Individual-based Microsimulation Model Research Articles

Evaluating Policies to Decrease the Risk of Introducing SARS-CoV-2 Infections to Nursing Home Facilities.

We used an individual-based microsimulation model of North Carolina to determine what facility-level policies would result in the greatest reduction in the number of individuals with SARS-CoV-2 entering the nursing home environment from 12/15/2021 to 1/3/2022 (e.g., Omicron variant surge). On average, there were 14,287 (Credible Interval [CI]: 13,477-15,147) daily visitors and 17,168 (CI: 16,571-17,768) HCW coming from the community into 426 nursing home facilities. Policies requiring a negative rapid test or vaccinated status for visitors resulted in the greatest reduction in the number of individuals with SARS-CoV-2 infection entering the nursing home environment with a 29.6% (26.9%-32.0%) and 24.0% (CI: 22.2%-25.5%) reduction, respectively. Policies halving visits (21.2% [20.0%-28.2%]), requiring all vaccinated HCW to receive a booster (7.8% [CI: 7.4%-8.7%]), and limiting visitation to a primary visitor (6.5% [CI: 3.5%-9.7%]) reduced infectious contacts to a lesser degree.

Estimate of undetected severe acute respiratory coronavirus virus 2 (SARS-CoV-2) infection in acute-care hospital settings using an individual-based microsimulation model.

Current guidance states that asymptomatic screening for severe acute respiratory coronavirus virus 2 (SARS-CoV-2) prior to admission to an acute-care setting is at the facility's discretion. This study's objective was to estimate the number of undetected cases of SARS-CoV-2 admitted as inpatients under 4 testing approaches and varying assumptions. Individual-based microsimulation of 104 North Carolina acute-care hospitals. All simulated inpatient admissions to acute-care hospitals from December 15, 2021, to January 13, 2022 [ie, during the SARS-COV-2 ο (omicron) variant surge]. We simulated (1) only testing symptomatic patients, (2) 1-stage antigen testing with no confirmatory polymerase chain reaction (PCR) test, (3) 1-stage antigen testing with a confirmatory PCR for negative results, and (4) serial antigen screening (ie, repeat antigen test 2 days after a negative result). Over 1 month, there were 77,980 admissions: 13.7% for COVID-19, 4.3% with but not for COVID-19, and 82.0% for non-COVID-19 indications without current infection. Without asymptomatic screening, 1,089 (credible interval [CI], 946-1,253) total SARS-CoV-2 infections (7.72%) went undetected. With 1-stage antigen screening, 734 (CI, 638-845) asymptomatic infections (67.4%) were detected, with 1,277 false positives. With combined antigen and PCR screening, 1,007 (CI, 875-1,159) asymptomatic infections (92.5%) were detected, with 5,578 false positives. A serial antigen testing policy detected 973 (CI, 845-1,120) asymptomatic infections (89.4%), with 2,529 false positives. Serial antigen testing identified >85% of asymptomatic infections and resulted in fewer false positives with less cost per identified infection compared to combined antigen plus PCR testing.

Health impact of delayed implementation of cervical cancer screening programs in India: A modeling analysis.

India has the highest burden of cervical cancer in the world. To estimate the consequences of delaying implementation of organized cervical cancer screening, we projected the avertable burden of disease under different implementation scenarios of a screening program. We used an individual‐based microsimulation model of human papillomavirus (HPV) infection and cervical cancer calibrated to epidemiologic data from India to project age‐specific cancer incidence and mortality reductions associated with screening (once‐in‐a‐lifetime among women aged 30–34 years) with one‐visit visual inspection with acetic acid (VIA) and one‐ and two‐visit HPV DNA testing. We then applied these reductions to a population model to project the lifetime cervical cancer cases and deaths averted under different implementation scenarios taking place from 2017 to 2026: (1) immediate implementation of screening with currently available screening tests (one‐visit VIA, two‐visit HPV testing); (2) immediate implementation of screening with currently available screening tests, with a switch to point‐of‐care one‐visit HPV testing in 5 years; and (3) 5‐year delayed implementation of screening with current screening tests or point‐of‐care HPV testing. Immediate implementation of two‐visit HPV testing with a switch to one‐visit HPV testing averted 574,100 cases and 382,500 deaths over the lifetimes of 81.4 million 30‐ to 34‐year‐old women screened once between 2017 and 2026. Delayed implementation with a one‐visit HPV test averted 209,300 cases and 139,100 deaths. Delaying implementation of screening programs in high‐burden settings will result in substantial morbidity and mortality among women beyond the age for adolescent HPV vaccination.

A microsimulation model projecting the health care costs for resistance to antibacterial drugs in Sweden.

