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 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.

Using mortuary and burial data to place COVID-19 in Lusaka, Zambia within a global context

Reported COVID-19 cases and associated mortality remain low in many sub-Saharan countries relative to global averages, but true impact is difficult to estimate given limitations around surveillance and mortality registration. In Lusaka, Zambia, burial registration and SARS-CoV-2 prevalence data during 2020 allow estimation of excess mortality and transmission. Relative to pre-pandemic patterns, we estimate age-dependent mortality increases, totalling 3212 excess deaths (95% CrI: 2104-4591), representing an 18.5% (95% CrI: 13.0-25.2%) increase relative to pre-pandemic levels. Using a dynamical model-based inferential framework, we find that these mortality patterns and SARS-CoV-2 prevalence data are in agreement with established COVID-19 severity estimates. Our results support hypotheses that COVID-19 impact in Lusaka during 2020 was consistent with COVID-19 epidemics elsewhere, without requiring exceptional explanations for low reported figures. For more equitable decision-making during future pandemics, barriers to ascertaining attributable mortality in low-income settings must be addressed and factored into discourse around reported impact differences.

Alternative epidemic indicators for COVID-19 in three settings with incomplete death registration systems

Not all COVID-19 deaths are officially reported, and particularly in low-income and humanitarian settings, the magnitude of reporting gaps remains sparsely characterized. Alternative data sources, including burial site worker reports, satellite imagery of cemeteries, and social media-conducted surveys of infection may offer solutions. By merging these data with independently conducted, representative serological studies within a mathematical modeling framework, we aim to better understand the range of underreporting using examples from three major cities: Addis Ababa (Ethiopia), Aden (Yemen), and Khartoum (Sudan) during 2020. We estimate that 69 to 100%, 0.8 to 8.0%, and 3.0 to 6.0% of COVID-19 deaths were reported in each setting, respectively. In future epidemics, and in settings where vital registration systems are limited, using multiple alternative data sources could provide critically needed, improved estimates of epidemic impact. However, ultimately, these systems are needed to ensure that, in contrast to COVID-19, the impact of future pandemics or other drivers of mortality is reported and understood worldwide.

No evidence of sustained nonzoonotic Plasmodium knowlesi transmission in Malaysia from modelling malaria case data

Reported incidence of the zoonotic malaria Plasmodium knowlesi has markedly increased across Southeast Asia and threatens malaria elimination. Nonzoonotic transmission of P. knowlesi has been experimentally demonstrated, but it remains unknown whether nonzoonotic transmission is contributing to increases in P. knowlesi cases. Here, we adapt model-based inference methods to estimate RC, individual case reproductive numbers, for P. knowlesi, P. falciparum and P. vivax human cases in Malaysia from 2012-2020 (n = 32,635). Best fitting models for P. knowlesi showed subcritical transmission (RC < 1) consistent with a large reservoir of unobserved infection sources, indicating P. knowlesi remains a primarily zoonotic infection. In contrast, sustained transmission (RC > 1) was estimated historically for P. falciparum and P. vivax, with declines in RC estimates observed over time consistent with local elimination. Together, this suggests sustained nonzoonotic P. knowlesi transmission is highly unlikely and that new approaches are urgently needed to control spillover risks.

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 PfPR_2-10 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.

Quantifying the effect of delaying the second COVID-19 vaccine dose in England: a mathematical modelling study

BACKGROUND

The UK was the first country to start national COVID-19 vaccination programmes, initially administering doses 3 weeks apart. However, early evidence of high vaccine effectiveness after the first dose and the emergence of the SARS-CoV-2 alpha variant prompted the UK to extend the interval between doses to 12 weeks. In this study, we aimed to quantify the effect of delaying the second vaccine dose in England.

METHODS

We used a previously described model of SARS-CoV-2 transmission, calibrated to COVID-19 surveillance data from England, including hospital admissions, hospital occupancy, seroprevalence data, and population-level PCR testing data, using a Bayesian evidence-synthesis framework. We modelled and compared the epidemic trajectory in the counterfactual scenario in which vaccine doses were administered 3 weeks apart against the real reported vaccine roll-out schedule of 12 weeks. We estimated and compared the resulting numbers of daily infections, hospital admissions, and deaths. In sensitivity analyses, we investigated scenarios spanning a range of vaccine effectiveness and waning assumptions.

FINDINGS

In the period from Dec 8, 2020, to Sept 13, 2021, the number of individuals who received a first vaccine dose was higher under the 12-week strategy than the 3-week strategy. For this period, we estimated that delaying the interval between the first and second COVID-19 vaccine doses from 3 to 12 weeks averted a median (calculated as the median of the posterior sample) of 58 000 COVID-19 hospital admissions (291 000 cumulative hospitalisations [95% credible interval 275 000-319 000] under the 3-week strategy vs 233 000 [229 000-238 000] under the 12-week strategy) and 10 100 deaths (64 800 deaths [60 200-68 900] vs 54 700 [52 800-55 600]). Similarly, we estimated that the 3-week strategy would have resulted in more infections compared with the 12-week strategy. Across all sensitivity analyses the 3-week strategy resulted in a greater number of hospital admissions. In results by age group, the 12-week strategy led to more hospitalisations and deaths in older people in spring 2021, but fewer following the emergence of the delta variant during summer 2021.

INTERPRETATION

England's delayed-second-dose vaccination strategy was informed by early real-world data on vaccine effectiveness in the context of limited vaccine supplies in a growing epidemic. Our study shows that rapidly providing partial (single-dose) vaccine-induced protection to a larger proportion of the population was successful in reducing the burden of COVID-19 hospitalisations and deaths overall.

FUNDING

UK National Institute for Health Research; UK Medical Research Council; Community Jameel; Wellcome Trust; UK Foreign, Commonwealth and Development Office; Australian National Health and Medical Research Council; and EU.

Quantifying the direct and indirect protection provided by insecticide treated bed nets against malaria

Long lasting insecticidal nets (LLINs) provide both direct and indirect protection against malaria. As pyrethroid resistance evolves in mosquito vectors, it will be useful to understand how the specific benefits LLINs afford individuals and communities may be affected. Here we use modelling to show that there is no minimum LLIN usage needed for users and non-users to benefit from community protection. Modelling results also indicate that pyrethroid resistance in local mosquitoes will likely diminish the direct and indirect benefits from insecticides, leaving the barrier effects intact, but LLINs are still expected to provide enhanced benefit over untreated nets even at high levels of pyrethroid resistance.

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

BACKGROUND

A 2021 clinical trial of seasonal RTS,S/AS01_E (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 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.

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.

Comparative analysis of the risks of hospitalisation and death associated with SARS-CoV-2 omicron (B.1.1.529) and delta (B.1.617.2) variants in England: a cohort study

BACKGROUND

The omicron variant (B.1.1.529) of SARS-CoV-2 has demonstrated partial vaccine escape and high transmissibility, with early studies indicating lower severity of infection than that of the delta variant (B.1.617.2). We aimed to better characterise omicron severity relative to delta by assessing the relative risk of hospital attendance, hospital admission, or death in a large national cohort.

METHODS

Individual-level data on laboratory-confirmed COVID-19 cases resident in England between Nov 29, 2021, and Jan 9, 2022, were linked to routine datasets on vaccination status, hospital attendance and admission, and mortality. The relative risk of hospital attendance or admission within 14 days, or death within 28 days after confirmed infection, was estimated using proportional hazards regression. Analyses were stratified by test date, 10-year age band, ethnicity, residential region, and vaccination status, and were further adjusted for sex, index of multiple deprivation decile, evidence of a previous infection, and year of age within each age band. A secondary analysis estimated variant-specific and vaccine-specific vaccine effectiveness and the intrinsic relative severity of omicron infection compared with delta (ie, the relative risk in unvaccinated cases).

