Rubella immunity among pregnant women aged 15–44 years, Namibia, 2010

Open AccessPublished:May 16, 2016DOI:https://doi.org/10.1016/j.ijid.2016.05.009

      Highlights

      • 15% of pregnant Namibian women are susceptible to rubella.
      • Women from rural residences were more likely to be seronegative for rubella.
      • The offspring of these women are at risk for congenital rubella syndrome (CRS).
      • The introduction of rubella vaccine will help reduce the risk of rubella and CRS.

      Summary

      Background

      The level of rubella susceptibility among women of reproductive age in Namibia is unknown. Documenting the risk of rubella will help estimate the potential burden of disease in Namibian women and the risk of congenital rubella syndrome (CRS) in infants, and will guide strategies for the introduction of rubella vaccine.

      Methods

      A total of 2044 serum samples from pregnant Namibian women aged 15–44 years were tested for rubella immunoglobulin G antibody; the samples were obtained during the 2010 National HIV Sentinel Survey. The proportion of women seropositive for rubella was determined by 5-year age strata, and factors associated with seropositivity were analyzed by logistic regression, including age, gravidity, HIV status, facility type, and urban/rural status.

      Results

      Overall rubella seroprevalence was 85% (95% confidence interval (CI) 83–86%). Seroprevalence varied by age group (83–90%) and health district (71–100%). In the multivariable model, women from urban residences had higher odds of seropositivity as compared to women from rural residences (odds ratio 1.40, 95% CI 1.09–1.81).

      Conclusions

      In the absence of a routine rubella immunization program, the high level of rubella seropositivity suggests rubella virus transmission in Namibia, yet 15% of pregnant Namibian women remain susceptible to rubella. The introduction of rubella vaccine will help reduce the risk of rubella in pregnant women and CRS in infants.

      Keywords

      1. Introduction

      Rubella is a vaccine-preventable viral disease that is characterized by a febrile illness and rash.
      Centers for Disease Control and Prevention
      Rubella and congenital rubella syndrome control and elimination—global progress, 2000–2012.
      Rubella infection in pregnant women can lead to congenital rubella syndrome (CRS), which can result in severe illness, disability, and death in the fetus.
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      • Robertson S.E.
      • Diaz-Ortega J.L.
      • Samuel R.
      Control of rubella and congenital rubella syndrome (CRS) in developing countries, Part 1: burden of disease from CRS.
      Worldwide, more than 100 000 children are born each year with CRS.

      World Health Organization. Global measles and rubella strategic plan: 2012–2020. Geneva: WHO; 2012. Available at: http://www.who.int/immunization/newsroom/Measles_Rubella_StrategicPlan_2012_2020.pdf (accessed March 31, 2016).