BackgroundPrevious studies have shown that increasing antibacterial resistance (ABR) globally will cause extensive morbidity, deaths and escalated health care costs.MethodsTo project economic consequences of resistance to antibacterial drugs for the Swedish health care sector, we used an individual-based microsimulation model, SESIM. Health care consumption was represented as increased numbers of hospital days, outpatient visits and contact tracing for individuals getting clinical infections or becoming asymptomatic carriers. The risk of contracting a resistant bacterium was calculated using the incidence of mandatorily notifiable ABR in Sweden.ResultsWe estimate accumulated additional health care costs attributable to notifiable ABR from 2018 until 2030 to EUR 406 million and EUR 1, 503 million until 2050. Until 2030 the largest proportion, more than EUR 247 million (EUR 958 million until 2050), was due to ESBL, followed by methicillin resistant Staphylococcus aureus, carbapenemase-producing Enterobacteriaceae, vancomycin-resistant Enterococci and penicillin non-susceptible Pneumococci which incurred costs of EUR 128 million (EUR 453 million, 2050), EUR 15 million (EUR 58 million, 2050), EUR 13 million (EUR 28 million, 2050) and EUR 2 million (EUR 6 million, 2050), respectively.ConclusionsProjections concerning the future costs of ABR can be used to guide priorities and distribution of limited health care resources. Our estimates imply that costs in Sweden will have doubled by 2030 and increased more than 4-fold by 2050 if present trends continue and infection control practices remain unchanged. Still, indirect societal costs and costs for non-notifiable resistance remain to be added.

Resources Required for Cervical Cancer Prevention in Low- and Middle-Income Countries.

BackgroundCervical cancer is the fourth leading cause of cancer death in women, with 85% of cases and deaths occurring in developing countries. While organized screening programs have reduced cervical cancer incidence in high-income countries through detection and treatment of precancerous lesions, the implementation of organized screening has not been effective in low-resource settings due to lack of infrastructure and limited budgets. Our objective was to estimate the cost of comprehensive primary and secondary cervical cancer prevention in low- and middle-income countries.Methods and FindingsWe performed a modeling analysis to estimate 1) for girls aged 10 years, the cost of 2-dose human papillomavirus (HPV) vaccination; and 2) for women aged 30 to 49 years, the cost of cervical cancer screening (with visual inspection with acetic acid (VIA), HPV testing, or cytology) and preventive treatment in 102 low- and middle-income countries from 2015 to 2024. We used an Excel-based costing and service utilization model to estimate financial costs (2013 US$) based on prevalence of HPV, prevalence of precancerous lesions, and screening test performance. Where epidemiologic data were unavailable, we extrapolated from settings with data using an individual-based microsimulation model of cervical carcinogenesis (calibrated to 20 settings) and multivariate regression. Total HPV vaccination costs ranged from US$8.6 billion to US$24.2 billion for all scenarios considered (immediate, 5-year, or 10-year roll-out; price per dose US$4.55-US$70 by country income level). The total cost of screening and preventive treatment ranged from US$5.1 billion (10-year roll-out, screening once at age 35 years) to US$42.3 billion (immediate roll-out, high intensity screening). Limitations of this analysis include the assumption of standardized protocols by country income level that did not account for the potential presence of multiple screening modalities or management strategies within a country, and extrapolation of cost and epidemiologic data to settings where data were limited.ConclusionsThe estimated cost of comprehensive cervical cancer prevention with 2-dose HPV vaccination of 10-year-old girls and screening of women aged 30 to 49 years ranges from US$13.7 billion to US$66.5 billion, depending on speed of roll-out, vaccine price per dose, and screening test and frequency. Findings demonstrate the substantial impact of vaccine price in middle-income countries that are not eligible for assistance from Gavi, the Vaccine Alliance. Replacing routine cytology with HPV-based screening may reduce total costs. Data on the health impact and relative cost-effectiveness of strategies are needed to determine the best value for public health dollars.

Required duration of mass ivermectin treatment for onchocerciasis elimination in Africa: a comparative modelling analysis.