FINDINGS

The adjusted hazard ratio (HR) of hospital attendance (not necessarily resulting in admission) with omicron compared with delta was 0·56 (95% CI 0·54-0·58); for hospital admission and death, HR estimates were 0·41 (0·39-0·43) and 0·31 (0·26-0·37), respectively. Omicron versus delta HR estimates varied with age for all endpoints examined. The adjusted HR for hospital admission was 1·10 (0·85-1·42) in those younger than 10 years, decreasing to 0·25 (0·21-0·30) in 60-69-year-olds, and then increasing to 0·47 (0·40-0·56) in those aged at least 80 years. For both variants, past infection gave some protection against death both in vaccinated (HR 0·47 [0·32-0·68]) and unvaccinated (0·18 [0·06-0·57]) cases. In vaccinated cases, past infection offered no additional protection against hospital admission beyond that provided by vaccination (HR 0·96 [0·88-1·04]); however, for unvaccinated cases, past infection gave moderate protection (HR 0·55 [0·48-0·63]). Omicron versus delta HR estimates were lower for hospital admission (0·30 [0·28-0·32]) in unvaccinated cases than the corresponding HR estimated for all cases in the primary analysis. Booster vaccination with an mRNA vaccine was highly protective against hospitalisation and death in omicron cases (HR for hospital admission 8-11 weeks post-booster vs unvaccinated: 0·22 [0·20-0·24]), with the protection afforded after a booster not being affected by the vaccine used for doses 1 and 2.

INTERPRETATION

The risk of severe outcomes following SARS-CoV-2 infection is substantially lower for omicron than for delta, with higher reductions for more severe endpoints and significant variation with age. Underlying the observed risks is a larger reduction in intrinsic severity (in unvaccinated individuals) counterbalanced by a reduction in vaccine effectiveness. Documented previous SARS-CoV-2 infection offered some protection against hospitalisation and high protection against death in unvaccinated individuals, but only offered additional protection in vaccinated individuals for the death endpoint. Booster vaccination with mRNA vaccines maintains over 70% protection against hospitalisation and death in breakthrough confirmed omicron infections.

FUNDING

Medical Research Council, UK Research and Innovation, Department of Health and Social Care, National Institute for Health Research, Community Jameel, and Engineering and Physical Sciences Research Council.

Optimizing social and economic activity while containing SARS-CoV-2 transmission using DAEDALUS

To study the trade-off between economic, social and health outcomes in the management of a pandemic, DAEDALUS integrates a dynamic epidemiological model of SARS-CoV-2 transmission with a multi-sector economic model, reflecting sectoral heterogeneity in transmission and complex supply chains. The model identifies mitigation strategies that optimize economic production while constraining infections so that hospital capacity is not exceeded but allowing essential services, including much of the education sector, to remain active. The model differentiates closures by economic sector, keeping those sectors open that contribute little to transmission but much to economic output and those that produce essential services as intermediate or final consumption products. In an illustrative application to 63 sectors in the United Kingdom, the model achieves an economic gain of between £161 billion (24%) and £193 billion (29%) compared to a blanket lockdown of non-essential activities over six months. Although it has been designed for SARS-CoV-2, DAEDALUS is sufficiently flexible to be applicable to pandemics with different epidemiological characteristics.

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.

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.

Communicating uncertainty in epidemic models

While mathematical models of disease transmission are widely used to inform public health decision-makers globally, the uncertainty inherent in results are often poorly communicated. We outline some potential sources of uncertainty in epidemic models, present traditional methods used to illustrate uncertainty and discuss alternative presentation formats used by modelling groups throughout the COVID-19 pandemic. Then, by drawing on the experience of our own recent modelling, we seek to contribute to the ongoing discussion of how to improve upon traditional methods used to visualise uncertainty by providing a suggestion of how this can be presented in a clear and simple manner.

Analysis of the potential for a malaria vaccine to reduce gaps in malaria intervention coverage

Background

The RTS,S/AS01 malaria vaccine is currently being evaluated in a cluster-randomized pilot implementation programme in three African countries. This study seeks to identify whether vaccination could reach additional children who are at risk from malaria but do not currently have access to, or use, core malaria interventions.

Methods

Using data from household surveys, the overlap between malaria intervention coverage and childhood vaccination (diphtheria-tetanus-pertussis dose 3, DTP3) uptake in 20 African countries with at least one first administrative level unit with Plasmodium falciparum parasite prevalence greater than 10% was calculated. Multilevel logistic regression was used to explore patterns of overlap by demographic and socioeconomic variables. The public health impact of delivering RTS,S/AS01 to those children who do not use an insecticide-treated net (ITN), but who received the DTP3 vaccine, was also estimated.

Results

Uptake of DTP3 was higher than malaria intervention coverage in most countries. Overall, 34% of children did not use ITNs and received DTP3, while 35% of children used ITNs and received DTP3, although this breakdown varied by country. It was estimated that there are 33 million children in these 20 countries who do not use an ITN. Of these, 23 million (70%) received the DTP3 vaccine. Vaccinating those 23 million children who receive DTP3 but do not use an ITN could avert up to an estimated 9.7 million (range 8.5–10.8 million) clinical malaria cases each year, assuming all children who receive DTP3 are administered all four RTS,S doses. An additional 10.8 million (9.5–12.0 million) cases could be averted by vaccinating those 24 million children who receive the DTP3 vaccine and use an ITN. Children who had access to or used an ITN were 9–13% more likely to reside in rural areas compared to those who had neither intervention regardless of vaccination status. Mothers’ education status was a strong predictor of intervention uptake and was positively associated with use of ITNs and vaccination uptake and negatively associated with having access to an ITN but not using it. Wealth was also a strong predictor of intervention coverage.

Conclusions

Childhood vaccination to prevent malaria has the potential to reduce inequity in access to existing malaria interventions and could substantially reduce the childhood malaria burden in sub-Saharan Africa, even in regions with lower existing DTP3 coverage.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12936-021-03966-x.

Non-pharmaceutical interventions, vaccination, and the SARS-CoV-2 delta variant in England: a mathematical modelling study

BACKGROUND

England's COVID-19 roadmap out of lockdown policy set out the timeline and conditions for the stepwise lifting of non-pharmaceutical interventions (NPIs) as vaccination roll-out continued, with step one starting on March 8, 2021. In this study, we assess the roadmap, the impact of the delta (B.1.617.2) variant of SARS-CoV-2, and potential future epidemic trajectories.

METHODS

This mathematical modelling study was done to assess the UK Government's four-step process to easing lockdown restrictions in England, UK. We extended a previously described model of SARS-CoV-2 transmission to incorporate vaccination and multi-strain dynamics to explicitly capture the emergence of the delta variant. We calibrated the model to English surveillance data, including hospital admissions, hospital occupancy, seroprevalence data, and population-level PCR testing data using a Bayesian evidence synthesis framework, then modelled the potential trajectory of the epidemic for a range of different schedules for relaxing NPIs. We estimated the resulting number of daily infections and hospital admissions, and daily and cumulative deaths. Three scenarios spanning a range of optimistic to pessimistic vaccine effectiveness, waning natural immunity, and cross-protection from previous infections were investigated. We also considered three levels of mixing after the lifting of restrictions.

