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A wide range of research has promised new tools for forecasting infectious disease dynamics, but little of that research is currently being applied in practice, because tools do not address key public health needs, do not produce probabilistic forecasts, have not been evaluated on external data, or do not provide sufficient forecast skill to be useful. We developed an open collaborative forecasting challenge to assess probabilistic forecasts for seasonal epidemics of dengue, a major global public health problem. Sixteen teams used a variety of methods and data to generate forecasts for 3 epidemiological targets (peak incidence, the week of the peak, and total incidence) over 8 dengue seasons in Iquitos, Peru and San Juan, Puerto Rico. Forecast skill was highly variable across teams and targets. While numerous forecasts showed high skill for midseason situational awareness, early season skill was low, and skill was generally lowest for high incidence seasons, those for which forecasts would be most valuable. A comparison of modeling approaches revealed that average forecast skill was lower for models including biologically meaningful data and mechanisms and that both multimodel and multiteam ensemble forecasts consistently outperformed individual model forecasts. Leveraging these insights, data, and the forecasting framework will be critical to improve forecast skill and the application of forecasts in real time for epidemic preparedness and response. Moreover, key components of this project-integration with public health needs, a common forecasting framework, shared and standardized data, and open participation-can help advance infectious disease forecasting beyond dengue.
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Dengue/epidemiología , Métodos Epidemiológicos , Brotes de Enfermedades , Epidemias/prevención & control , Humanos , Incidencia , Modelos Estadísticos , Perú/epidemiología , Puerto Rico/epidemiologíaRESUMEN
BACKGROUND: Seasonal influenza vaccination is an important behavior with significant individual and public health consequences, yet fewer than half of individuals in the USA are vaccinated annually. To promote vaccination adherence, it is important to understand the factors that affect vaccination behavior. PURPOSE: In this research, we focused on one such factor, an individual's vaccination history. We gathered longitudinal data to track and understand the relationship between an individual's vaccination history and their current behaviors. METHODS: U.S. adults completed multiple surveys over an 8 year period, which asked about whether they had received the influenza vaccination during the previous flu season. We analyzed the data to determine the strength of the relationship between vaccination decisions across single-year and multiyear intervals. Additionally, we fitted two mathematical models to the data to determine whether individuals were better characterized as having a stable propensity to vaccinate or a stable propensity to repeat their previous decisions. RESULTS: Individuals exhibited highly consistent behavior across adjacent years, yet, across the complete extent of the longitudinal study, they were far more likely to repeat the earlier decision to vaccinate. Surprisingly, the results of the mathematical model suggest that individuals are better characterized as having a stable propensity to repeat their previous decisions rather than a stable propensity to vaccinate per se. Although most individuals had an extremely strong tendency to repeat the previous decision, some had a far weaker propensity to do so. CONCLUSIONS: This suggests that interventions intended to increase vaccination uptake might be most impactful for those individuals with only a weak tendency to vaccinate or not to vaccinate.
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Toma de Decisiones , Conductas Relacionadas con la Salud , Conocimientos, Actitudes y Práctica en Salud , Gripe Humana/prevención & control , Vacunación/psicología , Adulto , Femenino , Humanos , Estudios Longitudinales , Masculino , Persona de Mediana Edad , Modelos Teóricos , Estaciones del Año , Estados Unidos/epidemiología , Vacunación/estadística & datos numéricosRESUMEN
BACKGROUND: Substantial gaps remain in understanding the trade-offs between the costs and benefits of choosing alternative human immunodeficiency virus (HIV) prevention strategies, including test-and-treat (expanded HIV testing combined with immediate treatment) and PrEP (initiation of preexposure prophylaxis by high-risk uninfected individuals) strategies. METHODS: We develop a mathematical epidemiological model to simulate HIV incidence among men residing in Los Angeles County, California, aged 15-65 years, who have sex with men. We combine these incidence data with an economic model to estimate the discounted cost, effectiveness (quality-adjusted life-years [QALYs]), and incremental cost-effectiveness ratios of various HIV prevention strategies using a societal perspective and a lifetime horizon. RESULTS: PrEP and test-and-treat yield the largest reductions in HIV incidence, and are highly cost-effective ($27 863/QALY and $19 302/QALY, respectively) relative to status quo and at a US willingness-to-pay threshold of $150 000/QALY saved. Status quo and 12 test-and-treat and PrEP strategies determine the frontier for efficient decisions. More aggressive strategies are costlier, but more effective, albeit with diminishing returns. The relative effectiveness of PrEP is sensitive to the initial HIV prevalence rate, PrEP and antiretroviral therapy (ART) adherence and initiation rates, the probabilities of HIV transmission, and the rates of sexual partner mixing. CONCLUSIONS: PrEP and test-and-treat offer cost-effective alternatives to the status quo. The success of these strategies depends on ART and PrEP adherence and initiation rates. The lack of evidence on adherence behaviors toward PrEP, therefore, warrants further studies.
