Estimating the health effects of COVID-19-related immunisation disruptions in 112 countries during 2020-30: a modelling study

BACKGROUND

There have been declines in global immunisation coverage due to the COVID-19 pandemic. Recovery has begun but is geographically variable. This disruption has led to under-immunised cohorts and interrupted progress in reducing vaccine-preventable disease burden. There have, so far, been few studies of the effects of coverage disruption on vaccine effects. We aimed to quantify the effects of vaccine-coverage disruption on routine and campaign immunisation services, identify cohorts and regions that could particularly benefit from catch-up activities, and establish if losses in effect could be recovered.

METHODS

For this modelling study, we used modelling groups from the Vaccine Impact Modelling Consortium from 112 low-income and middle-income countries to estimate vaccine effect for 14 pathogens. One set of modelling estimates used vaccine-coverage data from 1937 to 2021 for a subset of vaccine-preventable, outbreak-prone or priority diseases (ie, measles, rubella, hepatitis B, human papillomavirus [HPV], meningitis A, and yellow fever) to examine mitigation measures, hereafter referred to as recovery runs. The second set of estimates were conducted with vaccine-coverage data from 1937 to 2020, used to calculate effect ratios (ie, the burden averted per dose) for all 14 included vaccines and diseases, hereafter referred to as full runs. Both runs were modelled from Jan 1, 2000, to Dec 31, 2100. Countries were included if they were in the Gavi, the Vaccine Alliance portfolio; had notable burden; or had notable strategic vaccination activities. These countries represented the majority of global vaccine-preventable disease burden. Vaccine coverage was informed by historical estimates from WHO-UNICEF Estimates of National Immunization Coverage and the immunisation repository of WHO for data up to and including 2021. From 2022 onwards, we estimated coverage on the basis of guidance about campaign frequency, non-linear assumptions about the recovery of routine immunisation to pre-disruption magnitude, and 2030 endpoints informed by the WHO Immunization Agenda 2030 aims and expert consultation. We examined three main scenarios: no disruption, baseline recovery, and baseline recovery and catch-up.

FINDINGS

We estimated that disruption to measles, rubella, HPV, hepatitis B, meningitis A, and yellow fever vaccination could lead to 49 119 additional deaths (95% credible interval [CrI] 17 248-134 941) during calendar years 2020-30, largely due to measles. For years of vaccination 2020-30 for all 14 pathogens, disruption could lead to a 2·66% (95% CrI 2·52-2·81) reduction in long-term effect from 37 378 194 deaths averted (34 450 249-40 241 202) to 36 410 559 deaths averted (33 515 397-39 241 799). We estimated that catch-up activities could avert 78·9% (40·4-151·4) of excess deaths between calendar years 2023 and 2030 (ie, 18 900 [7037-60 223] of 25 356 [9859-75 073]).

INTERPRETATION

Our results highlight the importance of the timing of catch-up activities, considering estimated burden to improve vaccine coverage in affected cohorts. We estimated that mitigation measures for measles and yellow fever were particularly effective at reducing excess burden in the short term. Additionally, the high long-term effect of HPV vaccine as an important cervical-cancer prevention tool warrants continued immunisation efforts after disruption.

FUNDING

The Vaccine Impact Modelling Consortium, funded by Gavi, the Vaccine Alliance and the Bill & Melinda Gates Foundation.

TRANSLATIONS

For the Arabic, Chinese, French, Portguese and Spanish translations of the abstract see Supplementary Materials section.

Impact and cost-effectiveness of hepatitis B virus prophylaxis in pregnancy: a dynamic simulation modelling study

BACKGROUND

In 2020, WHO recommended the addition of peripartum antiviral prophylaxis (PAP) to hepatitis B birth dose vaccination (HepB-BD) and hepatitis B infant vaccination (HepB3) to reduce mother-to-child transmission of hepatitis B virus (HBV) infection in pregnant women who have a marker of high infectivity (ie, HBV DNA ≥200 000 international units per mL or HBeAg-positive). We aimed to evaluate the impact and cost-effectiveness of this recommendation and of a theoretical simplified strategy whereby PAP is given to all pregnant women who are HBsAg-positive without risk stratification.

