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Influenza pandemics and solar activity

Authors:
1
Influenza pandemics and solar activity
K.F. Tapping1, R.G. Mathias 2, D.L. Surkan3
1 Dominion Radio Astrophysical Observatory, National Research Council, P.O. Box 248,
Penticton, BC, V2A 6K3, Canada
2 Department of Health Care and Epidemiology, University of British Columbia, 5804
Fairview Avenue, Vancouver, BC, V6T 1Z3, Canada
3 R.B. White Clinic, 100-383 Ellis Street, Penticton, BC, V2A 4L9, Canada
Paper accepted for publication in the Canadian Journal of Infectious diseases
2
Kilbourne (1), suggested a quasi-decadal recurrence pattern to influenza pandemics. One
natural rhythm with such a time-scale, which is widely evident in many aspects of the
terrestrial environment, is the 11-year cycle of solar magnetic activity. The impact of the
solar magnetic activity cycle upon our environment are extensive and well documented
(e.g. 2, 3).
We have made a search for any correlation in the occurrence of influenza pandemics with
the solar magnetic activity cycle. We used two pandemics lists (Garrett, 4 and Potter, 5).
Good-quality observations of solar magnetic activity (numbers of sunspots) are available
back to at least 1700, which was therefore chosen as the starting point for the study.
The duration of the "11-year" solar activity cycle actually ranges from 10 to 13 years. To
compare the data we normalized the duration of each activity cycle to unity, and the
sunspot number to 100. This provided an average activity cycle for comparison purposes.
We then expressed the position of each pandemic in its (normalized) solar activity cycle
in terms of a "phase offset", given by (Year of Pandemic - Year of Maximum)/(Year of
Cycle End - Year of Cycle Start). An event at the solar maximum would have an offset of
zero, and one at solar minimum would be at an offset of plus or minus 0.5. The
pandemics in the two lists and the associated phase offsets are given in Table 1.
The phase offset values were divided into bins (-0.5 to -0.3, -0.3 to -0.1, -0.1 to +0.1,
+0.1 to +0.3, +0.3 to +0.5) and the pandemics binned according to their phase offsets.
The two distributions were scaled to have a mode of 100, and plotted with the average
activity cycle in Figure 1. There is a definite apparent tendency for pandemics to be more
likely around solar activity maxima.
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Table 1: Pandemics Since 1700 as Listed by Garrett (1994) and Potter (1998)
Pandemics Listed by Garrett-----------| Pandemics Listed by Potter------------|
Years Magnitude Phase Years Magnitude Phase
1729-30 High +0.20 1729-33 High +0.20
1732-33 High +0.50 - - -
1742-43 Moderate +0.36 - - -
1761-62 High +0.00 1761-62 Low +0.00
1767 Moderate -0.22 - - -
1775-76 Moderate -0.33 - - -
1781-82 High +0.33 1781-82 High +0.33
1788-89 Low +0.07 1788-90 Low +0.07
1800-02 Moderate -0.33 1799-1802 Moderate? +0.42
1830-33 High +0.00 1830-33 High +0.10
1837-37 High -0.10 - - -
1847-48 High -0.08 1847-48 Moderate -0.07
1850-51 Moderate +0.15 - - -
1857-58 Mild -0.27 1857-58 Low -0.27
1873-75 Mild +0.27 - - -
1889-90 High -0.33 1889-90 High -0.33
- - - 1900 Low? -0.50
1918-19 High +0.10 1918-20 High +0.10
1946 ? +0.20 1946-48 Low +0.20
1957 High +0.00 1957-58 High +0.00
1968-70 High +0.00 1968-70 High +0.00
1977 ? -0.20 1977-78 High -0.20
To estimate the probability that the association could simply be a random event, a
simulation run of one million trials was carried out. In each trial a number of events equal
to the number in the list in question (21 and 15 respectively for Garrett and Potter), were
assigned random phase offsets in the range -0.5 to +0.5 and then binned in five bins. If
bins 3 (phase offset in range -0.1 to 0.1) and bin 4 (phase offset from 0.1 to 0.3) together
4
contained at least 12 observations (Garrett) out of 21 or 9 observations out of 15 (Potter),
with no other bin containing more than 3 (Garrett) or 2 (Potter), then the trial was deemed
a success. Otherwise the trial was designated a failure.
Figure Caption: The two distributions of pandemic count versus phase offset scaled to a
peak value of 100. Pandemics listed by Garrett and Potter are shown respectively in solid
black and white. The circles connected by solid lines show an average solar activity
cycle, also scaled to have a peak value of 100.
