Evaluating the Effectiveness of Targeted Public Health Control Strategies for  Chlamydia Transmission in Omaha,  Nebraska: A Mathematical Modeling  Approach

Islam, K. M.; Araz, Özgür M.

doi:10.4236/aid.2014.43021

Cited by 4 publications

(2 citation statements)

References 17 publications

(17 reference statements)

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“…Imposing a baseline annual screening rate of 35% [23] of the population, it follows that 𝑐 𝑏𝑎𝑠𝑒𝑙𝑖𝑛𝑒 = 0.0083 per week. Alternatively, if we consider intervention scenarios that increase the annual proportion of the population screened to 40%, 50% and 70%, we have that 𝑐 40 = 0.0098 per week, 𝑐 50 = 0.0133 per week, and 𝑐 70 = 0.0231 per week respectively.…”

Section: Methodsmentioning

confidence: 99%

The effect of screening on the health burden of chlamydia: An evaluation of compartmental models based on person-days of infection

Farrell,

Spolyar,

Greenhalgh

2023

Preprint

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Sexually transmitted diseases are detrimental to the health and economic well-being of society. Consequently, predicting impending outbreaks and identifying effective disease interventions through the use of epidemiological tools, such as compartmental models, is of the utmost importance. Unfortunately, traditional compartmental models, specifically the differential equation models attributed to the work of Kermack and McKendrick, require either a duration of infection that follows the exponential or Erlang distribution, despite the biological invalidity of such assumptions. As these assumptions negatively impact the quality of model predictions, alternative approaches are required that capture the variability in the duration of infection, along with its associated effects on the trajectory of disease, and in the evaluation of disease interventions. So, we apply an entirely new family of differential equation compartmental models based on the quantity, "person-days of infection," to predict the trajectory of a disease. Importantly, this new family of models can alternative duration of infection distributions. As proof of concept, we calibrate our model to recent trends of chlamydia incidence in the United States and utilize a general statistical distribution that features periodic hazard rates. We then evaluate how increasing sexually transmitted disease screening rates alter predictions of incidence and saves disability adjusted life-years over a 5-year horizon. Our findings illustrate that increasing the annual screening rate of chlamydia from 35% to 40%-70% would annually avert 6.1-40.3 incidence and 1.68-11.14 disability adjusted life-years per 1000 people. This suggests increasing the screening rate of sexually transmitted diseases in the United States would greatly aid in ongoing public health efforts to curtail the rising trends in preventable sexually transmitted diseases.

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Section: Methodsmentioning

confidence: 99%

The effect of screening on the health burden of chlamydia: An evaluation of compartmental models based on person-days of infection

Farrell,

Spolyar,

Greenhalgh

2023

Preprint

View full text Add to dashboard Cite

show abstract

“…Moreover, mathematical models provide a means to evaluate and optimize control strategies, allowing for quantitative predictions that can be empirically tested through randomized comparative trials [7].1. Furthermore, mathematical modeling has been used to evaluate the impact of public health strategies in optimizing the use of limited resources [8]. The models are then optimized to find the best allocation of resources, such as vaccines or quarantine measures, to minimize the spread and impact of the disease.…”

Section: A Mathematical Optimization Techniquesmentioning

confidence: 99%

Review of Mathematical Optimization and Statistics-based Techniques for Public Health Intervention in India: Balancing Efficiency, Resources, and Policy Goals

Goswami

2024

IJIRCST

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The purpose of this academic paper is to present a concise overview of using mathematical optimization and statistics-based methods for public health intervention in India. Through the systematic examination of data, these methods support the efficient use of resources and decision-making based on evidence that aligns with policy objectives. They are vital in addressing constraints related to limited resources and policy goals while maximizing intervention efficiency and effectiveness.

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An Analytic Framework for Effective Public Health Program Design Using Correctional Facilities

Araz

Cruz-Aponte

Wilson

et al. 2022

INFORMS Journal on Computing

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We present a decision analytic framework that uses a mathematical model of Chlamydia trachomatis transmission dynamics in two interacting populations using ordinary differential equations. A public health survey informs model parametrization, and analytical findings guide the computational design of the decision-making process. The potential impact of jail-based screen-treat (S-T) programs on community health outcomes is presented. Numerical experiments are conducted for a case study population to quantify the effect and evaluate the cost-effectiveness of considered interventions. Numerical experiments show the effectiveness of increased jail S-T rates on community cases when resources for a community S-T program stays constant. Although this effect decreases when higher S-T rates are in place, jail-based S-T programs are cost-effective relative to community-based programs. Summary of Contribution: Public health programs have been developed to control community-wide infectious diseases and to reduce prevalence of sexually transmitted diseases (STD). These programs can consist of screening and treatment of diseases and behavioral interventions. Public correctional facilities play an important role in operational execution of these public health programs. However, because of lack of capacity and resources, public health programs using correctional facilities are questioned by policy-makers in terms of their costs and benefits. In this article, we present an analytical framework using a computational epidemiology model for supporting public health policy making. The system represents the dynamics of Chlamydia trachomatis transmission in two interacting populations, with an ordinary differential equations-based simulation model. The theoretical epidemic control conditions are derived and numerically tested, which guide the design of simulation experiments. Then cost-effectiveness of the potential policies is analyzed. We also present an extensive sensitivity analyses on model parameters. This study contributes to the computational epidemiology literature by presenting an analytical framework to guide effective simulation experimentation for policy decision making. The presented methodology can be applied to other complex policy and public health problems.

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Evaluating the Effectiveness of Targeted Public Health Control Strategies for Chlamydia Transmission in Omaha, Nebraska: A Mathematical Modeling Approach

Cited by 4 publications

References 17 publications

The effect of screening on the health burden of chlamydia: An evaluation of compartmental models based on person-days of infection

The effect of screening on the health burden of chlamydia: An evaluation of compartmental models based on person-days of infection

Review of Mathematical Optimization and Statistics-based Techniques for Public Health Intervention in India: Balancing Efficiency, Resources, and Policy Goals

An Analytic Framework for Effective Public Health Program Design Using Correctional Facilities

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