RESUMEN
When an influenza pandemic emerges, temporary school closures and antiviral treatment may slow virus spread, reduce the overall disease burden, and provide time for vaccine development, distribution, and administration while keeping a larger portion of the general population infection free. The impact of such measures will depend on the transmissibility and severity of the virus and the timing and extent of their implementation. To provide robust assessments of layered pandemic intervention strategies, the Centers for Disease Control and Prevention (CDC) funded a network of academic groups to build a framework for the development and comparison of multiple pandemic influenza models. Research teams from Columbia University, Imperial College London/Princeton University, Northeastern University, the University of Texas at Austin/Yale University, and the University of Virginia independently modeled three prescribed sets of pandemic influenza scenarios developed collaboratively by the CDC and network members. Results provided by the groups were aggregated into a mean-based ensemble. The ensemble and most component models agreed on the ranking of the most and least effective intervention strategies by impact but not on the magnitude of those impacts. In the scenarios evaluated, vaccination alone, due to the time needed for development, approval, and deployment, would not be expected to substantially reduce the numbers of illnesses, hospitalizations, and deaths that would occur. Only strategies that included early implementation of school closure were found to substantially mitigate early spread and allow time for vaccines to be developed and administered, especially under a highly transmissible pandemic scenario.
Asunto(s)
Vacunas contra la Influenza , Gripe Humana , Humanos , Gripe Humana/tratamiento farmacológico , Gripe Humana/epidemiología , Gripe Humana/prevención & control , Preparaciones Farmacéuticas , Pandemias/prevención & control , Vacunas contra la Influenza/uso terapéutico , Antivirales/farmacología , Antivirales/uso terapéuticoRESUMEN
The efficacy of influenza vaccines, currently at 44%, is limited by the rapid antigenic evolution of the virus and a manufacturing process that can lead to vaccine mismatch. The National Institute of Allergy and Infectious Diseases (NIAID) recently identified the development of a universal influenza vaccine with an efficacy of at least 75% as a high scientific priority. The US Congress approved $130 million funding for the 2019 fiscal year to support the development of a universal vaccine, and another $1 billion over 5 y has been proposed in the Flu Vaccine Act. Using a model of influenza transmission, we evaluated the population-level impacts of universal influenza vaccines distributed according to empirical age-specific coverage at multiple scales in the United States. We estimate that replacing just 10% of typical seasonal vaccines with 75% efficacious universal vaccines would avert â¼5.3 million cases, 81,000 hospitalizations, and 6,300 influenza-related deaths per year. This would prevent over $1.1 billion in direct health care costs compared to a typical season, based on average data from the 2010-11 to 2018-19 seasons. A complete replacement of seasonal vaccines with universal vaccines is projected to prevent 17 million cases, 251,000 hospitalizations, 19,500 deaths, and $3.5 billion in direct health care costs. States with high per-hospitalization medical expenses along with a large proportion of elderly residents are expected to receive the maximum economic benefit. Replacing even a fraction of seasonal vaccines with universal vaccines justifies the substantial cost of vaccine development.
