Sub-Saharan Africa has the highest incidence of malaria caused by Plasmodium falciparum. Almost all areas where P. falciparum parasite prevalence is >50% in the general population are located in Africa ( 1 ). However, malaria is not uniformly distributed ( 1 , 2 ) and many parts of Africa are characterized by low transmission intensity of malaria ( 1 ). These areas are considered suitable for intensive malaria control and disease elimination ( 3 , 4 ). Assessing malaria transmission intensity and evaluating interventions are complicated at low levels of malaria transmission. Assessing transmission intensity directly by determining the exposure to malaria-infected mosquitoes (entomologic inoculation rate [EIR]) is difficult when mosquito numbers are low, sometimes below the detection limits of commonly used trapping methods ( 5 , 6 ), and spatial and temporal variations in mosquito densities necessitate long-term intensive sampling ( 5 , 7 , 8 ). Determination of malaria parasite prevalence in the human population is a commonly used alternative ( 9 ), but it also becomes less reliable as an indicator of transmission intensity when endemicity is low ( 3 , 9 , 10 ). Therefore, an alternative method is needed to assess transmission intensity, evaluate interventions, and obtain information for control programs in areas of low endemicity. Prevalence of antibodies against malaria parasites has been explored as a means of assessing malaria transmission intensity ( 11 – 13 ). Antibody seroconversion rates are less susceptible to seasonal fluctuations in malaria exposure ( 11 , 12 ), show a tight correlation with EIR ( 12 , 13 ), and show potential to detect recent changes in malaria transmission intensity ( 14 ). Serologic markers could be particularly useful in areas of low endemicity, where it may be easier to detect relatively long-lasting antibody responses than a low prevalence of malaria infections in the human population or infected mosquitoes. We used serologic markers of exposure to determine spatial variation in malaria transmission intensity in an area of low endemicity in Somalia ( 15 ). Methods Study Area This study was conducted in the Gebiley District in Somaliland in northwestern Somalia. The district has a predominantly arid landscape with a few seasonal rivers and patches of irrigated farmlands. It is an area of intense seasonal rainfall with an average annual precipitation of 59.9 mm (2004–2007) and 2 peaks in rainfall in April and August. Three moderately sized communities were randomly selected from census maps by using spatial random sampling techniques in Arcview version 3.2 (Environmental Systems Research Institute, Redlands, CA, USA) ( 16 ). These communities were the villages of Xuunshaley (9.72140°N, 43.42416°E), Badahabo (9.68497°N, 43.65616°E), and Ceel-Bardaale (9.81777°N, 43.47455°E). The research protocol was reviewed and approved by the Research Ethics Review Committee of the World Health Organization (RPC246-EMRO) and the Ethical Committee of the Ministry of Health and Labor, Republic of Somaliland. Data Collection Two cross-sectional surveys were conducted. The first survey was conducted in March 2008 to determine parasite carriage at the end of the dry season ( 16 ). The purpose of the survey and the procedures were first discussed with the clan elders; thereafter, each household was visited, and informed consent was sought from each head of household. Households that agreed to participate were geolocated by using a global positioning system (Garmin eTrex; Garmin International, Inc., Olathe, KS, USA), and information was collected on demographic characteristics, bed net use, and travel history of the participants. Distance to seasonal rivers or other water bodies and distance to the nearest livestock enclosure was determined by using the global positioning system. Individual written consent was obtained from all literate adults; illiterate adults provided consent by a thumbprint in the presence of an independent literate adult witness. For children 37.5°C at time of survey 0.8 (10/1,177) 1.1 (12/1,124) Positive rapid diagnostic test result 0 (0/1,173) 0 (0/1,106) Plasmodium falciparum parasite prevalence† 0 (0/1,173) 0 (0/1,106) P. vivax parasite prevalence† 0 (0/1,173) 0 (0/1,106) *IQR, interquartile range (25th−75th percentile). Values are % (no. positive/no. tested) unless otherwise indicated.
