Antibody responses to avian influenza viruses in wild birds broaden with age

For viruses such as avian influenza, immunity within a host population can drive the emergence of new strains by selecting for viruses with novel antigens that avoid immune recognition. The accumulation of acquired immunity with age is hypothesized to affect how influenza viruses emerge and spread in species of different lifespans. Despite its importance for understanding the behaviour of avian influenza viruses, little is known about age-related accumulation of immunity in the virus's primary reservoir, wild birds. To address this, we studied the age structure of immune responses to avian influenza virus in a wild swan population (Cygnus olor), before and after the population experienced an outbreak of highly pathogenic H5N1 avian influenza in 2008. We performed haemagglutination inhibition assays on sampled sera for five avian influenza strains and show that breadth of response accumulates with age. The observed age-related distribution of antibody responses to avian influenza strains may explain the age-dependent mortality observed during the highly pathogenic H5N1 outbreak. Age structures and species lifespan are probably important determinants of viral epidemiology and virulence in birds

Estimating Dengue Transmission Intensity from Sero-Prevalence Surveys in Multiple Countries

BACKGROUND:Estimates of dengue transmission intensity remain ambiguous. Since the majority of infections are asymptomatic, surveillance systems substantially underestimate true rates of infection. With advances in the development of novel control measures, obtaining robust estimates of average dengue transmission intensity is key for assessing both the burden of disease from dengue and the likely impact of interventions. METHODOLOGY/PRINCIPAL FINDINGS:The force of infection (λ) and corresponding basic reproduction numbers (R0) for dengue were estimated from non-serotype (IgG) and serotype-specific (PRNT) age-stratified seroprevalence surveys identified from the literature. The majority of R0 estimates ranged from 1-4. Assuming that two heterologous infections result in complete immunity produced up to two-fold higher estimates of R0 than when tertiary and quaternary infections were included. λ estimated from IgG data were comparable to the sum of serotype-specific forces of infection derived from PRNT data, particularly when inter-serotype interactions were allowed for. CONCLUSIONS/SIGNIFICANCE:Our analysis highlights the highly heterogeneous nature of dengue transmission. How underlying assumptions about serotype interactions and immunity affect the relationship between the force of infection and R0 will have implications for control planning. While PRNT data provides the maximum information, our study shows that even the much cheaper ELISA-based assays would provide comparable baseline estimates of overall transmission intensity which will be an important consideration in resource-constrained settings

Effects of neutralizing antibodies on escape from CD8+ T-cell responses in HIV-1 infection.

Despite substantial advances in our knowledge of immune responses against HIV-1 and of its evolution within the host, it remains unclear why control of the virus eventually breaks down. Here, we present a new theoretical framework for the infection dynamics of HIV-1 that combines antibody and CD8(+) T-cell responses, notably taking into account their different lifespans. Several apparent paradoxes in HIV pathogenesis and genetics of host susceptibility can be reconciled within this framework by assigning a crucial role to antibody responses in the control of viraemia. We argue that, although escape from or progressive loss of quality of CD8(+) T-cell responses can accelerate disease progression, the underlying cause of the breakdown of virus control is the loss of antibody induction due to depletion of CD4(+) T cells. Furthermore, strong antibody responses can prevent CD8(+) T-cell escape from occurring for an extended period, even in the presence of highly efficacious CD8(+) T-cell responses

The Effects of Tertiary and Quaternary Infections on the Epidemiology of Dengue

The epidemiology of dengue is characterised by irregular epidemic outbreaks and desynchronised dynamics of its four cocirculating virus serotypes. Whilst infection by one serotype appears to convey life-long protection to homologous infection, it is believed to be a risk factor for severe disease manifestations upon secondary, heterologous infection due to the phenomenon of Antibody-Dependent Enhancement (ADE). Subsequent clinical infections are rarely reported and, since the majority of dengue infections are generally asymptomatic, it is not clear if and to what degree tertiary or quaternary infections contribute to dengue epidemiology. Here we investigate the effect of third and subsequent infections on the transmission dynamics of dengue and show that although the qualitative patterns are largely equivalent, the system more readily exhibits the desynchronised serotype oscillations and multi-annual epidemic outbreaks upon their inclusion. More importantly, permitting third and fourth infections significantly increases the force of infection without resorting to high basic reproductive numbers. Realistic age-prevalent patterns and seroconversion rates are therefore easier reconciled with a low value of dengue’s transmission potential if allowing for more than two infections; this should have importan

Comparison of synchronisation and single-serotype dominance between model (i) (<i>top</i>) and model (ii) (<i>bottom</i>).

<p>(a) The synchronisation pattern between serotypes 1 and 2 indicates that, for both models, most of parameter space is characterised by desynchronised behaviour i.e. the dynamics of the two serotypes are not ‘locked’ together. (b) Using a measure of single serotype dominance (where 0 corresponds to at least two serotypes being simultaneously dominant and higher values indicate a greater tendency for one serotype to be dominating at any given time), one can observe that in both models the trend is for increasing levels of dominance with increasing enhancement; this trend is more pronounced in model (ii) than model (i).</p

Comparison of age structured dynamics between model (i) and model (ii).