BackgroundThe World Health Organization (WHO) has set ambitious targets for the elimination of onchocerciasis by 2020–2025 through mass ivermectin treatment. Two different mathematical models have assessed the feasibility of reaching this goal for different settings and treatment scenarios, namely the individual-based microsimulation model ONCHOSIM and the population-based deterministic model EPIONCHO. In this study, we harmonize some crucial assumptions and compare model predictions on common outputs.MethodsUsing a range of initial endemicity levels and treatment scenarios, we compared the models with respect to the following outcomes: 1) model-predicted trends in microfilarial (mf) prevalence and mean mf intensity during 25 years of (annual or biannual) mass ivermectin treatment; 2) treatment duration needed to bring mf prevalence below a provisional operational threshold for treatment interruption (pOTTIS, i.e. 1.4 %), and 3) treatment duration needed to drive the parasite population to local elimination, even in the absence of further interventions. Local elimination was judged by stochastic fade-out in ONCHOSIM and by reaching transmission breakpoints in EPIONCHO.ResultsONCHOSIM and EPIONCHO both predicted that in mesoendemic areas the pOTTIS can be reached with annual treatment, but that this strategy may be insufficient in very highly hyperendemic areas or would require prolonged continuation of treatment. For the lower endemicity levels explored, ONCHOSIM predicted that the time needed to reach the pOTTIS is longer than that needed to drive the parasite population to elimination, whereas for the higher endemicity levels the opposite was true. In EPIONCHO, the pOTTIS was reached consistently sooner than the breakpoint.ConclusionsThe operational thresholds proposed by APOC may have to be adjusted to adequately reflect differences in pre-control endemicities. Further comparative modelling work will be conducted to better understand the main causes of differences in model-predicted trends. This is a pre-requisite for guiding elimination programmes in Africa and refining operational criteria for stopping mass treatment.Electronic supplementary materialThe online version of this article (doi:10.1186/s13071-015-1159-9) contains supplementary material, which is available to authorized users.

PCN95 - A Multi-State Model of Metatstatic Colorectal Cancer

The aim of this study is to develop and validate a decision-analytic model describing the current course of disease, including treatment, in metastatic colorectal cancer. This baseline model will serve as the comparator in analyses of the (cost-) effectiveness of new treatment strategies. An individual-based micro-simulation model was constructed based on the disease states a patient may experience after a diagnosis of metastatic colorectal cancer. The states include first-line second-line and third-line treatment, as well as states of progression of disease after first-, second- or third-line, finally a death state is included. Time spent in each disease state was predicted using log-logistic, log-normal or weibull survival models, each dependent on a number of patient characteristics. All survival models and patient characteristics were based on patient-level data, provided by the CAIRO trial (NCT00312000). Two oncologists evaluated the model for face validity, the model was further validated by comparing various model outcomes with the original data, the national cancer registry and a population based study. There were no significant differences in patient and treatment characteristics, nor intermediate and overall survival estimates between the simulated and original patient-level data. External validation with national cancer registry data showed few differences in survival with the simulated data. Additionally the simulated survival did not significantly differ from the survival as recorded in a pilot oxaliplatin study of 119 patients who were observed in the same timeframe as the RCT. The micro-simulation decision model described in this article underwent an internal and external validation and can be used to evaluate new possibilities for research and treatment in metastatic colorectal cancer.

P3.227 A Comparison of Microsimulation and Deterministic Approaches to Modelling of Sexually Transmitted Infection Dynamics

BackgroundDeterministic models are widely used in simulating the potential effect of programmes for the prevention and treatment of HIV and other sexually transmitted infections (STIs). However, most deterministic models are...

The potential impact of RV144-like vaccines in rural South Africa: A study using the STDSIM microsimulation model

Background The only successful HIV vaccine trial to date is the RV144 trial of the ALVAC/AIDSVAX vaccine in Thailand, which showed an overall incidence reduction of 31%. Most cases were prevented in the first year, suggesting a rapidly waning efficacy. Here, we predict the population level impact and cost-effectiveness of practical implementation of such a vaccine in a setting of a generalised epidemic with high HIV prevalence and incidence. Methods We used STDSIM, an established individual-based microsimulation model, tailored to a rural South African area with a well-functioning HIV treatment and care programme. We estimated the impact of a single round of mass vaccination for everybody aged 15–49, as well as 5-year and 2-year re-vaccination strategies for young adults (aged 15–29). We calculated proportion of new infections prevented, cost-effectiveness indicators, and budget impact estimates of combined ART and vaccination programmes. Results A single round of mass vaccination with a RV144-like vaccine will have a limited impact, preventing only 9% or 5% of new infections after 10 years at 60% and 30% coverage levels, respectively. Revaccination strategies are highly cost-effective if vaccine prices can be kept below 150 US$/vaccine for 2-year revaccination strategies, and below 200 US$/vaccine for 5-year revaccination strategies. Net cost-savings through reduced need for HIV treatment and care occur when vaccine prices are kept below 75 US$/vaccine. These results are sensitive to alternative assumptions on the underlying sexual network, background prevention interventions, and individual's propensity and consistency to participate in the vaccination campaign. Discussion A modestly effective vaccine can be a cost-effective intervention in highly endemic settings. To predict the impact of vaccination strategies in other endemic situations, sufficient knowledge of the underlying sexual network, prevention and treatment interventions, and individual propensity and consistency to participate, is key. These issues are all best addressed in an individual-based microsimulation model.