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Modelers typically use detailed simulation models and vary the fraction vaccinated to study outbreak control. However, there is currently no guidance for modelers on how much detail (i.e., heterogeneity) is necessary and how large a population to simulate. We provide theoretical and numerical guidance for those decisions and also analyze the benefit of a faster public health response through a stochastic simulation model in the case of measles in the United States. Theoretically, we prove that the outbreak size converges as the simulation population increases and that the outbreaks are slightly larger with a heterogeneous community structure. We find that the simulated outbreak size is not sensitive to the size of the simulated population beyond a certain size. We also observe that in case of an outbreak, a faster public health response provides benefits similar to increased vaccination. Insights from this study can inform the control and elimination measures of the ongoing coronavirus disease (COVID-19) as measles has shown to have a similar structure to COVID-19.

A recent study showed that progestogen-only injectable hormonal contraception (POIHC) doubles the risk of HIV transmission. This may affect contraceptive use and HIV-related outcomes, if women switch away from POIHC. A deterministic compartmental model of individuals aged 15–49 distinguishing gender and HIV status was used to simulate various contraceptive use scenarios. We specifically tracked HIV prevalence, new infections, HIV-related deaths, vertical transmission, and births over a 15-year period for five African countries. Stopping POIHC use will result in a large increase in births and vertical transmission. Switching from POIHC to other contraceptives limits these increases while still improving HIV outcomes.

Objectives Herpes simplex virus-2 (HSV-2) and syphilis are associated with increased risk of HIV, highlighting the importance of understanding their transmission dynamics. In India, most studies of HSV-2 and syphilis incidence are in high-risk populations and may not accurately reflect infectious activity. In this study, we aim to define HSV-2/syphilis incidence and risk factors in a population sample. Methods We conducted a longitudinal population-based survey in Andhra Pradesh, India, in two rounds: 2004–2005 and 2010–2011. Sociodemographic and behavioural data were collected, and dried blood spots tested for HSV-2 and Treponema pallidum IgG. After calculating sexually transmitted infection (STI) incidence, associated factors were assessed using modified Poisson regression and within-couple transmission rates modelled using seroconcordance/discordance data. Results 12 617 adults participated at baseline with 8494 at follow-up. Incidence of HSV-2 and syphilis per 1000 person-years was 25.6 (95% CI 24.1 to 27.2) and 3.00 (95% CI 2.52 to 3.54). Incidence of HSV-2 was higher in women vs men (31.1 vs 20.2) and in rural vs urban residents (31.1 vs 19.0) (p

Background Contact tracing (CT) has rarely been used to improve HIV case-finding in sub-Saharan Africa because of concerns regarding privacy protection and possibly high costs.

Concurrent partnerships (CPs) can accelerate the transmission of HIV (and other sexually transmitted infections) in a population [1–4]. CPs have been described as the “key driver” of generalized HIV epidemics [5]. Long-term CPs (i.e., partnerships that overlap for months, possibly years) in particular, may play a crucial role in connecting the sexual networks that transmit HIV [6]. Despite a recent surge of interest in targeting CPs for HIV prevention [7], the evidence that they are an important risk factor of HIV transmission remains limited [8–12]. The lack of association between partnership concurrency and HIV infection in empirical investigations could in part be due to the poor quality of survey data on CPs. To estimate the extent of CPs, survey respondents are typically asked questions about their 3–5 most recent sexual partners, including the dates at first and last sex, as well as whether the relationship with a given partner is still ongoing. These questions are used to check whether relationship intervals overlap [13, 14]. Such data are potentially affected by large biases [15–19], but few studies have evaluated the impact of measurement errors on survey estimates of partnership concurrency [14, 20], particularly in sub-Saharan settings. Only Morris and O'Gorman [15] argued that “measurement errors introduce a slight positive bias in estimates of the prevalence of CPs, and a slight negative bias in the length of the overlap [between CPs]”. This pioneering study suffers from two major limitations however: first, it only considered the impact of date heaping and recall errors on survey reports of partnership dates, but it did not consider the likely hypothesis that partnership histories (on which estimates are based) may not be reliable; second, it hypothesized that reporting errors occurred at random among population members, in ways that are unrelated to parameters of partnership concurrency. If patterns of misreporting are associated with partnership duration (for example), biases in concurrency measurements are likely to be significantly larger than previously thought. We use sociocentric network data collected on Likoma (an island located in the northern region of Lake Malawi) to (i) assess the inter-partner reliability of partnership histories collected during sexual behaviors surveys, and (ii) test whether reliability varies with partnership duration and timing. In doing so, and contrary to Morris and O'Gorman's previous assessment, we show that biases in survey measurements of CPs are large and of unknown direction.

