The potential of gene drives in malaria vector species to control malaria in African environments.

Gene drives are a promising means of malaria control with the potential to cause sustained reductions in transmission. In real environments, however, their impacts will depend on local ecological and epidemiological factors. We develop a data-driven model to investigate the impacts of gene drives that causes vector population suppression. We simulate gene drive releases in sixteen ~ 12,000 km2 areas of west Africa that span variation in vector ecology and malaria prevalence, and estimate reductions in vector abundance, malaria prevalence and clinical cases. Average reductions in vector abundance ranged from 71.6-98.4% across areas, while impacts on malaria depended strongly on which vector species were targeted. When other new interventions including RTS,S vaccination and pyrethroid-PBO bednets were in place, at least 60% more clinical cases were averted when gene drives were added, demonstrating the benefits of integrated interventions. Our results show that different strategies for gene drive implementation may be required across different African settings.

Impact of the 100 days mission for vaccines on COVID-19: a mathematical modelling study.

BACKGROUND: The COVID-19 pandemic has underscored the beneficial impact of vaccines. It also highlighted the need for future investments to expedite an equitable vaccine distribution. The 100 Days Mission aims to develop and make available a new vaccine against a future pathogen with pandemic potential within 100 days of that pathogen threat being recognised. We assessed the value of this mission by estimating the impact that it could have had on the COVID-19 pandemic. METHODS: Using a previously published model of SARS-CoV-2 transmission dynamics fitted to excess mortality during the COVID-19 pandemic, we projected scenarios for three different investment strategies: rapid development and manufacture of a vaccine, increasing manufacturing capacity to eliminate supply constraints, and strengthening health systems to enable faster vaccine roll-outs and global equity. Each scenario was compared against the observed COVID-19 pandemic to estimate the public health and health-economic impacts of each scenario. FINDINGS: If countries implemented non-pharmaceutical interventions (NPIs) as they did historically, the 100 Days Mission could have averted an estimated 8·33 million deaths (95% credible interval [CrI] 7·70-8·68) globally, mostly in lower-middle income countries. This corresponds to a monetary saving of US$14·35 trillion (95% CrI 12·96-17·87) based on the value of statistical life-years saved. Investment in manufacturing and health systems further increases deaths averted to 11·01 million (95% CrI 10·60-11·49). Under an alternative scenario whereby NPIs are lifted earlier on the basis of vaccine coverage, the 100 Days Mission alone could have reduced restrictions by 12 600 days (95% CrI 12 300-13 100) globally while still averting 5·76 million deaths (95% CrI 4·91-6·81). INTERPRETATION: Our findings show the value of the 100 Days Mission and how these can be amplified through improvements in manufacturing and health systems equity. However, these investments must be enhanced by prioritising a more equitable global vaccine distribution. FUNDING: Schmidt Science Fellowship in partnership with the Rhodes Trust, WHO, UK Medical Research Council, Coalition for Epidemic Preparedness Innovations.

Risk of selection and timelines for the continued spread of artemisinin and partner drug resistance in Africa.

