Literature DB >> 27899197

Reply to comments on Monitoring vaccination coverage: Defining the role of surveys.

Felicity T Cutts1, Pierre Claquin2, M Carolina Danovaro-Holliday3, Dale A Rhoda4.   

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Year:  2016        PMID: 27899197      PMCID: PMC5142421          DOI: 10.1016/j.vaccine.2016.09.067

Source DB:  PubMed          Journal:  Vaccine        ISSN: 0264-410X            Impact factor:   3.641


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Dear Editor, We thank Pond and Mounier-Jack for their comments on our paper, “Monitoring vaccination coverage: Defining the role of surveys” [1]. We agree that for many countries, administrative estimates of coverage are greatly inflated and misleading for programme planning purposes. The robustness of the WHO-UNICEF estimates of national immunization coverage (WUENIC) depends on the quality of the underlying data reviewed, which include administrative reports, as well as probability and non-probability sample surveys. In 2012, the Grade of Confidence (GoC) was introduced as a means of conveying uncertainty in WUENIC [2] and is low in the seven conflict-affected countries listed by Pond and Mounier-Jack. Table 1 shows that in five of these countries, vaccination cards were available for less than half the children surveyed; when card availability is low, it is particularly difficult to compare coverage trends. For example, in Nigeria, the proportion of children with DTP3 according to card was similar in surveys in 2010, 2011 and 2013, but in the EPI survey of 2010 a verbal history of vaccination was reported for 43% of children, more than double that of previous or subsequent surveys. Elsewhere, results from surveys did not always match expected trends (e.g. no apparent fall in coverage between surveys despite a 7 month stockout of DTP in one country), and some results were very unlikely (e.g. zero dropout between DTP1 and DTP3 in one Multiple Indicator Cluster Survey (MICS) (data from country reports at http://apps.who.int/immunization_monitoring/globalsummary/wucoveragecountrylist.html)).
Table 1

Surveys reviewed for WUENIC in 7 countries, 2008–2015, children aged 12–23 months.

CountryYear of WUENICYear of SurveySurvey type% cardsDTP3% by cardDTP3%HistoryDTP3%Total
Afghanistan20122013EPI6654660
20102010–11MICS3132941



Cote d’Ivoire20142015EPI review9170676
20132014Post-SIA75611182
20122013EPI8878482
20112011–12DHS7456864



Central African20112012EPI5041647
Republic20092010MICS32161632



Democratic20122013–14DHS26243660
Republic of Congo20112012EPI35215677
20092010MICS43372562



Mali20112012–13DHS38293463
20092010MICS59492372
20082009–10EPI65472875



Nigeria20122013DHS28221638
20102011MICS24261845
20092010EPI40254368
20072008DHS26201535



Pakistan20132014–15PSLMn/a652388
20122012–13DHS36323365
20122013–14PSLMn/a612081
20102010–11PSLMn/a561985
20072008–9PSLMn/a513384

WUENIC: WHO/UNICEF Estimates of National Immunization Coverage.

DTP3: third dose of diphtheria-tetanus-pertussis vaccine (results are for children aged 12–23 months).

EPI: Expanded Programme on Immunization.

MICS: UNICEF Multiple Indicator Cluster Survey.

DHS: Demographic and Health Survey.

PSLM: Pakistan Social and Living Standards Measurement Survey.

The updated WHO guidelines on vaccination coverage surveys (http://www.who.int/immunization/monitoring_surveillance/Vaccination_coverage_cluster_survey_with_annexes.pdf) discuss the challenges of using a new survey to compare with an older one, particularly an immunization coverage survey – these often lacked information on likely biases and confidence intervals were either not reported or not very meaningful from non-probability samples. The best way to compare results from different surveys is to plan a pair of surveys for such a purpose and work very hard to ensure standardised, well-documented and high quality data collection in both. Pond and Mounier-Jack suggest that two such surveys are feasible within each 5 years period. We would be reluctant to stipulate any particular interval as the usefulness of repeat surveys will depend in part on the likelihood of a change in coverage having occurred (which can be predicted from monitoring other indicators) [1] and the availability of accurate documentation of vaccination status on home-based or clinic records. Most of all, surveys should lead to action to strengthen programme performance and this is likely the weakest link in many countries, including those affected by conflict. We also question whether frequent conduct of high-quality surveys is always the best investment, particularly when countries may not use results to improve EPI performance. In the Americas, strong progress towards programme goals has been attributed to technical oversight, partnership and coordination to strengthen routine information systems and the continuous monitoring of administrative data (including numerators separate from denominators), surveillance and public health laboratory networks, as well as pooled vaccine purchase [3], [4]. The Pan American Health Organization (PAHO) rarely recommended or funded surveys [4]. We encourage the global community to continue its support to improve monitoring systems as well as surveys, while building-up the evidence regarding the best uses of vaccination coverage surveys and other monitoring tools, without losing focus on the actual implementation of strategies proven to improve immunization programme performance.

Conflict of interest statement

The authors declare that they have no conflict of interest.
  3 in total

Review 1.  Assessing and monitoring vaccination coverage levels: lessons from the Americas.

Authors:  Vance Dietz; Linda Venczel; Héctor Izurieta; George Stroh; Elizabeth R Zell; Edgar Monterroso; Gina Tambini
Journal:  Rev Panam Salud Publica       Date:  2004-12

2.  Regional immunization programs as a model for strengthening cooperation among nations.

Authors:  Gina Tambini; Jon Kim Andrus; John W Fitzsimmons; Mirta Roses Periago
Journal:  Rev Panam Salud Publica       Date:  2006-07

Review 3.  Monitoring vaccination coverage: Defining the role of surveys.

Authors:  Felicity T Cutts; Pierre Claquin; M Carolina Danovaro-Holliday; Dale A Rhoda
Journal:  Vaccine       Date:  2016-06-24       Impact factor: 3.641

  3 in total
  3 in total

1.  A systematic review of the agreement of recall, home-based records, facility records, BCG scar, and serology for ascertaining vaccination status in low and middle-income countries.

Authors:  Emily Dansereau; David Brown; Lena Stashko; M Carolina Danovaro-Holliday
Journal:  Gates Open Res       Date:  2020-02-03

Review 2.  Characterization of immunization secondary analyses using demographic and health surveys (DHS) and multiple indicator cluster surveys (MICS), 2006-2018.

Authors:  Yue Huang; M Carolina Danovaro-Holliday
Journal:  BMC Public Health       Date:  2021-02-12       Impact factor: 3.295

3.  Collecting and using reliable vaccination coverage survey estimates: Summary and recommendations from the "Meeting to share lessons learnt from the roll-out of the updated WHO Vaccination Coverage Cluster Survey Reference Manual and to set an operational research agenda around vaccination coverage surveys", Geneva, 18-21 April 2017.

Authors:  M Carolina Danovaro-Holliday; Emily Dansereau; Dale A Rhoda; David W Brown; Felicity T Cutts; Marta Gacic-Dobo
Journal:  Vaccine       Date:  2018-07-21       Impact factor: 3.641

  3 in total

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