ZAMPHIA design and study population
From March-August 2016, a cross-sectional household survey with blood collection (ZAMPHIA) was conducted. It was a stratified national multistage cluster survey designed to estimate HIV incidence and the percentage of HIV-positive adults with viral load suppression in each province. Participants provided written informed consent, parental permission was obtained children under 18 years old, and assent was obtained for participants 10–17 years old. Up to 14 mL of venous blood (or 1 mL of liquid capillary blood for children younger than 2 years) was collected from adults 15–49 years of age in every selected household and from children younger than 15 years of age in every other household.15 Specimens were collected from 88.5% of adult respondents 15–49 years old and 68% of children younger than 15 years.15 Specimens were transported to a central laboratory where whole blood was processed into plasma aliquots and dried blood spot (DBS) samples for storage at -20°C. After testing for the primary study was completed, residual plasma and DBS were stored in a biorepository at -80°C at the Tropical Diseases Research Center in Ndola, Zambia.
Nested serosurvey: Subsample selection and survey weights
A subsample of residual specimens was selected from the ZAMPHIA biorepository to generate age-specific seroprevalence estimates for measles and rubella in each province with 10% precision for age categories 0–4, 5–9, 10–14, 15–19, and 20–49 years. A total of 11,500 participants were subsampled from the 25,383 ZAMPHIA participants younger than 50 years of age who had blood collected. Specimens were selected based on HIV infection status, geographic cluster, and age (Supplemental Methods).
Challenges linking sociodemographic data from the ZAMPHIA survey to specimens caused delays and difficulty in specimen selection. Not all the selected specimens could be tested, not all participants provided ethical consent for future testing, and some specimens had insufficient volume or could not be located. We calculated survey weights for each specimen starting with the original ZAMPHIA survey weights and then accounted for the inverse probability of selection at each stage of subsampling, non-availability of specimens, and post-stratification adjustments to represent the provincial-level age and sex structure (Supplemental Methods).
This study was conducted in accordance with relevant guidelines and regulations. Ethical approvals for protocols were provided by Johns Hopkins Bloomberg School of Public Health as well as the Tropical Disease Research Center and the National Health Regulatory Agency in Zambia.
Specimen testing
Plasma specimens were thawed overnight at 4°C, processed as recommended by the manufacturer, and tested for anti-measles virus IgG and anti-rubella virus IgG antibodies using indirect enzyme immunoassays (EIA; Euroimmun; Lübeck, Germany). For DBS, a 6 mm punch was eluted in 450 uL of sample buffer. The DBS elution protocol was optimized for use with the Euroimmun assays and validated on a subset of paired plasma and DBS. A quantitative antibody concentration was generated using the plate-specific standard curve from plotting the four calibrators. Samples were classified as positive, negative, or equivocal according to the manufacturer thresholds. Measles results were classified as positive (≥ 200 mIU/mL), equivocal (≥ 150 to < 200 mIU/mL), or negative (< 150 mIU/mL). Similarly, rubella results were classified as positive (≥ 11 IU/mL), equivocal (≥ 8 to < 11 IU/mL), or negative (< 8 IU/mL). Specimens with equivocal results were retested. Retest results were used but, if equivocal again, were categorized as positive for the primary analysis. Testing was conducted at the National Virology Laboratory at the University Teaching Hospital in Lusaka and the Tropical Disease Research Center in Ndola between April and October 2019. Internal controls and sample panels were tested, and near-real time data management was conducted to monitor variability.
Analysis and Modeling
We used the R package survey to account for the complex survey design in national, provincial, and age-group measles and rubella seroprevalence estimates.16 Univariate and multivariate generalized linear regression models were fit to evaluate associations between seropositivity and categorical variables (province, age group, sex), taking into account survey weights. All 95% confidence intervals were calculated using linearized Taylor series variance estimation.
For national and provincial age-specific measles and rubella seroprevalence, a hierarchical generalized additive model was fit to individual seropositivity. The models included a single national level smoother over age. Final models were selected by minimizing the Akaike Information Criterion (AIC). We reconstructed the national age-profile of measles immunity using vaccination and case data. This indirect method estimates the proportion of each birth cohort that is immune based on vaccination coverage (routine and campaigns), age-specific vaccine effectiveness (85% at 9 months, 95% at 12 months), natural infection, and maternally derived immunity.17
To estimate district-specific measles seroprevalence, a hierarchical spatial model was fit to individual seropositivity. District-specific random effects were included in the model based on a conditional autoregressive (CAR) specification where adjacent districts were assumed to be more similar than non-adjacent districts. We explored model covariates of routinely collected data (e.g., individual HIV positivity, district routine vaccination coverage) and demographic data (e.g., age, population density). The final model was selected by minimizing the Widely Applicable Information Criterion (WAIC).
We estimated national measles outbreak risk using the 2016 cross-sectional serological data to predict seroprevalence for 2017–2019 based on methods developed by Funk et al. 2019.18 We focused on changes in immunity due to vaccination, assuming no immunity from natural infection given the small number of measles cases reported since 2016 (average of 11 annual cases between 2016–2019).19 Using age-specific seroprevalence and an assumed who-acquires-infection-from-whom matrix (WAIFW), we estimated the measles effective reproduction number (Reff, average number of secondary cases per infectious individual) 2016–2019. If Reff >1, cases increase and there is risk of an outbreak. If Reff <1, cases decline, and transmission will eventually cease.
Because sera were collected before the introduction of rubella-containing vaccine, we evaluated the rubella basic reproductive number and burden of congenital rubella syndrome (CRS) prior to vaccination. The estimated CRS rate (CRS incident cases per 100,000 live births) for each reproductive age in years was calculated by \((1-\pi (a\left)\right) \times (1-{exp}^{-16\lambda \left(a\right)/52}) \times 0.65 \times \text{100,000}\), where \(\pi \left(a\right)\)is the estimated seroprevalence at age a, \(\lambda \left(a\right)\) is the estimated force of infection at age a. We assumed 65% of infants born to women infected during the first 16 weeks of pregnancy were born with CRS.11
All computations were done in R, version 4.0.5.20 Supplemental methods provides additional details on all methods described above.