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Persistence of Passive Immunity, Natural Immunity (and Vaccination)
Published in Leonhard Held, Niel Hens, Philip O’Neill, Jacco Wallinga, Handbook of Infectious Disease Data Analysis, 2019
Amy K. Winter, C. Jessica E. Metcalf
To move from modeling the probability of being infected over age to considering the dynamical underpinnings of this pattern, we focus on settings with no vaccination. The force of infection, , is defined as the rate at which susceptible individuals become infected. Because indicates the probability of being infected before age , and immune status is never lost, by analogy with survival analysis [34], the relationship between seropositivity and the force of infection is given by where the bracketed term in indicates that we are allowing the force of infection to vary over age (other covariates could also be encompassed [18]) after maternal immunity has waned (). Here the lower margin of the integral can be set to 6 months, 9 months, or 1 year of age to exclude individuals with maternal antibodies, as described previously. Since the term can be interpreted as the age specific hazard of infection, is the cumulative hazard by age . It follows that the force of infection by age, , can be calculated from the proportion seropositive by age, following where the acute marker indicates the first derivative. For cases where is fitted using a logit function, we can express the estimated force of infection as see [18] for other link functions. Importantly, this does not necessarily constrain estimates of to be positive [18], and this must be considered carefully in the analysis. Various additional approaches to constrain estimates of the force of infection to be positive exist, and are further detailed in [18], illustrated in the Supplement.
The potential clinical impact of implementing different COVID-19 boosters in fall 2022 in the United States
Published in Journal of Medical Economics, 2022
Michele A. Kohli, Michael Maschio, Amy Lee, Kelly Fust, Nicolas Van de Velde, Philip O. Buck, Milton C. Weinstein
All individuals start in the susceptible (S) compartments and move through to the recovered (R) compartments as they develop an infection followed by natural immunity. The force of infection, which is indicated by arrows in the model figure, is a function of effective contact between the susceptible and infected people. This rate is dictated by an age-specific contact matrix, which is modified by reduction in social mobility and masking behavior, and transmissibility of the virus. Vaccination also acts to reduce the force of infection. The model was calibrated between 31 January 2020 to 31 May 2022 to match all infections as estimated by the Institute for Health Metrics Evaluation (IHME) by varying the transmissibility parameter11. This process gave us an estimate of the number of people who had natural immunity and the average vaccine effectiveness (VE) for the proportions of the population in each of the vaccination strata, by age group in June 2022. All fixed model parameters and a more detailed description of the calibration process are described in the Technical Appendix.
Economic evaluation using dynamic transition modeling of ebola virus vaccination in lower-and-middle-income countries
Published in Journal of Medical Economics, 2021
Mavis Obeng-Kusi, Magdiel A. Habila, Denise J. Roe, Brian Erstad, Ivo Abraham
The transmission rate is crucial to the cost-effectiveness of a vaccine, and this was evidenced also in the one-way sensitivity analyses in our model. The force of infection, a measure of the rate at which susceptible individuals in a population contract the disease and a parameter-dependent also on the transmission rate of the disease, drives infectious disease outbreaks42. Another driver of cost-effectiveness revealed in our analyses is the cost of screening. With the highly fatal nature of EVD and the potential for spread within the population at risk, screening is critical for infection prevention and control43,44. In the light of this, our model accounted for daily screening of all persons living in the population during the assessment duration. The impact in our model attributed to the cost of screening could be caused by the cumulative cost of this daily testing routine, which depending on the affected country’s protocol, may differ from one population to another.
The clinical use of parvovirus B19 assays: recent advances
Published in Expert Review of Molecular Diagnostics, 2018
In most epidemiological settings, considering the presence of specific IgG as the marker of occurred infection, the highest force of infection occurs before age of 20, reaching a prevalence of about 60% in the population aged 20–30 years. Infection can occur until elder ages, reaching maximal prevalence values higher than 80%, and data fitting epidemiological models indicate the best scenarios allowing for waning immunity at an age-specific rate over the maintenance of lifelong immunity, assuming that the transmission rates are directly proportional to the contact rates. The main route of transmission of the virus is through the respiratory system, estimated overall R0 values are ~ 2.4, and duration of contacts is the main determinant of transmission, so that prolonged contacts as in the household and community settings are especially effective in transmission. In temperate climate countries, circulation of the virus is higher in the spring/early summer months, and epidemic cycles are reported to occur. For sophisticated epidemiological models and related data, see [13–15]. The virus can be transmitted from mother to fetus posing a risk of fetal damage that should prompt for an antenatal assessment of risk of fetal infections and diagnostic attention towards the development of intrauterine infections (see [16–18] for recent reviews). Finally, due to a viremic phase with high viral load, there is a risk of iatrogenic transmission of the virus via blood and blood-derived products, implying blood and blood product safety issues (see [19,20] for recent reviews).