FINDINGS

The roadmap policy was successful in offsetting the increased transmission resulting from lifting NPIs starting on March 8, 2021, with increasing population immunity through vaccination. However, because of the emergence of the delta variant, with an estimated transmission advantage of 76% (95% credible interval [95% CrI] 69-83) over alpha, fully lifting NPIs on June 21, 2021, as originally planned might have led to 3900 (95% CrI 1500-5700) peak daily hospital admissions under our central parameter scenario. Delaying until July 19, 2021, reduced peak hospital admissions by three fold to 1400 (95% CrI 700-1700) per day. There was substantial uncertainty in the epidemic trajectory, with particular sensitivity to the transmissibility of delta, level of mixing, and estimates of vaccine effectiveness.

INTERPRETATION

Our findings show that the risk of a large wave of COVID-19 hospital admissions resulting from lifting NPIs can be substantially mitigated if the timing of NPI relaxation is carefully balanced against vaccination coverage. However, with the delta variant, it might not be possible to fully lift NPIs without a third wave of hospital admissions and deaths, even if vaccination coverage is high. Variants of concern, their transmissibility, vaccine uptake, and vaccine effectiveness must be carefully monitored as countries relax pandemic control measures.

FUNDING

National Institute for Health Research, UK Medical Research Council, Wellcome Trust, and UK Foreign, Commonwealth and Development Office.

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Setting-specific Transmission Rates: A Systematic Review and Meta-analysis

BACKGROUND

Understanding the drivers of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission is crucial for control policies, but evidence of transmission rates in different settings remains limited.

METHODS

We conducted a systematic review to estimate secondary attack rates (SARs) and observed reproduction numbers (Robs) in different settings exploring differences by age, symptom status, and duration of exposure. To account for additional study heterogeneity, we employed a beta-binomial model to pool SARs across studies and a negative-binomial model to estimate Robs.

RESULTS

Households showed the highest transmission rates, with a pooled SAR of 21.1% (95% confidence interval [CI]:17.4-24.8). SARs were significantly higher where the duration of household exposure exceeded 5 days compared with exposure of ≤5 days. SARs related to contacts at social events with family and friends were higher than those for low-risk casual contacts (5.9% vs 1.2%). Estimates of SARs and Robs for asymptomatic index cases were approximately one-seventh, and for presymptomatic two-thirds of those for symptomatic index cases. We found some evidence for reduced transmission potential both from and to individuals younger than 20 years of age in the household context, which is more limited when examining all settings.

CONCLUSIONS

Our results suggest that exposure in settings with familiar contacts increases SARS-CoV-2 transmission potential. Additionally, the differences observed in transmissibility by index case symptom status and duration of exposure have important implications for control strategies, such as contact tracing, testing, and rapid isolation of cases. There were limited data to explore transmission patterns in workplaces, schools, and care homes, highlighting the need for further research in such settings.

Global patterns of submicroscopic Plasmodium falciparum malaria infection: insights from a systematic review and meta-analysis of population surveys

Background

Adoption of molecular techniques to detect Plasmodium falciparum infection has revealed many previously undetected (by microscopy) yet transmissible low-density infections. The proportion of these infections is typically highest in low transmission settings, but drivers of submicroscopic infection remain unclear. Here, we updated a previous systematic review of asexual P falciparum prevalence by microscopy PCR in the same population. We aimed to explore potential drivers of submicroscopic infection and to identify the locations where submicroscopic infections are most common.

Methods

In this systematic review and meta-analysis we searched PubMed and Web of Science from Jan 1, 2010, until Oct 11, 2020, for cross-sectional studies reporting data on asexual P falciparum prevalence by both microscopy and PCR. Surveys of pregnant women, surveys in which participants had been chosen based on symptoms or treatment, or surveys that did not involve a population from a defined location were excluded. Both the number of individuals tested and the number of individuals who tested positive by microscopy or PCR, or both, for P falciparum infection were extracted. Bayesian regression modelling was used to explore determinants of the size of the submicroscopic reservoir including geographical location, seasonality, age, methodology, and current or historical patterns of transmission.

Findings

Of 4893 identified studies, we retained 121 after screening and removal of duplicates. 45 studies from a previous systematic review were included giving 166 studies containing 551 cross-sectional survey microscopy and PCR prevalence pairs. Our results show that submicroscopic infections predominate in low-transmission settings across all regions, but also reveal marked geographical variation, with the proportion of infections that are submicroscopic being highest in South American surveys and lowest in west African surveys. Although current transmission levels partly explain these results, we find that historical transmission intensity also represents a crucial determinant of the size of the submicroscopic reservoir, as does the demographic structure of the infected population (with submicroscopic infection more likely to occur in adults than in children) and the PCR or microscopy methodology used. We also observed a small yet significant influence of seasonality, with fewer submicroscopic infections observed in the wet season than the dry season. Integrating these results with estimates of infectivity in relation to parasite density suggests the contribution of submicroscopic infections to transmission across different settings is likely to be highly variable.

Interpretation

Significant variation in the prevalence of submicroscopic infection exists even across settings characterised by similar current levels of transmission. These differences in submicroscopic epidemiology potentially warrant different approaches to targeting this infected subgroup across different settings to eliminate malaria.

Funding

Bill & Melinda Gates Foundation, The Royal Society, and the UK Medical Research Council.

Interpreting estimates of coronavirus disease 2019 (COVID-19) vaccine efficacy and effectiveness to inform simulation studies of vaccine impact: a systematic review

Background: The multiple efficacious vaccines authorised for emergency use worldwide represent the first preventative intervention against coronavirus disease 2019 (COVID-19) that does not rely on social distancing measures. The speed at which data are emerging and the heterogeneities in study design, target populations, and implementation make it challenging to interpret and assess the likely impact of vaccine campaigns on local epidemics. We reviewed available vaccine efficacy and effectiveness studies to generate working estimates that can be used to parameterise simulation studies of vaccine impact. Methods: We searched MEDLINE, the World Health Organization’s Institutional Repository for Information Sharing, medRxiv, and vaccine manufacturer websites for studies that evaluated the emerging data on COVID-19 vaccine efficacy and effectiveness. Studies providing an estimate of the efficacy or effectiveness of a COVID-19 vaccine using disaggregated data against SARS-CoV-2 infection, symptomatic disease, severe disease, death, or transmission were included. We extracted information on study population, variants of concern (VOC), vaccine platform, dose schedule, study endpoints, and measures of impact. We applied an evidence synthesis approach to capture a range of plausible and consistent parameters for vaccine efficacy and effectiveness that can be used to inform and explore a variety of vaccination strategies as the COVID-19 pandemic evolves. Results: Of the 602 articles and reports identified, 53 were included in the analysis. The availability of vaccine efficacy and effectiveness estimates varied by vaccine and were limited for VOCs. Estimates for non-primary endpoints such as effectiveness against infection and onward transmission were sparse. Synthesised estimates were relatively consistent for the same vaccine platform for wild-type, but was more variable for VOCs. Conclusions: Assessment of efficacy and effectiveness of COVID-19 vaccines is complex. Simulation studies must acknowledge and capture the uncertainty in vaccine effectiveness to robustly explore and inform vaccination policies and policy around the lifting of non-pharmaceutical interventions.