The introduction of artemisinin combination therapies (ACTs) has significantly reduced the burden of Plasmodium falciparum malaria, yet the emergence of artemisinin partial resistance (ART-R) as well as partner drug resistance threatens these gains. Recent confirmations of prevalent de novo ART-R mutations in Africa, in particular in Rwanda, Uganda and Ethiopia, underscore the urgency of addressing this issue in Africa. Our objective is to characterise this evolving resistance landscape in Africa and understand the speed with which ART-R will continue to spread. We produce estimates of both ART-R and partner drug resistance by bringing together WHO, WWARN and MalariaGen Pf7k data on antimalarial resistance in combination with a literature review. We integrate these estimates within a mathematical modelling approach, aincorporating to estimate parameters known to impact the selection of ART-R for each malaria-endemic country and explore scenarios of ART-R spread and establishment. We identify 16 malaria-endemic countries in Africa to prioritise for surveillance and future deployment of alternative antimalarial strategies, based on ART-R reaching greater than 10% prevalence by 2040 under current malaria burden and effective-treatment coverage. If resistance continues to spread at current rates with no change in drug policy, we predict that partner drug resistance will emerge and the mean percentage of treatment failure across Africa will reach 30.74% by 2060 (parameter uncertainty range: 24.98% - 34.54%). This translates to an alarming number of treatment failures, with 52,980,600 absolute cases of treatment failure predicted in 2060 in Africa (parameter uncertainty range: 26,374,200 - 93,672,400) based on current effective treatment coverage. Our results provide a refined and updated prediction model for the emergence of ART-R to help guide antimalarial policy and prioritise future surveillance efforts and innovation in Africa. These results put into stark context the speed with which antimalarial resistance may spread in Africa if left unchecked, confirming the need for swift and decisive action in formulating antimalarial treatment policies focused on furthering malaria control and containing antimalarial resistance in Africa. The rise of artemisinin partial resistance (ART-R) and increasing partner drug tolerance by Plasmodium falciparum malaria in Africa threatens to undo malaria control efforts. Recent confirmations of de novo ART-R markers in Rwanda, Uganda, and Ethiopia highlight the urgent need to address this threat in Africa, where the vast majority of cases and deaths occur. This study characterises the resistance landscape and predicts the spread of antimalarial resistance across Africa. We estimate and map the current levels of resistance markers related to artemisinin and its partner drugs using WHO, WWARN, and MalariaGen Pf7k data. We combine these estimates with current malaria transmission and treatment data and use an established individual-based model of malaria resistance to simulate future resistance spread. We identify 16 African countries at highest risk of ART-R for prioritisation of enhanced surveillance and alternative antimalarial strategies. We project that, without policy changes, ART-R will exceed 10% in these regions by 2040. By 2060, if resistance spreads unchecked, we predict mean treatment failure rates will reach 30.74% (parameter uncertainty range: 24.98% - 34.54%) across Africa. This alarming spread of resistance is predicted to cause 52.98 million treatment failures (uncertainty range: 26.37 million - 93.67 million) in 2060. The impact of antimalarial resistance in Africa, if left unchecked, would hugely damage efforts to reduce malaria burden. Our results underscore the critical need for swift policy action to contain resistance and guide future surveillance and intervention efforts.

The public health impact and cost-effectiveness of the R21/Matrix-M malaria vaccine: a mathematical modelling study.

BACKGROUND: The R21/Matrix-M vaccine has demonstrated high efficacy against Plasmodium falciparum clinical malaria in children in sub-Saharan Africa. Using trial data, we aimed to estimate the public health impact and cost-effectiveness of vaccine introduction across sub-Saharan Africa. METHODS: We fitted a semi-mechanistic model of the relationship between anti-circumsporozoite protein antibody titres and vaccine efficacy to data from 3 years of follow-up in the phase 2b trial of R21/Matrix-M in Nanoro, Burkina Faso. We validated the model by comparing predicted vaccine efficacy to that observed over 12-18 months in the phase 3 trial. Integrating this framework within a mathematical transmission model, we estimated the cases, malaria deaths, and disability-adjusted life-years (DALYs) averted and cost-effectiveness over a 15-year time horizon across a range of transmission settings in sub-Saharan Africa. Cost-effectiveness was estimated incorporating the cost of vaccine introduction (dose, consumables, and delivery) relative to existing interventions at baseline. We report estimates at a median of 20% parasite prevalence in children aged 2-10 years (PfPR2-10) and ranges from 3% to 65% PfPR2-10. FINDINGS: Anti-circumsporozoite protein antibody titres were found to satisfy the criteria for a surrogate of protection for vaccine efficacy against clinical malaria. Age-based implementation of a four-dose regimen of R21/Matrix-M vaccine was estimated to avert 181 825 (range 38 815-333 491) clinical cases per 100 000 fully vaccinated children in perennial settings and 202 017 (29 868-405 702) clinical cases per 100 000 fully vaccinated children in seasonal settings. Similar estimates were obtained for seasonal or hybrid implementation. Under an assumed vaccine dose price of US$3, the incremental cost per clinical case averted was $7 (range 4-48) in perennial settings and $6 (3-63) in seasonal settings and the incremental cost per DALY averted was $34 (29-139) in perennial settings and $30 (22-172) in seasonal settings, with lower cost-effectiveness ratios in settings with higher PfPR2-10. INTERPRETATION: Introduction of the R21/Matrix-M malaria vaccine could have a substantial public health benefit across sub-Saharan Africa. FUNDING: The Wellcome Trust, the Bill & Melinda Gates Foundation, the UK Medical Research Council, the European and Developing Countries Clinical Trials Partnership 2 and 3, the NIHR Oxford Biomedical Research Centre, and the Serum Institute of India, Open Philanthropy.