Asunto(s)
Análisis Costo-Beneficio , Costos de la Atención en Salud/estadística & datos numéricos , Hospitalización/economía , Vacunas contra la Influenza/economía , Gripe Humana/economía , Gripe Humana/prevención & control , Vacunación/economía , Adolescente , Adulto , Anciano , Niño , Preescolar , Femenino , Humanos , Lactante , Recién Nacido , Virus de la Influenza A/aislamiento & purificación , Vacunas contra la Influenza/uso terapéutico , Gripe Humana/epidemiología , Masculino , Persona de Mediana Edad , Estaciones del Año , Estados Unidos/epidemiología , Vacunación/métodos , Adulto JovenRESUMEN
Cancer occurs as a consequence of multiple somatic mutations that lead to uncontrolled cell growth. Mutual exclusivity and co-occurrence of mutations imply-but do not prove-that mutations exert synergistic or antagonistic epistatic effects on oncogenesis. Knowledge of these interactions, and the consequent trajectories of mutation and selection that lead to cancer has been a longstanding goal within the cancer research community. Recent research has revealed mutation rates and scaled selection coefficients for specific recurrent variants across many cancer types. However, there are no current methods to quantify the strength of selection incorporating pairwise and higher-order epistatic effects on selection within the trajectory of likely cancer genotoypes. Therefore, we have developed a continuous-time Markov chain model that enables the estimation of mutation origination and fixation (flux), dependent on somatic cancer genotype. Coupling this continuous-time Markov chain model with a deconvolution approach provides estimates of underlying mutation rates and selection across the trajectory of oncogenesis. We demonstrate computation of fluxes and selection coefficients in a somatic evolutionary model for the four most frequently variant driver genes (TP53, LRP1B, KRAS and STK11) from 565 cases of lung adenocarcinoma. Our analysis reveals multiple antagonistic epistatic effects that reduce the possible routes of oncogenesis, and inform cancer research regarding viable trajectories of somatic evolution whose progression could be forestalled by precision medicine. Synergistic epistatic effects are also identified, most notably in the somatic genotype TP53 LRP1B for mutations in the KRAS gene, and in somatic genotypes containing KRAS or TP53 mutations for mutations in the STK11 gene. Large positive fluxes of KRAS variants were driven by large selection coefficients, whereas the flux toward LRP1B mutations was substantially aided by a large mutation rate for this gene. The approach enables inference of the most likely routes of site-specific variant evolution and estimation of the strength of selection operating on each step along the route, a key component of what we need to know to develop and implement personalized cancer therapies.
Asunto(s)
Tasa de Mutación , Proteínas Proto-Oncogénicas p21(ras) , Humanos , Proteínas Proto-Oncogénicas p21(ras)/genética , Mutación , Carcinogénesis/genética , GenotipoRESUMEN
Modeling time-since-last-infection (TSLI) provides a means of formulating epidemiological models with fewer state variables (or epidemiological classes) and more flexible descriptions of infectivity after infection and susceptibility after recovery than usual. The model considered here has two time variables: chronological time (t) and the TSLI (τ), and it has only two classes: never infected ( N ) and infected at least once (i). Unlike most age-structured epidemiological models, in which the i equation is formulated using ( ∂ ∂ τ + ∂ ∂ t ) i ( τ , t ) , ours uses a more general differential operator. This allows weaker conditions for the infectivity and susceptibility functions, and thus, is more generally applicable. We reformulate the model as an age dependent population problem for analysis, so that published results for these types of problems can be applied, including the existence and regularity of model solutions. We also show how other coupled models having two types of time variables can be stated as age dependent population problems.
Asunto(s)
Adenocarcinoma del Pulmón , Adenocarcinoma , Neoplasias Pulmonares , Adenocarcinoma/genética , Adenocarcinoma/patología , Adenocarcinoma del Pulmón/genética , Humanos , Neoplasias Pulmonares/genética , Neoplasias Pulmonares/patología , Mutagénesis , Mutación , Proteínas Proto-Oncogénicas p21(ras)/genética , NicotianaRESUMEN
BACKGROUND: As the Zika virus epidemic continues to spread internationally, countries such as the United States must determine how much to invest in prevention, control, and response. Fundamental to these decisions is quantifying the potential economic burden of Zika under different scenarios. METHODOLOGY/PRINCIPLE FINDINGS: To inform such decision making, our team developed a computational model to forecast the potential economic burden of Zika across six states in the US (Alabama, Florida, Georgia, Louisiana, Mississippi, and Texas) which are at greatest risk of Zika emergence, under a wide range of attack rates, scenarios and circumstances. In order to accommodate a wide range of possibilities, different scenarios explored the effects of varying the attack rate from 0.01% to 10%. Across the six states, an attack rate of 0.01% is estimated to cost $183.4 million to society ($117.1 million in direct medical costs and $66.3 million in productivity losses), 0.025% would result in $198.6 million ($119.4 million and $79.2 million), 0.10% would result in $274.6 million ($130.8 million and $143.8 million) and 1% would result in $1.2 billion ($268.0 million and $919.2 million). CONCLUSIONS: Our model and study show how direct medical costs, Medicaid costs, productivity losses, and total costs to society may vary with different attack rates across the six states and the circumstances at which they may exceed certain thresholds (e.g., Zika prevention and control funding allocations that are being debated by the US government). A Zika attack rate of 0.3% across the six states at greatest risk of Zika infection, would result in total costs that exceed $0.5 billion, an attack rate of 1% would exceed $1 billion, and an attack rate of 2% would exceed $2 billion.