      • Vynnycky E.
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      • Simons E.
      • et al.
      Using seroprevalence and immunisation coverage data to estimate the global burden of congenital rubella syndrome, 1996–2010: a systematic review.
      From 2000 to 2009, reported rubella cases increased 20-fold in the World Health Organization (WHO) African Region.
      Centers for Disease Control and Prevention
      Progress toward control of rubella and prevention of congenital rubella syndrome—worldwide, 2009.
      Despite this increase in reported number of cases, as of 2015, there is no rubella elimination, control, or prevention goal in the African Region.
      • Vynnycky E.
      • Adams E.J.
      • Cutts F.T.
      • Reef S.E.
      • Navar A.M.
      • Simons E.
      • et al.
      Using seroprevalence and immunisation coverage data to estimate the global burden of congenital rubella syndrome, 1996–2010: a systematic review.
      Thus far, a small number of Sub-Saharan African countries have introduced rubella-containing vaccine in their Expanded Programme on Immunization (EPI) childhood immunization schedule (Burkina Faso, Ghana, Rwanda, Senegal, and Tanzania), and others are planning to do so in the next few years.
      Centers for Disease Control and Prevention
      Rubella and congenital rubella syndrome control and elimination—global progress, 2000–2012.
      The WHO recommends that countries without rubella vaccine assess the burden of rubella and CRS.
      World Health Organization
      Preventing congenital rubella syndrome.
      Serosurveys have suggested rubella virus circulation in a number of African countries,
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      • Nshimirimana D.
      • Cochi S.
      • et al.
      Rubella epidemiology in Africa in the prevaccine era, 2002–2009.
      but no published studies have investigated seroprevalence in Namibia. Currently, rubella-containing vaccine (RCV) is not available publicly in Namibia. Understanding the level of rubella susceptibility in pregnant women in Namibia will provide important information to help determine the burden of disease and the need for the introduction of rubella vaccine.
      • Thompson K.M.
      • Odahowski C.L.
      Systematic review of measles and rubella serology studies.
      Namibia is a country in southwestern Africa that gained independence from South Africa in 1990. It has an estimated population of 2.1 million.
      The Namibia Ministry of Health and Social Services (MoHSS) and ICF International
      The Namibia Demographic and Health Survey 2013.
      The capital city is Windhoek, and the country is administratively organized into 34 health districts in 14 regions, including those with the highest populations in the northern part of the country along the border with Angola, and in the central and the southern parts of the country.
      World Health Organization
      Namibia—annual report 2011.
      The majority (57%) of Namibian residents are rural dwellers.
      The Namibia Ministry of Health and Social Services (MoHSS) and ICF International
      The Namibia Demographic and Health Survey 2013.
      In 2014, Namibia had one of the highest HIV prevalence rates for adults aged 15–49 years in the world at 16.0%;

      UNAIDS Country Reports. HIV and AIDS estimates 2014: Namibia. UNAIDS. Available at: http://www.unaids.org/en/Regionscountries/Countries/Namibia/ (accessed March 31, 2016).

      overall prevalence was high compared with other countries in the Sub-Saharan Africa region.

      AIDSinfo online database. Available at: http://www.aidsinfoonline.org/devinfo/libraries/aspx/Home.aspx (accessed March 31, 2016).

      The total fertility rate has been estimated at 3.1 per woman and the crude birth rate at 26 per 1000 population.

      World Health Organization. Global Health Observatory data repository. Available at: http://apps.who.int/gho/data/node.main.110?lang=en (accessed March 31, 2016).

      To evaluate rubella immunity in pregnant women 15–44 years of age and examine factors associated with seropositivity, stored serum samples from the 2010 Namibia National HIV Sentinel Survey were tested. Rubella immunoglobulin G (IgG) antibody seroprevalence estimates will provide evidence to support the decision to introduce rubella vaccine as part of the Namibia national EPI and to guide efforts to prevent rubella and CRS.

      2. Methods

      In 2010, the Namibia Ministry of Health and Social Services (MoHSS) conducted a nationwide sentinel survey to estimate HIV prevalence in pregnant women aged 15–49 years. The survey was designed using the standardized WHO methodology for HIV prevalence surveys, using convenient consecutive sampling of women attending antenatal clinics (ANC) selected based on geographic representation from all regions and health districts, urban and rural clinics, areas with different population densities and sizes, and women of different socioeconomic status.

      UNAIDS/WHO Working Group on Global HIV/AIDS and STI Surveillance. Guidelines for conducting HIV sentinel serosurveys among pregnant women and other groups. UNAIDS/WHO 2003; Available at: http://data.unaids.org/Publications/IRC-pub06/jc954-anc-serosurveys_guidelines_en.pdf (accessed March 31, 2016).

      Report on the 2010 National HIV Sentinel Survey: HIV prevalence rate in pregnant woman, biannual survey 1992–2010, Namibia. Republic of Namibia: Ministry of Health and Social Services, 2014.

      All pregnant women aged 15–49 years were included in the survey if they attended an ANC for the first time during their current pregnancy, were not referred from another health facility, and agreed to a routine blood draw.
      The 2010 survey enrolled 7983 pregnant women from all 34 health districts, 35 main hospitals, and 93 satellite health centers and clinics; 7888 (98.8%) of the enrollees had specimens collected during March 22 to September 6, 2010.

