scholarly journals Modeling Zika Vaccination Combined With Vector Interventions in DoD Populations

2021 ◽  
Vol 186 (Supplement_1) ◽  
pp. 82-90
Author(s):  
Colleen Burgess ◽  
Lis Nelis ◽  
Cassie Huang
Keyword(s):  
Mosquito Control ◽  
Cost Benefit Analysis ◽  
Herd Immunity ◽  
Febrile Illness ◽  
Sensitivity Analyses ◽  
Transmission Model ◽  
Model Parameters ◽  
Military Installations ◽  
Low Level ◽  
Limited Effectiveness

ABSTRACT Introduction Zika virus (ZIKV) is a mild febrile illness generally transmitted via the bite of infected Aedes species mosquitoes, including Aedes aegypti, with the potential to cause neurological complications. Nearly 200 U.S. military installations are located within areas where Aedes mosquitos are found, putting thousands of personnel at risk for infection with ZIKV. This analysis aims to quantify the benefits of interventions, including vaccination, to decrease the risk of ZIKV on U.S. military installations. Methods The authors developed a dynamic transmission model to test the “effectiveness” of vaccination, personal protective measures (PPM), and mosquito control at reducing morbidity within U.S. military populations. ZIKV transmission was modeled as a compartmental susceptible-exposed-infected-recovered model tracking interactions between humans and mosquitos and incorporating seasonality of mosquito populations and the potential for herd immunity. The model included two-dose vaccination as well as symptomatic and asymptomatic infection. The model was calibrated against 2016 public health data in Puerto Rico; sensitivity analyses were performed on model parameters and interventions. Results The greatest reduction in total modeled ZIKV cases resulted from vaccination combined with mosquito control and PPM. All three interventions at their highest estimated level of efficiency reduced ZIKV cases by 99.9% over the baseline case of low-level adherence to PPM. The addition of vaccination had limited additional benefit over effective vector control and PPM since the significant lag to vaccine-induced protection limited effectiveness of vaccination. Conclusions Given the current vaccine, the model predicted that up to 92.8% of Zika cases occurring in deployment settings over a 10-year period could be prevented by adding vaccination to current low-level PPM. Combining vaccination with other interventions can reduce cases further. A location-specific cost-benefit analysis would be a valuable contribution to outbreak control policy as it could evaluate the economic impact of the interventions versus the reduced level of illness and downtime in this setting.

scholarly journals Understanding transmission and control of the pork tapeworm with CystiAgent: a spatially explicit agent-based model

2020 ◽  
Author(s):  
Ian Wright Pray ◽  
Wayne Wakeland ◽  
William Pan ◽  
William E. Lambert ◽  
Hector H. Garcia ◽  
...  
Keyword(s):  
Taenia Solium ◽  
Model Performance ◽  
Rank Correlation ◽  
Public Health Problem ◽  
Sensitivity Analyses ◽  
Transmission Model ◽  
Spatially Explicit ◽  
Model Parameters ◽  
Agent Based Model ◽  
Agent Based

Abstract Background The pork tapeworm ( Taenia solium ) is a serious public health problem in rural low-resource areas of Latin America, Africa, and Asia, where the associated conditions of nuerocysticercosis (NCC) and porcine cysticercosis cause substantial health and economic harms. An accurate and validated transmission model for T. solium would serve as an important new tool for control and elimination, as it would allow for comparison of available intervention strategies, and prioritization of the most effective strategies for control and elimination efforts. Methods We developed a spatially-explicit agent-based model (ABM) for T. solium (“CystiAgent”) that differs from prior T. solium models by including a spatial framework and behavioral parameters such as pig roaming, open human defecation, and human travel. In this article, we introduce the structure and function of the model, describe the data sources used to parameterize the model, and apply sensitivity analyses (Latin hypercube sampling–partial rank correlation coefficient (LHS-PRCC)) to evaluate model parameters. Results LHS-PRCC analysis of CystiAgent found that the parameters with the greatest impact on model uncertainty were the roaming range of pigs, the infectious duration of human taeniasis, use of latrines, and the set of “tuning” parameters defining the probabilities of infection in humans and pigs given exposure to T. solium. Conclusions CystiAgent is a novel ABM that has the ability to model spatial and behavioral features of T. solium transmission not available in other models. There is a small set of impactful model parameters that contribute uncertainty to the model and may impact the accuracy of model projections. Field and laboratory studies to better understand these key components of transmission may help reduce uncertainty, while current applications of CystiAgent may consider calibration of these parameters to improve model performance. These results will ultimately allow for improved interpretation of model validation results, and usage of the model to compare available control and elimination strategies for T. solium .

