Effectiveness of a COVID-19 contact tracing app in a simulation model with indirect and informal contact tracing.

During the COVID-19 pandemic, contact tracing was used to identify individuals who had been in contact with a confirmed case so that these contacted individuals could be tested and quarantined to prevent further spread of the SARS-CoV-2 virus. Many countries developed mobile apps to find these contacted individuals faster. We evaluate the epidemiological effectiveness of the Dutch app CoronaMelder, where we measure effectiveness as the reduction of the reproduction number R. To this end, we use a simulation model of SARS-CoV-2 spread and contact tracing, informed by data collected during the study period (December 2020 - March 2021) in the Netherlands. We show that the tracing app caused a clear but small reduction of the reproduction number, and the magnitude of the effect was found to be robust in sensitivity analyses. The app could have been more effective if more people had used it, and if notification of contacts could have been done directly by the user and thus reducing the time intervals between symptom onset and reporting of contacts. The model has two innovative aspects: i) it accounts for the clustered nature of social networks and ii) cases can alert their contacts informally without involvement of health authorities or the tracing app.

Prevalence and Severity of Symptoms 3 Months After Infection With SARS-CoV-2 Compared to Test-Negative and Population Controls in the Netherlands.

BACKGROUND: This prospective study assesses symptoms 3 months after severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection compared to test-negative and population controls, and the effect of vaccination prior to infection. METHODS: Participants enrolled after a positive (cases) or negative (test-negative controls) SARS-CoV-2 test, or after invitation from the general population (population controls). After 3 months, participants indicated presence of 41 symptoms and severity of 4 symptoms. Permutation tests were used to select symptoms significantly elevated in cases compared to controls and to compare symptoms between cases that were vaccinated or unvaccinated prior to infection. RESULTS: In total, 9166 cases, 1698 symptomatic but test-negative controls, and 3708 population controls enrolled. At 3 months, 13 symptoms, and severity of fatigue, cognitive impairment, and dyspnea were significantly elevated incases compared to controls. Of cases, 48.5% reported ≥1 significantly elevated symptom compared to 29.8% of test-negative controls and 26.0% of population controls. Effect of vaccination could be determined for cases aged <65 years, and was significantly protective for loss of smell and taste but not for other symptoms. DISCUSSION: Three months after SARS-CoV-2 infection, almost half of cases report symptoms, which was higher than background prevalence and test-negative prevalence. Vaccination prior to infection was protective against loss of smell and taste in cases aged <65 years.

A scenario modelling analysis to anticipate the impact of COVID-19 vaccination in adolescents and children on disease outcomes in the Netherlands, summer 2021.

BackgroundSince the roll-out of COVID-19 vaccines in late 2020 and throughout 2021, European governments have relied on mathematical modelling to inform policy decisions about COVID-19 vaccination.AimWe present a scenario-based modelling analysis in the Netherlands during summer 2021, to inform whether to extend vaccination to adolescents (12-17-year-olds) and children (5-11-year-olds).MethodsWe developed a deterministic, age-structured susceptible-exposed-infectious-recovered (SEIR) model and compared modelled incidences of infections, hospital and intensive care admissions, and deaths per 100,000 people across vaccination scenarios, before the emergence of the Omicron variant.ResultsOur model projections showed that, on average, upon the release of all non-pharmaceutical control measures on 1 November 2021, a large COVID-19 wave may occur in winter 2021/22, followed by a smaller, second wave in spring 2022, regardless of the vaccination scenario. The model projected reductions in infections/severe disease outcomes when vaccination was extended to adolescents and further reductions when vaccination was extended to all people over 5 years-old. When examining projected disease outcomes by age group, individuals benefitting most from extending vaccination were adolescents and children themselves. We also observed reductions in disease outcomes in older age groups, particularly of parent age (30-49 years), when children and adolescents were vaccinated, suggesting some prevention of onward transmission from younger to older age groups.ConclusionsWhile our scenarios could not anticipate the emergence/consequences of SARS-CoV-2 Omicron variant, we illustrate how our approach can assist decision making. This could be useful when considering to provide booster doses or intervening against future infection waves.

COVID-19 Vaccination Intent and Belief that Vaccination Will End the Pandemic.