Modeling resource allocation strategies for insecticide-treated bed nets to achieve malaria eradication.

Large reductions in the global malaria burden have been achieved, but plateauing funding poses a challenge for progressing towards the ultimate goal of malaria eradication. Using previously published mathematical models of Plasmodium falciparum and Plasmodium vivax transmission incorporating insecticide-treated nets (ITNs) as an illustrative intervention, we sought to identify the global funding allocation that maximized impact under defined objectives and across a range of global funding budgets. The optimal strategy for case reduction mirrored an allocation framework that prioritizes funding for high-transmission settings, resulting in total case reductions of 76% and 66% at intermediate budget levels, respectively. Allocation strategies that had the greatest impact on case reductions were associated with lesser near-term impacts on the global population at risk. The optimal funding distribution prioritized high ITN coverage in high-transmission settings endemic for P. falciparum only, while maintaining lower levels in low-transmission settings. However, at high budgets, 62% of funding was targeted to low-transmission settings co-endemic for P. falciparum and P. vivax. These results support current global strategies to prioritize funding to high-burden P. falciparum-endemic settings in sub-Saharan Africa to minimize clinical malaria burden and progress towards elimination, but highlight a trade-off with 'shrinking the map' through a focus on near-elimination settings and addressing the burden of P. vivax.

Long-term vaccination strategies to mitigate the impact of SARS-CoV-2 transmission: A modelling study.

BACKGROUND: Vaccines have reduced severe disease and death from Coronavirus Disease 2019 (COVID-19). However, with evidence of waning efficacy coupled with continued evolution of the virus, health programmes need to evaluate the requirement for regular booster doses, considering their impact and cost-effectiveness in the face of ongoing transmission and substantial infection-induced immunity. METHODS AND FINDINGS: We developed a combined immunological-transmission model parameterised with data on transmissibility, severity, and vaccine effectiveness. We simulated Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) transmission and vaccine rollout in characteristic global settings with different population age-structures, contact patterns, health system capacities, prior transmission, and vaccine uptake. We quantified the impact of future vaccine booster dose strategies with both ancestral and variant-adapted vaccine products, while considering the potential future emergence of new variants with modified transmission, immune escape, and severity properties. We found that regular boosting of the oldest age group (75+) is an efficient strategy, although large numbers of hospitalisations and deaths could be averted by extending vaccination to younger age groups. In countries with low vaccine coverage and high infection-derived immunity, boosting older at-risk groups was more effective than continuing primary vaccination into younger ages in our model. Our study is limited by uncertainty in key parameters, including the long-term durability of vaccine and infection-induced immunity as well as uncertainty in the future evolution of the virus. CONCLUSIONS: Our modelling suggests that regular boosting of the high-risk population remains an important tool to reduce morbidity and mortality from current and future SARS-CoV-2 variants. Our results suggest that focusing vaccination in the highest-risk cohorts will be the most efficient (and hence cost-effective) strategy to reduce morbidity and mortality.

Estimating the burden of severe malarial anaemia and access to hospital care in East Africa.

Severe malarial anaemia can be fatal if not promptly treated. Hospital studies may under-represent the true burden because cases often occur in settings with poor access to healthcare. We estimate the relationship of community prevalence of malaria infection and severe malarial anaemia with the incidence of severe malarial anaemia cases in hospital, using survey data from 21 countries and hospital data from Kenya, Tanzania and Uganda. The estimated percentage of severe malarial anaemia cases that were hospitalised is low and consistent for Kenya (21% (95% CrI: 7%, 47%)), Tanzania (18% (95% CrI: 5%, 52%)) and Uganda (23% (95% CrI: 9%, 48%)). The majority of severe malarial anaemia cases remain in the community, with the consequent public health burden being contingent upon the severity of these cases. Alongside health system strengthening, research to better understand the spectrum of disease associated with severe malarial anaemia cases in the community is a priority.