scholarly journals Projecting the end of the Zika virus epidemic in Latin America: a modelling analysis

2018 ◽  
Author(s):  
Kathleen M O’Reilly ◽  
Rachel Lowe ◽  
W John Edmunds ◽  
Philippe Mayaud ◽  
Adam Kucharski ◽  
...  
Keyword(s):  
Latin America ◽  
Zika Virus ◽  
Herd Immunity ◽  
Reporting Rate ◽  
World Health ◽  
Transmission Model ◽  
Parameter Estimates ◽  
Model Parameters ◽  
Spatio Temporal ◽  
Reporting Rates

AbstractBackground Zika virus (ZIKV) emerged in Latin America & the Caribbean (LAC) region in 2013, and has had serious implications for population health in the region. In 2016, the World Health Organization declared the ZIKV outbreak a Public Health Emergency of International Concern following a cluster of associated neurological disorders and neonatal malformations. In 2017, Zika cases declined, but future incidence in LAC remains uncertain due to gaps in our understanding, considerable variation in surveillance and a lack of a comprehensive collation of data from affected countries.Methods Our analysis combines information on confirmed and suspected Zika cases across LAC countries and a spatio-temporal dynamic transmission model for ZIKV infection to determine key transmission parameters and projected incidence in 91 major cities within 35 countries. Seasonality was determined by spatio-temporal estimates of Aedes aegypti vector capacity. We used country and state-level data from 2015 to mid-2017 to infer key model parameters, country-specific disease reporting rates, and the 2018 projected incidence. A 10-fold cross-validation approach was used to validate parameter estimates to out-of-sample epidemic trajectories.Results There was limited transmission in 2015, but in 2016 and 2017 there was sufficient opportunity for wide-spread ZIKV transmission in most cities, resulting in the depletion of susceptible individuals. We predict that the highest number of cases in 2018 within some Brazilian States (Sao Paulo and Rio de Janeiro), Colombia and French Guiana, but the estimated number of cases were no more than a few hundred. Model estimates of the timing of the peak in incidence were correlated (p<0.05) with the reported peak in incidence. The reporting rate varied across countries, with lower reporting rates for those with only confirmed cases compared to those who reported both confirmed and suspected cases.Conclusions The findings suggest that the ZIKV epidemic is by and large over, with incidence projected to be low in most cities in LAC in 2018. Local low levels of transmission are probable but the estimated rate of infection suggests that most cities have a population with high levels of herd immunity.

scholarly journals Understanding transmission and control of the pork tapeworm with CystiAgent: a spatially explicit agent-based model

2020 ◽  
Author(s):  
Ian Wright Pray ◽  
Wayne Wakeland ◽  
William Pan ◽  
William E. Lambert ◽  
Hector H. Garcia ◽  
...  
Keyword(s):  
Taenia Solium ◽  
Model Performance ◽  
Rank Correlation ◽  
Public Health Problem ◽  
Sensitivity Analyses ◽  
Transmission Model ◽  
Spatially Explicit ◽  
Model Parameters ◽  
Agent Based Model ◽  
Agent Based

Abstract BackgroundThe pork tapeworm (Taenia solium) is a serious public health problem in rural low-resource areas of Latin America, Africa, and Asia, where the associated conditions of nuerocysticercosis (NCC) and porcine cysticercosis cause substantial health and economic harms. An accurate and validated transmission model for T. solium would serve as an important new tool for control and elimination, as it would allow for comparison of available intervention strategies, and prioritization of the most effective strategies for control and elimination efforts. MethodsWe developed a spatially-explicit agent-based model (ABM) for T. solium (“CystiAgent”) that differs from prior T. solium models by including a spatial framework and behavioral parameters such as pig roaming, open human defecation, and human travel. In this article, we introduce the structure and function of the model, describe the data sources used to parameterize the model, and apply sensitivity analyses (Latin hypercube sampling–partial rank correlation coefficient (LHS-PRCC)) to evaluate model parameters. ResultsLHS-PRCC analysis of CystiAgent found that the parameters with the greatest impact on model uncertainty were the roaming range of pigs, the infectious duration of human taeniasis, use of latrines, and the set of “tuning” parameters defining the probabilities of infection in humans and pigs given exposure to T. solium.ConclusionsCystiAgent is a novel ABM that has the ability to model spatial and behavioral features of T. solium transmission not available in other models. There is a small set of impactful model parameters that contribute uncertainty to the model and may impact the accuracy of model projections. Field and laboratory studies to better understand these key components of transmission may help reduce uncertainty, while current applications of CystiAgent may consider calibration of these parameters to improve model performance. These results will ultimately allow for improved interpretation of model validation results, and usage of the model to compare available control and elimination strategies for T. solium.