Key epidemiological drivers and impact of interventions in the 2020 SARS-CoV-2 epidemic in England

We fitted a model of SARS-CoV-2 transmission in care homes and the community to regional surveillance data for England. Compared with other approaches, our model provides a synthesis of multiple surveillance data streams into a single coherent modeling framework, allowing transmission and severity to be disentangled from features of the surveillance system. Of the control measures implemented, only national lockdown brought the reproduction number (R_t ^eff) below 1 consistently; if introduced 1 week earlier, it could have reduced deaths in the first wave from an estimated 48,600 to 25,600 [95% credible interval (CrI): 15,900 to 38,400]. The infection fatality ratio decreased from 1.00% (95% CrI: 0.85 to 1.21%) to 0.79% (95% CrI: 0.63 to 0.99%), suggesting improved clinical care. The infection fatality ratio was higher in the elderly residing in care homes (23.3%, 95% CrI: 14.7 to 35.2%) than those residing in the community (7.9%, 95% CrI: 5.9 to 10.3%). On 2 December 2020, England was still far from herd immunity, with regional cumulative infection incidence between 7.6% (95% CrI: 5.4 to 10.2%) and 22.3% (95% CrI: 19.4 to 25.4%) of the population. Therefore, any vaccination campaign will need to achieve high coverage and a high degree of protection in vaccinated individuals to allow nonpharmaceutical interventions to be lifted without a resurgence of transmission.

Key epidemiological drivers and impact of interventions in the 2020 SARS-CoV-2 epidemic in England

We fitted a model of SARS-CoV-2 transmission in care homes and the community to regional surveillance data for England. Compared with other approaches, our model provides a synthesis of multiple surveillance data streams into a single coherent modeling framework, allowing transmission and severity to be disentangled from features of the surveillance system. Of the control measures implemented, only national lockdown brought the reproduction number (Rt eff) below 1 consistently; if introduced 1 week earlier, it could have reduced deaths in the first wave from an estimated 48,600 to 25,600 [95% credible interval (CrI): 15,900 to 38,400]. The infection fatality ratio decreased from 1.00% (95% CrI: 0.85 to 1.21%) to 0.79% (95% CrI: 0.63 to 0.99%), suggesting improved clinical care. The infection fatality ratio was higher in the elderly residing in care homes (23.3%, 95% CrI: 14.7 to 35.2%) than those residing in the community (7.9%, 95% CrI: 5.9 to 10.3%). On 2 December 2020, England was still far from herd immunity, with regional cumulative infection incidence between 7.6% (95% CrI: 5.4 to 10.2%) and 22.3% (95% CrI: 19.4 to 25.4%) of the population. Therefore, any vaccination campaign will need to achieve high coverage and a high degree of protection in vaccinated individuals to allow nonpharmaceutical interventions to be lifted without a resurgence of transmission.

Modelling intensive care unit capacity under different epidemiological scenarios of the COVID-19 pandemic in three Western European countries

BACKGROUND

The coronavirus disease 2019 (COVID-19) pandemic has placed enormous strain on intensive care units (ICUs) in Europe. Ensuring access to care, irrespective of COVID-19 status, in winter 2020-2021 is essential.

METHODS

An integrated model of hospital capacity planning and epidemiological projections of COVID-19 patients is used to estimate the demand for and resultant spare capacity of ICU beds, staff and ventilators under different epidemic scenarios in France, Germany and Italy across the 2020-2021 winter period. The effect of implementing lockdowns triggered by different numbers of COVID-19 patients in ICUs under varying levels of effectiveness is examined, using a 'dual-demand' (COVID-19 and non-COVID-19) patient model.

RESULTS

Without sufficient mitigation, we estimate that COVID-19 ICU patient numbers will exceed those seen in the first peak, resulting in substantial capacity deficits, with beds being consistently found to be the most constrained resource. Reactive lockdowns could lead to large improvements in ICU capacity during the winter season, with pressure being most effectively alleviated when lockdown is triggered early and sustained under a higher level of suppression. The success of such interventions also depends on baseline bed numbers and average non-COVID-19 patient occupancy.

CONCLUSION

Reductions in capacity deficits under different scenarios must be weighed against the feasibility and drawbacks of further lockdowns. Careful, continuous decision-making by national policymakers will be required across the winter period 2020-2021.

Using syndromic measures of mortality to capture the dynamics of COVID-19 in Java, Indonesia, in the context of vaccination rollout

BACKGROUND

As in many countries, quantifying COVID-19 spread in Indonesia remains challenging due to testing limitations. In Java, non-pharmaceutical interventions (NPIs) were implemented throughout 2020. However, as a vaccination campaign launches, cases and deaths are rising across the island.

METHODS

We used modelling to explore the extent to which data on burials in Jakarta using strict COVID-19 protocols (C19P) provide additional insight into the transmissibility of the disease, epidemic trajectory, and the impact of NPIs. We assess how implementation of NPIs in early 2021 will shape the epidemic during the period of likely vaccine rollout.

RESULTS

C19P burial data in Jakarta suggest a death toll approximately 3.3 times higher than reported. Transmission estimates using these data suggest earlier, larger, and more sustained impact of NPIs. Measures to reduce sub-national spread, particularly during Ramadan, substantially mitigated spread to more vulnerable rural areas. Given current trajectory, daily cases and deaths are likely to increase in most regions as the vaccine is rolled out. Transmission may peak in early 2021 in Jakarta if current levels of control are maintained. However, relaxation of control measures is likely to lead to a subsequent resurgence in the absence of an effective vaccination campaign.

CONCLUSIONS

Syndromic measures of mortality provide a more complete picture of COVID-19 severity upon which to base decision-making. The high potential impact of the vaccine in Java is attributable to reductions in transmission to date and dependent on these being maintained. Increases in control in the relatively short-term will likely yield large, synergistic increases in vaccine impact.

Within-country age-based prioritisation, global allocation, and public health impact of a vaccine against SARS-CoV-2: A mathematical modelling analysis

The worldwide endeavour to develop safe and effective COVID-19 vaccines has been extraordinary, and vaccination is now underway in many countries. However, the doses available in 2021 are likely to be limited. We extend a mathematical model of SARS-CoV-2 transmission across different country settings to evaluate the public health impact of potential vaccines using WHO-developed target product profiles. We identify optimal vaccine allocation strategies within- and between-countries to maximise averted deaths under constraints on dose supply. We find that the health impact of SARS-CoV-2 vaccination depends on the cumulative population-level infection incidence when vaccination begins, the duration of natural immunity, the trajectory of the epidemic prior to vaccination, and the level of healthcare available to effectively treat those with disease. Within a country we find that for a limited supply (doses for < 20% of the population) the optimal strategy is to target the elderly. However, with a larger supply, if vaccination can occur while other interventions are maintained, the optimal strategy switches to targeting key transmitters to indirectly protect the vulnerable. As supply increases, vaccines that reduce or block infection have a greater impact than those that prevent disease alone due to the indirect protection provided to high-risk groups. Given a 2 billion global dose supply in 2021, we find that a strategy in which doses are allocated to countries proportional to population size is close to optimal in averting deaths and aligns with the ethical principles agreed in pandemic preparedness planning.

The J-IDEA Pandemic Planner: A Framework for Implementing Hospital Provision Interventions During the COVID-19 Pandemic

BACKGROUND

Planning for extreme surges in demand for hospital care of patients requiring urgent life-saving treatment for coronavirus disease 2019 (COVID-19), while retaining capacity for other emergency conditions, is one of the most challenging tasks faced by health care providers and policymakers during the pandemic. Health systems must be well-prepared to cope with large and sudden changes in demand by implementing interventions to ensure adequate access to care. We developed the first planning tool for the COVID-19 pandemic to account for how hospital provision interventions (such as cancelling elective surgery, setting up field hospitals, or hiring retired staff) will affect the capacity of hospitals to provide life-saving care.

