Cyclic patterns of malaria incidence in Burundi

Dimitrov, Borislav D., Valev, Dimitar, Werner, Rolf and Atanassova, Penka A. (2011) Cyclic patterns of malaria incidence in Burundi. Central European Journal of Biology, 6 (1), 58-67. (doi:10.2478/s11535-010-0099-9).

Abstract

Best available descriptions of malaria incidence and mortality dynamics are important to improve and evaluate the implementation of programs to monitor (e.g., remote sensing) and control disease, especially in endemic zones. High-frequency (e.g., semi-annual and seasonal) cycles in malaria incidence have been observed in various countries and they coincide with cycles in the natural environment (e.g., temperature, heliogeophysical activity, etc.). However, neither trend nor cyclical oscillations beyond a 6-month (0.5-year) period for this vector-borne disease were reported in a recent analysis on monthly notifications in Burundi for the years 1997–2003. Since the examination of graphical plots indicated an eventual existence of trans-year (multiannual) variations, we further analyzed the same data in more detail. Here we explore whether low-frequency cycles (beyond seasonality) might exist (e.g., trans-year cycles with periods of 13–24 months or longer). Monthly incidence rate per 100 inhabitants from the Province of Karuzi, Burundi, over the years 1997–2003 was analysed. The exploration of underlying chronomes (time structures) was done by linear and non-linear parametric regression models, autocorrelation, spectral analysis (e.g., fast Fourier transforms), periodogram regression analysis (PRA) and wavelet transform (WT). By using a periodogram regression analysis, we describe a multicomponent cyclic chronome with periods T>12 months (19 and 86 months, all at P<0.05). Notably, the strongest cyclic pattern in the periodogram of the detrended malaria rates (whereas the peak was suppressed and beyond the semi-annual cycle of 6 months) was ?1.5–1.6 years (T=19.0 months, R=0.32). A dynamic pattern of “shortening” of the length (period) of the cycles was observed during the pre-epidemic interval (from 8–9 to 5–6 months and from 20–22 to 16–18 months in years 1997–2000) that can be used to anticipate a forthcoming incidence increase and epidemic levels of malaria at a regional level. Indeed, these cycles in malaria incidence correspond to cyclic components of heliogeophysical activity (HGA) such as the sunspot cycle impulses of 0.5–2.0 years as well as the quasi-biennial solar magnetic cycle of 1.5–2.5 years and further, detailed analyses are warranted to investigate such relationships. A multicomponent dynamic cyclical pattern of malaria incidence variations in Burundi (1997–2003) exists thus allowing further, more specific analyses and modelling as well as correlations with similar environmental cycles to be explored. These results might also contribute to better estimates for forecasting, prevention and understanding of malaria dynamics and aetiology

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