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.

The value-based price of transformative gene therapy for sickle cell disease: a modeling analysis.

Sickle cell disease (SCD) is an inherited, progressively debilitating blood disorder. Emerging gene therapies (GTx) may lead to a complete remission, the benefits of such can only be realized if GTx is affordable and accessible in the low-and middle-income countries (LMIC) with the greatest SCD burden. To estimate the health impacts and country-specific value-based prices (VBP) of a future gene therapy for SCD using a cost-utility model framework. We developed a lifetime Markov model to compare the costs and health outcomes of GTx versus standard of care for SCD. We modeled populations in seven LMICs and six high-income countries (HICs) estimating lifetime costs and disability-adjusted life-years (DALYs) in comparison to estimates of a country's cost-effectiveness threshold. Each country's unique VBP for GTx was calculated via threshold analysis. Relative to SOC treatment alone, we found that hypothetical GTx reduced the number of people symptomatic with SCD over time leading to fewer DALYs. Across countries, VBPs ranged from $3.6 million (US) to $700 (Uganda). Our results indicate a wide range of GTx prices are required if it is to be made widely available and may inform burden and affordability for 'target product profiles' of GTx in SCD.

The changes in health service utilisation in Malawi during the COVID-19 pandemic.

INTRODUCTION: The COVID-19 pandemic and the restriction policies implemented by the Government of Malawi may have disrupted routine health service utilisation. We aimed to find evidence for such disruptions and quantify any changes by service type and level of health care. METHODS: We extracted nationwide routine health service usage data for 2015-2021 from the electronic health information management systems in Malawi. Two datasets were prepared: unadjusted and adjusted; for the latter, unreported monthly data entries for a facility were filled in through systematic rules based on reported mean values of that facility or facility type and considering both reporting rates and comparability with published data. Using statistical descriptive methods, we first described the patterns of service utilisation in pre-pandemic years (2015-2019). We then tested for evidence of departures from this routine pattern, i.e., service volume delivered being below recent average by more than two standard deviations was viewed as a substantial reduction, and calculated the cumulative net differences of service volume during the pandemic period (2020-2021), in aggregate and within each specific facility. RESULTS: Evidence of disruptions were found: from April 2020 to December 2021, services delivered of several types were reduced across primary and secondary levels of care-including inpatient care (-20.03% less total interactions in that period compared to the recent average), immunisation (-17.61%), malnutrition treatment (-34.5%), accidents and emergency services (-16.03%), HIV (human immunodeficiency viruses) tests (-27.34%), antiretroviral therapy (ART) initiations for adults (-33.52%), and ART treatment for paediatrics (-41.32%). Reductions of service volume were greatest in the first wave of the pandemic during April-August 2020, and whereas some service types rebounded quickly (e.g., outpatient visits from -17.7% to +3.23%), many others persisted at lower level through 2021 (e.g., under-five malnutrition treatment from -15.24% to -42.23%). The total reduced service volume between April 2020 and December 2021 was 8 066 956 (-10.23%), equating to 444 units per 1000 persons. CONCLUSION: We have found substantial evidence for reductions in health service delivered in Malawi during the COVID-19 pandemic which may have potential health consequences, the effect of which should inform how decisions are taken in the future to maximise the resilience of healthcare system during similar events.

Do risk, time and prosocial preferences predict risky sexual behaviour of youths in a low-income, high-risk setting?

Young people in sub-Saharan Africa are particularly at high risk of sexually transmitted infections. Little is known about their preferences and even less about their association with risky sexual behaviour. We conducted incentivized economic experiments to measure risk, time and prosocial preferences in Zimbabwe. Preferences measured at baseline predict biomarker and self-reported measures of risky sexual behaviour gathered 12 months later. We find robust evidence that individuals more altruistic at baseline are more likely to be Herpes Simplex Virus Type-2 (HSV-2) positive 12 months later. Analysis by sex shows this association is driven by our sample of women. Having more sexual partners is associated with greater risk tolerance amongst men and greater impatience amongst women. Results highlight heterogeneity in the association between preferences and risky sexual behaviour.

Modeling Contraception and Pregnancy in Malawi: A Thanzi La Onse Mathematical Modeling Study.

