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   J Public Health Policy. Author manuscript; available in PMC 2008 July
   24.
   Published in final edited form as:
   [7]J Public Health Policy. 2006; 27(1): 2-12.
   doi: 10.1057/palgrave.jphp.3200061.
   PMCID: PMC2483431
   NIHMSID: NIHMS58476
   [8]Copyright notice and [9]Disclaimer
   Mystery of Seasonality: Getting the Rhythm of Nature
   Elena N. Naumova^*
   ^*Address for Correspondence: Department of Public Health and Family
   Medicine, Tufts University School of Medicine, 136 Harrison Avenue,
   Boston, MA 02111, USA. E-mail: elena.naumova/at/tufts.edu
   Small right arrow pointing to: The publisher's final edited version of
   this article is available at [10]J Public Health Policy.
   Small right arrow pointing to: See other articles in PMC that [11]cite
   the published article.
   Abstract
   Seasonality, a systematic periodic occurrence of events over the course
   of a year, is a well-known phenomenon in life and health sciences.
   Understanding seasonal fluctuations in diseases patterns presents us
   with a major challenge. To develop efficient strategies for disease
   prevention and control, we need to grasp the main determinants of
   temporal variations and their interactions. This paper will introduce
   the notion of seasonality by outlining several of its factors, using as
   illustrations respiratory and enteric water- or food-borne infections.
   Keywords: seasonality, water-borne infection, food-borne infection,
   respiratory infection
     * [12] Other Sectionsv
          + [13]Abstract
          + [14]Introduction
          + [15]Notion of Seasonality
          + [16]Diseases Seasonal Patterns
          + [17]Seasonal Host Susceptibility
          + [18]Seasonality in Pathogens Survival and Transmissibility
          + [19]Disease Seasonality and Calendar Effects
          + [20]Climate Change, [dot.gif] Extreme Weather Events,
            [dot.gif] and Disease Seasonality
          + [21]Methodology in Studying Seasonality: Brining Mathematics
            and Philosophy to Public Health Thinking
          + [22]References

   Introduction

   Now let us consider the seasons and the way we can predict whether it
   is going to be a healthy or an unhealthy year.

   (Hippocrates. Air, Waters, Places, 10)^[23]1

   Seasonal fluctuations in birth and death, in sickness and health, are
   the haunting mysteries of mankind. People have made predictions from
   winds, tides, birds' migrations, spring blooms, sunsets, and
   constellations in hope of grasping the future. The complexity and
   uncertainty of ancient and modern means of prediction make us wonder to
   what extent we are able to understand the rhythm of nature. One might
   argue the future cannot be known, but from a practical point of view, a
   better understanding of changes in disease occurrences is essential for
   building efficient strategies for disease prevention and control.
   Seasonality, a systematic periodic occurrence of events over the course
   of a year, is a well-known phenomenon in life and health sciences.
   Since Hippocrates, observers worldwide have noted and documented marked
   fluctuations in the incidence of many diseases. In the modern view, the
   main determinants of temporal variations in disease manifestation are
   evolving host susceptibility, periodicity in pathogen abundance and
   transmissibility, and the ever-changing environment that can support or
   repress a host or pathogen. Interactions among these factors
   responsible for seasonal variation are interwoven into the intricate
   fabric of life.
   For many diseases, explanations for self-sustained oscillations still
   remain elusive. We lack adequate methods and sufficient analytical
   tools for comprehensive examination of seasonality in public health
   field studies. A dearth of observations, recorded over long periods at
   fine resolution, compounded by an enormous number of factors associated
   with periodic changes, obscure our ability to understand disease
   variation. Urgent need for effective strategies to prevent and control
   a spread of emerging infections in the rapidly changing world, however,
   demands a deeper insight into the cyclic nature of diseases.
   This paper will introduce the notion of seasonality and outline several
   factors associated with seasonality using as illustrations enteric
   water- or food-borne infections and respiratory infections. Then I
   propose a framework for systematic evaluation of seasonal oscillations.
   In every part of this presentation, and most importantly, I wish to
   stimulate discussion on this challenging topic.
     * [24] Other Sectionsv
          + [25]Abstract
          + [26]Introduction
          + [27]Notion of Seasonality
          + [28]Diseases Seasonal Patterns
          + [29]Seasonal Host Susceptibility
          + [30]Seasonality in Pathogens Survival and Transmissibility
          + [31]Disease Seasonality and Calendar Effects
          + [32]Climate Change, [dot.gif] Extreme Weather Events,
            [dot.gif] and Disease Seasonality
          + [33]Methodology in Studying Seasonality: Brining Mathematics
            and Philosophy to Public Health Thinking
          + [34]References

   Notion of Seasonality

   Every disease occurs at any season of the year but some of them more
   frequently occur and are of greater severity at certain times.