Estimating long-term vaccine effectiveness against SARS-CoV-2 variants: a model-based approach.

With the ongoing evolution of the SARS-CoV-2 virus updated vaccines may be needed. We fitted a model linking immunity levels and protection to vaccine effectiveness data from England for three vaccines (Oxford/AstraZeneca AZD1222, Pfizer-BioNTech BNT162b2, Moderna mRNA-1273) and two variants (Delta, Omicron). Our model reproduces the observed sustained protection against hospitalisation and death from the Omicron variant over the first six months following dose 3 with the ancestral vaccines but projects a gradual waning to moderate protection after 1 year. Switching the fourth dose to a variant-matched vaccine against Omicron BA.1/2 is projected to prevent nearly twice as many hospitalisations and deaths over a 1-year period compared to administering the ancestral vaccine. This result is sensitive to the degree to which immunogenicity data can be used to predict vaccine effectiveness and uncertainty regarding the impact that infection-induced immunity (not captured here) may play in modifying future vaccine effectiveness.

The societal cost of vaccine refusal: A modelling study using measles vaccination as a case study.

BACKGROUND: Increasing vaccine hesitancy and refusal poses a challenge to public health as even small reductions in vaccine uptake can result in large outbreaks of infectious diseases. Here we estimate the societal costs of vaccine refusal using measles as a case study. METHODS: We developed a compartmental metapopulation model of measles transmission to explore how the changes in the size and level of social mixing between populations that are "pro-vaccination", and "anti-vaccination" impacts the burden of measles. Using the projected cases and deaths, we calculated the health, healthcare, direct medical costs, and productivity loss associated with vaccine refusal. Using measles in England as a case study, we quantified the societal costs that each vaccine refusal imposes on society. FINDINGS: When there is a high level of mixing between the pro- and anti-vaccination populations, those that refuse to be vaccinated benefit from the herd immunity afforded by the pro-vaccination population. At the same time, their refusal to be vaccinated increases the burden in those that are vaccinated due to imperfect vaccines, and in those that are not able to be vaccinated due to other underlying health conditions. Using England as a case study, we estimate that this translates to a societal loss of GBP 292 million and disease burden of 17 630 quality-adjusted-life-years (sensitivity range 10 594-50 379) over a 20-year time horizon. Of these costs, 26 % are attributable to healthcare costs and 74 % to productivity losses for patients and their carers. This translates to a societal loss per vaccine refusal of GBP 162.21 and 0.01 (0.006-0.03) quality-adjusted-life-years. INTERPRETATION: Our findings demonstrate that even low levels of vaccine refusal can have a substantial and measurable societal burden on the population. These estimates can support the value of investment in interventions that address vaccine hesitancy and vaccine refusal, providing not only improved public health but also potential economic benefits to society.

Modelling the relative cost-effectiveness of the RTS,S/AS01 malaria vaccine compared to investment in vector control or chemoprophylaxis.

BACKGROUND: The World Health Organization has recommended a 4-dose schedule of the RTS,S/AS01 (RTS,S) vaccine for children in regions of moderate to high P. falciparum transmission. Faced with limited supply and finite resources, global funders and domestic malaria control programs will need to examine the relative cost-effectiveness of RTS,S and identify target areas for vaccine implementation relative to scale-up of existing interventions. METHODS: Using an individual-based mathematical model of P. falciparum, we modelled the cost-effectiveness of RTS,S across a range of settings in sub-Saharan Africa, incorporating various rainfall patterns, insecticide-treated net (ITN) use, treatment coverage, and parasite prevalence bands. We compare age-based and seasonal RTS,S administration to increasing ITN usage, switching to next generation ITNs in settings experiencing insecticide-resistance, and introduction of seasonal malaria chemoprevention (SMC) in areas of seasonal transmission. RESULTS: For RTS,S to be the most cost-effective intervention option considered, the maximum cost per dose was less than $9.30 USD in 90.9% of scenarios. Nearly all (89.8%) values at or above $9.30 USD per dose were in settings with 60% established bed net use and / or with established SMC, and 76.3% were in the highest PfPR2-10 band modelled (40%). Addition of RTS,S to strategies involving 60% ITN use, increased ITN usage or a switch to PBO nets, and SMC, if eligible, still led to significant marginal case reductions, with a median of 2,653 (IQR: 1,741 to 3,966) cases averted per 100,000 people annually, and 82,270 (IQR: 54,034 to 123,105) cases averted per 100,000 fully vaccinated children (receiving at least three doses). CONCLUSIONS: Use of RTS,S results in reductions in malaria cases and deaths even when layered upon existing interventions. When comparing relative cost-effectiveness, scale up of ITNs, introduction of SMC, and switching to new technology nets should be prioritized in eligible settings.

