Comparative study of meningitis dynamics across nine African countries: a global perspective

Abstract

Background: Meningococcal meningitis (MM) represents an important public health problem especially in the "meningitis belt" in Africa. Although seasonality of epidemics is well known with outbreaks usually starting in the dry season, pluri-annual cycles are still less understood and even studied. In this context, we aimed at study MM cases time series across 9 sahelo-sudanian countries to detect pluri-annual periodicity and determine or not synchrony between dynamics. This global and comparative approach allows a better understanding of MM evolution in time and space in the long-term.

Results: We used the most adapted mathematical tool to time series analyses, the wavelet method. We showed that, despite a strong consensus on the existence of a global pluri-annual cycle of MM epidemics, it is not the case. Indeed, even if a clear cycle is detected in all countries, these cycles are not as permanent and regular as generally admitted since many years. Moreover, no global synchrony was detected although many countries seemed correlated.

Conclusion: These results of the first large-scale study of MM dynamics highlight the strong interest and the necessity of a global survey of MM in order to be able to predict and prevent large epidemics by adapted vaccination strategy. International cooperation in Public Health and cross-disciplines studies are highly recommended to hope controlling this infectious disease.

Figure 1

Wavelet analyses of meningitis time series with annual data from 1939 to 1999 across 9 African countries: (A) Burkina Faso, (B) Chad, (C) Sudan; (D) Nigeria, (E) Niger, (F) Mali, (G) Ghana, (H) Togo, (I) Benin. For each country (i) left panel represents the time series of cases in the country (ii) middle panel represents the wavelet power spectrum of meningitis cases (detrended); colours code for increasing spectrum intensity, from blue to red; dotted lines show statistically significant area (threshold of 5% confidence interval); the black curve delimits the cone of influence (region not influenced by edge effects) (iii) right panel corresponds to the mean spectrum (in blue) with its significant threshold value of 5% (black line).

Figure 2

Wavelet coherence and phase analyses of meningitis time series between countries. The left or top panel represents the wavelet coherence (x-axis: year, y-axis: period, in years). Blue, low coherence; red, high coherence. The dotted lines show the α = 5% and α = 10% significance levels based on 500 bootstrapped series. The cone of influence (black curve) indicates the region not influenced by edge effects. The right or bottom panels represent the phase analyse between two countries (in blue and red), based on wavelets for a given periodic band (white band). Green boxes represents the period of time where coherency is significant, i.e. when the interpretation of analyse is possible. Blue lines: first country (name in blue); red lines: second country (name in red); dashed lines: time delay between the two oscillating components (ΔT).

Figure 3

Wavelet coherence and phase analyses of meningitis time series between countries. The left or top panel represents the wavelet coherence (x-axis: year, y-axis: period, in years). Blue, low coherence; red, high coherence. The dotted lines show the α = 5% and α = 10% significance levels based on 500 bootstrapped series. The cone of influence (black curve) indicates the region not influenced by edge effects. The right or bottom panels represent the phase analyse between two countries (in blue and red), based on wavelets for a given periodic band (white band). Green boxes represents the period of time where coherency is significant, i.e. when the interpretation of analyse is possible. Blue lines: first country (name in blue); red lines: second country (name in red); dashed lines: time delay between the two oscillating components (ΔT).

Figure 4

Schematic illustration of the synchrony results obtained (A) before 60's and (B) after 70's for the 9 African countries under study. Each arrow corresponds to significant coherency between two countries: red arrows show the sense of disease spread and blue arrows symbolize synchrony between the 2 countries.