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Auzenbergs M, Fu H, Abbas K, Procter SR, Cutts FT, Jit M. Health effects of routine measles vaccination and supplementary immunisation activities in 14 high-burden countries: a Dynamic Measles Immunization Calculation Engine (DynaMICE) modelling study. Lancet Glob Health 2023; 11:e1194-e1204. [PMID: 37474227 PMCID: PMC10369016 DOI: 10.1016/s2214-109x(23)00220-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2022] [Revised: 04/17/2023] [Accepted: 05/02/2023] [Indexed: 07/22/2023]
Abstract
BACKGROUND WHO recommends at least 95% population coverage with two doses of measles-containing vaccine (MCV). Most countries worldwide use routine services to offer a first dose of measles-containing vaccine (MCV1) and later, a second dose of measles-containing vaccine (MCV2). Many countries worldwide conduct supplementary immunisation activities (SIAs), offering vaccination to all people in a specific age range irrespective of previous vaccination history. We aimed to estimate the relative effects of each dose and delivery route in 14 countries with high measles burden. METHODS We used an age-structured compartmental dynamic model, the Dynamic Measles Immunization Calculation Engine (DynaMICE), to assess the effects of different vaccination strategies on measles susceptibility and burden during 2000-20 in 14 countries with high measles incidence (containing 53% of the global birth cohort and 78% of the global measles burden). Country-specific routine MCV1 and MCV2 coverage data during 1980-2020 were obtained from the WHO and UNICEF Estimates of National Immunization Coverage database for all modelled countries and SIA data were obtained from the WHO summary of measles and rubella SIAs. We estimated the incremental health effects of different vaccination strategies using prevented cases of measles and deaths from measles and their efficiency using the incremental number needed to vaccinate (NNV) to prevent an additional measles case. FINDINGS Compared with no vaccination, MCV1 implementation was estimated to have prevented 824 million cases of measles and 9·6 million deaths from measles, with a median NNV of 1·41 (IQR 1·35-1·44). Adding routine MCV2 to MCV1 was estimated to have prevented 108 million cases and 404 270 deaths, whereas adding SIAs to MCV1 was estimated to have prevented 256 million cases and 4·4 million deaths. Despite larger incremental effects, adding SIAs to MCV1 (median incremental NNV 6·02, 5·30-7·68) showed reduced efficiency compared with adding routine MCV2 (5·41, 4·76-6·11). INTERPRETATION Vaccination strategies, including non-selective SIAs, reach a greater proportion of children who are unvaccinated and reduce measles burden more than MCV2 alone, but efficiency is lower because of the wide age range targeted by SIAs. This analysis provides information to help improve the health effects and efficiency of measles vaccination strategies. The interplay between MCV1, MCV2, and SIAs should be considered when planning future measles vaccination strategies. FUNDING Gavi, the Vaccine Alliance and the Bill & Melinda Gates Foundation.
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Affiliation(s)
- Megan Auzenbergs
- Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK.
| | - Han Fu
- Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK
| | - Kaja Abbas
- Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK; Public Health Foundation of India, New Delhi, India
| | - Simon R Procter
- Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK
| | - Felicity T Cutts
- Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK
| | - Mark Jit
- Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK; School of Public Health, University of Hong Kong, Hong Kong Special Administrative Region, China
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Yang Y, Kostandova N, Mwansa FD, Nakazwe C, Namukoko H, Sakala C, Bobo P, Masumbu PK, Nachinga B, Ngula D, Carcelen AC, Prosperi C, Winter AK, Moss WJ, Mutembo S. Challenges Addressing Inequalities in Measles Vaccine Coverage in Zambia through a Measles-Rubella Supplementary Immunization Activity during the COVID-19 Pandemic. Vaccines (Basel) 2023; 11:608. [PMID: 36992192 PMCID: PMC10059977 DOI: 10.3390/vaccines11030608] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Revised: 03/02/2023] [Accepted: 03/05/2023] [Indexed: 03/10/2023] Open
Abstract
BACKGROUND Measles-rubella supplementary immunization activities (MR-SIAs) are conducted to address inequalities in coverage and fill population immunity gaps when routine immunization services fail to reach all children with two doses of a measles-containing vaccine (MCV). We used data from a post-campaign coverage survey in Zambia to measure the proportion of measles zero-dose and under-immunized children who were reached by the 2020 MR-SIA and identified reasons associated with persistent inequalities following the MR-SIA. METHODS Children between 9 and 59 months were enrolled in a nationally representative, cross-sectional, multistage stratified cluster survey in October 2021 to estimate vaccination coverage during the November 2020 MR-SIA. Vaccination status was determined by immunization card or through caregivers' recall. MR-SIA coverage and the proportion of measles zero-dose and under-immunized children reached by MR-SIA were estimated. Log-binomial models were used to assess risk factors for missing the MR-SIA dose. RESULTS Overall, 4640 children were enrolled in the