   (Hippocrates. Aphorisms, III, 19)

   Seasonality, as noted above, refers to the cyclic appearance of events
   over a period of time. A seasonal pattern may appear as a tight cluster
   of isolated outbreaks that occurred during a relatively short time
   period, then spreading over a wide geographic area.
   For example, in a temporal curve of enteric infection cases (i.e.
   giardiasis, cryptosporidiosis, or rotavirus infections), a compact
   cluster of outbreaks is followed by a long interval of low incidence.
   Systematic recurrence of such sequences forms a seasonal pattern
   typical of a specific pathogen in a given population and in a given
   locality. A seasonal increase in enteric or respiratory infection often
   produces a well-defined oscillating curve that starts to rise in one
   season and declines over the next one.
   The three main features characterize seasonality:
     * a point in time when a seasonal curve reaches its maximum,
     * an amplitude from peak to nadir, and
     * a duration of a seasonal increase defined by a shape of a curve.
       (The shape of a seasonal pattern reflects how fast a temporal curve
       reaches its peak and declines to nadir over a course of a full
       cycle. Depending on the length of a cycle whether it is one year or
       a half of a year, a seasonal curve would have one or two peaks.)

   Seasonal patterns, described by these three characteristics, may vary
   for different diseases, different locations, or different
   subpopulations. Many viral and bacterial infections in humans show
   marked seasonal changes. In some diseases, like salmonellosis and
   influenza, annual oscillations explain up to 60% of variability. Such
   impact should not be ignored and deserves a proper examination.
     * [35] Other Sectionsv
          + [36]Abstract
          + [37]Introduction
          + [38]Notion of Seasonality
          + [39]Diseases Seasonal Patterns
          + [40]Seasonal Host Susceptibility
          + [41]Seasonality in Pathogens Survival and Transmissibility
          + [42]Disease Seasonality and Calendar Effects
          + [43]Climate Change, [dot.gif] Extreme Weather Events,
            [dot.gif] and Disease Seasonality
          + [44]Methodology in Studying Seasonality: Brining Mathematics
            and Philosophy to Public Health Thinking
          + [45]References

   Diseases Seasonal Patterns

   Diseases vary in their relationships one with another; some are
   opposed, some are mutually agreeable.

   (Hippocrates. Aphorisms, III, 3)

   Differences in diseases peaks reflect different etiology, heterogeneity
   in host susceptibility, or route of transmission. In temperate
   climates, Campylobacter and Salmonella infections are known to rise in
   summer, giardiasis in early fall, and rotavirus infection in
   mid-winter, etc. Interestingly, for the same infectious agent,
   infections recorded in two different locations may present a different
   pattern of incidence. A seasonal pattern for cryptosporidiosis in the
   United States exhibits one late summer peak ([46]1); in contrast, in
   the United Kingdom, two seasonal peaks are seen ([47]2). The UK picture
   reflects two dominant sources of exposure: one from animals in the late
   spring, and another from humans in the fall ([48]3).
   Close temporal clustering of seasonal peaks in diseases that share
   similar sources of exposure suggests dominant routes of transmissions.
   Peaks in water-borne cryptosporidiosis and giardiasis often cluster
   after a summer peak in ambient temperature. Such synchronization in
   disease manifestation can be governed by environmental and social
   factors. In some instances, periodicity of a given infection observed
   in a particular population may be not present in another. A seasonal
   peak in cryptosporidiosis cases observed in the general population is
   not apparent in the immunocompromized HIV-positive gay men, even though
   the incidence of cryptosporidiosis in HIV-positive population is very
   high. This suggests differences in dominant routes of transmission.
   Seasonal patterns can change over time. After intense vaccination
   campaigns in the 1950s and 1970s in the United Kingdom, the patterns of
   measles and pertussis changed, with the high rates of disease usually
   seen when children were attending school diminishing for measles and
   practically disappearing for pertusis ([49]4). Explanations for these
   phenomena remain elusive. A departure from a systematically observed
   pattern could reflect the evolution of a pathogen or a change in herd
   immunity. A simple rule to remember is that a discovery hides in
   outliers.
   Faced with an abundance of causal agents, a bare observation of a rise
   in the incidence of non-specific enteritis should be interpreted with
   caution. A seasonal pattern can represent a mix of temporal curves.
   Imagine two periodic curves of similar intensity, but one peaks in a
   spring and another in a fall; the sum of these two curves might lose
   the appearance of seasonality, covering two distinctly seasonal
   phenomena.
   Some infections are very rare. Their seasonal patterns are difficult to
   examine because the relevant data must be collected over a very long
   time and/or aggregated over large spatial units. Precision in
   evaluating seasonality can thus be jeopardized by time-dependent and/or
   space-dependent confounders.
   Seasonal fluctuations can be found beyond infectious diseases; chronic
   somatic diseases also exhibit substantial temporal variations.
   Plausibly, exacerbations in chronic conditions are driven by infectious
   agents or environmental changes. Understanding the interplay of an
   infection and a chronic disease may lead to better control for both.
     * [50] Other Sectionsv
          + [51]Abstract
          + [52]Introduction
          + [53]Notion of Seasonality
          + [54]Diseases Seasonal Patterns
          + [55]Seasonal Host Susceptibility
          + [56]Seasonality in Pathogens Survival and Transmissibility
          + [57]Disease Seasonality and Calendar Effects
          + [58]Climate Change, [dot.gif] Extreme Weather Events,
            [dot.gif] and Disease Seasonality
          + [59]Methodology in Studying Seasonality: Brining Mathematics
            and Philosophy to Public Health Thinking
          + [60]References

