China, 2008-2015

Children who have received the enterovirus A71 vaccine are still at risk for disease with infections of enteroviruses of other serotypes.

Using China’s national surveillance data on hand, foot and mouth disease (HFMD) for 2008–2015, we described the epidemiologic and virologic features of recurrent HFMD. A total of 398,010 patients had HFMD recurrence; 1,767 patients had 1,814 cases of recurrent laboratory-confirmed HFMD: 99 reinfections of enterovirus A71 (EV-A71) with EV-A71, 45 of coxsackievirus A16 (CV-A16) with CV-A16, 364 of other enteroviruses with other enteroviruses, 383 of EV-A71 with CV-A16 and CV-A16 with EV-A71, and 923 of EV-A71 or CV-A16 with other enteroviruses and other enteroviruses with EV-A71 or CV-A16. The probability of HFMD recurrence was 1.9% at 12 months, 3.3% at 24 months, 3.9% at 36 months, and 4.0% at 38.8 months after the primary episode. HFMD severity was not associated with recurrent episodes or time interval between episodes. Elucidation of the mechanism underlying HFMD recurrence with the same enterovirus serotype and confirmation that HFMD recurrence is not associated with disease severity is needed.

Epidemiological characteristics and influential factors of hand, foot and mouth disease (HFMD) reinfection in children in Anhui province

Hand, foot and mouth disease (HFMD) is an acute contagious condition caused by a spectrum of human enteroviruses. HFMD reinfection is common in the absence of cross-protection from other virus subtypes. This study focused on reinfection in children in Anhui province, China between 2008 and 2013 using surveillance system data. We classified 8960 cases as reinfected, corresponding to a rate of 2·02%. The reinfection rate was higher in boys than in girls [odds ratio (OR) 1·27, 95% confidence interval (CI) 1·21-1·32, P < 0·001], children aged < 3 years (OR 3·82, 95% CI 3·58-4·07, P < 0·001), and children living in rural areas (OR 1·09, 95% CI 1·04-1·14, P = 0·001). The reinfection rate in children who were originally infected with non-enterovirus A71 (non-EVA71) enteroviruses was higher than those infected with EVA71 (OR 1·36, 95% CI 1·02-1·80, P = 0·034). Influential factors of reinfection rate included annual incidence (β coefficient = 0·715, P = 0·002) and the proportion of EVA71 in patients with mild HFMD (β coefficient = -0·509, P = 0·018). These results demonstrate that boys aged <3 years, especially those in rural areas or regions with a lower EVA71 proportion are more prone to reinfection, and specific health education programmes should be developed to protect these susceptible populations.

The influence of changing host immunity on 1918-19 pandemic dynamics

The sociological and biological factors which gave rise to the three pandemic waves of Spanish influenza in England during 1918-19 are still poorly understood. Symptom reporting data available for a limited set of locations in England indicates that reinfection in multiple waves occurred, suggesting a role for loss of infection-acquired immunity. Here we explore the role that changes in host immunity, driven by a combination of within-host factors and viral evolution, may play in explaining weekly mortality data and wave-by-wave symptomatic attack-rates available for a subset of English cities. Our results indicate that changes in the phenotype of the pandemic virus are likely required to explain the closely spaced waves of infection, but distinguishing between the detailed contributions of viral evolution and changing adaptive immune responses to transmission rates is difficult given the dearth of sero-epidemiological and virological data available even for more contemporary pandemics. We find that a dynamical model in which pre-pandemic protection in older "influenza-experienced" cohorts is lost rapidly prior to the second wave provides the best fit to the mortality and symptom reporting data. Best fitting parameter estimates for such a model indicate that post-infection protection lasted of order months, while other statistical analyses indicate that population-age was inversely correlated with overall mortality during the herald wave. Our results suggest that severe secondary waves of pandemic influenza may be triggered by viral escape from pre-pandemic immunity, and thus that understanding the role of heterosubtypic or cross-protective immune responses to pandemic influenza may be key to controlling the severity of future influenza pandemics.

Does homologous reinfection drive multiple-wave influenza outbreaks? Accounting for immunodynamics in epidemiological models

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We model the primary immune responses to influenza infection in humans.

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We examine the interplay between immunological and epidemiological dynamics.

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The model explains cases of homologous reinfection reported during past pandemics.

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Three epidemic profiles can arise depending on the degree of population mixing.

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A substantial proportion of infected host would remain unprotected after the 2009 influenza pandemic.

Epidemiological models of influenza transmission usually assume that recovered individuals instantly develop a fully protective immunity against the infecting strain. However, recent studies have highlighted host heterogeneity in the development of this immune response, characterized by delay and even absence of protection, that could lead to homologous reinfection (HR). Here, we investigate how these immunological mechanisms at the individual level shape the epidemiological dynamics at the population level. In particular, because HR was observed during the successive waves of past pandemics, we assess its role in driving multiple-wave influenza outbreaks. We develop a novel mechanistic model accounting for host heterogeneity in the immune response. Immunological parameters are inferred by fitting our dynamical model to a two-wave influenza epidemic that occurred on the remote island of Tristan da Cunha (TdC) in 1971, and during which HR occurred in 92 of 284 islanders. We then explore the dynamics predicted by our model for various population settings. We find that our model can explain HR over both short (e.g. week) and long (e.g. month) time-scales, as reported during past pandemics. In particular, our results reveal that the HR wave on TdC was a natural consequence of the exceptional contact configuration and high susceptibility of this small and isolated community. By contrast, in larger, less mixed and partially protected populations, HR alone cannot generate multiple-wave outbreaks. However, in the latter case, we find that a significant proportion of infected hosts would remain unprotected at the end of the pandemic season and should therefore benefit from vaccination. Crucially, we show that failing to account for these unprotected individuals can lead to large underestimation of the magnitude of the first post-pandemic season. These results are relevant in the context of the 2009 A/H1N1 influenza post-pandemic era.

Simultaneous and complete genome sequencing of influenza A and B with high coverage by Illumina MiSeq Platform

Active global surveillance and characterization of influenza viruses are essential for better preparation against possible pandemic events. Obtaining comprehensive information about the influenza genome can improve our understanding of the evolution of influenza viruses and emergence of new strains, and improve the accuracy when designing preventive vaccines. This study investigated the use of deep sequencing by the next-generation sequencing (NGS) Illumina MiSeq Platform to obtain complete genome sequence information from influenza virus isolates. The influenza virus isolates were cultured from 6 respiratory acute clinical specimens collected in Thailand and Nepal. DNA libraries obtained from each viral isolate were mixed and all were sequenced simultaneously. Total information of 2.6 Gbases was obtained from a 455±14 K/mm2 density with 95.76% (8,571,655/8,950,724 clusters) of the clusters passing quality control (QC) filters. Approximately 93.7% of all sequences from Read1 and 83.5% from Read2 contained high quality sequences that were ≥Q30, a base calling QC score standard. Alignments analysis identified three seasonal influenza A H3N2 strains, one 2009 pandemic influenza A H1N1 strain and two influenza B strains. The nearly entire genomes of all six virus isolates yielded equal or greater than 600-fold sequence coverage depth. MiSeq Platform identified seasonal influenza A H3N2, 2009 pandemic influenza A H1N1and influenza B in the DNA library mixtures efficiently.