PERSPECTIVE Data manipulation and statistical transformation were per- formed in Excel 2000 (Microsoft Corp., Seattle, WA) unless otherwise stated. Monthly mean adult (>15 years) and child (<15 years) admissions were calculated and displayed as spi- der plots. The time series of admissions at each site was also plotted with a 25-point (month) moving average of the series to show more clearly the long-term movement in these data. For each hospital, we performed trend analysis through linear regression of the malaria admission data against a trend vari- able (observation month number/12). The coefficient of trend therefore indicates the annual trend (positive = increasing in time, negative = decreasing in time, zero = a stationary series). Such regression models are sensitive to seasonal variation, outliers, and heteroscedasticity (a term which refers to situa- tions in which the variability of the residuals is not constant). To show the long-term trend unambiguously, seasonality was removed from each series by using an additive seasonal decomposition procedure (37,38) and the residuals were checked for normality and heteroscedasticity in SPSS version 11 (SPSS Inc., Chicago, IL). Furthermore, we applied a proximate measure of transmis- sion stability through a comparison of the numbers of adults to children with malaria admitted to the three hospitals. This adult:child ratio (ACR) of cases was calculated from total adult and child admissions for the duration of the available records. In areas of stable transmission, we assumed that the risks for complicated malaria in adulthood would be signifi- cantly lower than the risks in childhood; this assumption was based on expectations of the age distribution of malaria cases under varying transmission intensities (39–41). Conversely, areas of infrequent parasite exposure lend themselves to equiv- alent risks in adults and children. As such, an ACR derived from hospital admissions approaching unity would suggest an increasing tendency toward unstable transmission, assuming that the typical age-structured population pyramid for develop- ing country and rural communities prevailed (36) and that there were no age-dependent biases in attendance rates. Results Time series of malaria admissions from 1980 to 1999, 1987 to 2000, and 1981 to 2000 were recorded for Kilgoris, Kisii, and Tabaka hospitals, respectively. These clinical data represent 171,312 admissions with a primary, coprimary, or coincidental diagnosis of complicated malaria over a total of 54 admission years. The Kilgoris, Kisii, and Tabaka hospitals managed an average of 2,243; 9,191; and 3,929 malaria admis- sions per year, respectively, for the duration over which records were available (Table 1). Throughout the study period, the frequency of childhood admissions was on average twice that of adult admissions (Table 1; Figure 1a,c,e). The average ACR calculated for all months was 0.46 for Kilgoris (14,079/ 30,793), 0.52 for Kisii (44,043/84,648), and 0.42 for Tabaka (23,692/55,871). The ACRs derived from monthly admissions are relatively constant throughout the duration of observation (Figure 1b,d,f). Several anomalies in these data were evident, however, particularly at Tabaka in 1985 and Kisii in 1999; we did not identify any obvious explanation for these exceptions in the time series, although they did not occur during periods of major epidemics at the sites (32). In further analysis, we focused on the primary pediatric clinical case data. We consid- ered data from children to be more likely to give an accurate picture of local malaria transmission, as they are less likely to have developed functional immunity or to have traveled and acquired infections elsewhere. The long-term data used in this analysis indicate that clini- cal cases of malaria occur every month at each hospital; acute seasonal peaks occur in June and July (Figure 1a,c,e). On aver- age, one third of the total annual child malaria admissions were concentrated in these 2 months (35%, 32%, and 27% for Kilgoris, Kisii, and Tabaka, respectively). The trends and interannual variation in pediatric malaria admissions at each facility are shown in Figure 2a–c. These graphs demonstrate clear, substantial between-year variation in child malaria admissions. The 2 years of highest case pre- sentations were 1994 and 1998 for Kilgoris, 1996 and 1997 for Kisii, and 1997 and 1996 for Tabaka (the moving average line in Figure 2a–c clearly shows these years). Although Kisii and Tabaka showed similarities, little coherence occurred in peak years of child admissions between these sites and Kilgoris, despite their close geographic proximity. At each facility, pedi- atric malaria admissions rose substantially over the period of observation (Table 2). In Kilgoris, deseasonalized child malaria admissions rose from 56 in January 1980 to 200 in December 1999, an increase of 256% over 20 years (p<0.001). Similar trends were observed at Kisii (32% increase from Jan- uary 1987 through December 1999; p=0.019) and Tabaka (91% increase from January 1980 through December 1999; p<0.001). In parallel with these significant rises in number of cases, estimates of the annual rate of natural population growth in the communities around the hospitals suggest that child popula- tions have increased by 215%, 49%, and 77% during the same period at Kilgoris, Kisii, and Tabaka, respectively. Discussion We examined longitudinal, age-structured, clinical data on the frequency of admission for severe and complicated P. falci- parum malaria at the three hospitals located above 1,600 m in the highlands of western Kenya. These data provided an opportunity to explore in more detail several generally accepted positions about the clinical epidemiology of malaria at high altitude in East Africa. In these time series, the increased malaria admission at each of the three hospitals was concentrated in children <15 years of age (approximately two thirds of all admissions). Given the equivalent sizes of at-risk population below and above 15 years of age (36), one must assume that adults have developed a degree of functional immunity to the severe 544 Emerging Infectious Diseases • Vol. 8, No. 6, June 2002