Janneke C. M. Heijne

The Effects of Influenza Vaccination of Health Care Workers in Nursing Homes: Insights from a Mathematical Model

Background Annual influenza vaccination of institutional health care workers (HCWs) is advised in most Western countries, but adherence to this recommendation is generally low. Although protective effects of this intervention for nursing home patients have been demonstrated in some clinical trials, the exact relationship between increased vaccine uptake among HCWs and protection of patients remains unknown owing to variations between study designs, settings, intensity of influenza seasons, and failure to control all effect modifiers. Therefore, we use a mathematical model to estimate the effects of HCW vaccination in different scenarios and to identify a herd immunity threshold in a nursing home department. Methods and Findings We use a stochastic individual-based model with discrete time intervals to simulate influenza virus transmission in a 30-bed long-term care nursing home department. We simulate different levels of HCW vaccine uptake and study the effect on influenza virus attack rates among patients for different institutional and seasonal scenarios. Our model reveals a robust linear relationship between the number of HCWs vaccinated and the expected number of influenza virus infections among patients. In a realistic scenario, approximately 60% of influenza virus infections among patients can be prevented when the HCW vaccination rate increases from 0 to 1. A threshold for herd immunity is not detected. Due to stochastic variations, the differences in patient attack rates between departments are high and large outbreaks can occur for every level of HCW vaccine uptake. Conclusions The absence of herd immunity in nursing homes implies that vaccination of every additional HCW protects an additional fraction of patients. Because of large stochastic variations, results of small-sized clinical trials on the effects of HCW vaccination should be interpreted with great care. Moreover, the large variations in attack rates should be taken into account when designing future studies.

Enhanced Hygiene Measures and Norovirus Transmission during an Outbreak

Enhanced hygiene measures can reduce norovirus transmission potential by 85%.

Transmission dynamics of Chlamydia trachomatis affect the impact of screening programmes.

To assess the impact of screening programmes in reducing the prevalence of Chlamydia trachomatis, mathematical and computational models are used as a guideline for decision support. Unfortunately, large uncertainties exist about the parameters that determine the transmission dynamics of C. trachomatis. Here, we use a SEIRS (susceptible-exposed-infected-recovered-susceptible) model to critically analyze the turnover of C. trachomatis in a population and the impact of a screening programme. We perform a sensitivity analysis on the most important steps during an infection with C. trachomatis. Varying the fraction of the infections becoming symptomatic as well as the duration of the symptomatic period within the range of previously used parameter estimates has little effect on the transmission dynamics. However, uncertainties in the duration of temporary immunity and the asymptomatic period can result in large differences in the predicted impact of a screening programme. We therefore analyze previously published data on the persistence of asymptomatic C. trachomatis infection in women and estimate the mean duration of the asymptomatic period to be longer than anticipated so far, namely 433 days (95% CI: 420-447 days). Our study shows that a longer duration of the asymptomatic period results in a more pronounced impact of a screening programme. However, due to the slower turnover of the infection, a substantial reduction in prevalence can only be achieved after screening for several years or decades.

The role of reinfection and partner notification in the efficacy of Chlamydia screening programs.

Repeated Chlamydia trachomatis infections after treatment are common. One reason is reinfection from untreated partners in ongoing sexual partnerships. Mathematical models that are used to predict the impact of screening on reducing chlamydia prevalence often do not incorporate reinfection and might overestimate the expected impact. We describe a pair compartmental model that explicitly incorporates sexual partnership duration and reinfection. The pair model predicts a weaker impact of screening when compared directly with a model that does not accommodate partnerships. Effective management of sex partners to prevent reinfection might need to be strengthened in chlamydia control programs.