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Fármacos Anti-VIH/economía , Infecciones por VIH/prevención & control , Costos de la Atención en Salud , Homosexualidad Masculina , Profilaxis Pre-Exposición/economía , Adolescente , Adulto , Anciano , Fármacos Anti-VIH/administración & dosificación , Análisis Costo-Beneficio , Infecciones por VIH/economía , Infecciones por VIH/epidemiología , Infecciones por VIH/virología , Humanos , Incidencia , Los Angeles/epidemiología , Masculino , Persona de Mediana Edad , Modelos Económicos , Modelos Teóricos , Profilaxis Pre-Exposición/estadística & datos numéricos , Prevalencia , Años de Vida Ajustados por Calidad de Vida , Adulto JovenRESUMEN
BACKGROUND: Data on effectiveness of preexposure prophylaxis (PrEP) for human immunodeficiency virus (HIV)-uninfected women attempting conception with HIV-infected male partners are limited to observational studies. METHODS: To explore the benefits of PrEP for conception, we developed a model to estimate the average annual probability of a woman remaining HIV-uninfected and having a child ("successful" outcome) via condomless sex with an HIV-infected male. The outcome likelihood is dependent upon parameters defining HIV-1 infectivity. We simulated 2 scenarios: optimal (condomless sex acts limited to the ovulation window), and suboptimal (acts not limited to ovulation). RESULTS: In the optimal scenario when the male is on antiretroviral therapy (ART), the average annual probability of the successful outcome is 29.1%, increasing to 29.2% with the addition of PrEP (P = .45). In the suboptimal scenario, the probability is 26.8% with ART alone versus 27.3% with ART/PrEP (P < .0001). Older maternal age reduces the probability of success in both scenarios, particularly after age 30. CONCLUSIONS: In our model, PrEP provides little added benefit when the HIV-infected male partner is on ART, condomless sex is limited to the ovulation window, and other modifiable transmission risks are optimized. Older female age decreases the probability of success by increasing the number of condomless sex acts required for conception.
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Transmisión de Enfermedad Infecciosa/prevención & control , Infecciones por VIH/prevención & control , Infecciones por VIH/transmisión , Profilaxis Pre-Exposición/métodos , Adolescente , Adulto , Femenino , Fertilización , Humanos , Masculino , Persona de Mediana Edad , Embarazo , Resultado del Tratamiento , Adulto JovenRESUMEN
Like the United States as a whole, Virginia faces a significant shortage of health care workers in nursing, primary care, and behavioral health. If current trends persist, these shortages will increase across Virginia. The authors of this study identify interventions that can help the Virginia Health Workforce Development Authority (VHWDA) address these health care workforce shortages. To accomplish this goal, they applied an analytic framework to existing or potential interventions for retaining, recruiting, and improving the structural efficiency of the nursing, primary care, and behavioral health workforces in Virginia. In this study, they highlight which interventions VHWDA should prioritize based on its desired outcomes and policy goals.