High vaccination coverage is considered to be key in dealing with the coronavirus disease (COVID-19) pandemic. However, vaccine hesitancy can limit uptake. We examined the specific coronavirus beliefs that persons have regarding COVID-19 and COVID-19 vaccines and to what extent these beliefs explain COVID-19 vaccination intentions. We conducted a survey among 4,033 residents of the Netherlands that examined COVID-19 vaccination intentions and various beliefs. Random forest regression analysis explained 76% of the variance in vaccination intentions. The strongest determinant in the model was the belief the COVID-19 crisis will only end if many persons get vaccinated. Other strong determinants were beliefs about safety of vaccines, specifically in relation to vaccine development and approval process; (social) benefits of vaccination; social norms regarding vaccination behavior; and effectiveness of vaccines. We propose to address these specific beliefs in communications about COVID-19 vaccinations to stimulate vaccine uptake.

Prevalence and determinants of persistent symptoms after infection with SARS-CoV-2: protocol for an observational cohort study (LongCOVID-study).

INTRODUCTION: A substantial proportion of individuals infected with severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), report persisting symptoms weeks and months following acute infection. Estimates on prevalence vary due to differences in study designs, populations, heterogeneity of symptoms and the way symptoms are measured. Common symptoms include fatigue, cognitive impairment and dyspnoea. However, knowledge regarding the nature and risk factors for developing persisting symptoms is still limited. Hence, in this study, we aim to determine the prevalence, severity, risk factors and impact on quality of life of persisting symptoms in the first year following acute SARS-CoV-2 infection. METHODS AND ANALYSIS: The LongCOVID-study is both a prospective and retrospective cohort study being conducted in the Netherlands, with a one year follow-up. Participants aged 5 years and above, with self-reported positive or negative tests for SARS-CoV-2 will be included in the study. The primary outcome is the prevalence and severity of persistent symptoms in participants that tested positive for SARS-CoV-2 compared with controls. Symptom severity will be assessed for fatigue (Checklist Individual Strength (CIS subscale fatigue severity)), pain (Rand-36/SF-36 subscale bodily pain), dyspnoea (Medical Research Council (mMRC)) and cognitive impairment (Cognitive Failure Questionnaire (CFQ)). Secondary outcomes include effect of vaccination prior to infection on persistent symptoms, loss of health-related quality of life (HRQoL) and risk factors for persisting symptoms following infection with SARS-CoV-2. ETHICS AND DISSEMINATION: The Utrecht Medical Ethics Committee (METC) declared in February 2021 that the Medical Research Involving Human Subjects Act (WMO) does not apply to this study (METC protocol number 21-124/C). Informed consent is required prior to participation in the study. Results of this study will be submitted for publication in a peer-reviewed journal.

Versatile lifestyles of Edwardsiella: Free-living, pathogen, and core bacterium of the aquatic resistome.

Edwardsiella species in aquatic environments exist either as individual planktonic cells or in communal biofilms. These organisms encounter multiple stresses, include changes in salinity, pH, temperature, and nutrients. Pathogenic species such as E. piscicida, can multiply within the fish hosts. Additionally, Edwardsiella species (E. tarda), can carry antibiotic resistance genes (ARGs) on chromosomes and/or plasmids, that can be transmitted to the microbiome via horizontal gene transfer. E. tarda serves as a core in the aquatic resistome. Edwardsiela uses molecular switches (RpoS and EsrB) to control gene expression for survival in different environments. We speculate that free-living Edwardsiella can transition to host-living and vice versa, using similar molecular switches. Understanding such transitions can help us understand how other similar aquatic bacteria switch from free-living to become pathogens. This knowledge can be used to devise ways to slow down the spread of ARGs and prevent disease outbreaks in aquaculture and clinical settings.

Modelling varicella vaccination - What does a lack of surge in herpes zoster incidence tell us about exogenous boosting?