      Report on the 2010 National HIV Sentinel Survey: HIV prevalence rate in pregnant woman, biannual survey 1992–2010, Namibia. Republic of Namibia: Ministry of Health and Social Services, 2014.

      Unlinked, de-identified specimens were tested for HIV antibodies. All de-identified data fields (unique identification, district abbreviation and site number, facility type, date of ANC visit, woman's age, gravidity, place of residence, antiretroviral therapy participation, and counseling for prevention of maternal-to-child transmission) were retained electronically. Specimens were stored at 4–8 °C at the Namibia Institute of Pathology in Windhoek.
      To estimate the prevalence of rubella IgG antibody within each 5-year age group, it was determined that 428 specimens in each age group would be necessary, assuming seroprevalence of 50%, desired precision of ±5%, probability of achieving the desired precision of 0.95, and 10% loss due to specimens not found or inadequate. There were too few specimens in the 45–49 years age stratum for meaningful estimates, so these samples were excluded. The number of specimens in the 40–44 years age stratum was less than the targeted number, so all specimens were sampled. To control for the distribution of HIV-infected women within each age group, the target sample size was allocated to the HIV-positive and HIV-negative groups based on their observed distributions in the sentinel survey.

      Report on the 2010 National HIV Sentinel Survey: HIV prevalence rate in pregnant woman, biannual survey 1992–2010, Namibia. Republic of Namibia: Ministry of Health and Social Services, 2014.

      Testing for rubella IgG antibody was performed by the Namibia Institute of Pathology in 2012, using an enzyme immunoassay (EIA) to detect rubella-specific IgG (Enzygnost; Siemens, Germany); tests were performed in accordance with the manufacturer's recommendations. Samples with corrected optical density (OD) values >0.2 were considered positive, samples with values <0.1 were considered negative, and samples with values of 0.1–0.2 were considered equivocal. Specimens that tested equivocal were retested as per the manufacturer's instructions, and if the result was confirmed, samples were classified as equivocal, otherwise as positive or negative. To monitor the performance of the EIA, an in-house positive control for rubella IgG antibody was included on every EIA plate in addition to the controls supplied by the manufacturer. A 5% random sample of specimens were tested at the US Centers for Disease Control and Prevention (CDC, Atlanta, GA, USA) for quality assurance; high concordance was found with the testing at the Namibia Institute of Pathology (results not shown).
      Seroprevalence estimates and 95% confidence intervals (CI) were calculated using the Wilson-score method for each 5-year age group and for the following sub-groups: gravidity, HIV status, urban/rural residence, facility type (hospital, health center, or clinic), and health district. The odds of seropositivity were calculated by multiple logistic regression while controlling for age group, gravidity, HIV status, urban/rural residence, and facility type. All analyses included sampling weights, which were calculated based on the probability of selection within each of the 12 age–HIV strata and adjusted for non-response (i.e., specimens not available or inadequate for testing) in each of the strata by the propensity cell adjustment method. These weights were then scaled to the total sample size: (weight/sum of weights) × total sample. A large percentage of specimens were not available or suitable for testing. However, demographic information was available for all women sampled, so multiple imputation using chained equations was conducted to impute seropositivity, and the imputed results were compared with estimates based on the subset of non-missing data. As the imputed estimates were not substantially different from the estimates based on the complete non-missing data, only the laboratory results from complete specimens tested are reported. The multiple imputations were done using the mice package in R statistical software version 3.1.2. Other data were analyzed using SAS version 9.3 (SAS Institute, Cary, NC, USA). Comparisons of seroprevalence among groups were done using the Chi-square test on the weighted data. This study received ethical approval from the CDC and the Namibia MoHSS.

