RESUMO
BACKGROUND: A global stockpile of oral cholera vaccine (OCV) was established in 2013 for use in outbreak response and are licensed as two-dose regimens. Vaccine availability, however, remains limited. Previous studies have found that a single dose of OCV may provide substantial protection against cholera. METHODS: Using a mathematical model with two age groups paired with optimization algorithms, we determine the optimal vaccination strategy with one and two doses of vaccine to minimize cumulative overall infections, symptomatic infections, and deaths. We explore counterfactual vaccination scenarios in three distinct settings: Maela, the largest refugee camp in Thailand, with high in- and out-migration; N'Djamena, Chad, a densely populated region; and Haiti, where departments are connected by rivers and roads. RESULTS: Over the short term under limited vaccine supply, the optimal strategies for all objectives prioritize one dose to the older age group (over five years old), irrespective of setting and level of vaccination coverage. As more vaccine becomes available, it is optimal to administer a second dose for long-term protection. With enough vaccine to cover the whole population with one dose, the optimal strategies can avert up to 30% to 90% of deaths and 36% to 92% of symptomatic infections across the three settings over one year. The one-dose optimal strategies can avert 1.2 to 1.8 times as many cases and deaths compared to the standard two-dose strategy. CONCLUSIONS: In an outbreak setting, speedy vaccination campaigns with a single dose of OCV is likely to avert more cases and deaths than a two-dose pro-rata campaign under a limited vaccine supply.
Assuntos
Vacinas contra Cólera , Cólera , Administração Oral , Idoso , Pré-Escolar , Cólera/epidemiologia , Cólera/prevenção & controle , Surtos de Doenças/prevenção & controle , Humanos , Programas de ImunizaçãoRESUMO
Most COVID-19 vaccines require two doses, however with limited vaccine supply, policymakers are considering single-dose vaccination as an alternative strategy. Using a mathematical model combined with optimization algorithms, we determined optimal allocation strategies with one and two doses of vaccine under various degrees of viral transmission. Under low transmission, we show that the optimal allocation of vaccine vitally depends on the single-dose efficacy. With high single-dose efficacy, single-dose vaccination is optimal, preventing up to 22% more deaths than a strategy prioritizing two-dose vaccination for older adults. With low or moderate single-dose efficacy, mixed vaccination campaigns with complete coverage of older adults are optimal. However, with modest or high transmission, vaccinating older adults first with two doses is best, preventing up to 41% more deaths than a single-dose vaccination given across all adult populations. Our work suggests that it is imperative to determine the efficacy and durability of single-dose vaccines, as mixed or single-dose vaccination campaigns may have the potential to contain the pandemic much more quickly.
Assuntos
Vacinas contra COVID-19/imunologia , COVID-19/imunologia , Vacinação , Número Básico de Reprodução , COVID-19/transmissão , COVID-19/virologia , Relação Dose-Resposta Imunológica , Hospitalização , Humanos , Imunidade , Unidades de Terapia Intensiva , SARS-CoV-2/imunologiaRESUMO
Most COVID-19 vaccines require two doses, however with limited vaccine supply, policymakers are considering single-dose vaccination as an alternative strategy. Using a mathematical model combined with optimization algorithms, we determined optimal allocation strategies with one and two doses of vaccine under various degrees of viral transmission. Under low transmission, we show that the optimal allocation of vaccine vitally depends on the single-dose efficacy (SDE). With high SDE, single-dose vaccination is optimal, preventing up to 22% more deaths than a strategy prioritizing two-dose vaccination for older adults. With low or moderate SDE, mixed vaccination campaigns with complete coverage of older adults are optimal. However, with modest or high transmission, vaccinating older adults first with two doses is best, preventing up to 41% more deaths than a single-dose vaccination given across all adult populations. Our work suggests that it is imperative to determine the efficacy and durability of single-dose vaccines, as mixed or single-dose vaccination campaigns may have the potential to contain the pandemic much more quickly.
RESUMO
A vaccine, when available, will likely become our best tool to control the current COVID-19 pandemic. Even in the most optimistic scenarios, vaccine shortages will likely occur. Using an age-stratified mathematical model paired with optimization algorithms, we determined optimal vaccine allocation for four different metrics (deaths, symptomatic infections, and maximum non-ICU and ICU hospitalizations) under many scenarios. We find that a vaccine with effectiveness ≥50% would be enough to substantially mitigate the ongoing pandemic provided that a high percentage of the population is optimally vaccinated. When minimizing deaths, we find that for low vaccine effectiveness, irrespective of vaccination coverage, it is optimal to allocate vaccine to high-risk (older) age-groups first. In contrast, for higher vaccine effectiveness, there is a switch to allocate vaccine to high-transmission (younger) age-groups first for high vaccination coverage. While there are other societal and ethical considerations, this work can provide an evidence-based rationale for vaccine prioritization.
RESUMO
Vaccines, when available, will likely become our best tool to control the COVID-19 pandemic. Even in the most optimistic scenarios, vaccine shortages will likely occur. Using an age-stratified mathematical model paired with optimization algorithms, we determined optimal vaccine allocation for four different metrics (deaths, symptomatic infections, and maximum non-ICU and ICU hospitalizations) under many scenarios. We find that a vaccine with effectiveness ≥50% would be enough to substantially mitigate the ongoing pandemic, provided that a high percentage of the population is optimally vaccinated. When minimizing deaths, we find that for low vaccine effectiveness, irrespective of vaccination coverage, it is optimal to allocate vaccine to high-risk (older) age groups first. In contrast, for higher vaccine effectiveness, there is a switch to allocate vaccine to high-transmission (younger) age groups first for high vaccination coverage. While there are other societal and ethical considerations, this work can provide an evidence-based rationale for vaccine prioritization.
Assuntos
Vacinas contra COVID-19/imunologia , COVID-19/prevenção & controle , Pandemias/prevenção & controle , Vacinação/métodos , Fatores Etários , Algoritmos , COVID-19/epidemiologia , COVID-19/patologia , COVID-19/virologia , Epidemias , Hospitalização/estatística & dados numéricos , Humanos , Modelos Biológicos , Risco , SARS-CoV-2/isolamento & purificaçãoRESUMO
Secondary use of clinical health data for near real-time public health surveillance presents challenges surrounding its utility due to data quality issues. Data used for real-time surveillance must be timely, accurate and complete if it is to be useful; if incomplete data are used for surveillance, understanding the structure of the incompleteness is necessary. Such data are commonly aggregated due to privacy concerns. The Distribute project was a near real-time influenza-like-illness (ILI) surveillance system that relied on aggregated secondary clinical health data. The goal of this work is to disseminate the data quality tools developed to gain insight into the data quality problems associated with these data. These tools apply in general to any system where aggregate data are accrued over time and were created through the end-user-as-developer paradigm. Each tool was developed during the exploratory analysis to gain insight into structural aspects of data quality. Our key finding is that data quality of partially accruing data must be studied in the context of accrual lag-the difference between the time an event occurs and the time data for that event are received, i.e. the time at which data become available to the surveillance system. Our visualization methods therefore revolve around visualizing dimensions of data quality affected by accrual lag, in particular the tradeoff between timeliness and completion, and the effects of accrual lag on accuracy. Accounting for accrual lag in partially accruing data is necessary to avoid misleading or biased conclusions about trends in indicator values and data quality.