key: cord-1015633-bhg710n1 authors: Evans, Beth; Jombart, Thibaut title: Worldwide routine immunisation coverage regressed during the first year of the COVID-19 pandemic date: 2022-01-26 journal: Vaccine DOI: 10.1016/j.vaccine.2022.01.044 sha: 85f893386da78ca67fa3ae2ff9ee1d832c9bcaa2 doc_id: 1015633 cord_uid: bhg710n1 Whilst COVID-19 vaccination strategies continue to receive considerable emphasis worldwide, the extent to which routine immunisation (RI) has been impacted during the first year of the pandemic remains unclear. Understanding the existence, extent, and variations in RI disruptions globally may help inform policy and resource prioritisation as the pandemic continues. We modelled historical, country-specific RI trends using publicly available vaccination coverage data for diphtheria, tetanus and pertussis-containing vaccine first-dose (DTP1) and third-dose (DTP3) from 2000 to 2019. We report a 2·9% (95%(CI): [2·2%; 3·6%]) global decline in DTP3 coverage from an expected 89·2% to a reported 86·3%; and a 2·2% decline in DTP1 coverage (95%(CI): [1·6%; 2·8%]). These declines translate to levels of coverage last observed in 2005, thus suggesting a potential 15-years setback in RI improvements. Further research is required to understand which factors – e.g., health seeking behaviours or non-pharmaceutical interventions – linked to the COVID-19 crisis impacted vaccination coverage. The COVID-19 pandemic has impacted society and public health infrastructures worldwide, influencing mobility [1] , access to health services [2] , livelihoods and poverty [3] . While COVID-19 vaccination strategies continue to receive considerable emphasis [4, 5] , the extent to which routine immunisation (RI) has been impacted during the first year of the pandemic remains unclear. Indeed, the World Health Organisation (WHO) pulse surveys reported disruptions in the first half of 2020 [2] , and while some later studies suggested a potential recovery [6] , recent observations again hinted at global coverage declines [7, 8] . RI is estimated to prevent four to five million deaths worldwide every year [9] . As such, there is an urgent need for assessing potential changes in RI coverage, as declines may result in considerable added morbidity and mortality. We investigated changes in RI coverage using two key indicators: diphtheria-tetanuspertussis first-dose (DTP1) and third-dose (DTP3) vaccine coverage. DTP3 serves as a general marker for immunisation system performance, used by national and global immunisation stakeholders [10] . DTP1 is used as a proxy for inequity -quantifying Zero Dose (ZD) children, those that receive no childhood vaccinations [11] . We compiled vaccination coverage data from the WHO and United Nations Children's Fund (UNICEF) Estimates of National Immunisation Coverage (WUENIC) [12, 13] for the last 20 years, using the latest (October 2021) WUENIC data release. Countries were excluded if (a) they did not have complete time series coverage estimates for 2000-2019 inclusive to enable expected coverage modelling (three countries); or (b) they had not yet reported 2020 coverage through WUENIC (16 countries). We used AutoRegressive Integrated Moving Average (ARIMA) modelling [14] to capture temporal trends in coverage for each country from 2000 to 2019, and predicted expected coverage levels in 2020 for each country and vaccine dose. Prior to investigating differences between expected and observed coverage, historic and predicted time series were assessed and countries were removed from analyses if they met one of three criteria -(1) large volatility in coverage estimates (over 10 percentage points) in the last decade since this may indicate high uncertainty in point estimates, (2) strong influence of most recent coverage estimates (i.e., 2018 or and 2019) contributing to model fitting, corroborated by WUENIC documentation indicating potential anomalous or rare events, and (3) ARIMAmodels predict coverage improvement greater than or equal to five percentage points from WUENIC-reported 2020 levels, since this may not be programmatically feasible. See Supplementary Text for details on removed countries and contexts by dose. We additionally conducted analyses with no exclusions as a sensitivity study. After removing countries for which reliable temporal trends could not be assessed, changes in coverage were measured as the difference between the reported and expected coverage for 2020, expressed as percentage values, for the remaining 167 countries per vaccine dose. The significance of global changes was assessed using a t-test against the null hypothesis of the absence of change. Heterogeneities between groups of countries (UN regions or income groups) were tested using linear models with coverage change as a response variable and the corresponding ANOVA. Differences between individual countries were assessed by comparing the 95% confidence intervals derived from the linear models. For additional validation we conducted the same analysis for Measles-Containing Vaccine first-dose (MCV1) to compare whether similar trends were seen across other vaccine doses and immunisation touchpoints (MCV1 is typically administered at age 9-months compared to six-weeks for DTP1 and 10-weeks for DPT3). We calculated missed immunisations by combining the estimated changes in coverage with surviving infant population estimates (medium variant births minus infant deaths) of the United Nations World Population Prospects (UNWPP) for 2020 [15] . All analyses were conducted using R [16] and can be reproduced using a publicly available reportfactory including all required data and scripts [17] . After excluding countries for which reliable coverage