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BACKGROUND: There is evidence to suggest that antiretroviral therapy (ART) and testing for human immunodeficiency virus (HIV) reduce the probability of transmission of HIV. This has led health officials across the United States to take steps toward a test-and-treat policy. However, the extent of the benefits generated by test-and-treat is debatable, and there are concerns, such as increased multidrug resistance (MDR), that remain unaddressed. METHODS: We developed a deterministic epidemiologic model to simulate the HIV/AIDS epidemic for men who have sex with men (MSM) in Los Angeles County (LAC). We calibrated the model to match the HIV surveillance data from LAC across a 10-year period, starting in 2000. We then modified our model to simulate the test-and-treat policy and compared epidemiologic outcomes under the test-and-treat scenario to the status quo scenario over the years 2012-2023. Outcome measures included new infections, deaths, new AIDS cases, and MDR. RESULTS: Relative to the status quo, the test-and-treat model resulted in a 34% reduction in new infections, 19% reduction in deaths, and 39% reduction in new AIDS cases by 2023. However, these results are counterbalanced by a near doubling of the prevalence of MDR (9.06% compared to 4.79%) in 2023. We also found that the effects of increasing testing and treatment were not complementary. CONCLUSIONS: Although test-and-treat generates substantial benefits, it will not eliminate the epidemic for MSM in LAC. Moreover, these benefits are counterbalanced by large increases in MDR.
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Infecciones por VIH/epidemiología , Homosexualidad Masculina/estadística & datos numéricos , Modelos Estadísticos , Antirretrovirales/uso terapéutico , Farmacorresistencia Viral , Infecciones por VIH/diagnóstico , Infecciones por VIH/tratamiento farmacológico , Infecciones por VIH/transmisión , Humanos , Los Angeles/epidemiología , Masculino , Tamizaje Masivo , Vigilancia en Salud Pública/métodos , Resultado del TratamientoRESUMEN
The COVID-19 pandemic has called for swift action from local governments, which have instated non-pharmaceutical interventions (NPIs) to curb the spread of the disease. The swift implementation of social distancing policies has raised questions about the costs and benefits of strategies that either aim to keep cases as low as possible (suppression) or aim to reach herd immunity quickly (mitigation) to tackle the COVID-19 pandemic. While curbing COVID-19 required blunt instruments, it is unclear whether a less-transmissible and less-deadly emerging pathogen would justify the same response. This paper illuminates this question using a parsimonious transmission model by formulating the social distancing lives vs. livelihoods dilemma as a boundary value problem using calculus of variations. In this setup, society balances the costs and benefits of social distancing contingent on the costs of reducing transmission relative to the burden imposed by the disease. We consider both single-objective and multi-objective formulations of the problem. To the best of our knowledge, our approach is distinct in the sense that strategies emerge from the problem structure rather than being imposed a priori. We find that the relative time-horizon of the pandemic (i.e., the time it takes to develop effective vaccines and treatments) and the relative cost of social distancing influence the choice of the optimal policy. Unsurprisingly, we find that the appropriate policy response depends on these two factors. We discuss the conditions under which each policy archetype (suppression vs. mitigation) appears to be the most appropriate.
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COVID-19 , Humanos , COVID-19/epidemiología , COVID-19/prevención & control , Pandemias/prevención & control , Distanciamiento Físico , PolíticasRESUMEN
Policymakers in Connecticut are considering various options to increase the affordability of insurance in the state, such as expansions to premium and cost-sharing reduction subsidies on the state's health insurance marketplace, as well as expanded plan offerings, including extending eligibility for the state employee health plan (SEHP) to other groups and a publicly contracted, privately operated plan (the public option plan) offered to individuals on the marketplace. The authors used the RAND Corporation's COMPARE microsimulation model to estimate the impacts of such policy options. For each policy scenario, they calculated enrollment, premiums, consumer spending, and state spending and considered whether the results differed by race, ethnicity, or income group. The individual market reforms substantially increased affordability for people with incomes between 175 and 200 percent of the federal poverty level (FPL), reducing out-of-pocket spending as a share of income by 50 percent in some scenarios. Changes to affordability for higher-income groups were smaller, in part because the proposed policy changes for people with incomes between 200 and 400 percent of FPL were relatively modest and focused only on reducing cost-sharing (not premiums). New costs to the state for 2023 ranged from $19 million to $94 million, depending on the scenario. All four SEHP specifications led to the same bottom-line conclusion that offering a SEHP plan would improve insurance coverage and affordability for those eligible for the plan. Expanding eligibility for the SEHP holds promise for stabilizing or reducing consumer costs, improving plan generosity, and bringing more people into the market.
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The coronavirus disease 2019 pandemic required significant public health interventions from local governments. Early in the pandemic, RAND researchers developed a decision support tool to provide policymakers with insight into the trade-offs they might face when choosing among nonpharmaceutical intervention levels. Using an updated version of the model, the researchers performed a stress-test of a variety of alternative reopening plans, using California as an example. This article presents the general lessons learned from these experiments and discusses four characteristics of the best reopening strategies.