Malawi has high unmet need for contraception with a costed national plan to increase contraception use. Estimating how such investments might impact future population size in Malawi can help policymakers understand effects and value of policies to increase contraception uptake. We developed a new model of contraception and pregnancy using individual-level data capturing complexities of contraception initiation, switching, discontinuation, and failure by contraception method, accounting for differences by individual characteristics. We modeled contraception scale-up via a population campaign to increase initiation of contraception (Pop) and a postpartum family planning intervention (PPFP). We calibrated the model without new interventions to the UN World Population Prospects 2019 medium variant projection of births for Malawi. Without interventions Malawi's population passes 60 million in 2084; with Pop and PPFP interventions. it peaks below 35 million by 2100. We compare contraception coverage and costs, by method, with and without interventions, from 2023 to 2050. We estimate investments in contraception scale-up correspond to only 0.9 percent of total health expenditure per capita though could result in dramatic reductions of current pressures of very rapid population growth on health services, schools, land, and society, helping Malawi achieve national and global health and development goals.

The long-term impact and value of curative therapy for HIV: a modelling analysis.

INTRODUCTION: Curative therapies (CTx) to achieve durable remission of HIV disease without the need for antiretroviral therapy (ART) are currently being explored. Our objective was to model the long-term health and cost outcomes of HIV in various countries, the impact of future CTx on those outcomes and the country-specific value-based prices (VBPs) of CTx. METHODS: We developed a decision-analytic model to estimate the future health economic impacts of a hypothetical CTx for HIV in countries with pre-existing access to ART (CTx+ART), compared to ART alone. We modelled populations in seven low-and-middle-income countries and five high-income countries, accounting for localized ART and other HIV-related costs, and calibrating variables for HIV epidemiology and ART uptake to reproduce historical HIV outcomes before projecting future outcomes to year 2100. Health was quantified using disability-adjusted life-years (DALYs). Base case, pessimistic and optimistic scenarios were modelled for CTx+ART and ART alone. Based on long-term outcomes and each country's estimated health opportunity cost, we calculated the country-specific VBP of CTx. RESULTS: The introduction of a hypothetical CTx lowered HIV prevalence and prevented future infections over time, which increased life-years, reduced the number of individuals on ART, reduced AIDS-related deaths, and ultimately led to fewer DALYs versus ART-alone. Our base case estimates for the VBP of CTx ranged from $5400 (Kenya) up to $812,300 (United States). Within each country, the VBP was driven to be greater primarily by lower ART coverage, lower HIV incidence and prevalence, and higher CTx cure probability. The VBP estimates were found to be greater in countries where HIV prevalence was higher, ART coverage was lower and the health opportunity cost was greater. CONCLUSIONS: Our results quantify the VBP for future curative CTx that may apply in different countries and under different circumstances. With greater CTx cure probability, durability and scale up, CTx commands a higher VBP, while improvements in ART coverage may mitigate its value. Our framework can be utilized for estimating this cost given a wide range of scenarios related to the attributes of a given CTx as well as various parameters of the HIV epidemic within a given country.

Strengthening the HIV prevention cascade to maximise epidemiological impact in eastern Zimbabwe: a modelling study.

BACKGROUND: HIV prevention cascades provide a systematic understanding of barriers to prevention. In this study we used mathematical modelling to understand the consequences of these barriers and how the cascade could be strengthened to maximise epidemiological impact, providing potentially important insights for programmes. METHODS: We used an individual-based model of HIV transmission (PopART-IBM), calibrated to data from the Manicaland cohort from eastern Zimbabwe. HIV prevention cascade estimates from this cohort were used as probabilities for indicators in the model representing an individual's motivation, access, and capacity to effectively use pre-exposure prophylaxis, voluntary male medical circumcision, and condoms. We examined how current barriers affect the number and distribution of HIV infections compared with a no-barrier scenario. Using assumptions about how interventions could strengthen the HIV prevention cascade, we estimated the reduction in HIV infections over a 10-year period through addressing different elements of the cascade. FINDINGS: 21 200 new potentially avertable HIV infections will occur over the next 10 years due to existing HIV prevention cascade barriers, 74·2% of the 28 500 new infections that would occur with existing barriers in a population of approximately 1·2 million adults. Removing these barriers would reduce HIV incidence below the benchmarks for epidemic elimination. Addressing all cascade steps in one priority population is substantially more effective than addressing one step across all populations. INTERPRETATION: Interventions exist in eastern Zimbabwe to reduce HIV towards elimination, but barriers of motivation, access, and effective use prevent their full effect being realised. Interventions need to be multilayered and address all steps along the HIV prevention cascade. Models incorporating the HIV prevention cascade can help to identify the main barriers to greater effectiveness. FUNDING: National Institutes of Mental Health, Bill & Melinda Gates Foundation, and Medical Research Council Centre for Global Infectious Disease Analysis funding from the UK Medical Research Council and UK Foreign, Commonwealth & Development Office (FCDO).