scholarly journals Cost-utility analysis of antiviral use under pandemic influenza using a novel approach – linking pharmacology, epidemiology and heath economics

2018 ◽  
Vol 146 (4) ◽  
pp. 496-507 ◽  
Author(s):  
D. B. C. Wu ◽  
N. Chaiyakunapruk ◽  
C. Pratoomsoot ◽  
K. K. C. Lee ◽  
H. Y. Chong ◽  
...  
Keyword(s):  
Pandemic Influenza ◽  
Influenza Pandemic ◽  
Cost Utility ◽  
Cost Utility Analysis ◽  
Sensitivity Analyses ◽  
Transmission Model ◽  
Decision Analytic Model ◽  
Model Parameters ◽  
Utility Analysis ◽  
The Impact

AbstractSimulation models are used widely in pharmacology, epidemiology and health economics (HEs). However, there have been no attempts to incorporate models from these disciplines into a single integrated model. Accordingly, we explored this linkage to evaluate the epidemiological and economic impact of oseltamivir dose optimisation in supporting pandemic influenza planning in the USA. An HE decision analytic model was linked to a pharmacokinetic/pharmacodynamics (PK/PD) – dynamic transmission model simulating the impact of pandemic influenza with low virulence and low transmissibility and, high virulence and high transmissibility. The cost-utility analysis was from the payer and societal perspectives, comparing oseltamivir 75 and 150 mg twice daily (BID) to no treatment over a 1-year time horizon. Model parameters were derived from published studies. Outcomes were measured as cost per quality-adjusted life year (QALY) gained. Sensitivity analyses were performed to examine the integrated model's robustness. Under both pandemic scenarios, compared to no treatment, the use of oseltamivir 75 or 150 mg BID led to a significant reduction of influenza episodes and influenza-related deaths, translating to substantial savings of QALYs. Overall drug costs were offset by the reduction of both direct and indirect costs, making these two interventions cost-saving from both perspectives. The results were sensitive to the proportion of inpatient presentation at the emergency visit and patients’ quality of life. Integrating PK/PD–EPI/HE models is achievable. Whilst further refinement of this novel linkage model to more closely mimic the reality is needed, the current study has generated useful insights to support influenza pandemic planning.

scholarly journals Understanding transmission and control of the pork tapeworm with CystiAgent: a spatially explicit agent-based model

2020 ◽  
Author(s):  
Ian Wright Pray ◽  
Wayne Wakeland ◽  
William Pan ◽  
William E. Lambert ◽  
Hector H. Garcia ◽  
...  
Keyword(s):  
Taenia Solium ◽  
Model Performance ◽  
Rank Correlation ◽  
Public Health Problem ◽  
Sensitivity Analyses ◽  
Transmission Model ◽  
Spatially Explicit ◽  
Model Parameters ◽  
Agent Based Model ◽  
Agent Based

Abstract Background The pork tapeworm (Taenia solium) is a serious public health problem in rural low-resource areas of Latin America, Africa, and Asia, where the associated conditions of nuerocysticercosis (NCC) and porcine cysticercosis cause substantial health and economic harms. An accurate and validated transmission model for T. solium would serve as an important new tool for control and elimination, as it would allow for comparison of available intervention strategies, and prioritization of the most effective strategies for control and elimination efforts. Methods We developed a spatially-explicit agent-based model (ABM) for T. solium (“CystiAgent”) that differs from prior T. solium models by including a spatial framework and behavioral parameters such as pig roaming, open human defecation, and human travel. In this article, we introduce the structure and function of the model, describe the data sources used to parameterize the model, and apply sensitivity analyses (Latin hypercube sampling–partial rank correlation coefficient (LHS-PRCC)) to evaluate model parameters. Results LHS-PRCC analysis of CystiAgent found that the parameters with the greatest impact on model uncertainty were the roaming range of pigs, the infectious duration of human taeniasis, use of latrines, and the set of “tuning” parameters defining the probabilities of infection in humans and pigs given exposure to T. solium.Conclusions CystiAgent is a novel ABM that has the ability to model spatial and behavioral features of T. solium transmission not available in other models. There is a small set of impactful model parameters that contribute uncertainty to the model and may impact the accuracy of model projections. Field and laboratory studies to better understand these key components of transmission may help reduce uncertainty, while current applications of CystiAgent may consider calibration of these parameters to improve model performance. These results will ultimately allow for improved interpretation of model validation results, and usage of the model to compare available control and elimination strategies for T. solium.