nationwide coverage survey. Only 68.6% (95% CI: 66.7%, 70.6%) received MCV during the MR-SIA. The MR-SIA provided MCV1 to 4.2% (95% CI: 0.9%, 4.6%) and MCV2 to 6.3% (95% CI: 5.6%, 7.1%) of enrolled children, but 58.1% (95% CI: 59.8%, 62.8%) of children receiving the MR-SIA dose had received at least two prior MCV doses. Furthermore, 27.8% of measles zero-dose children were vaccinated through the MR-SIA. The MR-SIA reduced the proportion of measles zero-dose children from 15.1% (95% CI: 13.6%, 16.7%) to 10.9% (95% CI: 9.7%, 12.3%). Zero-dose and under-immunized children were more likely to miss MR-SIA doses (prevalence ratio (PR): 2.81; 95% CI: 1.80, 4.41 and 2.22; 95% CI: 1.21 and 4.07) compared to fully vaccinated children. CONCLUSIONS The MR-SIA reached more under-immunized children with MCV2 than measles zero-dose children with MCV1. However, improvement is needed to reach the remaining measles zero-dose children after SIA. One possible solution to address the inequalities in vaccination is to transition from nationwide non-selective SIAs to more targeted and selective strategies.
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Affiliation(s)
- Yangyupei Yang
- Department of International Health, International Vaccine Access Center, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21231, USA
| | - Natalya Kostandova
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21231, USA
| | - Francis Dien Mwansa
- Ministry of Health, Government of the Republic of Zambia, Lusaka 10101, Zambia
| | | | | | - Constance Sakala
- Ministry of Health, Government of the Republic of Zambia, Lusaka 10101, Zambia
| | - Patricia Bobo
- Ministry of Health, Government of the Republic of Zambia, Lusaka 10101, Zambia
| | | | | | - David Ngula
- Ministry of Health, Government of the Republic of Zambia, Lusaka 10101, Zambia
| | - Andrea C. Carcelen
- Department of International Health, International Vaccine Access Center, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21231, USA
| | - Christine Prosperi
- Department of International Health, International Vaccine Access Center, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21231, USA
| | - Amy K. Winter
- Department of Epidemiology, University of Georgia, Athens, GA 30602, USA
| | - William J. Moss
- Department of International Health, International Vaccine Access Center, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21231, USA
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21231, USA
- W Harry Feinstone Department of Molecular Microbiology and Immunology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21231, USA
| | - Simon Mutembo
- Department of International Health, International Vaccine Access Center, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21231, USA
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Prosperi C, Thangaraj J, Hasan A, Kumar M, Truelove S, Kumar V, Winter A, Bansal A, Chauhan S, Grover G, Jain A, Kulkarni R, Sharma S, Soman B, Chaaithanya I, Kharwal S, Mishra S, Salvi N, Sharma N, Sharma S, Varghese A, Sabarinathan R, Duraiswamy A, Rani D, Kanagasabai K, Lachyan A, Gawali P, Kapoor M, Chonker S, Cutts F, Sangal L, Mehendale S, Sapkal G, Gupta N, Hayford K, Moss W, Murhekar M. Added value of the measles-rubella supplementary immunization activity in reaching unvaccinated and under-vaccinated children, a cross-sectional study in five Indian districts, 2018-20. Vaccine 2023; 41:486-495. [PMID: 36481106 PMCID: PMC9831119 DOI: 10.1016/j.vaccine.2022.11.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Revised: 10/29/2022] [Accepted: 11/04/2022] [Indexed: 12/12/2022]
Abstract
INTRODUCTION Supplementary immunization activities (SIAs) aim to interrupt measles transmission by reaching susceptible children, including children who have not received the recommended two routine doses of MCV before the SIA. However, both strategies may miss the same children if vaccine doses are highly correlated. How well SIAs reach children missed by routine immunization is a key metric in assessing the added value of SIAs. METHODS Children aged 9 months to younger than 5 years were enrolled in cross-sectional household serosurveys conducted in five districts in India following the 2017-2019 measles-rubella (MR) SIA. History of measles containing vaccine (MCV) through routine services or SIA was obtained from documents and verbal recall. Receipt of a first or second MCV dose during the SIA was categorized as "added value" of the SIA in reaching un- and under-vaccinated children. RESULTS A total of 1,675 children were enrolled in these post-SIA surveys. The percentage of children receiving a 1st or 2nd dose through the SIA ranged from 12.8% in Thiruvananthapuram District to 48.6% in Dibrugarh District. Although the number of zero-dose children prior to the SIA was small in most sites, the proportion reached by the SIA ranged from 45.8% in Thiruvananthapuram District to 94.9% in Dibrugarh District. Fewer than 7% of children remained measles zero-dose after the MR SIA (range: 1.1-6.4%) compared to up to 28% before the SIA (range: 7.3-28.1%). DISCUSSION We demonstrated the MR SIA provided considerable added value in terms of measles vaccination coverage, although there was variability across districts due to differences in routine and SIA coverage, and which children were reached by the SIA. Metrics evaluating the added value of an SIA can help to inform the design of vaccination strategies to better reach zero-dose or undervaccinated children.