Seasonal dynamics of Anopheles stephensi and its implications for mosquito detection and emergent malaria control in the Horn of Africa.

Invasion of the malaria vector Anopheles stephensi across the Horn of Africa threatens control efforts across the continent, particularly in urban settings where the vector is able to proliferate. Malaria transmission is primarily determined by the abundance of dominant vectors, which often varies seasonally with rainfall. However, it remains unclear how An. stephensi abundance changes throughout the year, despite this being a crucial input to surveillance and control activities. We collate longitudinal catch data from across its endemic range to better understand the vector's seasonal dynamics and explore the implications of this seasonality for malaria surveillance and control across the Horn of Africa. Our analyses reveal pronounced variation in seasonal dynamics, the timing and nature of which are poorly predicted by rainfall patterns. Instead, they are associated with temperature and patterns of land use; frequently differing between rural and urban settings. Our results show that timing entomological surveys to coincide with rainy periods is unlikely to improve the likelihood of detecting An. stephensi. Integrating these results into a malaria transmission model, we show that timing indoor residual spraying campaigns to coincide with peak rainfall offers little improvement in reducing disease burden compared to starting in a random month. Our results suggest that unlike other malaria vectors in Africa, rainfall may be a poor guide to predicting the timing of peaks in An. stephensi-driven malaria transmission. This highlights the urgent need for longitudinal entomological monitoring of the vector in its new environments given recent invasion and potential spread across the continent.

Projected health impact of post-discharge malaria chemoprevention among children with severe malarial anaemia in Africa.

Children recovering from severe malarial anaemia (SMA) remain at high risk of readmission and death after discharge from hospital. However, a recent trial found that post-discharge malaria chemoprevention (PDMC) with dihydroartemisinin-piperaquine reduces this risk. We developed a mathematical model describing the daily incidence of uncomplicated and severe malaria requiring readmission among 0-5-year old children after hospitalised SMA. We fitted the model to a multicentre clinical PDMC trial using Bayesian methods and modelled the potential impact of PDMC across malaria-endemic African countries. In the 20 highest-burden countries, we estimate that only 2-5 children need to be given PDMC to prevent one hospitalised malaria episode, and less than 100 to prevent one death. If all hospitalised SMA cases access PDMC in moderate-to-high transmission areas, 38,600 (range 16,900-88,400) malaria-associated readmissions could be prevented annually, depending on access to hospital care. We estimate that recurrent SMA post-discharge constitutes 19% of all SMA episodes in moderate-to-high transmission settings.

Seasonal use case for the RTS,S/AS01 malaria vaccine: a mathematical modelling study.