<p>(a) The lines show the proportion of the population at each age (for model (i) (top) and model (ii) (bottom)) who have suffered one (solid dark blue line), two (solid red), three (solid green), four (solid magenta) and any (solid black) dengue infections. For model (ii) the proportion of the population that is at risk of disease (defined as having seen 1, 2 or 3 serotypes) is also plotted (dotted black) for comparison to the equivalent in model (i) (solid dark blue). Generally, in model (ii) people are exposed to dengue at an earlier age, experience heterologous infections younger, and take much longer to become completely immune. (b) For model (i) ((ii)), the blue (green) bar shows how the average age of disease (DHF), determined as heterologous infection, changes with the number of serotypes present whilst the small bars show the change in age of first infection. The increase in the total force of infection with the number of serotypes is shown as dotted lines (model (i): blue, and model (ii): green). (c) For model (i) (blue line) and model (ii) (green line) we observe that increasing acts to decrease the average age of first infection (here estimated as 1/total force of infection) and that for all levels of this value is significantly lower when allowing for third and fourth infection (model (ii)). Parameter values: ((a), (b) and (c)) and (a), (b).</p

Real-time seroprevalence and exposure levels of emerging pathogens in infection-naive host populations

For endemic pathogens, seroprevalence mimics overall exposure and is minimally influenced by the time that recent infections take to seroconvert. Simulating spatially-explicit and stochastic outbreaks, we set out to explore how, for emerging pathogens, the mix of exponential growth in infection events and a constant rate for seroconversion events could lead to real-time significant differences in the total numbers of exposed versus seropositive. We find that real-time seroprevalence of an emerging pathogen can underestimate exposure depending on measurement time, epidemic doubling time, duration and natural variation in the time to seroconversion among hosts. We formalise mathematically how underestimation increases non-linearly as the host’s time to seroconversion is ever longer than the pathogen’s doubling time, and how more variable time to seroconversion among hosts results in lower underestimation. In practice, assuming that real-time seroprevalence reflects the true exposure to emerging pathogens risks overestimating measures of public health importance (e.g. infection fatality ratio) as well as the epidemic size of future waves. These results contribute to a better understanding and interpretation of real-time serological data collected during the emergence of pathogens in infection-naive host populations

Dengue epidemiology in South Vietnam.

<p>The total annual number of dengue cases (blue bars) and relative serotype prevalence (lines) over the period 1994–2008 in the southern 20 provinces of Viet Nam show the characteristic fluctuation in disease incidence and sequential replacements of dominant serotypes. Source of data: Vietnamese Ministry of Health Dengue passive surveillance scheme and kindly provided by the Pasteur Institute, HCMC, Viet Nam. The Hospital for Tropical Diseases is a tertiary referral hospital for infectious diseases.</p

Comparison of inter-epidemic period and serotype persistence between model (i) (<i>top</i>) and model (ii) (<i>bottom</i>).

<p>(a) As enhancement increases so too does the epidemic period observed in each model. There is also a trend towards longer periods at lower . However, these trends both appear to be stronger in model (ii). (b) The risk of stochastic extinction within the model is shown as the proportion of time in each model that the prevalence of a particular serotype exists above a specific threshold. In both models there is a low risk of extinction but the risk increases with enhancement; again, this trend is stronger in model (ii).</p

Potential impact of individual exposure histories to endemic human coronaviruses on age-dependent severity of COVID-19

Background Cross-reactivity to SARS-CoV-2 from exposure to endemic human coronaviruses (eHCoV) is gaining increasing attention as a possible driver of both protection against infection and COVID-19 severity. Here we explore the potential role of cross-reactivity induced by eHCoVs on age-specific COVID-19 severity in a mathematical model of eHCoV and SARS-CoV-2 transmission. Methods We use an individual-based model, calibrated to prior knowledge of eHCoV dynamics, to fully track individual histories of exposure to eHCoVs. We also model the emergent dynamics of SARS-CoV-2 and the risk of hospitalisation upon infection. Results We hypothesise that primary exposure with any eHCoV confers temporary cross-protection against severe SARS-CoV-2 infection, while life-long re-exposure to the same eHCoV diminishes cross-protection, and increases the potential for disease severity. We show numerically that our proposed mechanism can explain age patterns of COVID-19 hospitalisation in EU/EEA countries and the UK. We further show that some of the observed variation in health care capacity and testing efforts is compatible with country-specific differences in hospitalisation rates under this model. Conclusions This study provides a “proof of possibility” for certain biological and epidemiological mechanisms that could potentially drive COVID-19-related variation across age groups. Our findings call for further research on the role of cross-reactivity to eHCoVs and highlight data interpretation challenges arising from health care capacity and SARS-CoV-2 testing.</p