METHODS

We conducted a review of interventions implemented or considered in 12 European countries in March to April 2020, an evaluation of their impact on capacity, and a review of key parameters in the care of COVID-19 patients. This information was used to develop a planner capable of estimating the impact of specific interventions on doctors, nurses, beds, and respiratory support equipment. We applied this to a scenario-based case study of 1 intervention, the set-up of field hospitals in England, under varying levels of COVID-19 patients.

RESULTS

The Abdul Latif Jameel Institute for Disease and Emergency Analytics pandemic planner is a hospital planning tool that allows hospital administrators, policymakers, and other decision-makers to calculate the amount of capacity in terms of beds, staff, and crucial medical equipment obtained by implementing the interventions. Flexible assumptions on baseline capacity, the number of hospitalizations, staff-to-beds ratios, and staff absences due to COVID-19 make the planner adaptable to multiple settings. The results of the case study show that while field hospitals alleviate the burden on the number of beds available, this intervention is futile unless the deficit of critical care nurses is addressed first.

DISCUSSION

The tool supports decision-makers in delivering a fast and effective response to the pandemic. The unique contribution of the planner is that it allows users to compare the impact of interventions that change some or all inputs.

Power calculations for cluster randomized trials (CRTs) with right-truncated Poisson-distributed outcomes: a motivating example from a malaria vector control trial

Background

Cluster randomized trials (CRTs) are increasingly used to study the efficacy of interventions targeted at the population level. Formulae exist to calculate sample sizes for CRTs, but they assume that the domain of the outcomes being considered covers the full range of values of the considered distribution. This assumption is frequently incorrect in epidemiological trials in which counts of infection episodes are right-truncated due to practical constraints on the number of times a person can be tested.

Methods

Motivated by a malaria vector control trial with right-truncated Poisson-distributed outcomes, we investigated the effect of right-truncation on power using Monte Carlo simulations.

Results

The results demonstrate that the adverse impact of right-truncation is directly proportional to the magnitude of the event rate, λ, with calculations of power being overestimated in instances where right-truncation was not accounted for. The severity of the adverse impact of right-truncation on power was more pronounced when the number of clusters was ≤30 but decreased the further the right-truncation point was from zero.

Conclusions

Potential right-truncation should always be accounted for in the calculation of sample size requirements at the study design stage.

Estimating the potential impact of Attractive Targeted Sugar Baits (ATSBs) as a new vector control tool for Plasmodium falciparum malaria

BACKGROUND

Attractive targeted sugar baits (ATSBs) are a promising new tool for malaria control as they can target outdoor-feeding mosquito populations, in contrast to current vector control tools which predominantly target indoor-feeding mosquitoes.

METHODS

It was sought to estimate the potential impact of these new tools on Plasmodium falciparum malaria prevalence in African settings by combining data from a recent entomological field trial of ATSBs undertaken in Mali with mathematical models of malaria transmission. The key parameter determining impact on the mosquito population is the excess mortality due to ATSBs, which is estimated from the observed reduction in mosquito catch numbers. A mathematical model capturing the life cycle of P. falciparum malaria in mosquitoes and humans and incorporating the excess mortality was used to estimate the potential epidemiological effect of ATSBs.

RESULTS

The entomological study showed a significant reduction of ~ 57% (95% CI 33-72%) in mosquito catch numbers, and a larger reduction of ~ 89% (95% CI 75-100%) in the entomological inoculation rate due to the fact that, in the presence of ATSBs, most mosquitoes do not live long enough to transmit malaria. The excess mortality due to ATSBs was estimated to be lower (mean 0.09 per mosquito per day, seasonal range 0.07-0.11 per day) than the bait feeding rate obtained from one-day staining tests (mean 0.34 per mosquito per day, seasonal range 0.28-0.38 per day).

CONCLUSIONS

From epidemiological modelling, it was predicted that ATSBs could result in large reductions (> 30% annually) in prevalence and clinical incidence of malaria, even in regions with an existing high malaria burden. These results suggest that this new tool could provide a promising addition to existing vector control tools and result in significant reductions in malaria burden across a range of malaria-endemic settings.

Evaluating the Performance of Malaria Genetics for Inferring Changes in Transmission Intensity Using Transmission Modeling

Substantial progress has been made globally to control malaria, however there is a growing need for innovative new tools to ensure continued progress. One approach is to harness genetic sequencing and accompanying methodological approaches as have been used in the control of other infectious diseases. However, to utilize these methodologies for malaria, we first need to extend the methods to capture the complex interactions between parasites, human and vector hosts, and environment, which all impact the level of genetic diversity and relatedness of malaria parasites. We develop an individual-based transmission model to simulate malaria parasite genetics parameterized using estimated relationships between complexity of infection and age from five regions in Uganda and Kenya. We predict that cotransmission and superinfection contribute equally to within-host parasite genetic diversity at 11.5% PCR prevalence, above which superinfections dominate. Finally, we characterize the predictive power of six metrics of parasite genetics for detecting changes in transmission intensity, before grouping them in an ensemble statistical model. The model predicted malaria prevalence with a mean absolute error of 0.055. Different assumptions about the availability of sample metadata were considered, with the most accurate predictions of malaria prevalence made when the clinical status and age of sampled individuals is known. Parasite genetics may provide a novel surveillance tool for estimating the prevalence of malaria in areas in which prevalence surveys are not feasible. However, the findings presented here reinforce the need for patient metadata to be recorded and made available within all future attempts to use parasite genetics for surveillance.

Database of epidemic trends and control measures during the first wave of COVID-19 in mainland China

OBJECTIVES

In this data collation study, we aimed to provide a comprehensive database describing the epidemic trends and responses during the first wave of coronavirus disease 2019 (COVID-19) throughout the main provinces in China.

METHODS

From mid-January to March 2020, we extracted publicly available data regarding the spread and control of COVID-19 from 31 provincial health authorities and major media outlets in mainland China. Based on these data, we conducted descriptive analyses of the epidemic in the six most-affected provinces.

RESULTS

School closures, travel restrictions, community-level lockdown, and contact tracing were introduced concurrently around late January but subsequent epidemic trends differed among provinces. Compared with Hubei, the other five most-affected provinces reported a lower crude case fatality ratio and proportion of critical and severe hospitalised cases. From March 2020, as the local transmission of COVID-19 declined, switching the focus of measures to the testing and quarantine of inbound travellers may have helped to sustain the control of the epidemic.

CONCLUSIONS

Aggregated indicators of case notifications and severity distributions are essential for monitoring an epidemic. A publicly available database containing these indicators and information regarding control measures is a useful resource for further research and policy planning in response to the COVID-19 epidemic.

State-level tracking of COVID-19 in the United States

As of 1st June 2020, the US Centres for Disease Control and Prevention reported 104,232 confirmed or probable COVID-19-related deaths in the US. This was more than twice the number of deaths reported in the next most severely impacted country. We jointly model the US epidemic at the state-level, using publicly available death data within a Bayesian hierarchical semi-mechanistic framework. For each state, we estimate the number of individuals that have been infected, the number of individuals that are currently infectious and the time-varying reproduction number (the average number of secondary infections caused by an infected person). We use changes in mobility to capture the impact that non-pharmaceutical interventions and other behaviour changes have on the rate of transmission of SARS-CoV-2. We estimate that R_t was only below one in 23 states on 1st June. We also estimate that 3.7% [3.4%-4.0%] of the total population of the US had been infected, with wide variation between states, and approximately 0.01% of the population was infectious. We demonstrate good 3 week model forecasts of deaths with low error and good coverage of our credible intervals.