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.

Global reporting of progress towards elimination of hepatitis B and hepatitis C.

BACKGROUND: The 69th World Health Assembly endorsed the global health sector strategy on viral hepatitis to eliminate viral hepatitis as a public health threat by 2030. Achieving and measuring the 2030 targets requires a substantial increase in the capacity to test and treat viral hepatitis infections and a mechanism to monitor the progress of hepatitis elimination. This study aimed to identify the gaps in data availability or quality and create a new mechanism to monitor the progress of hepatitis elimination. METHODS: In 2020, using a questionnaire, we collected empirical, systematic, modelled, or surveyed data-reported by WHO country and WHO regional offices-on indicators of progress towards elimination of viral hepatitis, including burden of infection, incidence, mortality, and the cascade of care, and validated these data. FINDINGS: WHO received officially validated country-provided data from 130 countries or territories, and used partner-provided data for 70 countries or territories. We estimated that in 2019, globally, 295·9 million (3·8%) people were living with chronic hepatitis B virus (HBV) infection and 57·8 million (0·8%) people were living with chronic hepatitis C virus (HCV) infection. Globally, there were more than 3·0 million new infections with HBV and HCV and more than 1·1 million deaths due to the viruses in 2019. In 2019, 30·4 million (95% CI 24·3-38·0) individuals living with hepatitis B knew their infection status and 6·6 million (5·3-8·3) people diagnosed with hepatitis B received treatment. Among people with HCV infection, 15·2 million (95% CI 12·1-19·0) had been diagnosed between 2015 and 2019, and 9·4 million (7·5-11·7) people diagnosed with hepatitis C infection were treated with direct-acting antiviral drugs between 2015 and 2019. INTERPRETATION: There has been notable global progress towards hepatitis elimination. In 2019, 30·4 million (10·3%) people living with hepatitis B knew their infection status, which was slightly higher than in 2015 (22·0 million; 9·0%), and 6·6 million (22·7%) of those diagnosed with hepatitis B received treatment, compared with 1·7 million (8·0%) in 2015. Mortality from hepatitis C has declined since 2019, driven by an increase in HCV treatment ten times that of the strategy baseline. However, an estimated 89·7% of HBV infections and 78·6% of HCV infections remain undiagnosed. A new global strategy for 2022-30, based on these new estimates, should be implemented urgently to scale up the screening and treatment of viral hepatitis. FUNDING: World Health Organization.

Cost-effectiveness of different monitoring strategies in a screening and treatment programme for hepatitis B in The Gambia.

Background: Clinical management of chronic hepatitis B virus (HBV) infection is complex and access to antiviral treatment remains limited in sub-Saharan Africa. International guidelines recommend monitoring at least annually for disease progression among HBV-infected people not meeting treatment criteria at initial diagnosis. This study aimed to assess the impact and cost-effectiveness of alternative strategies for monitoring. Methods: We used a mathematical model of HBV transmission and natural history, calibrated to all available West African data, to project the population-level health impact, costs and cost-effectiveness of different monitoring strategies for HBV-infected individuals not initially eligible for antiviral treatment. We assumed that these patients were found in the year 2020 in a hypothetical community-based screening programme in The Gambia. Monitoring frequencies were varied between every 5 and every 1 year and targeted different age groups. Results: The currently recommended annual monitoring frequency was likely to be not cost-effective in comparison with other strategies in this setting. 5-yearly monitoring in 15-45-year olds, at US$338 per disability-adjusted life year averted, had the highest probability of being the most effective cost-effective monitoring strategy. Conclusions: Monitoring less frequently than once a year is a cost-effective strategy in a community-based HBV screening and treatment programme in The Gambia, with the optimal strategy depending on the cost-effectiveness threshold. Efficiencies may be gained by prioritising the 15-45-year age group for more intensive monitoring.

Cost-effectiveness of easy-access, risk-informed oral pre-exposure prophylaxis in HIV epidemics in sub-Saharan Africa: a modelling study.