BACKGROUND: For decades, assessments of the impact of universal varicella vaccination on the epidemiology of varicella and herpes zoster (HZ) have been made using mathematical modelling. Decreased virus circulation and the resulting diminished exogenous boosting have been predicted to lead to a surge in HZ incidence. Lately, the exogenous boosting hypothesis has been challenged due to a lack of an extensive surge in HZ incidence in countries with, by now long-standing universal varicella vaccination. METHODS: In a deterministic compartmental transmission model of varicella zoster virus disease, we model various levels and duration of protection from boosting to explore the impact of successful childhood varicella vaccination on HZ incidence. RESULTS: Considering total HZ incidence, lifelong and strong protection from boosting give a stable incidence of HZ for about 60 years followed by a decline, whereas lifelong intermediate protection leads to a decline. So does weak protection of intermediate duration. Full and short protection, lead to a small surge, while full and intermediate protection lead to the largest HZ surge. HZ incidence by age group show that total incidence is the result of opposing increasing and decreasing trends in the various age groups over time. CONCLUSIONS: The absence of an extensive surge in HZ incidence after varicella vaccination can, especially during the first 20-30 years, occur in either strong, intermediate or weak boosting scenarios. The impact seems to depend on an interplay of the protective level and duration of the protection in determining the basic reactivation rate and the proportion of the population that is susceptible at the start of vaccination. However, the picture depends on whether the entire population or specific age groups are observed.

Optimal vaccine allocation for COVID-19 in the Netherlands: A data-driven prioritization.

For the control of COVID-19, vaccination programmes provide a long-term solution. The amount of available vaccines is often limited, and thus it is crucial to determine the allocation strategy. While mathematical modelling approaches have been used to find an optimal distribution of vaccines, there is an excessively large number of possible allocation schemes to be simulated. Here, we propose an algorithm to find a near-optimal allocation scheme given an intervention objective such as minimization of new infections, hospitalizations, or deaths, where multiple vaccines are available. The proposed principle for allocating vaccines is to target subgroups with the largest reduction in the outcome of interest. We use an approximation method to reconstruct the age-specific transmission intensity (the next generation matrix), and express the expected impact of vaccinating each subgroup in terms of the observed incidence of infection and force of infection. The proposed approach is firstly evaluated with a simulated epidemic and then applied to the epidemiological data on COVID-19 in the Netherlands. Our results reveal how the optimal allocation depends on the objective of infection control. In the case of COVID-19, if we wish to minimize deaths, the optimal allocation strategy is not efficient for minimizing other outcomes, such as infections. In simulated epidemics, an allocation strategy optimized for an outcome outperforms other strategies such as the allocation from young to old, from old to young, and at random. Our simulations clarify that the current policy in the Netherlands (i.e., allocation from old to young) was concordant with the allocation scheme that minimizes deaths. The proposed method provides an optimal allocation scheme, given routine surveillance data that reflect ongoing transmissions. This approach to allocation is useful for providing plausible simulation scenarios for complex models, which give a more robust basis to determine intervention strategies.

Burkholderiaceae and Multidrug Resistance Genes Are Key Players in Resistome Development in a Germfree Soil Model.

Assembly of a resistome in parallel with the establishment of a microbial community is not well understood. Germfree models can reveal microbiota interactions and shed light on bacterial colonization and resistance development under antibiotic pressure. In this study, we exposed germfree soil (GS), GS with diluted nontreated soil (DS), and nontreated soil (NS) to various concentrations of tetracycline (TET) in a nongermfree environment for 10 weeks, followed by 2 weeks of exposure to water. High-throughput sequencing was used to profile bacterial communities and antibiotic resistance genes (ARGs) in the soils. The initial bacterial loads were found to shape the profiles of bacterial communities and the resistomes. GS and DS treated with TET and the same soils left untreated had similar profiles, whereas NS showed different profiles. Soils with the same initial bacterial loads had their profiles shifted by TET treatment. Multidrug resistance (MDR) genes were the most abundant ARG types in all soils, with multidrug efflux pump genes being the discriminatory ARGs in GS regardless of different TET treatments and in GS, DS, and NS after TET. Furthermore, MDR genes were significantly enriched by TET treatment. In contrast, tetracycline resistance genes were either absent or low in relative abundance. The family Burkholderiaceae was predominant in all soils (except in NS treated with water) and was positively selected for by TET treatment. Most importantly, Burkholderiaceae were the primary carrier of ARGs, including MDR genes. IMPORTANCE This is the first study to examine how resistomes develop and evolve using GS. GS can be used to study the colonization and establishment of bacterial communities under antibiotic selection. Surprisingly, MDR genes were the main ARGs detected in GS, and TET treatments did not positively select for specific tetracycline resistance genes. Additionally, Burkholderiaceae were the key bacterial hosts for MDR genes in the current GS model under the conditions investigated. These results show that the family Burkholderiaceae underpins the development of resistome and serves as a source of ARGs. The ease of establishment of Burkholderiaceae and MDR genes in soils has serious implications for human health, since these bacteria are versatile and ubiquitous in the environment.

