Modelling seasonal influenza: the role of weather and punctuated antigenic drift

Abstract

Seasonal influenza appears as annual oscillations in temperate regions of the world, yet little is known as to what drives these annual outbreaks and what factors are responsible for their inter-annual variability. Recent studies suggest that weather variables, such as absolute humidity, are the key drivers of annual influenza outbreaks. The rapid, punctuated, antigenic evolution of the influenza virus is another major factor. We present a new framework for modelling seasonal influenza based on a discrete-time, age-of-infection, epidemic model, which allows the calculation of the model's likelihood function in closed form. This framework may be used to perform model inference and parameter estimation rigorously. The modelling approach allows us to fit 11 years of Israeli influenza data, with the best models fitting the data with unusually high correlations in which r . 0.9. We show that using actual weather to modulate influenza transmission rate gives better results than using the inter-annual means of the weather variables, providing strong support for the role of weather in shaping the dynamics of influenza. This conclusion remains valid even when incorporating a more realistic depiction of the decay of immunity at the population level, which allows for discrete changes in immunity from year to year.

Humidity: A review and primer on atmospheric moisture and human health

“…For the United States, absolute humidity was identified as a critical determinant of 24 observed influenza mortality (Barreca and Shimshack, 2012) and anomalously low humidity levels were found to precede the onset of increased wintertime influenza-related mortality in the United States by several weeks (Davis et al, 2012;Shaman et al, 2010). The respiratory impact of low atmospheric humidity was evident in other studies in Belgium (Lander et al, 2012), China (Xiao et al, 2013), Japan (Harata et al, 2004), Israel (Yaari et al, 2010), the Netherlands and Portugal (van Noort et al, 2012), and was inferred in forensic studies of major historical influenza outbreaks in England and Wales (He et al, 2013). Yet in studies that utilized relative humidity, Zhang et al (2013) found a negative association between RSV and Rodriguez-Martinez (2015) uncovered no relationship.…”

Model-based reconstruction of an epidemic using multiple datasets: understanding influenza A/H1N1 pandemic dynamics in Israel

“…In a previous work, we have focused on modelling the stochasticity of the infection process described by the transmission model and the stochasticity in the reporting of clinical diagnoses [8]. Here, for the sake of simplicity, the stochasticities involved in these processes are ignored, and the likelihood function is based on the stochasticity of the sampling processes involved in the laboratory testing, as it is assumed that the latter are dominant, owing to the small populations involved in these data.…”

“…Figure 6b rsif.royalsocietypublishing.org J. R. Soc. Interface 13: 20160099 population as a whole, the optimal allocation strategy, which reduces the total attack rate to a minimum, is to vaccinate almost only school children (5)(6)(7)(8)(9)(10)(11)(12)(13)(14)(15)(16)(17)(18)(19). Vaccinating just 15% of the population using the optimal allocation strategy (vaccinating 58% of all school children) would have completely mitigated the winter wave of the outbreak.…”

“…This pattern presents an opportunity for investigating the changing factors affecting the transmission rates of influenza within a population. Weather conditions, in particular temperature and absolute humidity (AH), are the main factors currently used to explain the seasonal pattern of interpandemic influenza outbreaks in temperate regions [4][5][6][7][8]. With regards to the 2009 pandemic, several studies have found that varying AH conditions throughout the pandemic period & 2016 The Author(s) Published by the Royal Society.…”

Multiannual forecasting of seasonal influenza dynamics reveals climatic and evolutionary drivers

“…Depending on the circumstances, influenza typically infects between 10% and 50% of a given population and has become a source of considerable human morbidity and mortality (2). There is much controversy in identifying the seasonal drivers that generate annual influenza epidemics and the processes that give rise to their large variability (3)(4)(5)(6)(7)(8)(9)(10)(11)(12). This is an outstanding problem of influenza research today.…”