      3. Results

      Based on the sample size calculation, 2692 specimens were selected for inclusion in the study (Table 1); of these, 389 (14%) were not available, 230 (8%) had insufficient volume, 29 (1%) were hemolyzed and therefore could not be used for laboratory testing, and four (0.1%) had a missing test result, resulting in 2040 specimens that were tested and had a laboratory result.
      Table 1Target and observed sample sizes among pregnant women aged 15–44 years by age group and HIV status, from the 2010 Namibia National HIV Sentinel Survey
      Age group, yearsHIV statusTotal specimensTarget sample size% of total specimens sampledObserved sample size% Not tested (target-observed/ target)
      15–19Positive8632372425
      Negative12644503633526
      20–24Positive28260214623
      Negative19944222132124
      25–29Positive410110278126
      Negative13983722728324
      30–34Positive3731453911024
      Negative8713373925923
      35–39Positive2221446511520
      Negative5233386525225
      40–44Positive71711005325
      Negative21121110016124
      All agesBoth7705269235204024
      Overall rubella seroprevalence was 85% (95% CI 83–86%) (Table 2). While the 15–19 years age group had the lowest observed seroprevalence (83%) and the 40–44 year old age group had the highest (90%), no statistically significant difference among age groups was seen (p = 0.208). Seroprevalence was found to differ by type of facility (p = 0.033). Women from urban residences had higher seroprevalence (87%) compared with women from rural residences (83%) (p < 0.001).
      Table 2Rubella seroprevalence among pregnant women aged 15–44 years, overall and by age group, facility type, HIV status, gravidity, and setting, from the 2010 Namibia National HIV Sentinel Survey
      Unweighted total, NWeighted percent positive95% CI
      Wilson score.
      p-ValueWeighted percent negative95% CI
      Wilson score.
      Weighted percent equivocal95% CI
      Wilson score.
      Overall20408583–86-1210–1432–4
      Age group, years0.208
       15–193598379–871410–1832–6
       20–243678683–88119–1432–5
       25–293648278–851411–1842–6
       30–343698682–90129–1620.7–4
       35–393678882–9185–1342–8
       40–442149081–9573–1541–11
      Facility0.033
       Hospital2328479–881612–210.40.1–2
       Health center3018075–841713–2132–6
       Clinic15078684–88119–1243–5
      HIV status0.594
       Positive4298682–89129–1621–4
       Negative16118583–861211–1433–4
      Gravidity0.294
       15668481–861311–1642–5
       23968683–89119–1432–5
       33498379–871310–1742–6
       4+7298784–89118–1432–5
      Setting<0.001
       Rural11298381–851412–1643–5
       Urban9118785–89108–1232–4
      CI, confidence interval.
      a Wilson score.
      The multivariable model calculated the odds of rubella seropositivity while adjusting for age group, gravidity, HIV status, urban/rural residence, and facility type (Table 3). Women from urban residences had higher odds of seropositivity as compared with women from rural residences (odds ratio 1.41, 95% CI 1.10–1.82).
      Table 3Logistic regression calculating the odds of rubella seropositivity among pregnant women aged 15–44 years, from the 2010 Namibia National HIV Sentinel Survey
      OR95% CIp-Value
      Age group, years0.318
       15–19Ref.
       20–241.160.78–1.700.467
       25–290.850.54–1.330.478
       30–341.180.70–2.360.534
       35–391.270.68–2.360.453
       40–441.570.64–3.840.323
      Facility0.065
       HospitalRef.
       Health center0.770.49–1.210.248
       Clinic1.120.77–1.650.552
      HIV status0.661
       PositiveRef.
       Negative0.930.67–1.290.661
      Gravidity0.446
       1Ref.
       21.230.85–1.760.273
       30.950.62–1.440.809
       4+1.200.76–1.900.433
      Setting0.007
       RuralRef.
       Urban1.411.10–1.820.007
      OR, odds ratio; CI, confidence interval.