State-level tracking of COVID-19 in the United States

As of 1st June 2020, the US Centres for Disease Control and Prevention reported 104,232 confirmed or probable COVID-19-related deaths in the US. This was more than twice the number of deaths reported in the next most severely impacted country. We jointly model the US epidemic at the state-level, using publicly available death data within a Bayesian hierarchical semi-mechanistic framework. For each state, we estimate the number of individuals that have been infected, the number of individuals that are currently infectious and the time-varying reproduction number (the average number of secondary infections caused by an infected person). We use changes in mobility to capture the impact that non-pharmaceutical interventions and other behaviour changes have on the rate of transmission of SARS-CoV-2. We estimate that Rt was only below one in 23 states on 1st June. We also estimate that 3.7% [3.4%-4.0%] of the total population of the US had been infected, with wide variation between states, and approximately 0.01% of the population was infectious. We demonstrate good 3 week model forecasts of deaths with low error and good coverage of our credible intervals.

State-level tracking of COVID-19 in the United States

As of 1st June 2020, the US Centres for Disease Control and Prevention reported 104,232 confirmed or probable COVID-19-related deaths in the US. This was more than twice the number of deaths reported in the next most severely impacted country. We jointly model the US epidemic at the state-level, using publicly available death data within a Bayesian hierarchical semi-mechanistic framework. For each state, we estimate the number of individuals that have been infected, the number of individuals that are currently infectious and the time-varying reproduction number (the average number of secondary infections caused by an infected person). We use changes in mobility to capture the impact that non-pharmaceutical interventions and other behaviour changes have on the rate of transmission of SARS-CoV-2. We estimate that R_t was only below one in 23 states on 1st June. We also estimate that 3.7% [3.4%-4.0%] of the total population of the US had been infected, with wide variation between states, and approximately 0.01% of the population was infectious. We demonstrate good 3 week model forecasts of deaths with low error and good coverage of our credible intervals.

Estimated impact of RTS,S/AS01 malaria vaccine allocation strategies in sub-Saharan Africa: A modelling study

BACKGROUND

The RTS,S/AS01 vaccine against Plasmodium falciparum malaria infection completed phase III trials in 2014 and demonstrated efficacy against clinical malaria of approximately 36% over 4 years for a 4-dose schedule in children aged 5-17 months. Pilot vaccine implementation has recently begun in 3 African countries. If the pilots demonstrate both a positive health impact and resolve remaining safety concerns, wider roll-out could be recommended from 2021 onwards. Vaccine demand may, however, outstrip initial supply. We sought to identify where vaccine introduction should be prioritised to maximise public health impact under a range of supply constraints using mathematical modelling.

METHODS AND FINDINGS

Using a mathematical model of P. falciparum malaria transmission and RTS,S vaccine impact, we estimated the clinical cases and deaths averted in children aged 0-5 years in sub-Saharan Africa under 2 scenarios for vaccine coverage (100% and realistic) and 2 scenarios for other interventions (current coverage and World Health Organization [WHO] Global Technical Strategy targets). We used a prioritisation algorithm to identify potential allocative efficiency gains from prioritising vaccine allocation among countries or administrative units to maximise cases or deaths averted. If malaria burden at introduction is similar to current levels-assuming realistic vaccine coverage and country-level prioritisation in areas with parasite prevalence >10%-we estimate that 4.3 million malaria cases (95% credible interval [CrI] 2.8-6.8 million) and 22,000 deaths (95% CrI 11,000-35,000) in children younger than 5 years could be averted annually at a dose constraint of 30 million. This decreases to 3.0 million cases (95% CrI 2.0-4.7 million) and 14,000 deaths (95% CrI 7,000-23,000) at a dose constraint of 20 million, and increases to 6.6 million cases (95% CrI 4.2-10.8 million) and 38,000 deaths (95% CrI 18,000-61,000) at a dose constraint of 60 million. At 100% vaccine coverage, these impact estimates increase to 5.2 million cases (95% CrI 3.5-8.2 million) and 27,000 deaths (95% CrI 14,000-43,000), 3.9 million cases (95% CrI 2.7-6.0 million) and 19,000 deaths (95% CrI 10,000-30,000), and 10.0 million cases (95% CrI 6.7-15.7 million) and 51,000 deaths (95% CrI 25,000-82,000), respectively. Under realistic vaccine coverage, if the vaccine is prioritised sub-nationally, 5.3 million cases (95% CrI 3.5-8.2 million) and 24,000 deaths (95% CrI 12,000-38,000) could be averted at a dose constraint of 30 million. Furthermore, sub-national prioritisation would allow introduction in almost double the number of countries compared to national prioritisation (21 versus 11). If vaccine introduction is prioritised in the 3 pilot countries (Ghana, Kenya, and Malawi), health impact would be reduced, but this effect becomes less substantial (change of <5%) if 50 million or more doses are available. We did not account for within-country variation in vaccine coverage, and the optimisation was based on a single outcome measure, therefore this study should be used to understand overall trends rather than guide country-specific allocation.

CONCLUSIONS

These results suggest that the impact of constraints in vaccine supply on the public health impact of the RTS,S malaria vaccine could be reduced by introducing the vaccine at the sub-national level and prioritising countries with the highest malaria incidence.

Adapting hospital capacity to meet changing demands during the COVID-19 pandemic

BACKGROUND

To calculate hospital surge capacity, achieved via hospital provision interventions implemented for the emergency treatment of coronavirus disease 2019 (COVID-19) and other patients through March to May 2020; to evaluate the conditions for admitting patients for elective surgery under varying admission levels of COVID-19 patients.

METHODS

We analysed National Health Service (NHS) datasets and literature reviews to estimate hospital care capacity before the pandemic (pre-pandemic baseline) and to quantify the impact of interventions (cancellation of elective surgery, field hospitals, use of private hospitals, deployment of former medical staff and deployment of newly qualified medical staff) for treatment of adult COVID-19 patients, focusing on general and acute (G&A) and critical care (CC) beds, staff and ventilators.

RESULTS

NHS England would not have had sufficient capacity to treat all COVID-19 and other patients in March and April 2020 without the hospital provision interventions, which alleviated significant shortfalls in CC nurses, CC and G&A beds and CC junior doctors. All elective surgery can be conducted at normal pre-pandemic levels provided the other interventions are sustained, but only if the daily number of COVID-19 patients occupying CC beds is not greater than 1550 in the whole of England. If the other interventions are not maintained, then elective surgery can only be conducted if the number of COVID-19 patients occupying CC beds is not greater than 320. However, there is greater national capacity to treat G&A patients: without interventions, it takes almost 10,000 G&A COVID-19 patients before any G&A elective patients would be unable to be accommodated.

CONCLUSIONS

Unless COVID-19 hospitalisations drop to low levels, there is a continued need to enhance critical care capacity in England with field hospitals, use of private hospitals or deployment of former and newly qualified medical staff to allow some or all elective surgery to take place.

Modelling the roles of antibody titre and avidity in protection from Plasmodium falciparum malaria infection following RTS,S/AS01 vaccination

•

Models capturing key malaria life-cycle stages can help us evaluate vaccine candidates.

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Model fitting revealed antibody avidity to be an important determinant of RTS,S vaccine efficacy.

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High avidity and titre were associated with increased levels of vaccine efficacy.

•

Did not identify any thresholds of protection for either immune marker.