Asunto(s)
Costo de Enfermedad , Costos de la Atención en Salud , Infección por el Virus Zika/economía , Infección por el Virus Zika/epidemiología , Simulación por Computador , Femenino , Humanos , Embarazo , Estados Unidos/epidemiologíaRESUMEN
Cytomegalovirus (CMV) infection is the leading cause of congenital cognitive deficit, visual impairment and hearing loss in the US. Clinical trials are underway to evaluate the efficacy of CMV vaccine candidates in seronegative females. The optimal age of such vaccination depends on the interplay among age-specific transmission dynamics, vaccine efficacy and vaccine waning. We developed an age-structured model of CMV transmission dynamics in the US and estimated age-specific transmission rates of CMV based on age-stratified CMV prevalence, congenital infections per birth, breastfeeding patterns and demographic data. We found that the optimal age of vaccination depended on the duration of vaccine protection. For most scenarios, the optimal age of vaccination was between 19 and 21 years of age. However, for a rapidly waning vaccine, the optimal age of vaccination can shift to infants under 1 year. This shift arises when the duration of vaccine efficacy is too brief to offer appreciable protection during the child-bearing years. In this case, it becomes more effective to achieve indirect protection by reducing transmission from infants, the transmissibility from whom was estimated to be an order of magnitude higher than other age classes. Knowledge of vaccine waning is paramount to optimizing CMV vaccination and is thus a key parameter for longitudinal clinical evaluation.
Asunto(s)
Infecciones por Citomegalovirus/diagnóstico , Infecciones por Citomegalovirus/prevención & control , Vacunas contra Citomegalovirus/administración & dosificación , Transmisión de Enfermedad Infecciosa/prevención & control , Esquemas de Inmunización , Transmisión Vertical de Enfermedad Infecciosa/prevención & control , Tamizaje Masivo/métodos , Adolescente , Adulto , Anciano , Anciano de 80 o más Años , Niño , Preescolar , Femenino , Humanos , Lactante , Recién Nacido , Masculino , Persona de Mediana Edad , Estados Unidos , Adulto JovenRESUMEN
BACKGROUND: As Zika virus continues to spread, decisions regarding resource allocations to control the outbreak underscore the need for a tool to weigh policies according to their cost and the health burden they could avert. For example, to combat the current Zika outbreak the US President requested the allocation of $1.8 billion from Congress in February 2016. METHODOLOGY/PRINCIPAL FINDINGS: Illustrated through an interactive tool, we evaluated how the number of Zika cases averted, the period during pregnancy in which Zika infection poses a risk of microcephaly, and probabilities of microcephaly and Guillain-Barré Syndrome (GBS) impact the cost at which an intervention is cost-effective. From Northeast Brazilian microcephaly incidence data, we estimated the probability of microcephaly in infants born to Zika-infected women (0.49% to 2.10%). We also estimated the probability of GBS arising from Zika infections in Brazil (0.02% to 0.06%) and Colombia (0.08%). We calculated that each microcephaly and GBS case incurs the loss of 29.95 DALYs and 1.25 DALYs per case, as well as direct medical costs for Latin America and the Caribbean of $91,102 and $28,818, respectively. We demonstrated the utility of our cost-effectiveness tool with examples evaluating funding commitments by Costa Rica and Brazil, the US presidential proposal, and the novel approach of genetically modified mosquitoes. Our analyses indicate that the commitments and the proposal are likely to be cost-effective, whereas the cost-effectiveness of genetically modified mosquitoes depends on the country of implementation. CONCLUSIONS/SIGNIFICANCE: Current estimates from our tool suggest that the health burden from microcephaly and GBS warrants substantial expenditures focused on Zika virus control. Our results justify the funding committed in Costa Rica and Brazil and many aspects of the budget outlined in the US president's proposal. As data continue to be collected, new parameter estimates can be customized in real-time within our user-friendly tool to provide updated estimates on cost-effectiveness of interventions and inform policy decisions in country-specific settings.
