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We adopt a maximum-likelihood framework to estimate parameters of a stochastic susceptible-infected-recovered (SIR) model with contact tracing on a rooted random tree. Given the number of detectees per index case, our estimator allows to determine the degree distribution of the random tree as well as the tracing probability. Since we do not discover all infectees via contact tracing, this estimation is non-trivial. To keep things simple and stable, we develop an approximation suited for realistic situations (contract tracing probability small, or the probability for the detection of index cases small). In this approximation, the only epidemiological parameter entering the estimator is R . The estimator is tested in a simulation study and is furthermore applied to COVID-19 contact tracing data from India. The simulation study underlines the efficiency of the method. For the empirical COVID-19 data, we compare different degree distributions and perform a sensitivity analysis. We find that particularly a power-law and a negative binomial degree distribution fit the data well and that the tracing probability is rather large. The sensitivity analysis shows no strong dependency of the estimates on the reproduction number. Finally, we discuss the relevance of our findings.0 . The estimator is tested in a simulation study and is furthermore applied to COVID-19 contact tracing data from India. The simulation study underlines the efficiency of the method. For the empirical COVID-19 data, we compare different degree distributions and perform a sensitivity analysis. We find that particularly a power-law and a negative binomial degree distribution fit the data well and that the tracing probability is rather large. The sensitivity analysis shows no strong dependency of the estimates on the reproduction number. Finally, we discuss the relevance of our findings.

Background: Contact tracing (CT) is a key strategy when dealing with outbreaks of infectious diseases such as COVID-19. The scale of the COVID-19 pandemic has often left public health professionals (PHPs), who are responsible for the execution of CT, unable to keep up with the rapid and largescale spread of the virus. To enhance or support its execution, and potentially lower the workload for PHPs, citizens may be more actively involved in CT-tasks that are commonly executed by PHPs (referred to as 'self-led CT'). There is limited insight into citizens' perspectives on and needs for self-led CT for COVID-19. This study aims to explore the perspectives and needs of Dutch citizens on taking more responsibilities in the execution of CT for COVID-19, potentially through the use of digital tools., Methods: An exploratory qualitative study was performed, in which online semi-structured interviews were conducted. Questions were based on the Reasoned Action Approach and Health Belief Model. Interviews were audio-recorded and transcribed verbatim. A thematic analysis was conducted to identify citizens' perspectives and needs to participate in self-led CT., Results: We conducted 27 interviews with Dutch citizens. Seven main themes were identified from the interviews: 1) 'Citizens' perspectives on self-led CT are influenced by prior experiences with regular CT', 2) 'Citizens' felt responsibilities and the perceived responsibilities of the PHS in CT shape their perspectives on self-led CT', 3) 'Anticipated impacts of self-led CT on the CT-process', 4) 'Citizens' attitude towards the application of self-led CT depends on their own perceived skills and the willingness and skills of others', 5) 'Shame and social stigma may hamper participation in self-led CT', 6) 'Concerns about privacy and data security: a barrier for self-led CT', and 7) 'Citizens' perspectives and anticipated needs for the implementation and application of self-led CT in practice'., Conclusions: Most interviewees hold a positive attitude towards self-led CT and using digital tools for this purpose. However, their intention for self-led CT may depend on various factors, such as prior experiences with regular CT, and their perceived self-efficacy to participate. Perspectives and needs of citizens should be considered for the future implementation of self-led CT in practice., (© 2023. BioMed Central Ltd., part of Springer Nature.)