predictions could not be obtained (see Supplementary Text for details), we were able to estimate differences between expected and observed coverage in 2020 for 167 countries for DTP1 and DTP3 -examples shown in As UN regions and income groups are highly correlated (non-parametric Chi-square test: X 2 = 115·4, p < 10 -5 ), we also tested whether heterogeneities due to one variable (regions or income groups) remained after accounting for the effect of the other one. Interestingly, regional differences remained after accounting for differences in income groups (ANOVA: F = 5·67, df = 159, p < 2·7x10 -4 ), but evidence for the converse was weak (ANOVA: F = 2·67, df = 159, p = 0·05). The estimated changes in RI coverage reported in this study suggest a smaller global decline (approximately 1/3rd the magnitude) than previously found using alternative methodology and data [19] . We believe our findings may be more robust owing to a more comprehensive dataset including data from more countries (167 here vs. 94), plus increased data from the end of 2020 (annual here vs. majority of data from January-September 2020), and the use of WUENIC-reported data (less prone to data quality and completeness issues than administrative data). The observed discrepancies are compatible with a rebound of global RI coverage in late 2020 [6] . RI disruption may be worsened by the acceleration of COVID-19 vaccination campaigns, particularly in low-and middle-income countries where absorption capacity may be challenged [20] , potentially competing with RI services. Careful monitoring of the interaction, trade-offs and synergies between RI and COVID-19 vaccinations is essential. Further studies are needed to understand which factors linked to the COVID-19 crisis impacted vaccination coverage, such as changes in health-seeking behaviours or non-pharmaceutical intervention policies, in order to successfully and efficiently address pandemic-associated losses to coverage. As the COVID-19 pandemic continues to affect healthcare systems globally, maintaining the appropriate balance between access to routine immunisation and pandemic response will be essential to reduce both the direct and indirect mortality and morbidity associated with COVID-19. This research provides a transparent and replicable rationale for estimating gaps in RI coverage across countries, producing an objective measure for missed immunisations and coverage disruptions. As such, it can form a basis for identifying countries most affected by declines in RI coverage and prioritising efforts to alleviate the indirect impact of COVID- Funders had no role in the design and conduct of this study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication. All analyses were conducted using free software R [16] , and can be reproduced using a publicly available reportfactory including all required data and scripts [17] used to produce the results presented in this publication, and available on GitHub at: https://github.com/bevans249/modelling_covid_impact_RI Numbers displayed in bold font indicate significant differences between expected and observed coverage. LIC: Low-income Country. LMIC: Lower-middle-income Country. UMIC: Upper-middle-income Country. Impact of COVID-19 pandemic on mobility in ten countries and associated perceived risk for all transport modes Pulse survey on continuity of essential health services during the COVID-19 pandemic: interim report Impact of COVID-19 on people's livelihoods, their health and our food systems Board on Population Health and Public Health Practice, Board on Health Sciences Policy, Committee on Equitable Allocation of Vaccine for the Novel Coronavirus. Framework for Equitable Allocation of COVID-19 Vaccine International collaboration to ensure equitable access to vaccines for COVID-19: The ACT-accelerator and the COVAX facility Impact of the SARS-CoV-2 Pandemic on Routine Immunization Services: Evidence of Disruption and Recovery From 169 Countries and Territories World Health Organization Routine Vaccination Coverage -Worldwide Reported Diphtheria Tetanus toxoid and Pertussis (DTP3) immunization coverage among 1-year-olds (%) Zero-dose children and missed communities WHO and UNICEF estimates of national infant immunization coverage: methods and processes A Formal Representation of the WHO and UNICEF Estimates of National Immunization Coverage: A Computational Logic Approach Automatic time series forecasting: the forecast package for R World Population Prospects -Population Division -United Nations R: A Language and Environment for Statistical Computing Analysis of changes in worldwide routine immunisation coverage in 2020 Catch-up vaccination Estimating global and regional disruptions to routine childhood vaccine coverage during the COVID-19 pandemic in 2020: a modelling study What needs to change to enhance covid-19 vaccine access The authors have no conflicts of interest to declare.  We modelled historical, country-specific RI trends using publicly available vaccination coverage data for diphtheria, tetanus and pertussis-containing vaccine first-dose (DTP1) and third-dose (DTP3) from 2000 to 2019 -using a transparent and replicable methodology (R code and publicly available datasets provided). We report a 2·9% (95% CI : [2·2%; 3·6%]) global decline in DTP3 coverage from an expected 89·2% to a reported 86·3%; and a 2·2% decline in DTP1 coverage (95% CI : These declines translate to levels of coverage last observed in 2005, thus suggesting a potential 15-years setback in RI improvements. However, these declines are less than previous modelling -compatible with the hypothesis that coverage fell more acutely in early 2020 and may have then rebounded in late-2020.