Asunto(s)
Costos de la Atención en Salud , Política de Salud , Infección por el Virus Zika/economía , Infección por el Virus Zika/prevención & control , Aedes/genética , Aedes/virología , Animales , Animales Modificados Genéticamente , Brasil/epidemiología , Región del Caribe/epidemiología , Costo de Enfermedad , Análisis Costo-Beneficio/legislación & jurisprudencia , Costa Rica/epidemiología , Brotes de Enfermedades/economía , Brotes de Enfermedades/legislación & jurisprudencia , Brotes de Enfermedades/prevención & control , Femenino , Costos de la Atención en Salud/legislación & jurisprudencia , Humanos , Incidencia , Lactante , Microcefalia/etiología , Microcefalia/prevención & control , Microcefalia/virología , Embarazo , Complicaciones Infecciosas del Embarazo/economía , Complicaciones Infecciosas del Embarazo/prevención & control , Complicaciones Infecciosas del Embarazo/virología , Virus Zika/aislamiento & purificación , Infección por el Virus Zika/epidemiología , Infección por el Virus Zika/virologíaRESUMEN
BACKGROUND: A substantial scale-up in public health response is needed to control the unprecedented Ebola virus disease (EVD) epidemic in west Africa. Current international commitments seek to expand intervention capacity in three areas: new EVD treatment centres, case ascertainment through contact tracing, and household protective kit allocation. We aimed to assess how these interventions could be applied individually and in combination to avert future EVD cases and deaths. METHODS: We developed a transmission model of Ebola virus that we fitted to reported EVD cases and deaths in Montserrado County, Liberia. We used this model to assess the effectiveness of expanding EVD treatment centres, increasing case ascertainment, and allocating protective kits for controlling the outbreak in Montserrado. We varied the efficacy of protective kits from 10% to 50%. We compared intervention initiation on Oct 15, 2014, Oct 31, 2014, and Nov 15, 2014. The status quo intervention was defined in terms of case ascertainment and capacity of EVD treatment centres on Sept 23, 2014, and all behaviour and contact patterns relevant to transmission as they were occurring at that time. The primary outcome measure was the expected number of cases averted by Dec 15, 2014. FINDINGS: We estimated the basic reproductive number for EVD in Montserrado to be 2·49 (95% CI 2·38-2·60). We expect that allocating 4800 additional beds at EVD treatment centres and increasing case ascertainment five-fold in November, 2014, can avert 77â312 (95% CI 68â400-85â870) cases of EVD relative to the status quo by Dec 15, 2014. Complementing these measures with protective kit allocation raises the expectation as high as 97â940 (90â096-105â606) EVD cases. If deployed by Oct 15, 2014, equivalent interventions would have been expected to avert 137â432 (129â736-145â874) cases of EVD. If delayed to Nov 15, 2014, we expect the interventions will at best avert 53â957 (46â963-60â490) EVD cases. INTERPRETATION: The number of beds at EVD treatment centres needed to effectively control EVD in Montserrado substantially exceeds the 1700 pledged by the USA to west Africa. Accelerated case ascertainment is needed to maximise effectiveness of expanding the capacity of EVD treatment centres. Distributing protective kits can further augment prevention of EVD, but it is not an adequate stand-alone measure for controlling the outbreak. Our findings highlight the rapidly closing window of opportunity for controlling the outbreak and averting a catastrophic toll of EVD cases and deaths. FUNDING: US National Institutes of Health.
Asunto(s)
Transmisión de Enfermedad Infecciosa/prevención & control , Fiebre Hemorrágica Ebola/prevención & control , Fiebre Hemorrágica Ebola/transmisión , Modelos Teóricos , Número Básico de Reproducción , Fiebre Hemorrágica Ebola/epidemiología , Humanos , Control de Infecciones/métodos , Liberia/epidemiologíaRESUMEN
We describe a multiple strain Susceptible Infected Recovered deterministic model for the spread of an influenza subtype within a population. The model incorporates appearance of new strains due to antigenic drift, and partial immunity to reinfection with related circulating strains. It also includes optional seasonal forcing of the transmission rate of the virus, which allows for comparison between temperate zones and the tropics. Our model is capable of reproducing observed qualitative patterns such as the overall annual outbreaks in the temperate region, a reduced magnitude and an increased frequency of outbreaks in the tropics, and the herald wave phenomenon. Our approach to modelling antigenic drift is novel and further modifications of this model may help improve the understanding of complex influenza dynamics.