RESEARCH Data Management and Statistical Analyses Data were double-entered and imported into STATA version 10 (StataCorp LP, College Station, TX, USA). Du- plicate OD results were averaged and normalized against the positive control sample on each plate. A cutoff value above which samples were considered antibody positive was deﬁned by using a mixture model as described (17). Distribution of normalized OD values was ﬁtted as the sum of 2 Gaussian distributions by using maximum-likelihood methods. The mean OD of the Gaussian distribution cor- responding to the seronegative population plus 3 SD val- ues was used as the cutoff value for seropositivity (J. Cook et al., unpub. data). A separate cutoff value was generated for each antigen (MSP-119 and AMA-1) for each species (P. vivax and P. falciparum). The seroconversion rate was estimated by ﬁtting a simple reversible catalytic model to the measured seroprevalence by age in years by using max- imum-likelihood methods. The serologic-derived annual EIR was then estimated by using the MSP-119 seroconver- sion rate and a calibration curve derived from determined values (11).The titer of antibody responses was estimated by using the formula dilution/[maximum OD/(OD test se- rum – minimum OD) – 1]; the median titer and interquartile range (IQR) are given. Because of low overall antibody prevalence, antibody responses were combined by species to determine the presence of any reactivity against P. falci- parum or P. vivax. As a quantitative measure of reactivity to either malaria species, the highest titer in the MSP-119 and AMA-1 ELISAs was used. Factors associated with P. falciparum or P. vivax se- roreactivity were determined for each village separately by using generalized estimating equations adjusting for corre- lation between observations from the same household. The following factors were tested in the models: age in years, distance to the nearest seasonal river (in 100 m), distance to the nearest enclosure of livestock (in 100 m), number of household members, number of houses in a 100-m radius, rooﬁng material, wall material, ﬂoor material, travel histo- ry, recent or regular bed net use, and an indicator of house- hold wealth. The household wealth index was calculated on the basis of principal component analysis on characteristics such as ownership of a television, radio, telephone, bicycle, motorbike, cattle, and access to electricity (19). Variables that were signiﬁcant at p = 0.10 in univariate analyses were added to the multivariate model and retained in the ﬁnal multivariate model if their association with immune re- sponses was statistically signiﬁcant at p<0.05. For detection of spatial clusters in immune responses, age-adjusted log10-transformed ODs were calculated as de- scribed by Wilson et al (20). First, Loess lines were ﬁtted to scatter plots of age against log-transformed ODs for each antigen separately. For P. falciparum MSP-119 and P. vivax AMA-1, the linear regression was split at 49 and 46 years of age. Log-transformed ODs were adjusted for age by linear regression. SaTScan software (21) was used for detection of spatial clustering in log-transformed age-adjusted OD values by using the normal probability model. A circular- shaped window was used to systematically scan the area of each village separately; statistical signiﬁcance of the clus- ters was explored by using 999 Monte Carlo replications to ensure adequate power for deﬁning clusters. The upper limit was speciﬁed as 50% of the village population. Signiﬁcant increases in ODs were detected by calculation of the likeli- hood ratio for each window. Only clusters were reported that appeared for MSP-119, AMA-1, and their combined age-adjusted ODs. Maps were made by using ArcGIS ver- sion 9.1 (Environmental Systems Research Institute). Results The 2 cross-sectional surveys were completed in March (dry season, n = 1,178) and August–September (wet season, n = 1,128) 2008. These surveys were characterized by a clear seasonality with no rainfall detected during No- vember 2007–March 2008 and a median monthly rainfall of 114.5 mm in April–August 2008. None of the survey participants were positive by rapid diagnostic test, and P. falciparum or P. vivax parasites were not detected on any of the examined blood slides (Table 1). Available hospital records indicated 2/283 slide-conﬁrmed, RDT-conﬁrmed malaria cases in the study area in July and August 2008 (T. Bousema, unpub. data). Travel history was not avail- able for these persons. During August–September 2008, a total of 464 potential breeding sites were examined in Xu- unshaley (n = 40), Badahabo (n = 42), and Ceel-Bardaale (n = 382). In Ceel-Bardaale, 158 Anopheles mosquito larvae were found at 81 of 382 examined sites. In the 2 other vil- lages, no Anopheles larvae were observed. Malaria Exposure Assessed by Immunologic Methods In August–September 2008, serum samples were col- lected from 1,128 persons in Xuunshaley (n = 271), Ba- dahabo (n = 160), and Ceel-Bardaale (n = 697) (Table 2). In the 3 months before the survey, 19 persons reported having traveled to areas that are known to have higher malaria endemicity for a median of 4 (IQR 2–20) days. Persons who reported traveling to areas highly endemic for malaria were more likely to have a positive response to P. falciparum (odds ratio [OR] 2.62, 95% conﬁdence interval [CI] 0.98–7.01, p = 0.054) but not to P. vivax (OR 1.18, 95% CI 0.42–3.32, p = 0.75), after adjustment for age and village of residence. These 19 persons were excluded from further analyses. All antigens tested showed a clear increase in sero- prevalence with a person’s age (Figure 1). The data did not suggest a recent reduction in malaria transmission inten- sity (14). The EIR for P. falciparum based on seroconver- 394 Emerging Infectious Diseases • www.cdc.gov/eid • Vol. 16, No. 3, March 2010