BACKGROUND: Approaches that allow easy access to pre-exposure prophylaxis (PrEP), such as over-the-counter provision at pharmacies, could facilitate risk-informed PrEP use and lead to lower HIV incidence, but their cost-effectiveness is unknown. We aimed to evaluate conditions under which risk-informed PrEP use is cost-effective. METHODS: We applied a mathematical model of HIV transmission to simulate 3000 setting-scenarios reflecting a range of epidemiological characteristics of communities in sub-Saharan Africa. The prevalence of HIV viral load greater than 1000 copies per mL among all adults (HIV positive and negative) varied from 1·1% to 7·4% (90% range). We hypothesised that if PrEP was made easily available without restriction and with education regarding its use, women and men would use PrEP, with sufficient daily adherence, during so-called seasons of risk (ie, periods in which individuals are at risk of acquiring infection). We refer to this as risk-informed PrEP. For each setting-scenario, we considered the situation in mid-2021 and performed a pairwise comparison of the outcomes of two policies: immediate PrEP scale-up and then continuation for 50 years, and no PrEP. We estimated the relationship between epidemic and programme characteristics and cost-effectiveness of PrEP availability to all during seasons of risk. For our base-case analysis, we assumed a 3-monthly PrEP cost of US$29 (drug $11, HIV test $4, and $14 for additional costs necessary to facilitate education and access), a cost-effectiveness threshold of $500 per disability-adjusted life-year (DALY) averted, an annual discount rate of 3%, and a time horizon of 50 years. In sensitivity analyses, we considered a cost-effectiveness threshold of $100 per DALY averted, a discount rate of 7% per annum, the use of PrEP outside of seasons of risk, and reduced uptake of risk-informed PrEP. FINDINGS: In the context of PrEP scale-up such that 66% (90% range across setting-scenarios 46-81) of HIV-negative people with at least one non-primary condomless sex partner take PrEP in any given period, resulting in 2·6% (0·9-6·0) of all HIV negative adults taking PrEP at any given time, risk-informed PrEP was predicted to reduce HIV incidence by 49% (23-78) over 50 years compared with no PrEP. PrEP was cost-effective in 71% of all setting-scenarios, and cost-effective in 76% of setting-scenarios with prevalence of HIV viral load greater than 1000 copies per mL among all adults higher than 2%. In sensitivity analyses with a $100 per DALY averted cost-effectiveness threshold, a 7% per year discount rate, or with PrEP use that was less well risk-informed than in our base case, PrEP was less likely to be cost-effective, but generally remained cost-effective if the prevalence of HIV viral load greater than 1000 copies per mL among all adults was higher than 3%. In sensitivity analyses based on additional setting-scenarios in which risk-informed PrEP was less extensively used, the HIV incidence reduction was smaller, but the cost-effectiveness of risk-informed PrEP was undiminished. INTERPRETATION: Under the assumption that making PrEP easily accessible for all adults in sub-Saharan Africa in the context of community education leads to risk-informed use, PrEP is likely to be cost-effective in settings with prevalence of HIV viral load greater than 1000 copies per mL among all adults higher than 2%, suggesting the need for implementation of such approaches, with ongoing evaluation. FUNDING: US Agency for International Development, US President's Emergency Plan for AIDS Relief, and Bill & Melinda Gates Foundation.

Socio-demographic factors associated with early antenatal care visits among pregnant women in Malawi: 2004-2016.

