Surveillance for malaria elimination in Swaziland: A national cross-sectional study using pooled PCR and serology

Background: To guide malaria elimination efforts in Swaziland and other countries, accurate assessments of transmission are critical. Pooled-PCR has potential to efficiently improve sensitivity to detect infections; serology may clarify temporal and spatial trends in exposure. Methodology/Principal Findings: Using a stratified two-stage cluster, cross-sectional design, subjects were recruited from the malaria endemic region of Swaziland. Blood was collected for rapid diagnostic testing (RDT), pooled PCR, and ELISA detecting antibodies to Plasmodium falciparum surface antigens. Of 4330 participants tested, three were RDT-positive yet false positives by PCR. Pooled PCR led to the identification of one P. falciparum and one P. malariae infection among RDT-negative participants. The P. falciparum-infected participant reported recent travel to Mozambique. Compared to performing individual testing on thousands of samples, PCR pooling reduced labor and consumable costs by 95.5%. Seropositivity was associated with age ≥20 years (11·7% vs 1·9%, P<0.001), recent travel to Mozambique (OR 4.4 [95% CI 1.0-19.0]) and residence in southeast Swaziland (RR 3.78, P<0.001). Conclusions: The prevalence of malaria infection and recent exposure in Swaziland are extremely low, suggesting elimination is feasible. Future efforts should address imported malaria and target remaining foci of transmission. Pooled PCR and ELISA are valuable surveillance tools for guiding elimination efforts. We aimed to measure and describe the burden of malaria in Swaziland as relevant to planning for malaria elimination. We hypothesized that compared to using RDT, use of pooled-PCR and serology would improve sensitivity and efficiency for detection of infections and use of serology would clarify temporal and spatial trends in exposure. The historically malaria endemic eastern part of the country was included. Based on the ecological and administrative subdivisions of the country, census enumeration areas (EAs) were arranged into four strata. Of 598 EAs, 172 were randomly selected based on probabilities proportional to population size. Geo-coordinates of all households within selected EAs were recorded [27], [28]. Initially, 15 households were randomly selected within each EA; due to time and budget constraints, ten households were targeted as the study progressed. An MIS with a stratified two-stage cluster sample, cross-sectional design was used to generate representative estimates of intervention coverage and malaria disease burden. Given Swaziland's goal of elimination, several modifications were made to the traditional MIS design [6]. Intervention coverage and parasite prevalence were assessed in all age groups, not just children less than five years of age and women of reproductive age. Additional questions about travel in 2010 and residence were included, and microscopy and hemoglobin testing were excluded in favor of RDT, pooled PCR, and serology. Data and sample collection took place April to May of 2010, near the end of the annual high transmission season. A household questionnaire was administered to the household head or other consenting adult. A women's questionnaire was administered to women 15 to 49 years of age. A single finger prick was performed to collect blood for RDT (First Response Malaria Ag P. falciparum HRP2 Detection Rapid Card Test, Premier Medical Corporation Ltd) and Whatman 903 filter paper. Participants testing positive by RDT were transported to the nearest health facility for care. Blood spots were dried for at least three hours and stored in individual plastic bags with desiccant at ambient temperature. They were transferred to 4°C within one week and to −20°C within one month. In duplicate, dried blood spots from RDT-positive participants were individually chelex extracted then tested by PCR using nested PCR targeting the cytochrome b gene [9]. Samples from RDT-negative participants were tested using a three-stage PCR-based pooling strategy as previously described [9], [29]. Briefly, samples were first tested in master pools of 25. Positive master pools were divided and tested into sub pools of five, with positive sub pools tested as individual samples. At each stage, DNA was chelex extracted from pooled or individual dried blood spots, and then tested using nested PCR targeting the cytochrome b gene. In pooled stages, controls reflected the test pool size, e.g. controls for the master pool stage consisted of one punch from a laboratory generated dried blood spot (parasite density 100 parasites/µL) mixed with 24 negative spots. To determine species, PCR-positive samples underwent an AluI restriction digestion and were compared to digestion patterns of known controls [30]. A sub-sample of all participants with a dried blood spot was selected for serologic testing. Those less than one year of age were excluded due to potential persistence of maternal antibodies. All participants one to nine years of age were included because results in this age