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Affiliation(s)
- C. Prosperi
- International Vaccine Access Center, Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - J.W.V. Thangaraj
- Indian Council of Medical Research (ICMR)-National Institute of Epidemiology, Chennai, India
| | - A.Z. Hasan
- International Vaccine Access Center, Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - M.S. Kumar
- Indian Council of Medical Research (ICMR)-National Institute of Epidemiology, Chennai, India
| | - S. Truelove
- International Vaccine Access Center, Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA,Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - V.S. Kumar
- Indian Council of Medical Research (ICMR)-National Institute of Epidemiology, Chennai, India
| | - A.K. Winter
- International Vaccine Access Center, Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA,Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - A.K. Bansal
- ICMR-National JALMA Institute for Leprosy & Other Mycobacterial Diseases, Agra, India
| | - S.L. Chauhan
- ICMR- National Institute for Research in Reproductive and Child Health (NIRRCH), Mumbai, India
| | - G.S. Grover
- Directorate of Health Services, Government of Punjab, Chandigarh, India
| | - A.K. Jain
- ICMR-National Institute of Pathology, New Delhi, India
| | - R.N. Kulkarni
- ICMR- National Institute for Research in Reproductive and Child Health (NIRRCH), Mumbai, India
| | - S.K. Sharma
- ICMR-Regional Medical Research Centre, NE Region, Dibrugarh, India
| | - B. Soman
- Achutha Menon Centre for Health Science Studies, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Trivandrum, Kerala, India
| | - I.K. Chaaithanya
- Department of Health Research, Model Rural Health Research Unit-Dahanu, Maharashtra, India
| | - S. Kharwal
- Department of Health Research, Model Rural Health Research Unit-Hoshiarpur, Punjab, India
| | - S.K. Mishra
- Department of Health Research, Model Rural Health Research Unit-Hoshiarpur, Punjab, India
| | - N.R. Salvi
- Department of Health Research, Model Rural Health Research Unit-Dahanu, Maharashtra, India
| | - N.P. Sharma
- Department of Health Research, Model Rural Health Research Unit-Chabua, Assam, India
| | - S. Sharma
- Department of Health Research, Model Rural Health Research Unit-Kanpur, Uttar Pradesh, India
| | - A. Varghese
- Achutha Menon Centre for Health Science Studies, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Trivandrum, Kerala, India
| | - R. Sabarinathan
- Indian Council of Medical Research (ICMR)-National Institute of Epidemiology, Chennai, India
| | - A. Duraiswamy
- Indian Council of Medical Research (ICMR)-National Institute of Epidemiology, Chennai, India
| | - D.S. Rani
- Indian Council of Medical Research (ICMR)-National Institute of Epidemiology, Chennai, India
| | - K. Kanagasabai
- Indian Council of Medical Research (ICMR)-National Institute of Epidemiology, Chennai, India
| | - A. Lachyan
- Department of Health Research, Model Rural Health Research Unit-Dahanu, Maharashtra, India
| | - P. Gawali
- Department of Health Research, Model Rural Health Research Unit-Dahanu, Maharashtra, India
| | - M. Kapoor
- Department of Health Research, Model Rural Health Research Unit-Dahanu, Maharashtra, India
| | - S.K. Chonker
- Department of Health Research, Model Rural Health Research Unit-Kanpur, Uttar Pradesh, India
| | - F.T. Cutts
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK
| | - L. Sangal
- World Health Organization, Southeast Asia Region Office, New Delhi, India
| | - S.M. Mehendale
- PD Hinduja Hospital and Medical Research Centre, Mumbai, India
| | - G.N. Sapkal
- ICMR-National Institute of Virology, Pune, India
| | - N. Gupta
- Division of Epidemiology and Communicable Diseases, Indian Council of Medical Research, New Delhi, India
| | - K. Hayford
- International Vaccine Access Center, Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - W.J. Moss
- International Vaccine Access Center, Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA,Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA,Corresponding author at: International Vaccine Access Center, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA.