METHODS

This modelling study used a dynamic simulation model of the HBV epidemic in 110 countries in all WHO regions, structured by age, sex, and country. We assessed three strategies of scaling up PAP for pregnant women: PAP for those with high viral load (PAP-VL); PAP for those who are HBeAg-positive (PAP-HBeAg); and PAP for all pregnant women who are HBsAg-positive (PAP-universal), in comparison with neonatal vaccination alone (HepB-BD). We investigated how different diagnostic and antiviral drug costs affected the cost-effectiveness of the strategies evaluated. Using a health-care provider perspective, we calculated incremental cost-effectiveness ratios in cost (US$) per disability-adjusted life-year (DALY) averted in each country's population and compared these with country-specific cost-effectiveness thresholds. We also calculated new neonatal infections averted for each of the strategies.

FINDINGS

Adding PAP-VL to HepB-BD could avert around 1·1 million (95% uncertainty interval 1·0 million-1·2 million) new neonatal infections by 2030 and around 3·2 million (95% uncertainty interval 3·0 million-3·4 million) new neonatal infections and approximately 8·8 million (7·8 million-9·7 million) DALYs by 2100 across all the countries modelled. This strategy would probably be cost-effective up to 2100 in 28 (26%) of 106 countries analysed (which included some of the countries that have the greatest HBV burden) if costs are as currently expected to be, and in 74 (70%) countries if diagnostic and monitoring costs were lowered (by about 60-75%). The relative cost-effectiveness of PAP-VL and PAP-HBeAg was finely balanced and depended on the respective diagnostic and monitoring costs. The PAP-universal strategy could be more cost-effective than either of these strategies in most countries, but the use of antiviral treatment could be five times as high than with PAP-VL.

INTERPRETATION

PAP can provide substantial health benefits, and, although the current approach might already be cost-effective in some high-burden settings, decreased diagnostic costs would probably be needed for PAP to be cost-effective in most countries. Therefore, careful consideration needs to be given about how such a strategy is implemented, and securing reduced costs for diagnostics should be a priority. The theoretical strategy of offering PAP to all women who are HBsAg-positive (eg, if diagnostic tests to identify mothers at risk of transmission are not available) could be a cost-effective alternative, depending on prevailing costs of diagnostics and antiviral therapy.

FUNDING

UK Medical Research Council, UK National Institute for Health and Care Research, and the Vaccine Impact Modelling Consortium.

How can the public health impact of vaccination be estimated?

Background

Deaths due to vaccine preventable diseases cause a notable proportion of mortality worldwide. To quantify the importance of vaccination, it is necessary to estimate the burden averted through vaccination. The Vaccine Impact Modelling Consortium (VIMC) was established to estimate the health impact of vaccination.

Methods

We describe the methods implemented by the VIMC to estimate impact by calendar year, birth year and year of vaccination (YoV). The calendar and birth year methods estimate impact in a particular year and over the lifetime of a particular birth cohort, respectively. The YoV method estimates the impact of a particular year’s vaccination activities through the use of impact ratios which have no stratification and stratification by activity type and/or birth cohort. Furthermore, we detail an impact extrapolation (IE) method for use between coverage scenarios. We compare the methods, focusing on YoV for hepatitis B, measles and yellow fever.

Results

We find that the YoV methods estimate similar impact with routine vaccinations but have greater yearly variation when campaigns occur with the birth cohort stratification. The IE performs well for the YoV methods, providing a time-efficient mechanism for updates to impact estimates.

Conclusions

These methods provide a robust set of approaches to quantify vaccination impact; however it is vital that the area of impact estimation continues to develop in order to capture the full effect of immunisation.

The impact of the timely birth dose vaccine on the global elimination of hepatitis B

In 2016 the World Health Organization set the goal of eliminating hepatitis B globally by 2030. Horizontal transmission has been greatly reduced in most countries by scaling up coverage of the infant HBV vaccine series, and vertical transmission is therefore becoming increasingly dominant. Here we show that scaling up timely hepatitis B birth dose vaccination to 90% of new-borns in 110 low- and middle-income countries by 2030 could prevent 710,000 (580,000 to 890,000) deaths in the 2020 to 2030 birth cohorts compared to status quo, with the greatest benefits in Africa. Maintaining this could lead to elimination by 2030 in the Americas, but not before 2059 in Africa. Drops in coverage due to disruptions in 2020 may lead to 15,000 additional deaths, mostly in South-East Asia and the Western Pacific. Delays in planned scale-up could lead to an additional 580,000 deaths globally in the 2020 to 2030 birth cohorts.

