REVIEWS AND SYNTHESES Seasonality and the dynamics of infectious diseases (original) (raw)
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Seasonality and the dynamics of infectious diseases
Ecology Letters, 2006
Seasonal variations in temperature, rainfall and resource availability are ubiquitous and can exert strong pressures on population dynamics. Infectious diseases provide some of the best-studied examples of the role of seasonality in shaping population fluctuations. In this paper, we review examples from human and wildlife disease systems to illustrate the challenges inherent in understanding the mechanisms and impacts of seasonal environmental drivers. Empirical evidence points to several biologically distinct mechanisms by which seasonality can impact host-pathogen interactions, including seasonal changes in host social behaviour and contact rates, variation in encounters with infective stages in the environment, annual pulses of host births and deaths and changes in host immune defences. Mathematical models and field observations show that the strength and mechanisms of seasonality can alter the spread and persistence of infectious diseases, and that population-level responses can range from simple annual cycles to more complex multiyear fluctuations. From an applied perspective, understanding the timing and causes of seasonality offers important insights into how parasite-host systems operate, how and when parasite control measures should be applied, and how disease risks will respond to anthropogenic climate change and altered patterns of seasonality. Finally, by focusing on well-studied examples of infectious diseases, we hope to highlight general insights that are relevant to other ecological interactions.
Seasonal host dynamics drive the timing of recurrent epidemics in a wildlife population
Proceedings of The Royal Society B: Biological Sciences, 2009
The seasonality of recurrent epidemics has been largely neglected, especially where patterns are not driven by forces external to the population. Here, we use data on cowpox virus in field voles to explore the seasonal patterns in wildlife (variable abundance) populations and compare these with patterns previously found in humans. Timing in our system was associated with both the number and the rate of recruitment of susceptible hosts. A plentiful and sustained supply of susceptible hosts throughout the summer gave rise to a steady rise in infected hosts and a late peak. A meagre supply more limited in time was often insufficient to sustain an increase in infected hosts, leading to an early peak followed by a decline. These seasonal patterns differed from those found in humans, but the underlying association found between the timing and the supply of susceptible hosts was similar to that in humans. We also combine our data with a model to explore these differences between humans and wildlife. Model results emphasize the importance of the interplay between seasonal infection and recruitment and suggest that our empirical patterns have a relevance extending beyond our own system.
Seasonal host dynamics drive the timing of recurrent epidemics in a wildlife
2009
The seasonality of recurrent epidemics has been largely neglected, especially where patterns are not driven by forces external to the population. Here, we use data on cowpox virus in field voles to explore the seasonal patterns in wildlife (variable abundance) populations and compare these with patterns previously found in humans. Timing in our system was associated with both the number and the rate of recruitment of susceptible hosts. A plentiful and sustained supply of susceptible hosts throughout the summer gave rise to a steady rise in infected hosts and a late peak. A meagre supply more limited in time was often insufficient to sustain an increase in infected hosts, leading to an early peak followed by a decline. These seasonal patterns differed from those found in humans, but the underlying association found between the timing and the supply of susceptible hosts was similar to that in humans. We also combine our data with a model to explore these differences between humans and wildlife. Model results emphasize the importance of the interplay between seasonal infection and recruitment and suggest that our empirical patterns have a relevance extending beyond our own system.
Ecosphere, 2021
Ecological and environmental factors can influence the transmission of infectious diseases. They can accomplish this via effects on host susceptibility and exposure to infection, which are governed by host physiology and behavior, respectively. To better inform disease control, more information is needed about how extrinsic factors affect physiological and behavioral processes that determine transmission. We investigated how heterospecific competitors and seasonality may influence host susceptibility and intraspecific contact rates using a directly transmitted disease system, the North American deer mouse (Peromyscus maniculatus)-Sin Nombre hantavirus (SNV) system. In grasslands of western Montana, USA, deer mice compete with dominant voles (Microtus spp.) and shrews (Sorex spp.) and experience a seasonal temperate climate. Higher SNV transmission occurs primarily during spring/summer, when changes in physiology and behavior may serve as influential contributors. We hypothesized that (1) voles, and to a lesser extent shrews, will induce chronic stress, suppress immunity, and may change contact rates of deer mice; and (2) during spring/summer, deer mice may experience chronic stress, suppressed immunity, and higher contact rates, which may help explain the reported seasonality in SNV transmission. Over two years, we trapped small mammals at four grids in western Montana. Deer mice were sampled for feces and blood and evaluated for scar numbers, demography, and body condition scores (BCSs). We evaluated stress physiology with fecal corticosterone metabolites (FCMs), neutrophil/lymphocyte (N/L) ratios and BCSs, immunity with white blood cell (WBC) counts, and contact rates with scar numbers. We found that shrew density was negatively associated with stress response FCMs, suggestive of chronic stress. Additionally, although complex interactions existed, shrew and vole densities were negatively associated with BCSs, but differentially with scar numbers. N/L ratios were higher in spring/summer, whereas WBC counts were lower in summer, suggestive of chronic stress and suppressed immunity, respectively. Our results suggest that (1) heterospecific competitors may differentially influence disease transmission via stress physiology and contact rates, and that (2) chronic stress, suppressed immunity, and higher contact rates may help explain why higher SNV transmission has been previously reported during spring/summer in Montana. Our findings may extend to other directly transmitted disease systems.