      Rubella seroprevalence varied by health district and urban/rural residence, from 71% to 100% (Table 4). An analysis comparing demographics of the women whose specimens were not available, of insufficient volume, or hemolyzed, with the characteristics of women whose specimens were tested and included in the analysis, found no substantial differences by age group, gravidity, HIV status, or urban/rural residence (data not shown).
      Table 4Rubella seroprevalence among pregnant women aged 15–44 years, by health district and urban/rural status, from the 2010 Namibia National HIV Sentinel Survey
      DistrictSettingUnweighted, nWeighted % positive95% CIWeighted % negative95% CIWeighted % equivocal95% CI
      AndaraRural538978–95115–2300–7
      Urban
      Number too small to calculate meaningful estimates.
      0
      AranosRural1410083–10000–1700–17
      Urban210036–10000–6400–64
      EenhanaRural678676–9294–1852–14
      Urban
      Number too small to calculate meaningful estimates.
      0
      EngelaRural717160–811710–28116–21
      Urban110030–10000–7000–70
      GobabisRural1110073–10000–2700–27
      Urban559384–9773–1600–6
      GrootfonteinRural107647–92248–5300–26
      Urban408876–95125–2500–8
      OshakatiRural418874–9572–1952–17
      Urban387257–842011–3583–20
      KarasburgRural117747–93102–40123–42
      Urban2610087–10000–1300–13
      KatuturaRural
      Number too small to calculate meaningful estimates.
      0
      Urban769487–9852–130.40–6
      KeetmanshoopRural178965–9730.4–2482–31
      Urban299175–9793–2500–12
      KhorixasRural2010083–10000–1700–17
      Urban218864–9761–2961–29
      Katima MuliloRural268972–96114–2800–13
      Urban658980–95105–200.50–6
      LüderitzRural208463–9482–2692–28
      Urban549687–9941–1300–7
      MarientalRural238768–96134–3200–14
      Urban189171–9871–2630.3–21
      NankuduRural367661–872413–4000–9
      Urban
      Number too small to calculate meaningful estimates.
      0
      NyanganaRural668676–92148–2500–5
      Urban98150–95102–40102–40
      OkahaoRural1027969–861912–2830.8–8
      Urban
      Number too small to calculate meaningful estimates.
      0
      OkahandjaRural
      Number too small to calculate meaningful estimates.
      1
      Urban538573–92105–2251–14
      OkakararaRural358165–91199–3500–10
      Urban137649–91249–5100–22
      OkongoRural888676–9273–1673–15
      Urban
      Number too small to calculate meaningful estimates.
      0
      OmaruruRural299071–9750.8–2350.8–23
      Urban238769–9661–2272–24
      OnandjokweRural857968–862113–310.70–6
      Urban
      Number too small to calculate meaningful estimates.
      0
      OpuwoRural177549–91154–41102–35
      Urban
      Number too small to calculate meaningful estimates.
      0
      OshikukuRural708271–891710–2810.2–7
      Urban
      Number too small to calculate meaningful estimates.
      0
      OtjiwarongoRural
      Number too small to calculate meaningful estimates.
      0
      Urban628675–92115–2141–12
      OutjoRural397762–882111–3710.2–11
      Urban217353–8730.3–192411–45
      OutapiRural497966–88115–22105–22
      Urban
      Number too small to calculate meaningful estimates.
      1
      RehobothRural410052–10000–4800–48
      Urban228464–94124–3140.7–21
      RunduRural128757–9750.6–3392–37
      Urban559282–9662–1530.7–11
      SwakopmundRural
      Number too small to calculate meaningful estimates.
      0
      Urban568877–94105–2020.4–9
      TsandiRural878272–891811–280.40–5
      Urban
      Number too small to calculate meaningful estimates.
      0
      TsumebRural188967–9761–2650.9–26
      Urban548270–90137–2452–14
      UsakosRural710064–10000–3700–37
      Urban157248–872813–5200–18
      Walvis BayRural
      Number too small to calculate meaningful estimates.
      0
      Urban718372–901710–2800–5
      Windhoek Central HospitalRural
      Number too small to calculate meaningful estimates.
      0
      Urban318468–93167–3200–11
      CI, confidence interval.
      a Number too small to calculate meaningful estimates.