Distribution of antibiotic resistance genes in the environment.

The prevalence of antibiotic resistant bacteria (ARB) and antibiotic resistance genes (ARGs) in the microbiome is a major public health concern globally. Many habitats in the environment are under threat due to excessive use of antibiotics and evolutionary changes occurring in the resistome. ARB and ARGs from farms, cities and hospitals, wastewater treatment plants (WWTPs) or as water runoffs, may accumulate in water, soil, and air. We present a global picture of the resistome by examining ARG-related papers retrieved from PubMed and published in the last 30 years (1990-2020). Natural Language Processing (NLP) was used to retrieve 496,640 papers, out of which 9374 passed the filtering test and were further analyzed to determine the distribution and diversity of ARG subtypes. The papers revealed seven major antibiotic families together with their respective ARG subtypes in different habitats on six continents. Asia, especially China, had the highest number of ARGs related papers compared to other countries/regions/continents. ARGs belonging to multidrug, glycopeptide, and ß-lactam families were the most common in reports from hospitals and sulfonamide and tetracycline families were common in reports from farms, WWTPs, water and soil. We also highlight the 'omics' tools used in resistome research, describe some factors that shape the development of resistome, and suggest future work needed to better understand the resistome. The goal was to show the global nature of ARB and ARGs in order to encourage collaborate research efforts aimed at reducing the negative impacts of antibiotic resistance on the One Health concept.

Introducing pre-exposure prophylaxis to prevent HIV acquisition among men who have sex with men in Sweden: insights from a mathematical pair formation model.

OBJECTIVES: Since 2017, the Public Health Agency of Sweden recommends that pre-exposure prophylaxis (PrEP) for HIV should be offered to high-risk individuals, in particular to men who have sex with men (MSM). The objective of this study is to develop a mathematical model investigating the effect of introducing PrEP to MSM in Sweden. DESIGN: A pair formation model, including steady and casual sex partners, is developed to study the impact of introducing PrEP. Two groups are included in the model: sexually high active MSM and sexually low active MSM. Three mixing assumptions between the groups are considered. SETTING: A gay-friendly MSM HIV/sexually transmitted infection testing clinic in Stockholm, Sweden. This clinic started offering PrEP to MSM in October 2018. PARTICIPANTS: The model is calibrated according to detailed sexual behaviour data gathered in 2015 among 403 MSM. RESULTS: By targeting sexually high active MSM, a PrEP coverage of 3.5% of the MSM population (10% of all high actives) would result in the long-term HIV prevalence to drop considerably (close to 0%). While targeting only low actives would require a PrEP coverage of 35% for a similar reduction. The main effect of PrEP is the reduced susceptibility, whereas the increased HIV testing rate (every third month) among PrEP users plays a lesser role. CONCLUSIONS: To create a multifaceted picture of the effects of interventions against HIV, we need models that include the different stages of HIV infection and real-world data on detailed sexual behaviour to calibrate the mathematical models. Our findings conclude that targeting HIV high-risk individuals, within HIV risk populations such as MSM, with PrEP programmes could greatly decrease the long-term HIV prevalence in Sweden. Therefore, risk stratification of individuals is of importance in PrEP implementation programmes, to ensure optimising the effect and cost-effectiveness of such programmes.

Trxlp, a thioredoxin-like effector from Edwardsiella piscicida inhibits cellular redox signaling and nuclear translocation of NF-κB.

Redox signaling and homeostasis are essential for cell survival and the immune response. Peroxiredoxin (Prx) modulates the level of H2O2 as a redox signal through H2O2 decomposition. The redox activity of thioredoxin (Trx) is required as a reducing equivalent to regenerate Prx. Edwardsiella piscicida is an opportunistic Gram-negative enteric pathogen that secretes a novel Trx-like effector protein, ETAE_2186 (Trxlp). Trxlp has unique structural properties compared with other Trx proteins. In enzymatic and binding assays, we confirmed Trxlp to be redox-inactive due to the low reactivity and flexibility of the resolving cysteine residue, C35, at the active site motif "31WCXXC35". We identified key residues near the active site that are critical for reactivity and flexibility of C35 by site-directed mutagenesis analysis. NMR titration experiment demonstrated prolong inhibitory interaction of Trxlp with Prx1 resulting in the repression of Prx1-mediated H2O2 decomposition leading to increased ROS accumulation in infected host cells. Increased ROS in turn prevented nuclear translocation of NF-κB and inhibition of NF-κB target genes, leading to bacterial survival and enhanced replication inside host cells. Targeting Trxlp-mediated virulence promises to attenuate E. piscicida infection.