Background: Contact tracing (CT) is an important, but resource-intensive tool to control outbreaks of communicable diseases. Under pandemic circumstances, public health services may not have sufficient resources at their disposal to effectively facilitate CT. This may be addressed by giving cases and their contact persons more autonomy and responsibility in the execution of CT by public health professionals, through digital contact tracing support tools (DCTS-tools). However, the application of this approach has not yet been systematically investigated from the perspective of public health practice. Therefore, we investigated public health professionals' perspectives and needs regarding involving cases and contact persons in CT for COVID-19 through DCTS-tools., Methods: Between October 2020 and February 2021, we conducted online semi-structured interviews (N = 17) with Dutch public health professionals to explore their perspectives and needs regarding the involvement of cases and contact persons in CT for COVID-19 through DCTS-tools, in the contact identification, notification, and monitoring stages of the CT-process. Interviews were audio recorded and transcribed verbatim. A thematic analysis was performed., Results: Four main themes related to Dutch public health professionals' perspectives and needs regarding involving cases and contact persons in CT for COVID-19 through DCTS-tools emerged from the data: 'Distinct characteristics of CT with DCTS-tools'; 'Anticipated benefits and challenges of CT for COVID-19 with DCTS- tools'; 'Circumstances in CT for COVID-19 that permit or constrain the application of DCTS-tools'; and 'Public health professionals' needs regarding the development and application of DCTS-tools for CT'. Public health professionals seem to have a positive attitude towards involving cases and contact persons through DCTS-tools. Public health professionals' (positive) attitudes seem conditional on the circumstances under which CT is performed, and the fulfilment of their needs in the development and application of DCTS-tools., Conclusions: Dutch public health professionals seem positive towards involving cases and contact persons in CT for COVID-19 through DCTS-tools. Through adequate implementation of DCTS-tools in the CT-process, anticipated challenges can be overcome. Future research should investigate the perspectives and needs of cases and contact persons regarding DCTS-tools, and the application of DCTS-tools in practice., (© 2022. The Author(s).)

Objectives: Model impact of increasing screening and partner notification (PN) on chlamydia positivity., Methods: We used a stochastic simulation model describing pair formation and dissolution in an age-structured heterosexual population. The model accounts for steady, casual, and concurrent partnerships and a highly sexually active core group. The model used existing sexual behavior data from the United States and was validated using chlamydia positivity data from Region X (Alaska, Idaho, Oregon, Washington). A screening program with a coverage rate of 20% was implemented among women aged 15 to 24 years. After 10 years, we increased screening coverage to 35%, 50%, and 65% and partner treatment rates from 20% to 40% and 55%. Finally, we included male screening (aged 15-24, screening coverage: 20% and 35%, partner treatment: 25% and 40%). We analyzed the effects on chlamydia positivity in women and the frequency of reinfection 6 months after treatment., Results: The model described the decline in positivity observed from 1988 to 1997 in Region X, given screening coverage of 20% and a 25% partner treatment rate. Increasing screening coverage from 35% to 65% resulted in incremental decreases in positivity as did increasing the PN rate; a 23% reduction in positivity was achieved by either increasing screening by 3-fold or PN by 2-fold. Adding male screening to the program had less impact than increasing screening coverage or PN among women. Increased PN and treatment reduced reinfection rates considerably., Conclusions: Increasing efforts in PN may contribute at least as much to control of chlamydia infection as increasing screening coverage rates.

There are four major quantities that are measured in sexual behavior surveys that are thought to be especially relevant for the performance of sexual network models in terms of disease transmission. These are (i) the cumulative distribution of lifetime number of partners, (ii) the distribution of partnership durations, (iii) the distribution of gap lengths between partnerships, and (iv) the number of recent partners. Fitting a network model to these quantities as measured in sexual behavior surveys is expected to result in a good description of Chlamydia trachomatis transmission in terms of the heterogeneity of the distribution of infection in the population. Here we present a simulation model of a sexual contact network, in which we explored the role of behavioral heterogeneity of simulated individuals on the ability of the model to reproduce population-level sexual survey data from the Netherlands and UK. We find that a high level of heterogeneity in the ability of individuals to acquire and maintain (additional) partners strongly facilitates the ability of the model to accurately simulate the powerlaw-like distribution of the lifetime number of partners, and the age at which these partnerships were accumulated, as surveyed in actual sexual contact networks. Other sexual network features, such as the gap length between partnerships and the partnership duration, could-at the current level of detail of sexual survey data against which they were compared-be accurately modeled by a constant value (for transitional concurrency) and by exponential distributions (for partnership duration). Furthermore, we observe that epidemiological measures on disease prevalence in survey data can be used as a powerful tool for building accurate sexual contact networks, as these measures provide information on the level of mixing between individuals of different levels of sexual activity in the population, a parameter that is hard to acquire through surveying individuals.

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.

Nurses' contacts with potentially infectious persons probably place them at higher risk than the general population for infectious diseases. During an influenza pandemic, illness among nurses might result in staff shortage. We aimed to show the value of individual data from the healthcare sector for mathematical modeling of infectious disease transmission. Using a paper diary approach, we compared nurses' daily contacts (2-way conversation with >2 words or skin-to-skin contact) with those of matched controls from a representative population survey. Nurses (n = 129) reported a median of 40 contacts (85% work related), and controls (n = 129) reported 12 contacts (33% work related). For nurses, 51% of work-related contacts were with patients (74% involving skin-to-skin contact, and 63% lasted < or =15 minutes); 40% were with staff members (29% and 36%, respectively). Our data, used with simulation models, can help predict staff availability and provide information for pandemic preparedness planning.