Lives saved with vaccination for 10 pathogens across 112 countries in a pre-COVID-19 world

Background

Vaccination is one of the most effective public health interventions. We investigate the impact of vaccination activities for Haemophilus influenzae type b, hepatitis B, human papillomavirus, Japanese encephalitis, measles, Neisseria meningitidis serogroup A, rotavirus, rubella, Streptococcus pneumoniae, and yellow fever over the years 2000-2030 across 112 countries.

Methods

Twenty-one mathematical models estimated disease burden using standardised demographic and immunisation data. Impact was attributed to the year of vaccination through vaccine-activity-stratified impact ratios.

Results

We estimate 97 (95%CrI[80, 120]) million deaths would be averted due to vaccination activities over 2000-2030, with 50 (95%CrI[41, 62]) million deaths averted by activities between 2000 and 2019. For children under-5 born between 2000 and 2030, we estimate 52 (95%CrI[41, 69]) million more deaths would occur over their lifetimes without vaccination against these diseases.

Conclusions

This study represents the largest assessment of vaccine impact before COVID-19-related disruptions and provides motivation for sustaining and improving global vaccination coverage in the future.

Funding

VIMC is jointly funded by Gavi, the Vaccine Alliance, and the Bill and Melinda Gates Foundation (BMGF) (BMGF grant number: OPP1157270 / INV-009125). Funding from Gavi is channelled via VIMC to the Consortium's modelling groups (VIMC-funded institutions represented in this paper: Imperial College London, London School of Hygiene and Tropical Medicine, Oxford University Clinical Research Unit, Public Health England, Johns Hopkins University, The Pennsylvania State University, Center for Disease Analysis Foundation, Kaiser Permanente Washington, University of Cambridge, University of Notre Dame, Harvard University, Conservatoire National des Arts et Métiers, Emory University, National University of Singapore). Funding from BMGF was used for salaries of the Consortium secretariat (authors represented here: TBH, MJ, XL, SE-L, JT, KW, NMF, KAMG); and channelled via VIMC for travel and subsistence costs of all Consortium members (all authors). We also acknowledge funding from the UK Medical Research Council and Department for International Development, which supported aspects of VIMC's work (MRC grant number: MR/R015600/1).JHH acknowledges funding from National Science Foundation Graduate Research Fellowship; Richard and Peggy Notebaert Premier Fellowship from the University of Notre Dame. BAL acknowledges funding from NIH/NIGMS (grant number R01 GM124280) and NIH/NIAID (grant number R01 AI112970). The Lives Saved Tool (LiST) receives funding support from the Bill and Melinda Gates Foundation.This paper was compiled by all coauthors, including two coauthors from Gavi. Other funders had no role in study design, data collection, data analysis, data interpretation, or writing of the report. All authors had full access to all the data in the study and had final responsibility for the decision to submit for publication.

Estimating the health impact of vaccination against ten pathogens in 98 low-income and middle-income countries from 2000 to 2030: a modelling study

BACKGROUND

The past two decades have seen expansion of childhood vaccination programmes in low-income and middle-income countries (LMICs). We quantify the health impact of these programmes by estimating the deaths and disability-adjusted life-years (DALYs) averted by vaccination against ten pathogens in 98 LMICs between 2000 and 2030.

METHODS

16 independent research groups provided model-based disease burden estimates under a range of vaccination coverage scenarios for ten pathogens: hepatitis B virus, Haemophilus influenzae type B, human papillomavirus, Japanese encephalitis, measles, Neisseria meningitidis serogroup A, Streptococcus pneumoniae, rotavirus, rubella, and yellow fever. Using standardised demographic data and vaccine coverage, the impact of vaccination programmes was determined by comparing model estimates from a no-vaccination counterfactual scenario with those from a reported and projected vaccination scenario. We present deaths and DALYs averted between 2000 and 2030 by calendar year and by annual birth cohort.