Anti-circumsporozoite antibody titres have been established as an essential indicator for evaluating the immunogenicity and protective capacity of the RTS,S/AS01 malaria vaccine. However, a new delayed-fractional dose regime of the vaccine was recently shown to increase vaccine efficacy, from 62.5% (95% CI 29.4–80.1%) under the original dosing schedule to 86.7% (95% CI, 66.8–94.6%) without a corresponding increase in antibody titres. Here we reanalyse the antibody data from this challenge trial to determine whether IgG avidity may help to explain efficacy better than IgG titre alone by adapting a within-host mathematical model of sporozoite inoculation. We demonstrate that a model incorporating titre and avidity provides a substantially better fit to the data than titre alone. These results also suggest that in individuals with a high antibody titre response that also show high avidity (both metrics in the top tercile of observed values) delayed-fractional vaccination provided near perfect protection upon first challenge (98.2% [95% Credible Interval 91.6–99.7%]). This finding suggests that the quality of the vaccine induced antibody response is likely to be an important determinant in the development of highly efficacious pre-erythrocytic vaccines against malaria.

Response to COVID-19 in South Korea and implications for lifting stringent interventions

BACKGROUND

After experiencing a sharp growth in COVID-19 cases early in the pandemic, South Korea rapidly controlled transmission while implementing less stringent national social distancing measures than countries in Europe and the USA. This has led to substantial interest in their "test, trace, isolate" strategy. However, it is important to understand the epidemiological peculiarities of South Korea's outbreak and characterise their response before attempting to emulate these measures elsewhere.

METHODS

We systematically extracted numbers of suspected cases tested, PCR-confirmed cases, deaths, isolated confirmed cases, and numbers of confirmed cases with an identified epidemiological link from publicly available data. We estimated the time-varying reproduction number, R_t, using an established Bayesian framework, and reviewed the package of interventions implemented by South Korea using our extracted data, plus published literature and government sources.

RESULTS

We estimated that after the initial rapid growth in cases, R_t dropped below one in early April before increasing to a maximum of 1.94 (95%CrI, 1.64-2.27) in May following outbreaks in Seoul Metropolitan Region. By mid-June, R_t was back below one where it remained until the end of our study (July 13th). Despite less stringent "lockdown" measures, strong social distancing measures were implemented in high-incidence areas and studies measured a considerable national decrease in movement in late February. Testing the capacity was swiftly increased, and protocols were in place to isolate suspected and confirmed cases quickly; however, we could not estimate the delay to isolation using our data. Accounting for just 10% of cases, individual case-based contact tracing picked up a relatively minor proportion of total cases, with cluster investigations accounting for 66%.

CONCLUSIONS

Whilst early adoption of testing and contact tracing is likely to be important for South Korea's successful outbreak control, other factors including regional implementation of strong social distancing measures likely also contributed. The high volume of testing and the low number of deaths suggest that South Korea experienced a small epidemic relative to other countries. Caution is needed in attempting to replicate the South Korean response in populations with larger more geographically widespread epidemics where finding, testing, and isolating cases that are linked to clusters may be more difficult.

Response to COVID-19 in South Korea and implications for lifting stringent interventions

BACKGROUND

After experiencing a sharp growth in COVID-19 cases early in the pandemic, South Korea rapidly controlled transmission while implementing less stringent national social distancing measures than countries in Europe and the USA. This has led to substantial interest in their "test, trace, isolate" strategy. However, it is important to understand the epidemiological peculiarities of South Korea's outbreak and characterise their response before attempting to emulate these measures elsewhere.

METHODS

We systematically extracted numbers of suspected cases tested, PCR-confirmed cases, deaths, isolated confirmed cases, and numbers of confirmed cases with an identified epidemiological link from publicly available data. We estimated the time-varying reproduction number, Rt, using an established Bayesian framework, and reviewed the package of interventions implemented by South Korea using our extracted data, plus published literature and government sources.

RESULTS

We estimated that after the initial rapid growth in cases, Rt dropped below one in early April before increasing to a maximum of 1.94 (95%CrI, 1.64-2.27) in May following outbreaks in Seoul Metropolitan Region. By mid-June, Rt was back below one where it remained until the end of our study (July 13th). Despite less stringent "lockdown" measures, strong social distancing measures were implemented in high-incidence areas and studies measured a considerable national decrease in movement in late February. Testing the capacity was swiftly increased, and protocols were in place to isolate suspected and confirmed cases quickly; however, we could not estimate the delay to isolation using our data. Accounting for just 10% of cases, individual case-based contact tracing picked up a relatively minor proportion of total cases, with cluster investigations accounting for 66%.

CONCLUSIONS

Whilst early adoption of testing and contact tracing is likely to be important for South Korea's successful outbreak control, other factors including regional implementation of strong social distancing measures likely also contributed. The high volume of testing and the low number of deaths suggest that South Korea experienced a small epidemic relative to other countries. Caution is needed in attempting to replicate the South Korean response in populations with larger more geographically widespread epidemics where finding, testing, and isolating cases that are linked to clusters may be more difficult.

Evidence of initial success for China exiting COVID-19 social distancing policy after achieving containment

Background: The COVID-19 epidemic was declared a Global Pandemic by WHO on 11 March 2020. By 24 March 2020, over 440,000 cases and almost 20,000 deaths had been reported worldwide. In response to the fast-growing epidemic, which began in the Chinese city of Wuhan, Hubei, China imposed strict social distancing in Wuhan on 23 January 2020 followed closely by similar measures in other provinces. These interventions have impacted economic productivity in China, and the ability of the Chinese economy to resume without restarting the epidemic was not clear. Methods: Using daily reported cases from mainland China and Hong Kong SAR, we estimated transmissibility over time and compared it to daily within-city movement, as a proxy for economic activity. Results: Initially, within-city movement and transmission were very strongly correlated in the five mainland provinces most affected by the epidemic and Beijing. However, that correlation decreased rapidly after the initial sharp fall in transmissibility. In general, towards the end of the study period, the correlation was no longer apparent, despite substantial increases in within-city movement. A similar analysis for Hong Kong shows that intermediate levels of local activity were maintained while avoiding a large outbreak. At the very end of the study period, when China began to experience the re-introduction of a small number of cases from Europe and the United States, there is an apparent up-tick in transmission. Conclusions: Although these results do not preclude future substantial increases in incidence, they suggest that after very intense social distancing (which resulted in containment), China successfully exited its lockdown to some degree. Elsewhere, movement data are being used as proxies for economic activity to assess the impact of interventions. The results presented here illustrate how the eventual decorrelation between transmission and movement is likely a key feature of successful COVID-19 exit strategies.

The impact of delayed treatment of uncomplicated P. falciparum malaria on progression to severe malaria: A systematic review and a pooled multicentre individual-patient meta-analysis

BACKGROUND

Delay in receiving treatment for uncomplicated malaria (UM) is often reported to increase the risk of developing severe malaria (SM), but access to treatment remains low in most high-burden areas. Understanding the contribution of treatment delay on progression to severe disease is critical to determine how quickly patients need to receive treatment and to quantify the impact of widely implemented treatment interventions, such as 'test-and-treat' policies administered by community health workers (CHWs). We conducted a pooled individual-participant meta-analysis to estimate the association between treatment delay and presenting with SM.