      4. Discussion

      In 2010, rubella IgG antibody seroprevalence among pregnant women sampled by the National HIV Sentinel Survey in Namibia was 85%. Women residing in urban settings had higher rubella seroprevalence than those in rural settings. Variation was observed in rubella seroprevalence by health district; the lowest point estimate was 71% for women in a rural setting in one health district.
      This is the first study of rubella antibody seroprevalence in Namibia. The results are similar to those of previous studies in the African region, which have reported rubella seropositive estimates of 72–99% in women of reproductive age,
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      Systematic review of measles and rubella serology studies.
      • Njeru I.
      • Onyango D.
      • Ajack Y.
      • Kiptoo E.
      Rubella outbreak in a rural Kenyan district, 2014: documenting the need for routine rubella immunization in Kenya.
      For pregnant women, rubella susceptibility is concerning because of the risk of CRS in the fetus.
      These findings should be considered in light of limitations. First, only pregnant women 15–44 years old were examined in this study, and the ANC survey was not a random cross-section of the population of pregnant women. Therefore, the results may not be generalizable to all pregnant women in Namibia or to other age groups and populations. When feasible, prospective, population-based surveys could be considered to increase generalizability and allow for the collection of information such as immunization status; however, these studies are time- and resource-intensive, and utilizing specimens already collected and stored might allow for studies that would not otherwise be possible. Second, sample sizes were small at the health district level, limiting conclusions regarding geographic differences. Third, approximately one in four specimens was not available for testing, which might have biased the results. However, it is reassuring that the results from the multiple imputation analysis were very similar to the reported findings.
      Currently, inequity in access to rubella vaccine exists, and most countries in Africa do not have RCV available in the public sector. Because of this inequity, regions and countries not using rubella vaccine in the EPI bear the greatest burden of rubella and CRS.
      • Kirby T.
      Rubella is eliminated from the Americas.
      Efforts should be made to ensure that resources are available for all countries to introduce RCV into their EPI in accordance with WHO recommendations, including an initial wide age-range nationwide supplemental immunization activity (SIA) and periodic follow-up SIAs to achieve and maintain population immunity to prevent and eventually eliminate rubella and CRS.
      World Health Organization
      Rubella vaccines: WHO position paper.
      When considering the introduction of RCV into the national EPI, a potential concern is a theoretical risk of increasing CRS incidence through a phenomenon termed the ‘paradoxical effect’. This term refers to a hypothetical situation in which persistently low vaccination coverage over time might decrease rubella virus circulation sufficiently, but not eliminate it entirely, shifting both the average age of exposure to rubella virus and rubella susceptibility from children to older age groups, including women of childbearing age, and therefore increasing the incidence of CRS. In such a scenario, however, it is unclear whether the absolute number of CRS cases would actually increase over time compared with the pre-vaccine era. A shift in susceptibility to older age groups was previously documented in Greece and Costa Rica, but these shifts reflected the implementation of suboptimal strategies. In Greece, rubella vaccine was not introduced into the national EPI and it was available only in the private sector, and an initial wide age-range nationwide SIA was not implemented.
      • Panagiotopoulos T.
      • Antoniadou I.
      • Valassi-Adam E.
      Increase in congenital rubella occurrence after immunisation in Greece: retrospective survey and systematic review.
      In Costa Rica, rubella vaccine introduction was initially limited to 1-year-old children without an initial wide age-range nationwide SIA.
      • Morice A.
      • Gonzalez L.
      • Castillo-Solorzano C.
      Tendencias de la inmunidad a la rubeola en mujeres de edad fertil y pre-escolares en Costa Rica, 1969–1996.
      Following the implementation of WHO-recommended strategies for RCV introduction, including conducting an initial wide age-range SIA,

      World Health Organization. Introducing rubella vaccine into national immunization programmes. A step by step guide. WHO/IVB/15.07. Geneva: WHO, September 2015; Available at: http://apps.who.int/iris/bitstream/10665/184174/1/9789241549370_eng.pdf (accessed October 1, 2015).