Chronic viral diseases such as human immunodeficiency virus (HIV) and hepatitis B virus (HBV) afflict millions of people worldwide. A key public health challenge in managing such diseases is identifying infected, asymptomatic individuals so that they can receive antiviral treatment. Such treatment can benefit both the treated individual (by improving quality and length of life) and the population as a whole (through reduced transmission). We develop a compartmental model of a chronic, treatable infectious disease and use it to evaluate the cost and effectiveness of different levels of screening and contact tracing. We show that: (1) the optimal strategy is to get infected individuals into treatment at the maximal rate until the incremental health benefits balance the incremental cost of controlling the disease; (2) as one reduces the disease prevalence by moving people into treatment (which decreases the chance that they will infect others), one should increase the level of contact tracing to compensate for the decreased effectiveness of screening; (3) as the disease becomes less prevalent, it is optimal to spend more per case identified; and (4) the relative mix of screening and contact tracing at any level of disease prevalence is such that the marginal efficiency of contact tracing (cost per infected person found) equals that of screening if possible (e.g., when capacity limitations are not binding). We also show how to determine the cost-effective equilibrium level of disease prevalence (among untreated individuals), and we develop an approximation of the path of the optimal prevalence over time. Using this, one can obtain a close approximation of the optimal solution without having to solve an optimal control problem. We apply our methods to an example of hepatitis B virus.

Contact tracing (also known as partner notification) is a primary means of controlling infectious diseases such as tuberculosis (TB), human immunodeficiency virus (HIV), and sexually transmitted diseases (STDs). However, little work has been done to determine the optimal level of investment in contact tracing. In this paper, we present a methodology for evaluating the appropriate level of investment in contact tracing. We develop and apply a simulation model of contact tracing and the spread of an infectious disease among a network of individuals in order to evaluate the cost and effectiveness of different levels of contact tracing. We show that contact tracing is likely to have diminishing returns to scale in investment: incremental investments in contact tracing yield diminishing reductions in disease prevalence. In conjunction with a cost-effectiveness threshold, we then determine the optimal amount that should be invested in contact tracing. We first assume that the only incremental disease control is contact tracing. We then extend the analysis to consider the optimal allocation of a budget between contact tracing and screening for exogenous infection, and between contact tracing and screening for endogenous infection. We discuss how a simulation model of this type, appropriately tailored, could be used as a policy tool for determining the appropriate level of investment in contact tracing for a specific disease in a specific population. We present an example application to contact tracing for chlamydia control.

Two common means of controlling infectious diseases are screening and contact tracing. Which should be used, and when? We consider the problem of determining the cheapest mix of screening and contact tracing necessary to achieve a desired endemic prevalence of a disease or to identify a specified number of cases. We perform a partial equilibrium analysis of small-scale interventions, assuming that prevalence is unaffected by the intervention; we develop a full equilibrium analysis where we compare the long-term cost of various combinations of screening and contact tracing needed to achieve a given equilibrium prevalence; and we solve the problem of minimizing the total costs of identifying and treating disease cases plus the cost of untreated disease cases. Our analysis provides several insights. First, contact tracing is only cost effective when prevalence is below a threshold value. This threshold depends on the relative cost per case found by screening versus contact tracing. Second, for a given contact tracing policy, the screening rate needed to achieve a given prevalence or identify a specified number of cases is a decreasing function of disease prevalence. As prevalence increases above the threshold (and contact tracing is discontinued), the screening rate jumps discontinuously to a higher level. Third, these qualitative results hold when we consider unchanged or changed prevalence, and short-term or long-term costs.