BACKGROUND: A 2021 clinical trial of seasonal RTS,S/AS01E (RTS,S) vaccination showed that vaccination was non-inferior to seasonal malaria chemoprevention (SMC) in preventing clinical malaria. The combination of these two interventions provided significant additional protection against clinical and severe malaria outcomes. Projections of the effect of this novel approach to RTS,S vaccination in seasonal transmission settings for extended timeframes and across a range of epidemiological settings are needed to inform policy recommendations. METHODS: We used a mathematical, individual-based model of malaria transmission that was fitted to data on the relationship between entomological inoculation rate and parasite prevalence, clinical disease, severe disease, and deaths from multiple sites across Africa. The model was validated with results from a phase 3b trial assessing the effect of SV-RTS,S in Mali and Burkina Faso. We developed three intervention efficacy models with varying degrees and durations of protection for our population-level modelling analysis to assess the potential effect of an RTS,S vaccination schedule based on age (doses were delivered to children aged 6 months, 7·5 months, and 9 months for the first three doses, and at 27 months of age for the fourth dose) or season (children aged 5-17 months at the time of first vaccination received the first three doses in the 3 months preceding the transmission season, with any subsequent doses up to five doses delivered annually) in seasonal transmission settings both in the absence and presence of SMC with sulfadoxine-pyrimethamine plus amodiaquine. This is modelled as a full therapeutic course delivered every month for four or five months of the peak in transmission season. Estimates of cases and deaths averted in a population of 100 000 children aged 0-5 years were calculated over a 15-year time period for a range of levels of malaria transmission intensity (Plasmodium falciparum parasite prevalence in children aged 2-10 years between 10% and 65%) and over two west Africa seasonality archetypes. FINDINGS: Seasonally targeting RTS,S resulted in greater absolute reductions in malaria cases and deaths compared with an age-based strategy, averting an additional 14 000-47 000 cases per 100 000 children aged 5 years and younger over 15 years, dependent on seasonality and transmission intensity. We predicted that adding seasonally targeted RTS,S to SMC would reduce clinical incidence by up to an additional 42 000-67 000 cases per 100 000 children aged 5 years and younger over 15 years compared with SMC alone. Transmission season duration was a key determinant of intervention effect, with the advantage of adding RTS,S to SMC predicted to be smaller with shorter transmission seasons. INTERPRETATION: RTS,S vaccination in seasonal settings could be a valuable additional tool to existing interventions, with seasonal delivery maximising the effect relative to an age-based approach. Decisions surrounding deployment strategies of RTS,S in such settings will need to consider the local and regional variations in seasonality, current rates of other interventions, and potential achievable RTS,S coverage. FUNDING: UK Medical Research Council, UK Foreign Commonwealth & Development Office, The Wellcome Trust, and The Royal society.

Global variation in force-of-infection trends for human Taenia solium taeniasis/cysticercosis.

Infection by Taenia solium poses a major burden across endemic countries. The World Health Organization (WHO) 2021-2030 Neglected Tropical Diseases roadmap has proposed that 30% of endemic countries achieve intensified T. solium control in hyperendemic areas by 2030. Understanding geographical variation in age-prevalence profiles and force-of-infection (FoI) estimates will inform intervention designs across settings. Human taeniasis (HTT) and human cysticercosis (HCC) age-prevalence data from 16 studies in Latin America, Africa, and Asia were extracted through a systematic review. Catalytic models, incorporating diagnostic performance uncertainty, were fitted to the data using Bayesian methods, to estimate rates of antibody (Ab)-seroconversion, infection acquisition and Ab-seroreversion or infection loss. HCC FoI and Ab-seroreversion rates were also estimated across 23 departments in Colombia from 28,100 individuals. Across settings, there was extensive variation in all-ages seroprevalence. Evidence for Ab-seroreversion or infection loss was found in most settings for both HTT and HCC and for HCC Ab-seroreversion in Colombia. The average duration until humans became Ab-seropositive/infected decreased as all-age (sero)prevalence increased. There was no clear relationship between the average duration humans remain Ab-seropositive and all-age seroprevalence. Marked geographical heterogeneity in T. solium transmission rates indicate the need for setting-specific intervention strategies to achieve the WHO goals.

Global impact of the first year of COVID-19 vaccination: a mathematical modelling study.