      and as routine RCV vaccination coverage increases in younger age groups, the percentage of rubella cases that occur among older age groups might increase; however, the overall rubella susceptibility in the population, the rubella absolute risk, and the potential risk of CRS will decrease over time.
      The disparity in rubella susceptibility among pregnant Namibian women in rural settings compared with urban settings was not unexpected. Consistent with these findings, rubella susceptibility among persons in rural settings was found to be higher than in urban settings during the pre-vaccine era in countries throughout Africa, Europe, the Americas, and Asia.
      • Goodson J.L.
      • Masresha B.
      • Dosseh A.
      • Byabamazima C.
      • Nshimirimana D.
      • Cochi S.
      • et al.
      Rubella epidemiology in Africa in the prevaccine era, 2002–2009.
      • Assaad F.
      • Ljungars-Esteves K.
      Rubella—world impact.
      • Hinman A.R.
      • Hersh B.S.
      • de Quadros C.A.
      Rational use of rubella vaccine for prevention of congenital rubella syndrome in the Americas.
      Moreover, the mean age of infection of reported rubella cases in the pre-vaccine era in Africa was previously found to be significantly higher in rural settings compared to urban settings.
      • Goodson J.L.
      • Masresha B.
      • Dosseh A.
      • Byabamazima C.
      • Nshimirimana D.
      • Cochi S.
      • et al.
      Rubella epidemiology in Africa in the prevaccine era, 2002–2009.
      This was likely due to longer inter-epidemic periods and the occurrence of rubella infection at older ages in areas with lower population densities and contact rates. When introducing RCV, it is critical to ensure high vaccination coverage in both urban and rural areas to prevent outbreaks. Until all countries have introduced RCV and rubella virus transmission is interrupted, the threat of rubella virus importations, including from bordering countries, will remain a concern, particularly in rural settings.
      The Global Measles and Rubella Strategic Plan for 2012–2020 recognizes the need to achieve and maintain high levels of population immunity by providing high vaccination coverage with two doses of measles- and rubella-containing vaccines.

      World Health Organization. Global measles and rubella strategic plan: 2012–2020. Geneva: WHO; 2012. Available at: http://www.who.int/immunization/newsroom/Measles_Rubella_StrategicPlan_2012_2020.pdf (accessed March 31, 2016).

      Cross-sectional measles and rubella serosurveys provide important evidence to identify immunity gaps in populations and guide vaccination strategies to achieve elimination goals. Serological survey results should be considered along with estimated vaccination coverage and surveillance data to identify susceptible age groups or areas that need to be covered by vaccination activities, decide on vaccine introduction strategies, and determine target age groups and geographic areas for SIAs. In Namibia, based on the results from this study as well as other data sources indicating low measles seropositivity among adults, the MoHSS is considering implementing a nationwide SIA with measles–rubella vaccine among persons aged 9 months to 39 years, a target population of 1.8 million persons.

      WHO AFR measles weekly updates. Summary of measles SIAs in AFR. World Health Organization. Week of May 6, 2015. 2015.

      These efforts will be a historic first step on the path to achieve measles and rubella elimination in Namibia, if high coverage with measles–rubella vaccine can be achieved and maintained.

      Acknowledgements

      The authors would like to recognize the efforts of all staff of the Expanded Programme on Immunizations, the surveillance officers, and the laboratory staff in Namibia, as well as the laboratory and data management staff at the Centers for Disease Control and Prevention (CDC). This work was supported by the CDC, Atlanta, USA.
      Conflict of interest: None.

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      Linked Article

      • Measles immunity among pregnant women aged 15–44 years in Namibia, 2008 and 2010
        International Journal of Infectious DiseasesVol. 49
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          Globally, the number of reported measles cases decreased by 73% from 2000 to 2014.1 In the World Health Organization (WHO) African Region, estimated measles deaths decreased during this period by 86%; nonetheless, outbreaks continued to occur in this region and accounted for 73 914 cases and an estimated 48 000 deaths in 2014, representing 42% of the global measles mortality burden.1
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