OBJECTIVE Young men who have sex with men (YMSM) in the United States have a high HIV incidence with substantial racial disparities that are poorly understood. We use a data-driven simulation model to understand the impact of network-level mechanisms and sexually transmitted infections on the spread of HIV among YMSM. METHODS We designed and parameterized a stochastic agent-based network simulation model using results of a longitudinal cohort study of YMSM in Chicago. Within this model, YMSM formed and dissolved partnerships over time, and partnership types were stratified by length of partnership, sex, and age of the partner. In each partnership, HIV, gonorrhea, and chlamydia could be transmitted. Counterfactual scenarios were run to examine drivers of HIV. RESULTS Over a 15-year simulation, the HIV epidemic among YMSM continued to rise, with Latino/white YMSM facing a steeper increase in the HIV burden compared with black YMSM. YMSM in partnerships with older MSM, in particular black YMSM with older black MSM, were at highest risk for HIV, and 1 infection prevented with an older partner would prevent 0.8 additional infections among YMSM. Additionally, racial disparities in HIV were driven by differences in the HIV prevalence of YMSM partners. Finally, of all HIV infections among YMSM, 14.6% were attributable to NG and CT infections. CONCLUSION Network-level mechanisms and sexually transmitted infections play a significant role in the spread of HIV and in racial disparities among YMSM. HIV prevention efforts should target YMSM across race, and interventions focusing on YMSM partnerships with older MSM might be highly effective.

Background: Empirical estimates of the female-to-male ratio of infections in generalized HIV epidemics in sub-Saharan Africa range from 1.31 in Zambia to 2.21 in Ivory Coast. Inequalities in the gender ratio of infections can arise because of differences in exposure (to HIV-positive partners), susceptibility (given exposure), and survival (once infected). Differences in susceptibility have to date received most attention, but neither the relatively high gender ratio of infections nor the heterogeneity in empirical estimates is fully understood. Objective: Demonstrate the relevance of partnership network attributes and sexual mixing patterns to gender differences in the exposure to HIV-positive partners and the gender ratio of infections. Methods: Agent-based simulation model built in NetLogo. Results: The female-to-male ratio of infections predicted by our model ranges from 1.13 to 1.75. Gender-asymmetric partnership concurrency, rapid partnership turnover, elevated partnership dissolution in female-positive serodiscordant couples, and lower partnership re-entry rates among HIV-positive women can produce (substantial) differences in the gender ratio of infections. Coital dilution and serosorting have modest moderating effects. Conclusions: Partnership network attributes and sexual mixing patterns can have a considerable effect on the gender ratio of HIV infections. We need to look beyond individual behavior and gender differences in biological susceptibility if we are to fully understand, and remedy, gender inequalities in HIV infection in generalized epidemics.

Recent studies found a substantial fraction of ‘extended high viremics’ among HIV-1 subtype C, the most common subtype in southern Africa. Extended high viremics are HIV infected individuals who maintain a high viral load for a longer time period than usual after the initial infection. They are more infectious during this period, and their infection progresses to full-blown AIDS and death much faster than usual. This study investigates the impact of extended high viremics on the spread of the HIV epidemic in South Africa. We develop a simple deterministic compartmental model for HIV infection that includes extended high viremics. As the available data on extended high viremics are limited, we parameterize this model using only the fraction of extended high viremics among new infections and the reduced life-span of extended high viremics. We find that without extended high viremics, the HIV prevalence in South Africa would have remained close to its 1990 level, instead of increasing to the current epidemic levels. We also find that the greater the fraction of extended high viremics among susceptibles, the greater the steady-state HIV prevalence and the more sensitive the steady-state prevalence is to the HIV transmission probability. These results suggest that extended high viremics have an impact on the HIV epidemic in South Africa; justify the need for comprehensive epidemiological studies since the current data is limited; and suggest that future models of HIV for southern Africa should explicitly model extended high viremics.