A Measles Epidemic Threshold in a Highly Vaccinated Population

Background Mass vaccination against measles has successfully lowered the incidence of the disease and has changed the epidemic pattern from a roughly biennial cycle to an irregular sequence of outbreaks. A possible explanation for this sequence of outbreaks is that the vaccinated population is protected by solid herd immunity. If so, we would expect to see the fraction of susceptible individuals remaining below an epidemic threshold. An alternative explanation is the occurrence of occasional localised lapses in herd immunity that allow for major outbreaks in areas with a low vaccine coverage. In that case, we would expect the fraction of susceptible individuals to exceed an epidemic threshold before outbreaks occur. These two explanations for the irregular sequence of measles outbreaks can be tested against observations of both the fraction of susceptible individuals and infection attack rates. Methods and Findings We have estimated both the fraction of susceptible individuals at the start of each epidemic year and the infection attack rates for each epidemic year in the Netherlands over a 28-y period. During this period the vaccine coverage averaged 93%, and there was no sustained measles transmission. Several measles outbreaks occurred in communities with low vaccine coverage, and these ended without intervention. We show that there is a clear threshold value for the fraction of susceptible individuals, below which only minor outbreaks occurred, and above which both minor and major outbreaks occurred. A precise, quantitative relationship exists between the fraction of susceptible individuals in excess of this threshold and the infection attack rate during the major outbreaks. Conclusion In populations with a high but heterogeneous vaccine coverage, measles transmission can be interrupted without establishing solid herd immunity. When infection is reintroduced, a major outbreak can occur in the communities with low vaccine coverage. During such a major outbreak, each additional susceptible individual in excess of the threshold is associated with almost two additional infections. This quantitative relationship offers potential for anticipating both the likelihood and size of future major outbreaks when measles transmission has been interrupted.

Transmission of Chlamydia trachomatis through sexual partnerships: a comparison between three individual-based models and empirical data

Chlamydia trachomatis is the most common bacterial sexually transmitted infection (STI) in many developed countries. The highest prevalence rates are found among young adults who have frequent partner change rates. Three published individual-based models have incorporated a detailed description of age-specific sexual behaviour in order to quantify the transmission of C. trachomatis in the population and to assess the impact of screening interventions. Owing to varying assumptions about sexual partnership formation and dissolution and the great uncertainty about critical parameters, such models show conflicting results about the impact of preventive interventions. Here, we perform a detailed evaluation of these models by comparing the partnership formation and dissolution dynamics with data from Natsal 2000, a population-based probability sample survey of sexual attitudes and lifestyles in Britain. The data also allow us to describe the dispersion of C. trachomatis infections as a function of sexual behaviour, using the Gini coefficient. We suggest that the Gini coefficient is a useful measure for calibrating infectious disease models that include risk structure and highlight the need to estimate this measure for other STIs.

Uptake of Regular Chlamydia Testing by U.S. Women: A Longitudinal Study

BACKGROUND Routine chlamydia screening is a recommended preventive intervention for sexually active women aged </=25 years in the U.S. but rates of regular uptake are not known. PURPOSE This study aimed to examine rates of annual chlamydia testing and factors associated with repeat testing in a population of U.S. women. METHODS Women aged 15-25 years at any time from January 1, 2002, to December 31, 2006 who were enrolled in 130 commercial health plans were included. Data relating to chlamydia tests were analyzed in 2009. Chlamydia testing rates (per 100 woman-years) by age and rates of repeated annual testing were estimated. Poisson regression was used to examine the effects of age and previous testing on further chlamydia testing within the observation period. RESULTS In total, 2,632,365 women were included. The chlamydia testing rate over the whole study period was 13.6 per 100 woman years after adjusting for age-specific sexual activity; 8.5 (95% CI=6.0, 12.3) per 100 woman-years in those aged 15 years; and 17.7 (95% CI=17.1, 18.9) in those aged 25 years. Among women enrolled for the entire 5-year study period, 25.9% had at least one test but only 0.1% had a chlamydia test every year. Women tested more than once and older women were more likely to be tested again in the observation period. CONCLUSIONS The low rates of regular annual chlamydia testing do not comply with national recommendations and would not be expected to have a major impact on the control of chlamydia infection at the population level.