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OBJECTIVE: Our objective was to model the reciprocal relationships of perceived risk of contracting influenza with and without influenza vaccination, vaccination behavior, and reported influenza illness. METHODS: We fit structural equation models to data from a longitudinal survey of adults in the United States collected through the RAND American Life Panel. Data come from fall and spring surveys fielded before and after each of 3 influenza seasons, 2016/2017, 2017/2018, and 2018/2019, for a total of 6 waves. RESULTS: As expected, reported influenza experience was associated with increased perceived influenza risk in subsequent survey waves. Furthermore, perceived risk was associated with subsequent vaccination behavior, such that vaccination was more common for those with higher perceived unvaccinated influenza risk and lower perceived vaccinated influenza risk. Perhaps surprisingly, both elements of perceived risk were also associated with a greater likelihood of subsequent reported influenza illness. This malleability in illness reports may reflect uncertainty, as more respondents reported being sick but being unsure about whether they had influenza than reported certainty that they had influenza. CONCLUSIONS: Interventions that influence perceptions about past experience with influenza, including increased testing and informational campaigns about influenza symptoms, could have unanticipated impacts on perceptions of influenza vaccination and vaccination behavior.
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Vacunas contra la Influenza , Gripe Humana , Adulto , Humanos , Vacunas contra la Influenza/uso terapéutico , Gripe Humana/epidemiología , Gripe Humana/prevención & control , Estudios Longitudinales , Estaciones del Año , Encuestas y Cuestionarios , Estados Unidos/epidemiología , VacunaciónRESUMEN
The association between IGF-1 levels and mortality in humans is complex with low levels being associated with both low and high mortality. The present meta-analysis investigates this complex relationship between IGF-1 and all-cause mortality in prospective cohort studies. A systematic literature search was conducted in PubMed/MEDLINE, Scopus, and Cochrane Library up to September 2019. Published studies were eligible for the meta-analysis if they had a prospective cohort design, a hazard ratio (HR) and 95% confidence interval (CI) for two or more categories of IGF-1 and were conducted among adults. A random-effects model with a restricted maximum likelihood heterogeneity variance estimator was used to find combined HRs for all-cause mortality. Nineteen studies involving 30,876 participants were included. Meta-analysis of the 19 eligible studies showed that with respect to the low IGF-1 category, higher IGF-1 was not associated with increased risk of all-cause mortality (HR = 0.84, 95% CI = 0.68-1.05). Dose-response analysis revealed a U-shaped relation between IGF-1 and mortality HR. Pooled results comparing low vs. middle IGF-1 showed a significant increase of all-cause mortality (HR = 1.33, 95% CI = 1.14-1.57), as well as comparing high vs. middle IGF-1 categories (HR = 1.23, 95% CI = 1.06-1.44). Finally, we provide data on the association between IGF-1 levels and the intake of proteins, carbohydrates, certain vitamins/minerals, and specific foods. Both high and low levels of IGF-1 increase mortality risk, with a specific 120-160 ng/ml range being associated with the lowest mortality. These findings can explain the apparent controversy related to the association between IGF-1 levels and mortality.
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Factor I del Crecimiento Similar a la Insulina , Adulto , Estudios de Cohortes , Humanos , Modelos de Riesgos Proporcionales , Estudios ProspectivosRESUMEN
We developed a COVID-19 transmission model to compare the effects of nonpharmaceutical public health interventions (NPIs) on health and economic outcomes. An interdisciplinary approach informed the selection and use of multiple NPIs, combining quantitative modeling of the health and economic impacts of interventions with qualitative assessments of other important considerations (e.g., cost, ease of implementation, equity). We used our model to analyzed strategies that periodically switch between a base NPI and a high NPI level. We find that this systematic strategy could have produced similar health outcomes as static strategies but better social welfare and economic outcomes. Our findings suggest that there are opportunities to shape the tradeoffs between economic and health outcomes by carefully evaluating a more comprehensive range of reopening policies.