scholarly journals Estimating the Burden of Dengue in the Philippines Using a Dynamic Transmission Model

2018 ◽  
Vol 52 (2) ◽  
Author(s):  
Kent Jason G. Cheng ◽  
Hilton Y. Lam ◽  
Adovich S. Rivera ◽  
Bernadette A. Tumanan-Mendoza ◽  
Marissa M. Alejandria ◽  
...  
Keyword(s):  
The Philippines ◽  
Sensitivity Analyses ◽  
Transmission Model ◽  
Model Parameters ◽  
Government Interventions ◽  
Productivity Losses ◽  
Annual Productivity ◽  
Dynamic Transmission Model ◽  
Public Payer ◽  
The Cost

Objective. This study aimed to describe dengue burden in the Philippines. Specifically, health and economic costs of the disease were estimated. Methods. A published serotype-specific and age-stratified dengue dynamic transmission model was populated with Philippine-specific dengue epidemiology and cost data. Data were gathered from literature and record reviews. Dengue experts were consulted to validate the model parameters. Sensitivity analyses were performed to test the uncertainty of input parameters on model outcomes. Results. By 2016 to 2020, it is estimated that annually, average hospitalized cases will amount to 401,191 and ambulatory cases will amount to 239,497; resulting to USD 139 million (PhP 5.9 billion) and USD 19 million (PhP 827 million) worth of aggregate costs shouldered by the public payer for hospitalized and ambulatory cases, respectively. Average annual productivity losses may amount to USD 19 million (PhP 821 million) and DALY lost is expected to be 50,622. Conclusion. The cost of dengue is high especially since the Philippines is an endemic country. Thus, there is a need to optimize government interventions such as vector control and vaccination that aim to prevent dengue infections.

scholarly journals Evolution of disease transmission during the COVID-19 pandemic: patterns and determinants

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jie Zhu ◽  
Blanca Gallego
Keyword(s):  
Public Health ◽  
Disease Transmission ◽  
Clustering Algorithm ◽  
Health Interventions ◽  
Transmission Model ◽  
Model Parameters ◽  
Public Health Interventions ◽  
Forecasting Accuracy ◽  
Time Lagged ◽  
The Impact

AbstractEpidemic models are being used by governments to inform public health strategies to reduce the spread of SARS-CoV-2. They simulate potential scenarios by manipulating model parameters that control processes of disease transmission and recovery. However, the validity of these parameters is challenged by the uncertainty of the impact of public health interventions on disease transmission, and the forecasting accuracy of these models is rarely investigated during an outbreak. We fitted a stochastic transmission model on reported cases, recoveries and deaths associated with SARS-CoV-2 infection across 101 countries. The dynamics of disease transmission was represented in terms of the daily effective reproduction number ($$R_t$$ R t ). The relationship between public health interventions and $$R_t$$ R t was explored, firstly using a hierarchical clustering algorithm on initial $$R_t$$ R t patterns, and secondly computing the time-lagged cross correlation among the daily number of policies implemented, $$R_t$$ R t , and daily incidence counts in subsequent months. The impact of updating $$R_t$$ R t every time a prediction is made on the forecasting accuracy of the model was investigated. We identified 5 groups of countries with distinct transmission patterns during the first 6 months of the pandemic. Early adoption of social distancing measures and a shorter gap between interventions were associated with a reduction on the duration of outbreaks. The lagged correlation analysis revealed that increased policy volume was associated with lower future $$R_t$$ R t (75 days lag), while a lower $$R_t$$ R t was associated with lower future policy volume (102 days lag). Lastly, the outbreak prediction accuracy of the model using dynamically updated $$R_t$$ R t produced an average AUROC of 0.72 (0.708, 0.723) compared to 0.56 (0.555, 0.568) when $$R_t$$ R t was kept constant. Monitoring the evolution of $$R_t$$ R t during an epidemic is an important complementary piece of information to reported daily counts, recoveries and deaths, since it provides an early signal of the efficacy of containment measures. Using updated $$R_t$$ R t values produces significantly better predictions of future outbreaks. Our results found variation in the effect of early public health interventions on the evolution of $$R_t$$ R t over time and across countries, which could not be explained solely by the timing and number of the adopted interventions.