| | - M.V. Murhekar
- Indian Council of Medical Research (ICMR)-National Institute of Epidemiology, Chennai, India
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Cutts FT, Danovaro-Holliday MC, Rhoda DA. Challenges in measuring supplemental immunization activity coverage among measles zero-dose children. Vaccine 2021; 39:1359-1363. [PMID: 33551302 DOI: 10.1016/j.vaccine.2020.11.050] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2020] [Revised: 11/14/2020] [Accepted: 11/17/2020] [Indexed: 10/22/2022]
Affiliation(s)
- Felicity T Cutts
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK.
| | | | - Dale A Rhoda
- Biostat Global Consulting, Worthington, OH, USA.
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Cutts FT, Dansereau E, Ferrari MJ, Hanson M, McCarthy KA, Metcalf CJE, Takahashi S, Tatem AJ, Thakkar N, Truelove S, Utazi E, Wesolowski A, Winter AK. Using models to shape measles control and elimination strategies in low- and middle-income countries: A review of recent applications. Vaccine 2020; 38:979-992. [PMID: 31787412 PMCID: PMC6996156 DOI: 10.1016/j.vaccine.2019.11.020] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2019] [Revised: 11/07/2019] [Accepted: 11/08/2019] [Indexed: 01/30/2023]
Abstract
After many decades of vaccination, measles epidemiology varies greatly between and within countries. National immunization programs are therefore encouraged to conduct regular situation analyses and to leverage models to adapt interventions to local needs. Here, we review applications of models to develop locally tailored interventions to support control and elimination efforts. In general, statistical and semi-mechanistic transmission models can be used to synthesize information from vaccination coverage, measles incidence, demographic, and/or serological data, offering a means to estimate the spatial and age-specific distribution of measles susceptibility. These estimates complete the picture provided by vaccination coverage alone, by accounting for natural immunity. Dynamic transmission models can then be used to evaluate the relative impact of candidate interventions for measles control and elimination and the expected future epidemiology. In most countries, models predict substantial numbers of susceptible individuals outside the age range of routine vaccination, which affects outbreak risk and necessitates additional intervention to achieve elimination. More effective use of models to inform both vaccination program planning and evaluation requires the development of training to enhance broader understanding of models and where feasible, building capacity for modelling in-country, pipelines for rapid evaluation of model predictions using surveillance data, and clear protocols for incorporating model results into decision-making.
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Affiliation(s)
- F T Cutts
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK.
| | - E Dansereau
- Vaccine Delivery, Global Development, The Bill & Melinda Gates Foundation, Seattle, WA, USA
| | - M J Ferrari
- Center for Infectious Disease Dynamics, Pennsylvania State University, University Park, PA, USA
| | - M Hanson
- Vaccine Delivery, Global Development, The Bill & Melinda Gates Foundation, Seattle, WA, USA
| | - K A McCarthy
- Institute for Disease Modeling, 3150 139th Ave SE, Bellevue, WA 98005, USA
| | - C J E Metcalf
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA
| | - S Takahashi
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA; Department of Medicine, University of California San Francisco, San Francisco, CA 94143, USA
| | - A J Tatem
- WorldPop, Department of Geography and Environmental Science, University of Southampton, Highfield, Southampton SO17 1BJ, UK
| | - N Thakkar
- Institute for Disease Modeling, 3150 139th Ave SE, Bellevue, WA 98005, USA
| | - S Truelove
- Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
| | - E Utazi
- WorldPop, Department of Geography and Environmental Science, University of Southampton, Highfield, Southampton SO17 1BJ, UK
| | - A Wesolowski
- Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
| | - A K Winter
- Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
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