Seasonality and critical community size for infectious diseases
The ANZIAM Journal, 2003
The endemicity of infectious diseases is investigated from a deterministic viewpoint. Sus- tained oscillation of infectives is often due to seasonal effects which may be related to climatic changes. For example the transmission of the measles virus by droplets is en- hanced in cooler, more humid seasons. In many countries the onset of cooler, more humid weather coincides with the
Drivers of Infectious Disease Seasonality: Potential Implications for COVID-19
Journal of Biological Rhythms, 2021
Not 1 year has passed since the emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease 2019 (COVID-19). Since its emergence, great uncertainty has surrounded the potential for COVID-19 to establish as a seasonally recurrent disease. Many infectious diseases, including endemic human coronaviruses, vary across the year. They show a wide range of seasonal waveforms, timing (phase), and amplitudes, which differ depending on the geographical region. Drivers of such patterns are predominantly studied from an epidemiological perspective with a focus on weather and behavior, but complementary insights emerge from physiological studies of seasonality in animals, including humans. Thus, we take a multidisciplinary approach to integrate knowledge from usually distinct fields. First, we review epidemiological evidence of environmental and behavioral drivers of infectious disease seasonality. Subsequently, we take a chronobiological ...
Epidemics, 2013
The annual occurrence of many infectious diseases remains a constant burden to public health systems. The seasonal patterns in respiratory disease incidence observed in temperate regions have been attributed to the impact of environmental conditions on pathogen survival. A model describing the transmission of an infectious disease by means of a pathogenic state capable of surviving in an environmental reservoir outside of its host organism is presented in this paper. The ratio of pathogen lifespan to the duration of the infectious disease state is found to be a critical parameter in determining disease dynamics. The introduction of a seasonally forced pathogen inactivation rate identifies a time delay between peak pathogen survival and peak disease incidence. The delay is dependent on specific disease parameters and, for influenza, decreases with increasing reproduction number. The observed seasonal oscillations are found to have a period identical to that of the seasonally forced inactivation rate and which is independent of the duration of infection acquired immunity.
Seasonal dynamics of recurrent epidemics
Nature, 2007
Seasonality is a driving force that has a major effect on the spatiotemporal dynamics of natural systems and their populations 1-5 . This is especially true for the transmission of common infectious diseases (such as influenza, measles, chickenpox and pertussis), and is of great relevance for host-parasite relationships in general 1-23 . Here we gain further insights into the nonlinear dynamics of recurrent diseases through the analysis of the classical seasonally forced SIR (susceptible, infectious or recovered) epidemic model 6,7 . Our analysis differs from other modelling studies in that the focus is more on post-epidemic dynamics than the outbreak itself. Despite the mathematical intractability of the forced SIR model, we identify a new threshold effect and give clear analytical conditions for predicting the occurrence of either a future epidemic outbreak, or a 'skip'-a year in which an epidemic fails to initiate. The threshold is determined by the population's susceptibility measured after the last outbreak and the rate at which new susceptible individuals are recruited into the population. Moreover, the time of occurrence (that is, the phase) of an outbreak proves to be a useful parameter that carries important epidemiological information. In forced systems, seasonal changes can prevent late-peaking diseases (that is, those having high phase) from spreading widely, thereby increasing population susceptibility, and controlling the triggering and intensity of future epidemics. These principles yield forecasting tools that should have relevance for the study of newly emerging and re-emerging diseases controlled by seasonal vectors.