Desarrollamos un modelo de transmisión de COVID-19 para comparar los efectos de las intervenciones de salud pública (NPI) no farmacéuticas en los resultados económicos y de salud. Un enfoque interdisciplinario informó la selección y el uso de múltiples ISFL, combinando modelos cuantitativos de los impactos económicos y de salud de las intervenciones con evaluaciones cualitativas de otras consideraciones importantes (por ejemplo, costo, facilidad de implementación, equidad). Usamos nuestro modelo para analizar estrategias que cambian periódicamente entre un NPI base y un nivel alto de NPI. Encontramos que esta estrategia sistemática podría haber producido resultados de salud similares a los de las estrategias estáticas, pero mejores resultados económicos y de bienestar social. Nuestros hallazgos sugieren que existen oportunidades para dar forma a las compensaciones entre los resultados económicos y de salud al evaluar cuidadosamente una gama más completa de políticas de reapertura.
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We developed a COVID-19 transmission model used as part of RAND's web-based COVID-19 decision support tool that compares the effects of nonpharmaceutical public health interventions (NPIs) on health and economic outcomes. An interdisciplinary approach informed the selection and use of multiple NPIs, combining quantitative modeling of the health/economic impacts of interventions with qualitative assessments of other important considerations (e.g., cost, ease of implementation, equity). This paper provides further details of our model, describes extensions, presents sensitivity analyses, and analyzes strategies that periodically switch between a base NPI level and a higher NPI level. We find that a periodic strategy, if implemented with perfect compliance, could have produced similar health outcomes as static strategies but might have produced better outcomes when considering other measures of social welfare. Our findings suggest that there are opportunities to shape the tradeoffs between economic and health outcomes by carefully evaluating a more comprehensive range of reopening policies.
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We use mobile device data to construct empirical interpersonal physical contact networks in the city of Portland, Oregon, both before and after social distancing measures were enacted during the COVID-19 pandemic. These networks reveal how social distancing measures and the public's reaction to the incipient pandemic affected the connectivity patterns within the city. We find that as the pandemic developed there was a substantial decrease in the number of individuals with many contacts. We further study the impact of these different network topologies on the spread of COVID-19 by simulating an SEIR epidemic model over these networks and find that the reduced connectivity greatly suppressed the epidemic. We then investigate how the epidemic responds when part of the population is vaccinated, and we compare two vaccination distribution strategies, both with and without social distancing. Our main result is that the heavy-tailed degree distribution of the contact networks causes a targeted vaccination strategy that prioritizes high-contact individuals to reduce the number of cases far more effectively than a strategy that vaccinates individuals at random. Combining both targeted vaccination and social distancing leads to the greatest reduction in cases, and we also find that the marginal benefit of a targeted strategy as compared to a random strategy exceeds the marginal benefit of social distancing for reducing the number of cases. These results have important implications for ongoing vaccine distribution efforts worldwide.
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Amid global scarcity of COVID-19 vaccines and the threat of new variant strains, California and other jurisdictions face the question of when and how to implement and relax COVID-19 Nonpharmaceutical Interventions (NPIs). While policymakers have attempted to balance the health and economic impacts of the pandemic, decentralized decision-making, deep uncertainty, and the lack of widespread use of comprehensive decision support methods can lead to the choice of fragile or inefficient strategies. This paper uses simulation models and the Robust Decision Making (RDM) approach to stress-test California's reopening strategy and other alternatives over a wide range of futures. We find that plans which respond aggressively to initial outbreaks are required to robustly control the pandemic. Further, the best plans adapt to changing circumstances, lowering their stringent requirements to reopen over time or as more constituents are vaccinated. While we use California as an example, our results are particularly relevant for jurisdictions where vaccination roll-out has been slower.
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The COVID-19 pandemic required significant public health interventions from local governments. Although nonpharmaceutical interventions often were implemented as decision rules, few studies evaluated the robustness of those reopening plans under a wide range of uncertainties. This paper uses the Robust Decision Making approach to stress-test 78 alternative reopening strategies, using California as an example. This study uniquely considers a wide range of uncertainties and demonstrates that seemingly sensible reopening plans can lead to both unnecessary COVID-19 deaths and days of interventions. We find that plans using fixed COVID-19 case thresholds might be less effective than strategies with time-varying reopening thresholds. While we use California as an example, our results are particularly relevant for jurisdictions where vaccination roll-out has been slower. The approach used in this paper could also prove useful for other public health policy problems in which policymakers need to make robust decisions in the face of deep uncertainty.
