As with many pathogens, most dengue infections are subclinical and therefore unobserved
. Coupled with limited understanding of the dynamic behaviour of potential serological markers of infection, ...this observational problem has wide-ranging implications, including hampering our understanding of individual- and population-level correlates of infection and disease risk and how these change over time, between assay interpretations and with cohort design. Here we develop a framework that simultaneously characterizes antibody dynamics and identifies subclinical infections via Bayesian augmentation from detailed cohort data (3,451 individuals with blood draws every 91 days, 143,548 haemagglutination inhibition assay titre measurements)
. We identify 1,149 infections (95% confidence interval, 1,135-1,163) that were not detected by active surveillance and estimate that 65% of infections are subclinical. After infection, individuals develop a stable set point antibody load after one year that places them within or outside a risk window. Individuals with pre-existing titres of ≤1:40 develop haemorrhagic fever 7.4 (95% confidence interval, 2.5-8.2) times more often than naive individuals compared to 0.0 times for individuals with titres >1:40 (95% confidence interval: 0.0-1.3). Plaque reduction neutralization test titres ≤1:100 were similarly associated with severe disease. Across the population, variability in the size of epidemics results in large-scale temporal changes in infection and disease risk that correlate poorly with age.
Enterovirus outbreak dynamics Nikolay, Birgit; Cauchemez, Simon
Science (American Association for the Advancement of Science),
08/2018, Letnik:
361, Številka:
6404
Journal Article
Recenzirano
Predictability of outbreaks opens the door to model-guided public health planning
Outbreaks of pathogens that cause acute immunizing infections are often highly predictable. The most studied example ...is measles, for which case incidence over time is robustly explained with simple mathematical models that account for variations in the number of susceptible individuals through infection and birth (
1
). By contrast, it is more challenging to predict outbreaks of infectious diseases that exhibit complex patterns of immunity, such as influenza, for which antigenic characteristics of circulating strains continuously change (
2
). Enteroviruses can cause a wide spectrum of clinical manifestations—including hand-foot-and-mouth disease (HFMD)—with potentially severe neurological complications (
3
). With more than 100 serotypes that may have varying immunological cross-protection (
3
), predicting the transmission dynamics of enteroviruses was expected to be difficult. On page 800 of this issue, Pons-Salort and Grassly (
4
) demonstrate that in contrast to this expectation, enteroviruses are highly predictable pathogens, with outbreaks largely driven by serotype-specific long-term immunity and birth rates. This opens the door to model-guided public health planning and outbreak preparedness.
The dynamics of viral shedding and symptoms following influenza virus infection are key factors when considering epidemic control measures. The authors reviewed published studies describing the ...course of influenza virus infection in placebo-treated and untreated volunteers challenged with wild-type influenza virus. A total of 56 different studies with 1,280 healthy participants were considered. Viral shedding increased sharply between 0.5 and 1 day after challenge and consistently peaked on day 2. The duration of viral shedding averaged over 375 participants was 4.80 days (95% confidence interval: 4.31, 5.29). The frequency of symptomatic infection was 66.9% (95% confidence interval: 58.3, 74.5). Fever was observed in 37.0% of A/H1N1, 40.6% of A/H3N2 (p = 0.86), and 7.5% of B infections (p = 0.001). The total symptoms scores increased on day 1 and peaked on day 3. Systemic symptoms peaked on day 2. No such data exist for children or elderly subjects, but epidemiologic studies suggest that the natural history might differ. The present analysis confirms prior expert opinion on the duration of viral shedding or the frequency of asymptomatic influenza infection, extends prior knowledge on the dynamics of viral shedding and symptoms, and provides original results on the frequency of respiratory symptoms or fever.
Abstract
Higher transmissibility of SARS-CoV-2 in cold and dry weather conditions has been hypothesized since the onset of the COVID-19 pandemic but the level of epidemiological evidence remains low. ...During the first wave of the pandemic, Spain, Italy, France, Portugal, Canada and USA presented an early spread, a heavy COVID-19 burden, and low initial public health response until lockdowns. In a context when testing was limited, we calculated the basic reproduction number (R
0
) in 63 regions from the growth in regional death counts. After adjusting for population density, early spread of the epidemic, and age structure, temperature and humidity were negatively associated with SARS-CoV-2 transmissibility. A reduction of mean absolute humidity by 1 g/m
3
was associated with a 0.15-unit increase of R
0
. Below 10 °C, a temperature reduction of 1 °C was associated with a 0.16-unit increase of R
0
. Our results confirm a dependency of SARS-CoV-2 transmissibility to weather conditions in the absence of control measures during the first wave. The transition from summer to winter, corresponding to drop in temperature associated with an overall decrease in absolute humidity, likely contributed to the intensification of the second wave in north-west hemisphere countries. Non-pharmaceutical interventions must be adjusted to account for increased transmissibility in winter conditions.