Timing of progression from Chlamydia trachomatis infection to pelvic inflammatory disease: a mathematical modelling study

BackgroundPelvic inflammatory disease (PID) results from the ascending spread of microorganisms from the vagina and endocervix to the upper genital tract. PID can lead to infertility, ectopic pregnancy and chronic pelvic pain. The timing of development of PID after the sexually transmitted bacterial infection Chlamydia trachomatis (chlamydia) might affect the impact of screening interventions, but is currently unknown. This study investigates three hypothetical processes for the timing of progression: at the start, at the end, or throughout the duration of chlamydia infection.MethodsWe develop a compartmental model that describes the trial structure of a published randomised controlled trial (RCT) and allows each of the three processes to be examined using the same model structure. The RCT estimated the effect of a single chlamydia screening test on the cumulative incidence of PID up to one year later. The fraction of chlamydia infected women who progress to PID is obtained for each hypothetical process by the maximum likelihood method using the results of the RCT.ResultsThe predicted cumulative incidence of PID cases from all causes after one year depends on the fraction of chlamydia infected women that progresses to PID and on the type of progression. Progression at a constant rate from a chlamydia infection to PID or at the end of the infection was compatible with the findings of the RCT. The corresponding estimated fraction of chlamydia infected women that develops PID is 10% (95% confidence interval 7-13%) in both processes.ConclusionsThe findings of this study suggest that clinical PID can occur throughout the course of a chlamydia infection, which will leave a window of opportunity for screening to prevent PID.

Describing the progression from Chlamydia trachomatis and Neisseria gonorrhoeae to pelvic inflammatory disease: systematic review of mathematical modeling studies.

Background: Chlamydia screening is recommended to prevent pelvic inflammatory disease (PID). A systematic review was conducted to determine how the natural history of Chlamydia trachomatis or Neisseria gonorrhoeae infection and progression to PID have been described in mathematical modeling studies. Methods: Four databases, from their earliest dates to October 2009, and reference lists of included studies were searched. Models were defined as dynamic if progression from infection to PID was time dependent and static otherwise. Descriptions of the natural history of infection and parameter values used for progression to PID were extracted from all studies. Details of how disease progression was implemented were extracted from reports of dynamic models. Results: Forty-five publications from 40 unique models were included. Nine models were classed as dynamic, including 4 Markov, 3 compartmental, and 2 individual-based models. There were 28 static decision analysis models. For 3 publications, the model type could not be determined. Among the dynamic models, there were explicit statements that C. trachomatis could progress to PID uniformly throughout the infection, in the first 6 months of infection, in the second half of infection, or that there is a most likely interval from the initial infection for the development of PID, which varies from 1 to 12 months. In static models, the average fraction of cases of chlamydia developing PID was 22%. Conclusion: The reporting of key items in mathematical modeling studies about PID could be improved. The potential timings of progression to PID identified in this review can be investigated further to advance our understanding about how chlamydia screening interventions work to prevent PID.

Individual and Population Level Effects of Partner Notification for Chlamydia trachomatis

Partner notification (PN or contact tracing) is an important aspect of treating bacterial sexually transmitted infections (STIs), such as Chlamydia trachomatis. It facilitates the identification of new infected cases that can be treated through individual case management. PN also acts indirectly by limiting onward transmission in the general population. However, the impact of PN, both at the level of individuals and the population, remains unclear. Since it is difficult to study the effects of PN empirically, mathematical and computational models are useful tools for investigating its potential as a public health intervention. To this end, we developed an individual-based modeling framework called Rstisim. It allows the implementation of different models of STI transmission with various levels of complexity and the reconstruction of the complete dynamic sexual partnership network over any time period. A key feature of this framework is that we can trace an individual’s partnership history in detail and investigate the outcome of different PN strategies for C. trachomatis. For individual case management, the results suggest that notifying three or more partners from the preceding 18 months yields substantial numbers of new cases. In contrast, the successful treatment of current partners is most important for preventing re-infection of index cases and reducing further transmission of C. trachomatis at the population level. The findings of this study demonstrate the difference between individual and population level outcomes of public health interventions for STIs.