Edwardsiella induces microtubule-severing in host epithelial cells.

Edwardsiella bacteria cause economic losses to a variety of commercially important fish globally. Human infections are rare and result in a gastroenteritis-like illness. Because these bacteria are evolutionarily related to other Enterobacteriaceae and the host cytoskeleton is a common target of enterics, we hypothesized that Edwardsiella may cause similar phenotypes. Here we use HeLa and Caco-2 infection models to show that microtubules are severed during the late infections. This microtubule alteration phenotype was not dependant on the type III or type VI secretion system (T3SS and T6SS) of the bacteria as ΔT3SS and ΔT6SS mutants of E. piscicida EIB202 and E. tarda ATCC15947 that lacks both also caused microtubule disassembly. Immunolocalization experiments showed the host katanin catalytic subunits A1 and A like 1 proteins at regions of microtubule severing, suggesting their involvement in the microtubule disassembly events. To identify bacterial components involved in this phenotype, we screened a 2,758 transposon library of E. piscicida EIB202 and found that 4 single mutations in the atpFHAGDC operon disrupted microtubule disassembly in HeLa cells. We then constructed three atp deletion mutants; they all could not disassemble host microtubules. This work provides the first clear evidence of host cytoskeletal alterations during Edwardsiella infections.

Edwardsiella piscicida: A versatile emerging pathogen of fish.

Edwardsiella piscicida is an Enterobacteriaceae that is abundant in water and causes food and waterborne infections in fish, animals, and humans. The bacterium causes Edwardsiellosis in farmed fish and can lead to severe economic losses in aquaculture worldwide. E. piscicida is an intracellular pathogen that can also cause systemic infection. Type III and type VI secretion systems are the bacterium's most lethal weapons against host defenses. It also possesses multi-antibiotic resistant genes and is selected and enriched in the environment due to the overuse of antibiotics. Therefore, the bacterium has great potential to contribute to the evolution of the resistome. All these properties have made this bacterium a perfect model to study bacteria virulence mechanisms and the spread of antimicrobial genes in the environment. We summarize recent advance in E. piscicida biology and provide insights into future research in virulence mechanisms, vaccine development and novel therapeutics.

A stochastic SIR network epidemic model with preventive dropping of edges.

A Markovian Susceptible [Formula: see text] Infectious [Formula: see text] Recovered (SIR) model is considered for the spread of an epidemic on a configuration model network, in which susceptible individuals may take preventive measures by dropping edges to infectious neighbours. An effective degree formulation of the model is used in conjunction with the theory of density dependent population processes to obtain a law of large numbers and a functional central limit theorem for the epidemic as the population size [Formula: see text], assuming that the degrees of individuals are bounded. A central limit theorem is conjectured for the final size of the epidemic. The results are obtained for both the Molloy-Reed (in which the degrees of individuals are deterministic) and Newman-Strogatz-Watts (in which the degrees of individuals are independent and identically distributed) versions of the configuration model. The two versions yield the same limiting deterministic model but the asymptotic variances in the central limit theorems are greater in the Newman-Strogatz-Watts version. The basic reproduction number [Formula: see text] and the process of susceptible individuals in the limiting deterministic model, for the model with dropping of edges, are the same as for a corresponding SIR model without dropping of edges but an increased recovery rate, though, when [Formula: see text], the probability of a major outbreak is greater in the model with dropping of edges. The results are specialised to the model without dropping of edges to yield conjectured central limit theorems for the final size of Markovian SIR epidemics on configuration-model networks, and for the size of the giant components of those networks. The theory is illustrated by numerical studies, which demonstrate that the asymptotic approximations are good, even for moderate N.

Individual preventive social distancing during an epidemic may have negative population-level outcomes.