INTRODUCTION: In 2016, the WHO published recommendations increasing the number of recommended antenatal care (ANC) visits per pregnancy from four to eight. Prior to the implementation of this policy, coverage of four ANC visits has been suboptimal in many low-income settings. In this study we explore socio-demographic factors associated with early initiation of first ANC contact and attending at least four ANC visits ("ANC4+") in Malawi using the Malawi Demographic and Health Survey (MDHS) data collected between 2004 and 2016, prior to the implementation of new recommendations. METHODS: We combined data from the 2004-5, 2010 and 2015-16 MDHS using Stata version 16. Participants included all women surveyed between the ages of 15-49 who had given birth in the five years preceding the survey. We conducted weighted univariate, bivariate and multivariable logistic regression analysis of the effects of each of the predictor variables on the binary endpoint of the woman attending at least four ANC visits and having the first ANC attendance within or before the four months of pregnancy (ANC4+). To determine whether a factor was included in the model, the likelihood ratio test was used with a statistical significance of P< 0.05 as the threshold. RESULTS: We evaluated data collected in surveys in 2004/5, 2010 and 2015/6 from 26386 women who had given birth in the five years before being surveyed. The median gestational age, in months, at the time of presenting for the first ANC visit was 5 (inter quartile range: 4-6). The proportion of women initiating ANC4+ increased from 21.3% in 2004-5 to 38.8% in 2015-16. From multivariate analysis, there was increasing trend in ANC4+ from women aged 20-24 years (adjusted odds ratio (aOR) = 1.27, 95%CI:1.05-1.53, P = 0.01) to women aged 45-49 years (aOR = 1.91, 95%CI:1.18-3.09, P = 0.008) compared to those aged 15-19 years. Women from richest socio-economic position ((aOR = 1.32, 95%CI:1.12-1.58, P<0.001) were more likely to demonstrate ANC4+ than those from low socio-economic position. Additionally, women who had completed secondary (aOR = 1.24, 95%CI:1.02-1.51, P = 0.03) and tertiary (aOR = 2.64, 95%CI:1.65-4.22, P<0.001) education were more likely to report having ANC4+ than those with no formal education. Conversely increasing parity was associated with a reduction in likelihood of ANC4+ with women who had previously delivered 2-3 (aOR = 0.74, 95%CI:0.63-0.86, P<0.001), 4-5 (aOR = 0.65, 95%CI:0.53-0.80, P<0.001) or greater than 6 (aOR = 0.61, 95%CI: 0.47-0.79, <0.001) children being less likely to demonstrate ANC4+. CONCLUSION: The proportion of women reporting ANC4+ and of key ANC interventions in Malawi have increased significantly since 2004. However, we found that most women did not access the recommended number of ANC visits in Malawi, prior to the 2016 WHO policy change which may mean that women are less likely to undertake the 2016 WHO recommendation of 8 contacts per pregnancy. Additionally, our results highlighted significant variation in coverage according to key socio-demographic variables which should be considered when devising national strategies to ensure that all women access the appropriate frequency of ANC visits during their pregnancy.

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.

Modeling the epidemiological impact of the UNAIDS 2025 targets to end AIDS as a public health threat by 2030.

BACKGROUND: UNAIDS has established new program targets for 2025 to achieve the goal of eliminating AIDS as a public health threat by 2030. This study reports on efforts to use mathematical models to estimate the impact of achieving those targets. METHODS AND FINDINGS: We simulated the impact of achieving the targets at country level using the Goals model, a mathematical simulation model of HIV epidemic dynamics that includes the impact of prevention and treatment interventions. For 77 high-burden countries, we fit the model to surveillance and survey data for 1970 to 2020 and then projected the impact of achieving the targets for the period 2019 to 2030. Results from these 77 countries were extrapolated to produce estimates for 96 others. Goals model results were checked by comparing against projections done with the Optima HIV model and the AIDS Epidemic Model (AEM) for selected countries. We included estimates of the impact of societal enablers (access to justice and law reform, stigma and discrimination elimination, and gender equality) and the impact of Coronavirus Disease 2019 (COVID-19). Results show that achieving the 2025 targets would reduce new annual infections by 83% (71% to 86% across regions) and AIDS-related deaths by 78% (67% to 81% across regions) by 2025 compared to 2010. Lack of progress on societal enablers could endanger these achievements and result in as many as 2.6 million (44%) cumulative additional new HIV infections and 440,000 (54%) more AIDS-related deaths between 2020 and 2030 compared to full achievement of all targets. COVID-19-related disruptions could increase new HIV infections and AIDS-related deaths by 10% in the next 2 years, but targets could still be achieved by 2025. Study limitations include the reliance on self-reports for most data on behaviors, the use of intervention effect sizes from published studies that may overstate intervention impacts outside of controlled study settings, and the use of proxy countries to estimate the impact in countries with fewer than 4,000 annual HIV infections. CONCLUSIONS: The new targets for 2025 build on the progress made since 2010 and represent ambitious short-term goals. Achieving these targets would bring us close to the goals of reducing new HIV infections and AIDS-related deaths by 90% between 2010 and 2030. By 2025, global new infections and AIDS deaths would drop to 4.4 and 3.9 per 100,000 population, and the number of people living with HIV (PLHIV) would be declining. There would be 32 million people on treatment, and they would need continuing support for their lifetime. Incidence for the total global population would be below 0.15% everywhere. The number of PLHIV would start declining by 2023.

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.

Potential impact of intervention strategies on COVID-19 transmission in Malawi: a mathematical modelling study.