scholarly journals High COVID-19 transmission potential associated with re-opening universities can be mitigated with layered interventions

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Ellen Brooks-Pollock ◽  
Hannah Christensen ◽  
Adam Trickey ◽  
Gibran Hemani ◽  
Emily Nixon ◽  
...  
Keyword(s):  
Prediction Interval ◽  
Mitigation Strategies ◽  
Control Measures ◽  
Transmission Model ◽  
Model Parameters ◽  
Infection Rates ◽  
First Year Students ◽  
Transmission Potential ◽  
Plausible Model ◽  
Effective Option

AbstractControlling COVID-19 transmission in universities poses challenges due to the complex social networks and potential for asymptomatic spread. We developed a stochastic transmission model based on realistic mixing patterns and evaluated alternative mitigation strategies. We predict, for plausible model parameters, that if asymptomatic cases are half as infectious as symptomatic cases, then 15% (98% Prediction Interval: 6–35%) of students could be infected during the first term without additional control measures. First year students are the main drivers of transmission with the highest infection rates, largely due to communal residences. In isolation, reducing face-to-face teaching is the most effective intervention considered, however layering multiple interventions could reduce infection rates by 75%. Fortnightly or more frequent mass testing is required to impact transmission and was not the most effective option considered. Our findings suggest that additional outbreak control measures should be considered for university settings.

scholarly journals Optimal Investment and Proportional Reinsurance in a Regime-Switching Market Model under Forward Preferences

Mathematics ◽  
2021 ◽  
Vol 9 (14) ◽  
pp. 1610
Author(s):  
Katia Colaneri ◽  
Alessandra Cretarola ◽  
Benedetta Salterini
Keyword(s):  
Stock Prices ◽  
Regime Switching ◽  
Common Factor ◽  
Optimal Investment ◽  
Investment Strategy ◽  
Market Model ◽  
Sensitivity Analyses ◽  
Model Parameters ◽  
Insurance Company ◽  
Optimal Investment Strategy

In this paper, we study the optimal investment and reinsurance problem of an insurance company whose investment preferences are described via a forward dynamic exponential utility in a regime-switching market model. Financial and actuarial frameworks are dependent since stock prices and insurance claims vary according to a common factor given by a continuous time finite state Markov chain. We construct the value function and we prove that it is a forward dynamic utility. Then, we characterize the optimal investment strategy and the optimal proportional level of reinsurance. We also perform numerical experiments and provide sensitivity analyses with respect to some model parameters.

scholarly journals Cost Effectiveness of a Home-Based Intervention That Helps Functionally Vulnerable Older Adults Age in Place at Home

2012 ◽  
Vol 2012 ◽  
pp. 1-6 ◽  
Author(s):  
Eric Jutkowitz ◽  
Laura N. Gitlin ◽  
Laura T. Pizzi ◽  
Edward Lee ◽  
Marie P. Dennis
Keyword(s):  
Cost Effectiveness ◽  
Community Dwelling ◽  
Sensitivity Analyses ◽  
Model Parameters ◽  
Potential Cost ◽  
Functional Difficulties ◽  
Age In Place ◽  
Home Based ◽  
Occupational And Physical Therapy ◽  
Home Based Intervention

Evaluating cost effectiveness of interventions for aging in place is essential for adoption in service settings. We present the cost effectiveness of Advancing Better Living for Elders (ABLE), previously shown in a randomized trial to reduce functional difficulties and mortality in 319 community-dwelling elders. ABLE involved occupational and physical therapy sessions and home modifications to address client-identified functional difficulties, performance goals, and home safety. Incremental cost-effectiveness ratio (ICER), expressed as additional cost to bring about one additional year of life, was calculated. Two models were then developed to account for potential cost differences in implementing ABLE. Probabilistic sensitivity analyses were conducted to account for variations in model parameters. By two years, there were 30 deaths (9: ABLE; 21: control). Additional costs for 1 additional year of life was $13,179 for Model 1 and $14,800 for Model 2. Investment in ABLE may be worthwhile depending on society's willingness to pay.

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