†Determined by screening 200 high-power microscopic fields. Malaria Exposure Assessed by Immunologic Methods In August–September 2008, serum samples were collected from 1,128 persons in Xuunshaley (n = 271), Badahabo (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. Table 2 Immune responses against Plasmodium falciparum and P. vivax in study participants, by village, Somalia, 2008* Characteristic Village† p value‡ Xuunshaley Badahabo Ceel-Bardaale No. persons 271 160 697 Median age, y (IQR) 20 (7–40) 17.5 (5–35) 13 (6–35) 0.04 P. falciparum immune response Combined 9.4 (23/244) 21.7 (30/138) 20.4 (126/619) 0.58). Figure 1 Seroprevalence data for antibodies against A) Plasmodium falciparum merozoite surface protein 119 (MSP-119), B) P. falciparum apical membrane antigen 1 (AMA-1), C) P. vivax MSP-119, and D) P. vivax AMA-1 by age in the study population, Somalia, 2008. Gray lines indicate 95% confidence intervals. Seroconversion rates (95% confidence intervals) were as follows: P. falciparum MSP-119 0.0082 (0.0068–0.097); AMA-1 0.0053 (0.0042–0.0066); P. vivax MSP-119 0.0086 (0.0055–0.0133); AMA-1 0.0075 (0.0050–0.0112). Spatial Patterns in Seroreactivity P. falciparum antibody prevalence was 9.4% (23/244) in Xuunshaley, 21.7% (30/138) in Badahabo (p = 0.001), and 20.4% (126/619) in Ceel-Bardaale (p 7 km apart and were therefore likely to have their own transmission characteristics. In all 3 villages, P. falciparum antibody prevalence increased with age (Table 3). For Ceel-Bardaale, an independent negative association was found between P. falciparum antibody responses and distance to the nearest seasonal river (OR 0.94, 95% CI 0.88–0.99, p = 0.03) after adjustment for age and correlation between observations from the same household. Within the group of persons who had a positive antibody response against P. falciparum, the titer increased with age in Xuunshaley (β = 1.74, SE = 0.81, p = 0.031) and Ceel-Bardaale (β = 11.48, SE = 3.49, p = 0.001). Table 3 Factors associated with Plasmodium falciparum or P. vivax seroprevalence in 3 villages, Somalia, 2008* Village Factor P. falciparum P. vivax OR (95% CI) p value OR (95% CI) p value Xuunshaley Age 1.02 (1.00–1.04) 0.029 1.04 (1.02–1.06) 200 to P. falciparum (n = 17) or P. vivax (n = 6). The presence of strong antibody responses (indirect fluorescent antibody titer >20) in children <15 years of age was used as evidence for active transmission of malaria in area of low endemicity in Middle America (Costa Rica) ( 25 , 26 ). The indication for local malaria transmission we provide in this study is relevant for local health workers who should be prepared for fever investigations with standard parasitologic techniques (microscopy and RDT). Malaria should be considered as a plausible cause of febrile illness, particularly in an epidemic form. Low-intensity malaria transmission and the presence of malaria vectors make the area susceptible to malaria epidemics, which can have a high mortality rate in resource-poor areas ( 29 ), especially if outbreak detection systems ( 30 ) are not feasible because of a poor health infrastructure. We observed heterogeneity in seroreactivity within the study area. Although the 3 villages had low transmission intensity and showed no difference in microscopic parasite carriage, serologic markers showed variation in malaria exposure. Antibody prevalence against P. falciparum and, less markedly, P. vivax were lowest in Xuunshaley, which was furthest from seasonal rivers. Combined P. falciparum MSP-119 and AMA-1 antibody prevalence was 2× higher in Badahabo and Ceel-Bardaale than in Xuunshaley. SaTScan analysis indicated heterogeneity in malaria exposure at a microepidemiologic level. We observed 1 statistically significant cluster of persons with higher seroreactivity against P. falciparum and 1 with higher seroreactivity against P. vivax. In Ceel-Bardaale, where households were scattered along a delta of seasonal rivers, antibody prevalences to P. falciparum and P. vivax were negatively associated with distance to the nearest river. In several areas of higher endemicity, distance to the nearest body of water has been related to malaria incidence ( 5 , 20 , 31 , 32 ) and immune responses ( 20 , 32 ). No other factors were significantly related to malaria-specific immune responses. Our data indicate that serologic markers can be used to determine variation in transmission intensity at levels of malaria transmission that are too low for sensitive assessments by microscopy, RDT, or entomologic tools. The sensitivity of serologic analysis to detect small-scale differences in transmission intensity may prove extremely useful in evaluating malaria control programs in areas where conventional malariometric markers fail. It may also provide vital information on which areas are most likely to be receptive to transmission if malaria epidemics were to occur.