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COVID-19 , Pandemias , Humanos , Salud Pública , IncertidumbreRESUMEN
Purpose. "False consensus" refers to individuals with (v. without) an experience judging that experience as more (v. less) prevalent in the population. We examined the role of people's perceptions of their social circles (family, friends, and acquaintances) in shaping their population estimates, false consensus patterns, and vaccination intentions. Methods. In a national online flu survey, 351 participants indicated their personal vaccination and flu experiences, assessed the percentage of individuals with those experiences in their social circles and the population, and reported their vaccination intentions. Results. Participants' population estimates of vaccination coverage and flu prevalence were associated with their perceptions of their social circles' experiences, independent of their own experiences. Participants reporting less social circle "homophily" (or fewer social contacts sharing their experience) showed less false consensus and even "false uniqueness." Vaccination intentions were greater among nonvaccinators reporting greater social circle vaccine coverage. Discussion. Social circle perceptions play a role in population estimates and, among individuals who do not vaccinate, vaccination intentions. We discuss implications for the literature on false consensus, false uniqueness, and social norms interventions.
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Conocimientos, Actitudes y Práctica en Salud , Gripe Humana/prevención & control , Gripe Humana/psicología , Normas Sociales , Percepción Social , Vacunación/psicología , Adulto , Anciano , Consenso , Femenino , Humanos , Vacunas contra la Influenza/uso terapéutico , Masculino , Persona de Mediana Edad , Encuestas y Cuestionarios , Estados UnidosRESUMEN
OBJECTIVE: Flu vaccinations are recommended for almost everyone, but uptake may vary because of perceived social norms. We aimed to examine the relationship between perceived social circle vaccine coverage (including family, friends, and acquaintances) and own vaccination behavior as well as potential mediators. METHODS: In 2011, 357 participants from RAND's American Life Panel reported perceived social circle vaccine coverage for the 2010-2011 flu season, own vaccination behavior for the 2009-2010 and 2010-2011 flu seasons, perceived flu risk without and with vaccination, and perceived vaccine safety. In 2012 and 2016, respectively, participants returned to report their own vaccination behavior for the 2011-2012 flu season (N = 338) and 2015-2016 flu season (N = 216). RESULTS: Perceiving greater percentage of 2010-2011 social circle vaccine coverage was associated with a greater likelihood of getting vaccinated in the 2010-2011 flu season (odds ratio [OR] = 1.03, 95% confidence interval [CI] = 1.01, 1.04) and the subsequent 2011-2012 flu season (OR = 1.02, 95% CI = 1.01, 1.03) but not the 2015-2016 flu season (OR = 1.00, 95% CI = .99, 1.01), as seen in logistic regressions that controlled for demographics and 2009-2010 vaccination behavior. All significant relationships between social circle vaccine coverage and own vaccination behavior were mediated by perceived flu risk without vaccination. CONCLUSIONS: Perceived social circle vaccine coverage is associated with own vaccination behavior in the current and subsequent flu season, establishing behavior patterns that may persist into the future. People's vaccination decisions may be informed by their perceptions of their peers' beliefs and behaviors. We discuss intervention strategies for promoting vaccine uptake by counteracting negative and promoting positive perceived social norms. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
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Vacunas contra la Influenza/normas , Gripe Humana/epidemiología , Psicología Social/métodos , Femenino , Humanos , Estudios Longitudinales , Masculino , Encuestas y CuestionariosRESUMEN
We re-examine the evidence behind the controversial hypothesis that syphilis epidemics cycle. We used the same methods (spectral analysis) used by the proponents of this hypothesis to reanalyse a longitudinal dataset provided by the US Centers for Disease Control and Prevention (CDC). We also analysed a longitudinal CDC mortality dataset. To investigate the theoretical results generated by the transmission model that was used to support the hypothesis, we simulated the model and predicted the expected dynamics of syphilis epidemics. By contrast with previous findings, we found that neither of the CDC's datasets provides compelling evidence that syphilis epidemics cycle, and the transmission model (if more reasonable parameter values are used) does not predict cycling behaviour. We explain the possible reasons for the previous proposal that syphilis epidemics cycle. Our findings imply that it is quite possible that the CDC could be successful in eliminating syphilis within the next few decades.