group were expected to be most reflective of recent changes in transmission. Based on reported declines in incidence, age-stratified analyses were expected to be powered by a lower seroprevalence in younger age groups. Therefore, participants ten to 49 years of age were randomly sampled by district based on the maximum number of participants in the younger age categories. Participants 50 years of age and older were excluded. ELISA assays were performed similarly to previously described methods [31]. A 3 mm punch was excised from the dried blood spot and antibodies were eluted overnight in 240 µL phosphate buffered saline with 0.05% Tween 20 (PBS-T), which was also used for all washing steps. Elutes were assayed in duplicate for antibodies against Plasmodium falciparum FVO strain blood stage antigens merozoite surface protein-1 (MSP-142), and apical membrane antigen-1 (AMA-1), provided by Walter Reed Army Institute of Research [32]. High absorbance plates (Immulon 4HX) were coated with 75 µL of antigen at 0.5 µg/mL overnight. Plates were washed and then blocked using 150 µL of 5% Blotto, non-fat milk in phosphate buffered saline. After washing, plates were incubated with 75 µL of elutes as well as titrations of pooled serum from previously infected participants in Kampala, Uganda. After another washing step using PBS-T, plates were incubated with 75 µL of antihuman IgG antibody (AP-conjugated AffiniPure Goat Anti-Human IgG, Jackson Immunoresearch). After a final washing step, 75 µL of substrate (BluePhos Microwell Phosphatase Substrate System, KPL) was added and optical density detected using Versamax ELISA reader (Molecular Diagnostics). The sample size was generated to provide an estimate of insecticide-treated bed net (ITN) use in children less than five years of age. Based on previous surveys, response rate and design effect were estimated at 90% and 1.3, respectively, allowing for a sampling error of 12% [33]. With the average number of children under five per household being 0.13, 2500 households were targeted. Survey data were entered into personal digital assistants (PDAs) and downloaded into Microsoft Access (2007). Analyses were performed using SAS (version 9.2) and STATA (version 11.0). Point estimates and confidence intervals were calculated incorporating survey procedures and weights to adjust for multi-stage clustering and changing selection probability. For serologic analyses, raw optical densities were standardized by dividing values by a positive control on all plates. Samples with a coefficient of variation >0.3 between duplicates were repeated. To determine seropositivity cutoffs for each antigen, standardized optical densities were fitted to a mixture model that assumed a bi-modal normal distribution, and seropositivity was defined as three standard deviations above the mean of the lower distribution [31]. Due to the potential for false positive responses to a single antigen, seropositivity was defined as presence of antibodies to both AMA-1 and MSP-142. Evidence for temporal changes in exposure was explored by assessing the relationship between age and seroprevalence. To formally assess a temporal change in exposure, a catalytic conversion model assessing seroconversion rate was fitted to the data, allowing for a change in the seroconversion rate at a single time-point. The time point at which a change in seroconversion occurred was assessed by maximum likelihood with confidence intervals based on the chi-squared distribution on one degree of freedom [23]. To analyze relationships between seropositivity and baseline characteristics, chi-squared, t-test, logistic regression, or two-sample test of proportions was performed as appropriate. P-values less than .05 were considered statistically significant. To identify potential foci of transmission, spatial cluster analysis was performed with SatScan (version 9.0), using the Poisson model and allowing for elliptical clusters. Due to sampling among participants ten to 49 years of age, age was adjusted for as a categorical variable (<10 years, 10-19 years, ≥20 years). Maximum geographical cluster size was set at 50% of the population, allowing for nested clusters. Statistically significant clusters were reported, including nested clusters with a relative risk greater than that of the parent cluster. Maps were produced using ArcGIS software (version 10.0). For the household and women's questionnaires, oral informed consent was provided by a household head and women 15 to 49 years of age, respectively. Written consent was not performed because data along with oral consent was entered electronically into PDAs, and there were no sensitive questions and thus minimal risks for participants. Written informed consent for blood testing was obtained from participants or a parent or guardian for children less than 14 years of age. Ethical approval for the study, including the use of oral consent for the questionnaires, was obtained from the review committees at the Swaziland Ministry of Health, University of California, San Francisco, and United States Centers for Disease Control and Prevention.