   Seasonal Host Susceptibility

   When the weather is seasonable and the crops ripen at the regular
   times, diseases are regular in their appearance...

   (Hippocrates. Aphorisms, III, 8)

   Poor nutrition directly affects host susceptibility. In places of food
   scarcity, researchers suspect that temporal patterns in birth weight
   and preterm delivery result from seasonal variations in food
   availability ([61]5). In general, due to a less developed immune
   system, young children are susceptible to infection; their immune
   response may be further weakened by seasonal cutbacks in essential
   micronutrients and vitamins.
   Anemnestic responses to an antigen determine whether an infection
   recurs. Short-lived immune memory together with seasonal changes in
   pathogen transmissibility contribute further to the complexity of
   seasonal patterns. Even a perfectly healthy person can experience a
   change in susceptibility to infection due to stress, injuries, or
   trauma. The probability of a marked impact of such factors on disease
   seasonality is virtually unknown.
     * [62] Other Sectionsv
          + [63]Abstract
          + [64]Introduction
          + [65]Notion of Seasonality
          + [66]Diseases Seasonal Patterns
          + [67]Seasonal Host Susceptibility
          + [68]Seasonality in Pathogens Survival and Transmissibility
          + [69]Disease Seasonality and Calendar Effects
          + [70]Climate Change, [dot.gif] Extreme Weather Events,
            [dot.gif] and Disease Seasonality
          + [71]Methodology in Studying Seasonality: Brining Mathematics
            and Philosophy to Public Health Thinking
          + [72]References

   Seasonality in Pathogens Survival and Transmissibility

   Some diseases are produced by the manner of life that is followed;
   others by the life-giving air we breathe.

   (Hippocrates. The Nature of Man, 9)

