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PRINCIPLES AND PRACTICE OF CLINICAL PARASITOLOGY
Fig 2.7 Frequency distribution of differences in infection intensity from host-parasite systems involving fish, bird and mammal hosts. Arrows indicate the arithmetic mean difference. Values to the left of the broken line represent greater intensity in males, while values to the right indicate greater intensity in females. From Poulin (1996), with permission of the University of Chicago Press
The results of the study indicated a tendency for infection prevalence to be higher in males in many types of host-parasite associations, particularly for nematode infections in birds and mammals. The male bias in prevalence was also apparent in birds and mammals when all parasite species comparisons were pooled (birds X = —5.43,
df=90, t (two-tailed to compare estimated value against expected mean of zero)=3.970, ^<0.001; mammals, X= — 3.78, df=109, t=2.993,^<0.005). There were also more negative (male-biased) than positive (female-biased) differences in prevalence among bird and mammal hosts (birds: 63 vs. 25, X2=16.41,^<0.001; mammals: 64vs. 41, %2=5.04,
^<0.025; see Figure 2.6). By contrast, intensity of infection showed no clear sex bias except for nematodes parasitizing mammals, differences in infection intensity once again being significantly male-biased. When all comparisons were poled by host type, a male bias was again observed only in mammals X = — 0.69, df=58, t=4.086,^<0.001). The frequency of male-biased differences were also more common than female-biased ones (37 vs. 21, x2=4.41, ^<0.05; Figure 2.7).
The Association between Microfilaraemia and Chronic Disease in Lymphatic Filariasis
A long-held tenet in the epidemiology of lymphatic filariasis, the major mosquito-borne helminth infection of humans, is that patent infection (microfilaraemia) is negatively related to chronic disease. In conjunction with immunological findings (Ottesen, 1992), this perception had led to the conventional explanation that chronic pathology patients (i.e. those with lymphoedema and hydrocele) are negative for patent infection because of re-expression of antiparasite immunity.
Michael and colleagues (1994) employed metaanalysis techniques to examine the empirical evidence for the relationship between an individual’s microfilarial and disease status using published data from field studies carried out in a variety of bancroftian filariasis endemic areas. The aims were two-fold; first, to determine whether there is a negative association between the occurrence of chronic disease (hydrocele, lymphoedema and the two combined) and patent infection, as suggested by the immunological model; second, to determine whether the form of this association varies between studies, and whether this heterogeneity is attributable to variations in the local infection prevalence, as suggested by a dynamic model of disease (Bundy et al., 1991).
The analysis required information on the numbers of individuals in a given community with (a) microfilaraemia (mf) alone, (b) disease alone and (c) both mf and disease signs. An extensive literature survey located a total of 25 studies meeting this data requirement, although only 14 studies provided enough information to
undertake separate analyses for hydrocele and lymphoedema. These surveys encompassed the major filariasis endemic regions (Indian subcontinent, Africa, the South Pacific islands and Brazil) and vector species, as well as a broad range of local infection prevalences. For each community, the association between mf and clinical disease was assessed via the 2x2 contingency table using odds ratio analysis (Fleiss,
1993). The odds ratio (OR) is a measure of the degree of association between mf and disease status, and denotes the odds of disease occurring in mf-positives relative to mf-negatives. The x2 test is employed as a test of independence, an OR of 1 indicating an equal chance of disease in mf-positives and mf-negatives. The immunological model of filarial infection and disease implies a significantly lower odds of disease in mf-positives (OR less than 1). A fixed effects meta-analysis was undertaken to compare and aggregate results from different studies and to evaluate the global evidence for the observed association between mf and disease. Succinctly, let 0I be the odds of disease occurring in mf-positives relative to mf-negatives, and let wi denote the reciprocal of its variance in the ith study (see standard formulae given in Hedges and Olkin, 1985; Fleiss, 1993). Then a good estimator of the assumed common underlying effect size is:
0 = E 0,w,/E wi (4)
With an approximate 95% confidence interval for the estimate given by:
0 ± 1.96V( 1/Ewi) (5)
Michael and colleagues (1994) also tested for the existence of significant between-study heterogeneity in the relationship by constructing the statistic:
Q = £w№ - 0)2 (6)
When effect sizes are homogeneous, Q follows a X2 distribution with (k—1) degrees of freedom, where k denotes the number of studies.