BACKGROUND: The first COVID-19 vaccine outside a clinical trial setting was administered on Dec 8, 2020. To ensure global vaccine equity, vaccine targets were set by the COVID-19 Vaccines Global Access (COVAX) Facility and WHO. However, due to vaccine shortfalls, these targets were not achieved by the end of 2021. We aimed to quantify the global impact of the first year of COVID-19 vaccination programmes. METHODS: A mathematical model of COVID-19 transmission and vaccination was separately fit to reported COVID-19 mortality and all-cause excess mortality in 185 countries and territories. The impact of COVID-19 vaccination programmes was determined by estimating the additional lives lost if no vaccines had been distributed. We also estimated the additional deaths that would have been averted had the vaccination coverage targets of 20% set by COVAX and 40% set by WHO been achieved by the end of 2021. FINDINGS: Based on official reported COVID-19 deaths, we estimated that vaccinations prevented 14·4 million (95% credible interval [Crl] 13·7-15·9) deaths from COVID-19 in 185 countries and territories between Dec 8, 2020, and Dec 8, 2021. This estimate rose to 19·8 million (95% Crl 19·1-20·4) deaths from COVID-19 averted when we used excess deaths as an estimate of the true extent of the pandemic, representing a global reduction of 63% in total deaths (19·8 million of 31·4 million) during the first year of COVID-19 vaccination. In COVAX Advance Market Commitment countries, we estimated that 41% of excess mortality (7·4 million [95% Crl 6·8-7·7] of 17·9 million deaths) was averted. In low-income countries, we estimated that an additional 45% (95% CrI 42-49) of deaths could have been averted had the 20% vaccination coverage target set by COVAX been met by each country, and that an additional 111% (105-118) of deaths could have been averted had the 40% target set by WHO been met by each country by the end of 2021. INTERPRETATION: COVID-19 vaccination has substantially altered the course of the pandemic, saving tens of millions of lives globally. However, inadequate access to vaccines in low-income countries has limited the impact in these settings, reinforcing the need for global vaccine equity and coverage. FUNDING: Schmidt Science Fellowship in partnership with the Rhodes Trust; WHO; UK Medical Research Council; Gavi, the Vaccine Alliance; Bill & Melinda Gates Foundation; National Institute for Health Research; and Community Jameel.

Estimating the COVID-19 infection fatality ratio accounting for seroreversion using statistical modelling.

Background: The infection fatality ratio (IFR) is a key statistic for estimating the burden of coronavirus disease 2019 (COVID-19) and has been continuously debated throughout the COVID-19 pandemic. The age-specific IFR can be quantified using antibody surveys to estimate total infections, but requires consideration of delay-distributions from time from infection to seroconversion, time to death, and time to seroreversion (i.e. antibody waning) alongside serologic test sensitivity and specificity. Previous IFR estimates have not fully propagated uncertainty or accounted for these potential biases, particularly seroreversion. Methods: We built a Bayesian statistical model that incorporates these factors and applied this model to simulated data and 10 serologic studies from different countries. Results: We demonstrate that seroreversion becomes a crucial factor as time accrues but is less important during first-wave, short-term dynamics. We additionally show that disaggregating surveys by regions with higher versus lower disease burden can inform serologic test specificity estimates. The overall IFR in each setting was estimated at 0.49-2.53%. Conclusion: We developed a robust statistical framework to account for full uncertainties in the parameters determining IFR. We provide code for others to apply these methods to further datasets and future epidemics.

Modelling the impact of vaccine hesitancy in prolonging the need for Non-Pharmaceutical Interventions to control the COVID-19 pandemic.

Background: Vaccine hesitancy - a delay in acceptance or refusal of vaccines despite availability - has the potential to threaten the successful roll-out of SARS-CoV-2 vaccines globally. In this study, we aim to understand the likely impact of vaccine hesitancy on the control of the COVID-19 pandemic. Methods: We modelled the potential impact of vaccine hesitancy on the control of the pandemic and the relaxation of non-pharmaceutical interventions (NPIs) by combining an epidemiological model of SARS-CoV-2 transmission with data on vaccine hesitancy from population surveys. Results: Our simulations suggest that the mortality over a 2-year period could be up to 7.6 times higher in countries with high vaccine hesitancy compared to an ideal vaccination uptake if NPIs are relaxed. Alternatively, high vaccine hesitancy could prolong the need for NPIs to remain in place. Conclusions: While vaccination is an individual choice, vaccine-hesitant individuals have a substantial impact on the pandemic trajectory, which may challenge current efforts to control COVID-19. In order to prevent such outcomes, addressing vaccine hesitancy with behavioural interventions is an important priority in the control of the COVID-19 pandemic.

A novel statistical framework for exploring the population dynamics and seasonality of mosquito populations.