   Temperature, humidity, and precipitation -- the defining factors of
   seasons -- are important determinants of pathogens' survival. Changes
   influence pathogens' potency and life expectancy, resulting in temporal
   fluctuations in pathogens' abundance. In many instances, seasonal
   changes in pathogen survival and transmission are inseparably related
   to both biological and social aspects of our lives. They are
   synchronized by weather. High ambient temperature, for example,
   provides a supportive environment for food-borne pathogens, favoring
   their multiplication in food and on food preparation surfaces ([73]6).
   Food contamination is believed to be a significant mode of transmission
   for infections caused by Salmonella and Campylobacter ([74]7);
   therefore, during warm weather, the risk for food-borne diseases
   increases ([75]8).
   Seasonal changes in level of contamination, availability of potable
   water, sanitation and hygiene practices, as well as crowding and
   person-to-person contacts, affect pathogens' transmissibility.
   Worldwide, water use differs from season to season ([76]9). In
   temperate climates, warm weather leads to higher water consumption and
   encourages outdoor activities -- swimming, camping, and recreational
   water use. In tropical regions, contamination of surface water
   increases during wet seasons. Although spread of pathogens via food is
   certainly possible, contaminated water is the dominant source of
   exposure for enteric infections caused by protozoa Cryptosporidium and
   Giardia ([77]10 --[78]12). Depending on locality, outbreaks of
   cryptosporidiosis and giardiasis associated with drinking or
   recreational water frequently occur during warm or wet seasons
   ([79]13,[80]14).
   With the onset of cooler weather, the "heating season" marks a change
   in indoor air quality. Inadequate and poorly designed ventilation in
   crowded public places and urban transit systems may boost exposure to
   air-borne pathogens by increasing their concentration in stagnant air
   and by re-circulating contaminated air. Higher relative humidity may
   also affect the stability of air-borne droplets in which viruses travel
   from person to person.
     * [81] Other Sectionsv
          + [82]Abstract
          + [83]Introduction
          + [84]Notion of Seasonality
          + [85]Diseases Seasonal Patterns
          + [86]Seasonal Host Susceptibility
          + [87]Seasonality in Pathogens Survival and Transmissibility
          + [88]Disease Seasonality and Calendar Effects
          + [89]Climate Change, [dot.gif] Extreme Weather Events,
            [dot.gif] and Disease Seasonality
          + [90]Methodology in Studying Seasonality: Brining Mathematics
            and Philosophy to Public Health Thinking
          + [91]References

   Disease Seasonality and Calendar Effects

   You will find, as a general rule, that the constitutions and the habits
   of a people follow the nature of the land where they live.

   (Hippocrates. Air, Waters, Places, 24)

   Diseases do not watch calendars. Their incidence rises and falls
   because of changes in factors associated with the diseases. However, in
   every culture all social events are synchronized by calendars; and
   every calendar reflects the cyclic rhythm of nature.
   Traditional celebrations and gatherings observed by communities
   according to calendars affect pathogen transmission. Holidays, social
   activities, and seasonal travel are often associated with changes in
   food consumption and preparation, and are therefore associated with
   changes in disease incidence. Preparing meat on a barbecue increases
   the risk of Campylobacter infection ([92]15,[93]16) and foreign travel
   increases the risk for enteric infections. Aggregation of children in
   schools, daycare centers, and summer camps, reflecting school
   calendars, facilitates rapid exchange of pathogens. There are marked
   seasonal variations in transmission, and thus the incidence of enteric
   and respiratory infections.
     * [94] Other Sectionsv
          + [95]Abstract
          + [96]Introduction
          + [97]Notion of Seasonality
          + [98]Diseases Seasonal Patterns
          + [99]Seasonal Host Susceptibility
          + [100]Seasonality in Pathogens Survival and Transmissibility
          + [101]Disease Seasonality and Calendar Effects
          + [102]Climate Change, [dot.gif] Extreme Weather Events,
            [dot.gif] and Disease Seasonality
          + [103]Methodology in Studying Seasonality: Brining Mathematics
            and Philosophy to Public Health Thinking
          + [104]References

   Climate Change, Extreme Weather Events, and Disease Seasonality

   The changes of the seasons are especially liable to beget diseases, as
   are great changes from heat to cold, or cold to heat in any season.
   Other changes in the weather have similarly severe effects.

   (Hippocrates. Aphorisms, III, 1)