The estimation of transmission parameters has been problematic for diseases that rely predominantly on transmission of pathogens from person to person through small infectious droplets. Age-specific transmission parameters determine how such respiratory agents will spread among different age groups in a human population. Estimating the values of these parameters is essential in planning an effective response to potentially devastating pandemics of smallpox or influenza and in designing control strategies for diseases such as measles or mumps. In this study, the authors estimated age-specific transmission parameters by augmenting infectious disease data with auxiliary data on self-reported numbers of conversational partners per person. They show that models that use transmission parameters based on these self-reported social contacts are better able to capture the observed patterns of infection of endemically circulating mumps, as well as observed patterns of spread of pandemic influenza. The estimated age-specific transmission parameters suggested that school-aged children and young adults will experience the highest incidence of infection and will contribute most to further spread of infections during the initial phase of an emerging respiratory-spread epidemic in a completely susceptible population. These findings have important implications for controlling future outbreaks of novel respiratory-spread infectious agents.

We present a stochastic model for the spread of smallpox after a small number of index cases are introduced into a susceptible population. The model describes a branching process for the spread of the infection and the effects of intervention measures. We discuss scenarios in which ring vaccination of direct contacts of infected persons is sufficient to contain an epidemic. Ring vaccination can be successful if infectious cases are rapidly diagnosed. However, because of the inherent stochastic nature of epidemic outbreaks, both the size and duration of contained outbreaks are highly variable. Intervention requirements depend on the basic reproduction number (R0), for which different estimates exist. When faced with the decision of whether to rely on ring vaccination, the public health community should be aware that an epidemic might take time to subside even for an eventually successful intervention strategy.

We consider a simple unstructured individual based stochastic epidemic model with contact tracing. Even in the onset of the epidemic, contact tracing implies that infected individuals do not act independent of each other. Nevertheless, it is possible to analyze the embedded non-stationary Galton-Watson process. Based upon this analysis, threshold theorems and also the probability for major outbreaks can be derived. Furthermore, it is possible to obtain a deterministic model that approximates the stochastic process, and in this way, to determine the prevalence of disease in the quasi-stationary state and to investigate the dynamics of the epidemic.

A combined sexual network and lifecourse perspective is proposed as a basis for reconstructing the sexological infrastructure of HIV dissemination. Necessary data are drawn from a representative sample survey of 1001 adults (age range 18-50 years) in the Netherlands. Heterosexual respondents' behavioural risk level, expressed in the number of unprotected sexual interconnections with primary and secondary partners, is found to be related to both age and relational status, though these variables cannot fully predict risk. While those under 24 years of age are over-represented in the larger components of sexual networks, above 32 years of age there is a small group who follow a lifestyle of regularly changing sexual partners.

Background: Published individual-based, dynamic sexual network modelling studies reach different conclusions about the population impact of screening for Chlamydia trachomatis. The objective of this study was to conduct a direct comparison of the effect of organised chlamydia screening in different models. Methods: Three models simulating population-level sexual behaviour, chlamydia transmission, screening and partner notification were used. Parameters describing a hypothetical annual opportunistic screening program in 16-24 year olds were standardised, whereas other parameters from the three original studies were retained. Model predictions of the change in chlamydia prevalence were compared under a range of scenarios. Results: Initial overall chlamydia prevalence rates were similar in women but not men and there were age and sex-specific differences between models. The number of screening tests carried out was comparable in all models but there were large differences in the predicted impact of screening. After 10 years of screening, the predicted reduction in chlamydia prevalence in women aged 16-44 years ranged from 4% to 85%. Screening men and women had a greater impact than screening women alone in all models. There were marked differences between models in assumptions about treatment seeking and sexual behaviour before the start of the screening intervention. Conclusions: Future models of chlamydia transmission should be fitted to both incidence and prevalence data. This meta-modelling study provides essential information for explaining differences between published studies and increasing the utility of individual-based chlamydia transmission models for policy making. [ABSTRACT FROM AUTHOR]