Geospatial variation in measles vaccine coverage through routine and campaign strategies in Nigeria: Analysis of recent household surveys

Andrus, 2011, Measles and rubella eradication in the Americas, Vaccine, 29, D91, 10.1016/j.vaccine.2011.04.059 World Health Organization. Global measles and rubella strategic plan 2012–2020; 2012: Available from: http://apps.who.int/iris/bitstream/10665/44855/1/9789241503396_eng.pdf [accessed on 11 November 2019]. World Health Organization. Measles vaccines: WHO position paper – April 2017. Weekly Epidemiol Rec 2017;92(205–28). Portnoy, 2018, Impact of measles supplementary immunization activities on reaching children missed by routine programs, Vaccine, 36, 170, 10.1016/j.vaccine.2017.10.080 World Health Organization. Planning and implementing high-quality supplementary immunization activities for injectable vaccines using an example of measles and rubella vaccines: Field guide; 2016 [accessed on 30 October 2019]. Hanvoravongchai, 2011, Impact of measles elimination activities on immunization services and health systems: findings from six countries, J Infect Dis, 204, S82, 10.1093/infdis/jir091 Verguet, 2013, Impact of supplemental immunisation activity (SIA) campaigns on health systems: findings from South Africa, J Epidemiol Commun Health, 67, 947, 10.1136/jech-2012-202216 World Health Organization. Vaccination Coverage Cluster Surveys: Reference Manual; 2018. Available from: https://www.who.int/immunization/documents/who_ivb_18.09/en/ [accessed on 15 October 2019]. Subaiya S, Tabu C, N’ganga J, Awes AA, Sergon K, Cosmas L, et al. Use of the revised World Health Organization cluster survey methodology to classify measles-rubella vaccination campaign coverage in 47 counties in Kenya, 2016. PLOS ONE. 2018;13(7):e0199786. Cutts, 2016, Monitoring vaccination coverage: Defining the role of surveys, Vaccine, 34, 4103, 10.1016/j.vaccine.2016.06.053 Danovaro-Holliday, 2018, Vaccine, 36, 5150, 10.1016/j.vaccine.2018.07.019 Utazi, 2018, High resolution age-structured mapping of childhood vaccination coverage in low and middle income countries, Vaccine, 36, 1583, 10.1016/j.vaccine.2018.02.020 Takahashi, 2017, The geography of measles vaccination in the African Great Lakes region, Nat Commun, 8, 10.1038/ncomms15585 Utazi, 2019, Mapping vaccination coverage to explore the effects of delivery mechanisms and inform vaccination strategies, Nat Commun, 10, 1633, 10.1038/s41467-019-09611-1 Mosser, 2019, Mapping diphtheria-pertussis-tetanus vaccine coverage in Africa, 2000–2016: A spatial and temporal modelling study, Lancet, 393, 1843, 10.1016/S0140-6736(19)30226-0 Mayala BK, Dontamsetti T, Fish TD, Croft TN. Interpolation of DHS survey data at subnational administrative Level 2. DHS Spatial Analysis Reports No 17. Rockville (Maryland, USA): ICF; 2019. Utazi, 2018, A spatial regression model for the disaggregation of areal unit based data to high-resolution grids with application to vaccination coverage mapping, Stat Meth Med Res, 28, 3226 Tatem, 2017, WorldPop, open data for spatial demography, Sci Data, 4, 170004, 10.1038/sdata.2017.4 World Health Organization. Measles and rubella surveillance data; 2019. Available from: https://www.who.int/immunization/monitoring_surveillance/burden/vpd/surveillance_type/active/measles_monthlydata/en/ [accessed on 12 November 2019]. World Health Organization. WHO/UNICEF Estimates of National Immunization Coverage (WUENIC); 2019. Available from: https://www.who.int/immunization/monitoring_surveillance/data/en/ [accessed on 10 September 2019]. Goodson, 2011, Changing epidemiology of measles in Africa, J Infect Dis, 