METHODS AND FINDINGS

A search using Ovid MEDLINE and Embase was initially conducted to identify studies on severe Plasmodium falciparum malaria that included information on treatment delay, such as fever duration (inception to 22nd September 2017). Studies identified included 5 case-control and 8 other observational clinical studies of SM and UM cases. Risk of bias was assessed using the Newcastle-Ottawa scale, and all studies were ranked as 'Good', scoring ≥7/10. Individual-patient data (IPD) were pooled from 13 studies of 3,989 (94.1% aged <15 years) SM patients and 5,780 (79.6% aged <15 years) UM cases in Benin, Malaysia, Mozambique, Tanzania, The Gambia, Uganda, Yemen, and Zambia. Definitions of SM were standardised across studies to compare treatment delay in patients with UM and different SM phenotypes using age-adjusted mixed-effects regression. The odds of any SM phenotype were significantly higher in children with longer delays between initial symptoms and arrival at the health facility (odds ratio [OR] = 1.33, 95% CI: 1.07-1.64 for a delay of >24 hours versus ≤24 hours; p = 0.009). Reported illness duration was a strong predictor of presenting with severe malarial anaemia (SMA) in children, with an OR of 2.79 (95% CI:1.92-4.06; p < 0.001) for a delay of 2-3 days and 5.46 (95% CI: 3.49-8.53; p < 0.001) for a delay of >7 days, compared with receiving treatment within 24 hours from symptom onset. We estimate that 42.8% of childhood SMA cases and 48.5% of adult SMA cases in the study areas would have been averted if all individuals were able to access treatment within the first day of symptom onset, if the association is fully causal. In studies specifically recording onset of nonsevere symptoms, long treatment delay was moderately associated with other SM phenotypes (OR [95% CI] >3 to ≤4 days versus ≤24 hours: cerebral malaria [CM] = 2.42 [1.24-4.72], p = 0.01; respiratory distress syndrome [RDS] = 4.09 [1.70-9.82], p = 0.002). In addition to unmeasured confounding, which is commonly present in observational studies, a key limitation is that many severe cases and deaths occur outside healthcare facilities in endemic countries, where the effect of delayed or no treatment is difficult to quantify.

CONCLUSIONS

Our results quantify the relationship between rapid access to treatment and reduced risk of severe disease, which was particularly strong for SMA. There was some evidence to suggest that progression to other severe phenotypes may also be prevented by prompt treatment, though the association was not as strong, which may be explained by potential selection bias, sample size issues, or a difference in underlying pathology. These findings may help assess the impact of interventions that improve access to treatment.

Potential impact of the COVID-19 pandemic on HIV, tuberculosis, and malaria in low-income and middle-income countries: a modelling study

BACKGROUND

COVID-19 has the potential to cause substantial disruptions to health services, due to cases overburdening the health system or response measures limiting usual programmatic activities. We aimed to quantify the extent to which disruptions to services for HIV, tuberculosis, and malaria in low-income and middle-income countries with high burdens of these diseases could lead to additional loss of life over the next 5 years.

METHODS

Assuming a basic reproduction number of 3·0, we constructed four scenarios for possible responses to the COVID-19 pandemic: no action, mitigation for 6 months, suppression for 2 months, or suppression for 1 year. We used established transmission models of HIV, tuberculosis, and malaria to estimate the additional impact on health that could be caused in selected settings, either due to COVID-19 interventions limiting activities, or due to the high demand on the health system due to the COVID-19 pandemic.

FINDINGS

In high-burden settings, deaths due to HIV, tuberculosis, and malaria over 5 years could increase by up to 10%, 20%, and 36%, respectively, compared with if there was no COVID-19 pandemic. The greatest impact on HIV was estimated to be from interruption to antiretroviral therapy, which could occur during a period of high health system demand. For tuberculosis, the greatest impact would be from reductions in timely diagnosis and treatment of new cases, which could result from any prolonged period of COVID-19 suppression interventions. The greatest impact on malaria burden could be as a result of interruption of planned net campaigns. These disruptions could lead to a loss of life-years over 5 years that is of the same order of magnitude as the direct impact from COVID-19 in places with a high burden of malaria and large HIV and tuberculosis epidemics.

INTERPRETATION

Maintaining the most critical prevention activities and health-care services for HIV, tuberculosis, and malaria could substantially reduce the overall impact of the COVID-19 pandemic.

FUNDING

Bill & Melinda Gates Foundation, Wellcome Trust, UK Department for International Development, and Medical Research Council.

The potential public health consequences of COVID-19 on malaria in Africa

The burden of malaria is heavily concentrated in sub-Saharan Africa (SSA) where cases and deaths associated with COVID-19 are rising¹. In response, countries are implementing societal measures aimed at curtailing transmission of SARS-CoV-2^2,3. Despite these measures, the COVID-19 epidemic could still result in millions of deaths as local health facilities become overwhelmed⁴. Advances in malaria control this century have been largely due to distribution of long-lasting insecticidal nets (LLINs)⁵, with many SSA countries having planned campaigns for 2020. In the present study, we use COVID-19 and malaria transmission models to estimate the impact of disruption of malaria prevention activities and other core health services under four different COVID-19 epidemic scenarios. If activities are halted, the malaria burden in 2020 could be more than double that of 2019. In Nigeria alone, reducing case management for 6 months and delaying LLIN campaigns could result in 81,000 (44,000-119,000) additional deaths. Mitigating these negative impacts is achievable, and LLIN distributions in particular should be prioritized alongside access to antimalarial treatments to prevent substantial malaria epidemics.

Estimating the effects of non-pharmaceutical interventions on COVID-19 in Europe

Following the detection of the new coronavirus¹ severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its spread outside of China, Europe has experienced large epidemics of coronavirus disease 2019 (COVID-19). In response, many European countries have implemented non-pharmaceutical interventions, such as the closure of schools and national lockdowns. Here we study the effect of major interventions across 11 European countries for the period from the start of the COVID-19 epidemics in February 2020 until 4 May 2020, when lockdowns started to be lifted. Our model calculates backwards from observed deaths to estimate transmission that occurred several weeks previously, allowing for the time lag between infection and death. We use partial pooling of information between countries, with both individual and shared effects on the time-varying reproduction number (R_t). Pooling allows for more information to be used, helps to overcome idiosyncrasies in the data and enables more-timely estimates. Our model relies on fixed estimates of some epidemiological parameters (such as the infection fatality rate), does not include importation or subnational variation and assumes that changes in R_t are an immediate response to interventions rather than gradual changes in behaviour. Amidst the ongoing pandemic, we rely on death data that are incomplete, show systematic biases in reporting and are subject to future consolidation. We estimate that-for all of the countries we consider here-current interventions have been sufficient to drive R_t below 1 (probability R_t < 1.0 is greater than 99%) and achieve control of the epidemic. We estimate that across all 11 countries combined, between 12 and 15 million individuals were infected with SARS-CoV-2 up to 4 May 2020, representing between 3.2% and 4.0% of the population. Our results show that major non-pharmaceutical interventions-and lockdowns in particular-have had a large effect on reducing transmission. Continued intervention should be considered to keep transmission of SARS-CoV-2 under control.

The impact of COVID-19 and strategies for mitigation and suppression in low- and middle-income countries

The ongoing coronavirus disease 2019 (COVID-19) pandemic poses a severe threat to public health worldwide. We combine data on demography, contact patterns, disease severity, and health care capacity and quality to understand its impact and inform strategies for its control. Younger populations in lower-income countries may reduce overall risk, but limited health system capacity coupled with closer intergenerational contact largely negates this benefit. Mitigation strategies that slow but do not interrupt transmission will still lead to COVID-19 epidemics rapidly overwhelming health systems, with substantial excess deaths in lower-income countries resulting from the poorer health care available. Of countries that have undertaken suppression to date, lower-income countries have acted earlier. However, this will need to be maintained or triggered more frequently in these settings to keep below available health capacity, with associated detrimental consequences for the wider health, well-being, and economies of these countries.