Objective Men who have sex with men (MSM) practice role segregation – insertive or receptive only sex positions instead of a versatile role - in several international settings where candidate biomedical HIV prevention interventions (e.g., circumcision, anal microbicide) will be tested. The effects of these position-specific interventions on HIV incidence are modeled. Materials and Methods We developed a deterministic compartmental model to predict HIV incidence among Indian MSM using data from 2003–2010. The model’s sex mixing matrix was derived from network data of Indian MSM (n = 4604). Our model captures changing distribution of sex roles over time. We modeled microbicide and circumcision efficacy on trials with heterosexuals. Results Increasing numbers of versatile MSM resulted in little change in HIV incidence over 20 years. Anal microbicides and circumcision would decrease the HIV prevalence at 10 years from 15.6% to 12.9% and 12.7% respectively. Anal microbicides would provide similar protection to circumcision at the population level despite lower modeled efficacy (54% and 60% risk reduction, respectively). Combination of the interventions were additive: in 5 years, the reduction in HIV prevalence of the combination (−3.2%) is almost the sum of their individual reductions in HIV prevalence (−1.8% and −1.7%). Conclusions MSM sex role segregation and mixing, unlike changes in the sex role distribution, may be important for evaluating HIV prevention interventions in international settings. Synergies between some position-specific prevention interventions such as circumcision and anal microbicides warrant further study.

Objective: The current Centers of Disease Control and Prevention (CDC) guidelines from 2006 recommend a one-time test for low-risk individuals and annual testing for those at high risk. These guidelines may not be aggressive enough, even for those at low risk of infection, due to the earlier initiation of HAART and a movement towards a testand-treat environment. We evaluated the optimal testing frequencies for various risk groups in comparison to the CDC recommendations. Methods: We build a deterministic mathematical model optimizing the tradeoff between the societal cost of testing and the benefits over a patient’s lifetime of earlier diagnosis. Results: Under a test-and-treat scenario with immediate initiation of HAART, the optimal testing frequency is every 2.4 years for low-risk (0.01% annual incidence) individuals; every 9 months for moderate risk (0.1% incidence) individuals; and every 3 months for high-risk (1.0% incidence) individuals. The incremental cost-effectiveness of the optimal policy is $36342/quality-adjusted life-years (QALY) for low-risk individuals and $45074/QALY for high-risk individuals compared with 20-year and annual testing, respectively. Conclusion: The current CDC guidelines for HIV testing are too conservative, and more frequent testing is cost-effective for all risk groups. 2013 Wolters Kluwer Health | Lippincott Williams & Wilkins AIDS 2013, 27:795‐801

Objectives: HIV status aware couples with at least one HIV positive partner are characterized by high separation and divorce rates. This phenomenon is often described as a corollary of couples HIV Testing and Counseling (HTC) that ought to be minimized. In this contribution, we demonstrate the implications of partnership dissolution in serodiscordant couples for the propagation of HIV. Methods: We develop a compartmental model to study epidemic outcomes of elevated partnership dissolution rates in serodiscordant couples and parameterize it with estimates from population-based data (Rakai, Uganda). Results: Via its effect on partnership dissolution, every percentage point increase in HIV status awareness reduces HIV incidence in monogamous populations by 0.27 percent for women and 0.63 percent for men. These effects are even larger when the assumption of monogamy can be relaxed, but are moderated by other behavior changes (e.g., increased condom use) in HIV status aware serodiscordant partnerships. When these behavior changes are taken into account, each percentage point increase in HIV status awareness reduces HIV incidence by 0.13 and 0.32 percent for women and men, respectively (assuming monogamy). The partnership dissolution effect exists because it decreases the fraction of serodiscordant couples in the population and prolongs the time that individuals spend outside partnerships. Conclusion: Our model predicts that elevated partnership dissolution rates in HIV status aware serodiscordant couples reduce the spread of HIV. As a consequence, the full impact of couples HTC for HIV prevention is probably larger than recognized to date. Particularly high partnership dissolution rates in female positive serodiscordant couples contribute to the gender imbalance in HIV infections.