204, S205, 10.1093/infdis/jir129 World Health Organization. Summary of measles-rubella supplementary immunization activities 2000–2019. Available from: https://www.who.int/immunization/monitoring_surveillance/data/en/ [accessed on 15 October 2019]. WHO Regional Committee for Africa. Measles elimination by 2020: A strategy for the African Region; 2011. Available from: https://www.afro.who.int/about-us/governance/sessions/sixty-first-session-who-regional-committee-africa [accessed on 5 November 2019]. Nigeria Centre for Disease Control. Weekly Epidemiological Report. Available from: https://ncdc.gov.ng/reports/weekly [accessed on 10 September 2019]. National Population Commission - NPC/Nigeria, ICF International. Nigeria Demographic and Health Survey 2013. Abuja, Nigeria; 2014. National Bureau of Statistics (NBS) and United Nations Children’s Fund (UNICEF). 2017 Multiple Indicator Cluster Survey 2016–17, Survey Findings Report. Abuja (Nigeria): National Bureau of Statistics and United Nations Children’s Fund; 2017. National Primary Healthcare Development Agency and National Bureau of Statistics. Nigeria, National Immunisation Coverage Survey 2016/17, Final Report. Abuja (Nigeria): National Primary Healthcare Development Agency and National Bureau of Statistics; 2017. eHealth Africa, Oak Ridge National Laboratory, Proxy Logics. Geo-Referenced Infrastructure and Demographic Data for Development (GRID3) Nigeria Settlement Points; 2019. Weber, 2018, Census-independent population mapping in northern Nigeria, Remote Sens Environ, 204, 786, 10.1016/j.rse.2017.09.024 Tatem AJ. WorldPop, open data for spatial demography. Sci Data 2017;4(170004). Banerjee, 2014 Diggle, 1998, Model-based geostatistics, J Roy Stat Soc: Ser C (Appl Stat), 47, 299, 10.1111/1467-9876.00113 Matérn B. Spatial variation. 2nd ed. Berlin: Springer-Verlag; 1960 [reprinted 1986]. Lindgren, 2011, An explicit link between Gaussian fields and Gaussian Markov random fields: the stochastic partial differential equation approach, J Roy Stat Soc Series B (Stat Methodol), 73, 423, 10.1111/j.1467-9868.2011.00777.x Rue, 2009, Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations, J Roy Stat Soc: Series B (Stat Methodol), 71, 319, 10.1111/j.1467-9868.2008.00700.x R Core Team. R: A Language and Environment for Statistical Computing. Vienna, Austria; 2017. Lindgren, 2015, Bayesian Spatial Modelling with R-INLA, J Stat Softw, 63, 25, 10.18637/jss.v063.i19 World Health Organization. The RED strategy. Available from: http://www.who.int/immunization/programmes_systems/service_delivery/red/en/ [accessed on 15 October 2019]. World Health Organization. Global Vaccine Action Plan 2011–2020; 2013. Available from: http://www.who.int/immunization/global_vaccine_action_plan/en/ [accessed on 20 June 2017]. Masresha B, Braka F, Onwu NU, Oteri J, Erbeto T, Oladele S, et al. Progress towards measles elimination in Nigeria: 2012–2016. J Immunol Sci 2018;Suppl(135-9). Gunnala, 2016, Routine vaccination coverage in Northern Nigeria: results from 40 district-level cluster surveys, 2014–2015, PLoS ONE, 11, e0167835, 10.1371/journal.pone.0167835 Zimmermann, 2019, Optimization of frequency and targeting of measles supplemental immunization activities in Nigeria: A cost-effectiveness analysis, Vaccine, 37, 6039, 10.1016/j.vaccine.2019.08.050 Dansereau, 2019, 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, Gates Open Res, 3, 923, 10.12688/gatesopenres.12916.1 Doshi, 2015, The effect of immunization on measles incidence in the Democratic Republic of Congo: Results from a model of surveillance data, Vaccine, 33, 6786, 10.1016/j.vaccine.2015.10.020