BACKGROUND: COVID-19 mitigation strategies have been challenging to implement in resource-limited settings due to the potential for widespread disruption to social and economic well-being. Here we predict the clinical severity of COVID-19 in Malawi, quantifying the potential impact of intervention strategies and increases in health system capacity. METHODS: The infection fatality ratios (IFR) were predicted by adjusting reported IFR for China, accounting for demography, the current prevalence of comorbidities and health system capacity. These estimates were input into an age-structured deterministic model, which simulated the epidemic trajectory with non-pharmaceutical interventions and increases in health system capacity. FINDINGS: The predicted population-level IFR in Malawi, adjusted for age and comorbidity prevalence, is lower than that estimated for China (0.26%, 95% uncertainty interval (UI) 0.12%-0.69%, compared with 0.60%, 95% CI 0.4% to 1.3% in China); however, the health system constraints increase the predicted IFR to 0.83%, 95% UI 0.49%-1.39%. The interventions implemented in January 2021 could potentially avert 54 400 deaths (95% UI 26 900-97 300) over the course of the epidemic compared with an unmitigated outbreak. Enhanced shielding of people aged ≥60 years could avert 40 200 further deaths (95% UI 25 300-69 700) and halve intensive care unit admissions at the peak of the outbreak. A novel therapeutic agent which reduces mortality by 0.65 and 0.8 for severe and critical cases, respectively, in combination with increasing hospital capacity, could reduce projected mortality to 2.5 deaths per 1000 population (95% UI 1.9-3.6). CONCLUSION: We find the interventions currently used in Malawi are unlikely to effectively prevent SARS-CoV-2 transmission but will have a significant impact on mortality. Increases in health system capacity and the introduction of novel therapeutics are likely to further reduce the projected numbers of deaths.

Progress towards elimination of mother-to-child transmission of hepatitis B virus infection in China: a modelling analysis.

OBJECTIVE: To determine the projected burden of hepatitis B virus (HBV) in China, the intervention strategies that can eliminate mother-to-child transmission (MTCT) by 2030 or earlier and the measurable parameters that can be used to monitor progress towards this target. METHODS: We developed a dynamic, sex- and age-stratified model of the HBV epidemic in China, calibrated using hepatitis B surface antigen (HBsAg) and e antigen (HBeAg) prevalence data from sequential national serosurveys (1979-2014) and the numbers of HBV-related cancer deaths (2012). We determined whether China can achieve elimination of MTCT of HBV by 2030 under current prevention interventions. We modelled various intervention scenarios to represent different coverage levels of birth-dose HBV vaccination, hepatitis B immunoglobulin to newborns of HBsAg-positive mothers and antiviral therapy (tenofovir) to HBeAg-positive pregnant women. FINDINGS: We project that, if current levels of prevention interventions are maintained, China will achieve the elimination target by 2029. By modelling various intervention scenarios, we found that this can be brought forward to 2025 by increasing coverage of birth-dose vaccination, or to 2024 by the administration of tenofovir to HBeAg-positive pregnant women. We found that achievement of the target by 2025 would be predicted by a measurement of less than 2% MTCT in 2020. CONCLUSION: Our results highlight how high-quality national data can be combined with modelling in monitoring the elimination of MTCT of HBV. By demonstrating the impact of increased interventions on target achievement dates, we anticipate that other high-burden countries will be motivated to strengthen HBV prevention policies.

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.

Characteristics and outcomes of clinically diagnosed RT-PCR swab negative COVID-19: a retrospective cohort study.

Patients with strong clinical features of COVID-19 with negative real time polymerase chain reaction (RT-PCR) SARS-CoV-2 testing are not currently included in official statistics. The scale, characteristics and clinical relevance of this group are not well described. We performed a retrospective cohort study in two large London hospitals to characterize the demographic, clinical, and hospitalization outcome characteristics of swab-negative clinical COVID-19 patients. We found 1 in 5 patients with a negative swab and clinical suspicion of COVID-19 received a clinical diagnosis of COVID-19 within clinical documentation, discharge summary or death certificate. We compared this group to a similar swab positive cohort and found similar demographic composition, symptomology and laboratory findings. Swab-negative clinical COVID-19 patients had better outcomes, with shorter length of hospital stay, reduced need for > 60% supplementary oxygen and reduced mortality. Patients with strong clinical features of COVID-19 that are swab-negative are a common clinical challenge. Health systems must recognize and plan for the management of swab-negative patients in their COVID-19 clinical management, infection control policies and epidemiological assessments.