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.

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.

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.

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.

Predicting the public health impact of a malaria transmission-blocking vaccine.

Transmission-blocking vaccines that interrupt malaria transmission from humans to mosquitoes are being tested in early clinical trials. The activity of such a vaccine is commonly evaluated using membrane-feeding assays. Understanding the field efficacy of such a vaccine requires knowledge of how heavily infected wild, naturally blood-fed mosquitoes are, as this indicates how difficult it will be to block transmission. Here we use data on naturally infected mosquitoes collected in Burkina Faso to translate the laboratory-estimated activity into an estimated activity in the field. A transmission dynamics model is then utilised to predict a transmission-blocking vaccine's public health impact alongside existing interventions. The model suggests that school-aged children are an attractive population to target for vaccination. Benefits of vaccination are distributed across the population, averting the greatest number of cases in younger children. Utilising a transmission-blocking vaccine alongside existing interventions could have a substantial impact against malaria.

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.

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.