Understanding the temporal dynamics of mosquito populations underlying vector-borne disease transmission is key to optimizing control strategies. Many questions remain surrounding the drivers of these dynamics and how they vary between species-questions rarely answerable from individual entomological studies (that typically focus on a single location or species). We develop a novel statistical framework enabling identification and classification of time series with similar temporal properties, and use this framework to systematically explore variation in population dynamics and seasonality in anopheline mosquito time series catch data spanning seven species, 40 years and 117 locations across mainland India. Our analyses reveal pronounced variation in dynamics across locations and between species in the extent of seasonality and timing of seasonal peaks. However, we show that these diverse dynamics can be clustered into four 'dynamical archetypes', each characterized by distinct temporal properties and associated with a largely unique set of environmental factors. Our results highlight that a range of environmental factors including rainfall, temperature, proximity to static water bodies and patterns of land use (particularly urbanicity) shape the dynamics and seasonality of mosquito populations, and provide a generically applicable framework to better identify and understand patterns of seasonal variation in vectors relevant to public health.

Optimising the deployment of vector control tools against malaria: a data-informed modelling study.

BACKGROUND: Concern that insecticide resistant mosquitoes are threatening malaria control has driven the development of new types of insecticide treated nets (ITNs) and indoor residual spraying (IRS) of insecticide. Malaria control programmes have a choice of vector control interventions although it is unclear which controls should be used to combat the disease. The study aimed at producing a framework to easily compare the public health impact and cost-effectiveness of different malaria prevention measures currently in widespread use. METHODS: We used published data from experimental hut trials conducted across Africa to characterise the entomological effect of pyrethroid-only ITNs versus ITNs combining a pyrethroid insecticide with the synergist piperonyl butoxide (PBO). We use these estimates to parameterise a dynamic mathematical model of Plasmodium falciparum malaria which is validated for two sites by comparing simulated results to empirical data from randomised control trials (RCTs) in Tanzania and Uganda. We extrapolated model simulations for a series of potential scenarios likely across the sub-Saharan African region and include results in an online tool (Malaria INtervention Tool [MINT]) that aims to identify optimum vector control intervention packages for scenarios with varying budget, price, entomological and epidemiological factors. FINDINGS: Our model indicates that switching from pyrethroid-only to pyrethroid-PBO ITNs could averted up to twice as many cases, although the additional benefit is highly variable and depends on the setting conditions. We project that annual delivery of long-lasting, non-pyrethroid IRS would prevent substantially more cases over 3-years, while pyrethroid-PBO ITNs tend to be the most cost-effective intervention per case averted. The model was able to predict prevalence and efficacy against prevalence in both RCTs for the intervention types tested. MINT is applicable to regions of sub-Saharan Africa with endemic malaria and provides users with a method of designing intervention packages given their setting and budget. INTERPRETATION: The most cost-effective vector control package will vary locally. Models able to recreate results of RCTs can be used to extrapolate outcomes elsewhere to support evidence-based decision making for investment in vector control. FUNDING: Medical Research Council, IVCC, Wellcome Trust. TRANSLATION: For the French translation of the abstract see Supplementary Materials section.

Understanding the Potential Impact of Different Drug Properties on Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Transmission and Disease Burden: A Modelling Analysis.

BACKGROUND: The public health impact of the coronavirus disease 2019 (COVID-19) pandemic has motivated a rapid search for potential therapeutics, with some key successes. However, the potential impact of different treatments, and consequently research and procurement priorities, have not been clear. METHODS: Using a mathematical model of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission, COVID-19 disease and clinical care, we explore the public-health impact of different potential therapeutics, under a range of scenarios varying healthcare capacity, epidemic trajectories; and drug efficacy in the absence of supportive care. RESULTS: The impact of drugs like dexamethasone (delivered to the most critically-ill in hospital and whose therapeutic benefit is expected to depend on the availability of supportive care such as oxygen and mechanical ventilation) is likely to be limited in settings where healthcare capacity is lowest or where uncontrolled epidemics result in hospitals being overwhelmed. As such, it may avert 22% of deaths in high-income countries but only 8% in low-income countries (assuming R = 1.35). Therapeutics for different patient populations (those not in hospital, early in the course of infection) and types of benefit (reducing disease severity or infectiousness, preventing hospitalization) could have much greater benefits, particularly in resource-poor settings facing large epidemics. CONCLUSIONS: Advances in the treatment of COVID-19 to date have been focused on hospitalized-patients and predicated on an assumption of adequate access to supportive care. Therapeutics delivered earlier in the course of infection that reduce the need for healthcare or reduce infectiousness could have significant impact, and research into their efficacy and means of delivery should be a priority.