From this simulation, we estimate that the probability of obtaining a result leading to the
reported conclusion on a random basis is less than 2%. We conclude therefore that there
is a significant probability that influenza pandemics are more likely during solar magnetic
activity maxima. The solar-environmental connection is well-established, but the factor
modulated by the Sun that affects the development of influenza pandemics is not known.
0
20
40
60
80
100
120
-0.4 -0.2 0 0.2 0.4
Phase Offset
Normalized Data
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References
1. Kilbourne ED. An Explanation of the Interpandemic Antigenic Mutability of the
Influenza Virus. Journal of Infections Diseases 1978;128:668-670.
2. Withbroe GL, Kalkofen W. Solar Variability and its Terrestrial Effects. In: Pap JM,
Frölich C, Hudson HS, Solanki SK, editors. The Sun as a Variable Star. Proceedings
of International Astronomical Union Colloquium No. 143, 1993 Jun 20-25; Boulder,
Colorado, USA. Cambridge University Press; 1994. p. 11-19.
3. Lang KR. The Sun, Earth and Sky. Springer Verlag; 1995.
4. Garrett L. The Coming Plague. Penguin Books; 1994. p. 633-637.
5. Potter CW. Chronicle of Influenza Pandemics. In: Hay AJ, Nicholson K, Webster
RG, editors. Textbook of Influenza. Blackwell Science, Oxford; 1998. p. 3-18.
... Since 1978, a series of papers in the literature have claimed to find a significant association between sunspot activity and the timing of influenza pandemics. This paper examines these analyses, and attempts to recreate the three most recent statistical analyses by Ertel (1994), Tapping et al. (2001), andYeung (2006), which all have purported to find a significant relationship between sunspot numbers and pandemic influenza. As will be discussed, each analysis had errors in the data. ...
... Using these data, other researchers have attempted statistical analyses to verify the purported association between influenza pandemics and sunspots. This analysis examines the work of researchers that claim to verify the sunspot/pandemic effect; Ertel, Tapping et al., and Yeung [25][26][27]. Two of the analyses claim that maxima in sunspot activity are associated with influenza pandemics [26,27], while another claims that both maxima and minima in sunspot activity are associated with pandemics [25]. A brief synopsis of each analysis is given below, and each is described fully in Appendix A. ...
... This analysis examines the work of researchers that claim to verify the sunspot/pandemic effect; Ertel, Tapping et al., and Yeung [25][26][27]. Two of the analyses claim that maxima in sunspot activity are associated with influenza pandemics [26,27], while another claims that both maxima and minima in sunspot activity are associated with pandemics [25]. A brief synopsis of each analysis is given below, and each is described fully in Appendix A. ...
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Since 1978, a series of papers in the literature have claimed to find a significant association between sunspot activity and the timing of influenza pandemics. This paper examines these analyses, and attempts to recreate the three most recent statistical analyses by Ertel (1994), Tapping et al. (2001), and Yeung (2006), which all have purported to find a significant relationship between sunspot numbers and pandemic influenza. As will be discussed, each analysis had errors in the data. In addition, in each analysis arbitrary selections or assumptions were also made, and the authors did not assess the robustness of their analyses to changes in those arbitrary assumptions. Varying the arbitrary assumptions to other, equally valid, assumptions negates the claims of significance. Indeed, an arbitrary selection made in one of the analyses appears to have resulted in almost maximal apparent significance; changing it only slightly yields a null result. This analysis applies statistically rigorous methodology to examine the purported sunspot/pandemic link, using more statistically powerful un-binned analysis methods, rather than relying on arbitrarily binned data. The analyses are repeated using both the Wolf and Group sunspot numbers. In all cases, no statistically significant evidence of any association was found. However, while the focus in this particular analysis was on the purported relationship of influenza pandemics to sunspot activity, the faults found in the past analyses are common pitfalls; inattention to analysis reproducibility and robustness assessment are common problems in the sciences, that are unfortunately not noted often enough in review.
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... Some previous researches reported that Influenza epidemic changes had been 1.3 times more frequent in the years of the sudden increase in solar activity. Moreover, the cyclic variations of Influenza every 2-4 years can be associated with the frequency of such sudden changes [9,10]. ...
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... These authors also suggested that the cyclic variations of 2-4 years in flu epidemics could be associated with the frequency of such sudden changes, i.e. the so called 'reference points' along the 11-year sunspot cycle. Recent calculations indicated that such temporal appearances of flu epidemics [17] were very likely when taking into account all cycles together since the year 1700 -Tapping and collaborators [17] clearly illustrated by phase offset that five epidemic peaks occurred from 'minimum' to 'minimum' (inclusive) along the 11-year sunspot cycle. ...
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The Coming Plague. Penguin Books
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