Numerous epidemic models have been developed to capture aspects of human contact patterns, making model selection challenging when they fit (often-scarce) early epidemic data equally well but differ ...in predictions. Here we consider the invasion of a novel directly transmissible infection and perform an extensive, systematic and transparent comparison of models with explicit age and/or household structure, to determine the accuracy loss in predictions in the absence of interventions when ignoring either or both social components. We conclude that, with heterogeneous and assortative contact patterns relevant to respiratory infections, the model's age stratification is crucial for accurate predictions. Conversely, the household structure is only needed if transmission is highly concentrated in households, as suggested by an empirical but robust rule of thumb based on household secondary attack rate. This work serves as a template to guide the simplicity/accuracy trade-off in designing models aimed at initial, rapid assessment of potential epidemic severity.
Evaluating the characteristics of emerging SARS-CoV-2 variants of concern is essential to inform pandemic risk assessment. A variant may grow faster if it produces a larger number of secondary ...infections ('R advantage') or if the timing of secondary infections (generation time) is better. So far, assessments have largely focused on deriving the R advantage assuming the generation time was unchanged. Yet, knowledge of both is needed to anticipate impact. Here we develop an analytical framework to investigate the contribution of
the R advantage and generation time to the growth advantage of a variant. It is known that selection on a variant with larger R increases with levels of transmission in the community. We additionally show that variants conferring earlier transmission are more strongly favoured when the historical strains have fast epidemic growth, while variants conferring later transmission are more strongly favoured when historical strains have slow or negative growth. We develop these conceptual insights into a new statistical framework to infer both the R advantage and generation time of a variant. On simulated data, our framework correctly estimates both parameters when it covers time periods characterized by different epidemiological contexts. Applied to data for the Alpha and Delta variants in England and in Europe, we find that Alpha confers a +54% 95% CI, 45-63% R advantage compared to previous strains, and Delta +140% 98-182% compared to Alpha, and mean generation times are similar to historical strains for both variants. This work helps interpret variant frequency dynamics and will strengthen risk assessment for future variants of concern.
Characterizing the circulation of Mayaro virus (MAYV), an emerging arbovirus threat, is essential for risk assessment but challenging due to cross-reactivity with other alphaviruses such as ...chikungunya virus (CHIKV). Here, we develop an analytical framework to jointly assess MAYV epidemiology and the extent of cross-reactivity with CHIKV from serological data collected throughout French Guiana (N = 2697). We find strong evidence of an important sylvatic cycle for MAYV with most infections occurring near the natural reservoir in rural areas and in individuals more likely to go to the forest (i.e., adult males) and with seroprevalences of up to 18% in some areas. These findings highlight the need to strengthen MAYV surveillance in the region and showcase how modeling can improve interpretation of cross-reacting assays.
The threat posed by the highly pathogenic H5N1 influenza virus requires public health authorities to prepare for a human pandemic. Although pre-pandemic vaccines and antiviral drugs might ...significantly reduce illness rates, their stockpiling is too expensive to be practical for many countries. Consequently, alternative control strategies, based on non-pharmaceutical interventions, are a potentially attractive policy option. School closure is the measure most often considered. The high social and economic costs of closing schools for months make it an expensive and therefore controversial policy, and the current absence of quantitative data on the role of schools during influenza epidemics means there is little consensus on the probable effectiveness of school closure in reducing the impact of a pandemic. Here, from the joint analysis of surveillance data and holiday timing in France, we quantify the role of schools in influenza epidemics and predict the effect of school closure during a pandemic. We show that holidays lead to a 20-29% reduction in the rate at which influenza is transmitted to children, but that they have no detectable effect on the contact patterns of adults. Holidays prevent 16-18% of seasonal influenza cases (18-21% in children). By extrapolation, we find that prolonged school closure during a pandemic might reduce the cumulative number of cases by 13-17% (18-23% in children) and peak attack rates by up to 39-45% (47-52% in children). The impact of school closure would be reduced if it proved difficult to maintain low contact rates among children for a prolonged period.
The shielding of older individuals has been proposed to limit COVID-19 hospitalizations while relaxing general social distancing in the absence of vaccines. Evaluating such approaches requires a deep ...understanding of transmission dynamics across ages. Here, we use detailed age-specific case and hospitalization data to model the rebound in the French epidemic in summer 2020, characterize age-specific transmission dynamics and critically evaluate different age-targeted intervention measures in the absence of vaccines. We find that while the rebound started in young adults, it reached individuals aged ≥80 y.o. after 4 weeks, despite substantial contact reductions, indicating substantial transmission flows across ages. We derive the contribution of each age group to transmission. While shielding older individuals reduces mortality, it is insufficient to allow major relaxations of social distancing. When the epidemic remains manageable (R close to 1), targeting those most contributing to transmission is better than shielding at-risk individuals. Pandemic control requires an effort from all age groups.
PDF