OBJECTIVE: To build a deterministic compartmental model for exploring the effects on the transmission of human immunodeficiency virus (HIV) of a population abstaining from sex or practising only "safe" sex for one month each year. METHODS: A model of HIV transmission was built to simulate the effects of the intervention (i.e. an annual no-sex or safe-sex month in which no transmission occurred) in three countries, under several optimistic assumptions. The reduction in the modelled annual incidence of transmission that was attributable to this "test" intervention was compared with that seen with an alternative intervention. In the latter, monthly incidences of transmission were each reduced by one twelfth, so that, essentially, the month-long interruption was spread evenly across a full year. FINDINGS: Over the first modelled year, the test intervention averted only 2.5% (Kenya), 3.3% (South Africa) and 1.6% (Swaziland) more HIV infections than the alternative interruption. According to the model, if the test intervention were repeated each January, it would avert only 2% (Kenya), 2% (South Africa) and 1% (Swaziland) more HIV infections over 5 years than the alternative intervention. CONCLUSION: Although it did not appear markedly more effective than the alternative intervention, the test intervention may still be more feasible and therefore worthwhile. Before the test intervention can be recommended, the cost-effectiveness and feasibility of such an annual month-long break in HIV transmission need to be assessed and compared with those of other interventions that may reduce new HIV infections, such as circumcision and concurrency-reduction campaigns.

While ART has been studied for years, the specific quantitative implementation details have not. In order for this new scheme of radiation therapy (RT) to reach its potential, an effective ART treatment planning strategy capable of taking into account the dose delivery history and the patient's on-treatment geometric model must be in place. This paper performs a theoretical study of dynamic closed-loop control algorithms for ART and compares their utility with data from phantom and clinical cases. We developed two classes of algorithms: those Adapting to Changing Geometry and those Adapting to Geometry and Delivered Dose. The former class takes into account organ deformations found just before treatment. The latter class optimizes the dose distribution accumulated over the entire course of treatment by adapting at each fraction, not only to the information just before treatment about organ deformations but also to the dose delivery history. We showcase two algorithms in the class of those Adapting to Geometry and Delivered Dose. A comparison of the approaches indicates that certain closed-loop ART algorithms may significantly improve the current practice. We anticipate that improvements in imaging, dose verification and reporting will further increase the importance of adaptive algorithms.

Purpose: While ART has been studied for years, the specific quantitative implementation details have not. In order for this new scheme of radiation therapy to reach its potential, an effective ART planning strategy capable of taking into account the dosedelivery history and patient's on‐treatment geometric model must be in place. This work performs a study of dynamic closed‐loop control algorithms for ART and demonstrates their utilities with data from phantom and clinical cases with on‐treatment cone‐beam CTimages.Method: In closed‐loop control, the controller is not run just once but repeatedly, each time receiving the current state of the system as its input. To meet the requirements of different clinical applications, two classes of algorithms are developed: those Adapting to Changing Geometry (ACG) and those Adapting to Geometry and DeliveredDose (AGDD). The former takes into account organ deformations found just before treatment. The latter optimizes the dose distribution accumulated over the entire course of treatment by adapting at each fraction not only to the anatomic information just before treatment but also to the dosedelivery history. The closed‐loop algorithms are showcased by phantom and clinical cases. Results: A comparison of the approaches with conventional open‐loop IMRT without adaptively incorporating feedback information indicates that closed‐loop ART may significantly improve the current practice. In both phantom and clinical studies, AGDD outperforms ACG algorithms in three aspects: target dose coverage, sensitive‐structure sparing, and steeper gradients around the tumor. Within the AGDD formalism, it is beneficial not to correct all the previous dosimetric errors at once right after the information is available but over a number of fractions until next set of feedback data is available. Conclusion:ART with closed‐loop dynamic algorithms substantially improve the dose distribution. In addition, the differing performance of the specific implementations shows that the algorithmic details matter.