   As weather affects human health by creating favorable conditions for
   pathogen proliferation and transmission, severe weather can affect the
   timing and intensity of infectious outbreaks, and natural disasters
   lead to drastic changes in population structure and pathogen ecology.
   Catastrophic events like tsunamis, hurricanes, devastating floods, and
   heat waves that cause deaths, population displacement, and
   infrastructural damage may have dramatic effects on the incidence of
   infections and their seasonal patterns.
   Recent work has shown highly significant associations between extreme
   precipitation and water-borne disease outbreaks ([105]17). Heavy
   precipitation, rapid snowmelt, and floods flush animal wastes from the
   land into surface waters and may overwhelm drinking and wastewater
   treatment systems. The latter leads to discharges in watersheds of
   untreated human wastes. As a result, pathogens can appear in drinking
   and recreational water in very high concentrations ([106]18,[107]19). A
   rapid snowmelt, resultant runoff, and filtration system failure at the
   overloaded local drinking water treatment plant were implicated in the
   largest known water-borne outbreak of cryptosporidiosis, which occurred
   in Milwaukee, Wisconsin in 1993 ([108]20). This outbreak happened in
   April, not within the usual seasonal peak for cryptosporidiosis cases.
   A flood, which also resulted from a rapid snowmelt, has been linked
   with a similar increased incidence of diarrhea ([109]21).
   Experts expect that global climate change will increase climate
   variability and the frequency of extreme precipitation events in
   temperate regions ([110]22,[111]23). "Global warming" may also increase
   the frequency and magnitude of other extreme weather events, such as
   heat waves and droughts, and thereby have profound effects on public
   health ([112]24,[113]25). In a comprehensive study conducted in the
   United Kingdom that described a short-term link between temperature and
   food poisoning, the authors also hypothesized that climate change could
   lead to changes in rates of food poisoning ([114]26).
   Integration of environmental parameters into disease forecasting and
   warning systems could allow public health officials to alert the
   populace when specific meteorological conditions pose predictable risks
   to health ([115]27). Simple messages about proper food preparation and
   refrigeration and the risks of using contaminated recreational waters
   could, for example, be provided before, during, and after extreme
   events. Better understanding of disease seasonality would also help to
   predict outbreaks of infections triggered by climate variability.
     * [116] Other Sectionsv
          + [117]Abstract
          + [118]Introduction
          + [119]Notion of Seasonality
          + [120]Diseases Seasonal Patterns
          + [121]Seasonal Host Susceptibility
          + [122]Seasonality in Pathogens Survival and Transmissibility
          + [123]Disease Seasonality and Calendar Effects
          + [124]Climate Change, [dot.gif] Extreme Weather Events,
            [dot.gif] and Disease Seasonality
          + [125]Methodology in Studying Seasonality: Brining Mathematics
            and Philosophy to Public Health Thinking
          + [126]References

   Methodology in Studying Seasonality: Brining Mathematics and Philosophy
   to Public Health Thinking

   Desperate cases need the most desperate remedies.

   (Hippocrates. Aphorisms, I, 6)

   At first, seasonal fluctuations should be systematically described.
   This requires a framework with sound definitions and analytic tools
   suitable for routine use by public health professionals. In public
   health sciences, the existing methodology currently lacks methods and
   tests for assessing complex interactions in the time-dependent factors
   responsible for disease seasonality.
   Next, reliable data with fine temporal resolution are a must. The vast
   majority of epidemiological studies have examined seasonal patterns of
   infections using quarterly or monthly data. This coarse temporal
   aggregation can thwart an otherwise detailed, accurate, and
   comprehensive analysis of seasonal patterns and may even be misleading
   ([127]28). Examination of daily or weekly rates can substantially
   improve evaluation of seasonal curves, but a systematic approach for
   using at least weekly aggregates is needed.
   Finally, reluctance to apply sophisticated mathematical models in
   public health studies must be overcome. Underlying processes in disease
   manifestation and spread are complex and multifaceted. Causal pathways
   are often obscured. To disentangle causal effects of many factors
   within the circular processes of self-sustaining oscillations demands
   the careful building of sound conceptual models of seasonality; models
   that can be tested. The emerging fields of computational epidemiology
   and intelligent data mining will complement established work in
   philosophy of science and mathematical biology to become an essential
   part of thinking in public health and policy.
   Acknowledgments
   I thank Drs Eileen O'Neil and Beth Rosenberg for their thoughtful
   suggestions, and the support of funding agencies: the National
   Institute of Allergy and Infectious Diseases (U19AI062627), and the
   National Institute of Environmental Health Sciences (R01ES013171).
   Footnotes
   ^1Hippocrates' citations are taken from: Lloyd, GER, editor.
   Hippocratic Writings. Trans. Chadwick J and Mann WN. London: Penguin;
   1978.
     * [128] Other Sectionsv
          + [129]Abstract
          + [130]Introduction
          + [131]Notion of Seasonality
          + [132]Diseases Seasonal Patterns
          + [133]Seasonal Host Susceptibility
          + [134]Seasonality in Pathogens Survival and Transmissibility
          + [135]Disease Seasonality and Calendar Effects
          + [136]Climate Change, [dot.gif] Extreme Weather Events,
            [dot.gif] and Disease Seasonality
          + [137]Methodology in Studying Seasonality: Brining Mathematics
            and Philosophy to Public Health Thinking
          + [138]References

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     __________________________________________________________________

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     * [162]Naumova, E.

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 264. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2483431/
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