FINDINGS

We estimate that vaccination of the ten selected pathogens will have averted 69 million (95% credible interval 52-88) deaths between 2000 and 2030, of which 37 million (30-48) were averted between 2000 and 2019. From 2000 to 2019, this represents a 45% (36-58) reduction in deaths compared with the counterfactual scenario of no vaccination. Most of this impact is concentrated in a reduction in mortality among children younger than 5 years (57% reduction [52-66]), most notably from measles. Over the lifetime of birth cohorts born between 2000 and 2030, we predict that 120 million (93-150) deaths will be averted by vaccination, of which 58 million (39-76) are due to measles vaccination and 38 million (25-52) are due to hepatitis B vaccination. We estimate that increases in vaccine coverage and introductions of additional vaccines will result in a 72% (59-81) reduction in lifetime mortality in the 2019 birth cohort.

INTERPRETATION

Increases in vaccine coverage and the introduction of new vaccines into LMICs have had a major impact in reducing mortality. These public health gains are predicted to increase in coming decades if progress in increasing coverage is sustained.

FUNDING

Gavi, the Vaccine Alliance and the Bill & Melinda Gates Foundation.

Modelling hepatitis B virus infection and impact of timely birth dose vaccine: A comparison of two simulation models

Hepatitis B is a global epidemic that requires carefully orchestrated vaccination initiatives in geographical regions of medium to high endemicity to reach the World Health Organization’s elimination targets by 2030. This study compares two widely-used deterministic hepatitis B models—the Imperial HBV model and the CDA Foundation’s PRoGReSs—based on their predicted outcomes in four countries. The impact of scaling up of the timely birth dose of the hepatitis B vaccine is also investigated. The two models predicted largely similar outcomes for the impact of vaccination programmes on the projected numbers of new cases and deaths under high levels of the infant hepatitis B vaccine series. However, scenarios for the scaling up of the infant hepatitis B vaccine series had a larger impact in the PRoGReSs model than in the Imperial model due to the infant vaccine series directly leading to the reduction of perinatal transmission in the PRoGReSs model, but not in the Imperial model. Meanwhile, scaling up of the timely birth dose vaccine had a greater impact on the outcomes of the Imperial hepatitis B model than in the PRoGReSs model due to the greater protection that the birth dose vaccine confers to infants in the Imperial model compared to the PRoGReSs model. These differences underlie the differences in projections made by the models under some circumstances. Both sets of assumptions are consistent with available data and reveal a structural uncertainty that was not apparent in either model in isolation. Those relying on projections from models should consider outputs from both models and this analysis provides further evidence of the benefits of systematic model comparison for enhancing modelling analyses.

An approach to identify putative hybrids in the 'coalescent stochasticity zone', as exemplified in the African plant genus Streptocarpus (Gesneriaceae)

The inference of phylogenetic relationships is often complicated by differing evolutionary histories of independently-inherited markers. The causes of the resulting gene tree incongruence can be challenging to identify, often relying on coalescent simulations dependent on unverifiable assumptions. We investigated alternative techniques using the South African rosulate species of Streptocarpus as a study group. Two independent gene trees - from the nuclear ITS region and from three concatenated plastid regions (trnL-F, rpl20-rps12 and trnC-D) - displayed widespread, strongly supported incongruence. We investigated the causes by detecting genetic exchange across morphological borders using morphological optimizations and genetic exchange across species boundaries using the genealogical sorting index. Incongruence between gene trees was associated with ancestral shifts in growth form (in four species) but not in pollination syndrome, suggesting introgression limited by reproductive barriers. Genealogical sorting index calculations showed polyphyly of two additional species, while individuals of all others were significantly associated. In one case the association was stronger according to the internal transcribed spacer data than according to the plastid data, which, given the smaller effective population size of the plastid, may also indicate introgression. These approaches offer alternative ways to identify potential hybridization events where incomplete lineage sorting cannot be rejected using simulations.

A rapid and inexpensive method for the direct PCR amplification of DNA from plants

PREMISE OF THE STUDY

We present a rapid and inexpensive alternative to DNA isolation for polymerase chain reaction (PCR) amplification from plants. •

METHODS AND RESULTS

The method involves direct PCR amplification from material macerated in one buffer, followed by dilution and incubation in a second buffer. We describe the procedure and demonstrate its application for nuclear and plastid DNA amplification across a broad range of vascular plants. •

CONCLUSIONS

The method is fast, easy to perform, cost-effective, and consequently ideal for large sample numbers. It represents a considerable simplification of present approaches requiring DNA isolation prior to PCR amplification and will be useful in plant systematics and biotechnology, including applications such as DNA barcoding.