The outbreak of an infectious disease in a human population can lead to individuals responding with preventive measures in an attempt to avoid getting infected. This leads to changes in contact patterns. However, as we show in this paper, rational behaviour at the individual level, such as social distancing from infectious contacts, may not always be beneficial for the population as a whole. We use epidemic network models to demonstrate the potential negative consequences at the population level. We take into account the social structure of the population through several network models. As the epidemic evolves, susceptible individuals may distance themselves from their infectious contacts. Some individuals replace their lost social connections by seeking new ties. If social distancing occurs at a high rate at the beginning of an epidemic, then this can prevent an outbreak from occurring. However, we show that moderate social distancing can worsen the disease outcome, both in the initial phase of an outbreak and the final epidemic size. Moreover, the same negative effect can arise in real-world networks. Our results suggest that one needs to be careful when targeting behavioural changes as they could potentially worsen the epidemic outcome. Furthermore, network structure crucially influences the way that individual-level measures impact the epidemic at the population level. These findings highlight the importance of careful analysis of preventive measures in epidemic models.

Who is the infector? Epidemic models with symptomatic and asymptomatic cases.

What role do asymptomatically infected individuals play in the transmission dynamics? There are many diseases, such as norovirus and influenza, where some infected hosts show symptoms of the disease while others are asymptomatically infected, i.e. do not show any symptoms. The current paper considers a class of epidemic models following an SEIR (Susceptible  →  Exposed  →  Infectious  →  Recovered) structure that allows for both symptomatic and asymptomatic cases. The following question is addressed: what fraction ρ of those individuals getting infected are infected by symptomatic (asymptomatic) cases? This is a more complicated question than the related question for the beginning of the epidemic: what fraction of the expected number of secondary cases of a typical newly infected individual, i.e. what fraction of the basic reproduction number R0, is caused by symptomatic individuals? The latter fraction only depends on the type-specific reproduction numbers, while the former fraction ρ also depends on timing and hence on the probabilistic distributions of latent and infectious periods of the two types (not only their means). Bounds on ρ are derived for the situation where these distributions (and even their means) are unknown. Special attention is given to the class of Markov models and the class of continuous-time Reed-Frost models as two classes of distribution functions for latent and infectious periods. We show how these two classes of models can exhibit very different behaviour.

Transcriptomic dissection of the horizontally acquired response regulator EsrB reveals its global regulatory roles in the physiological adaptation and activation of T3SS and the cognate effector repertoire in Edwardsiella piscicida during infection toward turbot.

Edwardsiella piscicida is the leading pathogen threatening worldwide aquaculture industries. The 2-component system (TCS) EsrA-EsrB is essential for the pathogenesis of this bacterium. However, little is known about the regulon and regulatory mechanism of EsrA-EsrB or about the factors that mediate the interaction of TCS with bacterial hosts. Here, our RNA-seq analysis indicated that EsrB strongly induces type III and type VI secretion systems (T3/T6SS) expression and that it modulates the expression of both physiology- and virulence-associated genes in E. piscicida grown in DMEM. EsrB binds directly to a highly conserved 18-bp DNA motif to regulate the expression of T3SS and other genes. EsrB/DMEM-activated genes include 3 known and 6 novel T3SS-dependent effectors. All these effector genes are highly induced by EsrB during the late stage of in vivo infection in fish. Furthermore, although in vivo colonization by the bacterium relies on EsrB and T3/T6SS expression, it does not require the expression of individual effectors other than EseJ. The mutant lacking these 9 effectors showed significant defects in in vivo colonization and virulence toward turbot, and, more importantly, a high level of protection against challenges by wild-type E. piscicida, suggesting that it may represent a promising live attenuated vaccine. Taken together, our data demonstrate that EsrB plays a global regulatory role in controlling physiologic responses and the expression of T3SS and its cognate effector genes. Our findings will facilitate further work on the mechanism of molecular pathogenesis of this bacterium during infection.

Gender asymmetry in concurrent partnerships and HIV prevalence.

The structure of the sexual network of a population plays an essential role in the transmission of HIV. Concurrent partnerships, i.e. partnerships that overlap in time, are important in determining this network structure. Men and women may differ in their concurrent behavior, e.g. in the case of polygyny where women are monogamous while men may have concurrent partnerships. Polygyny has been shown empirically to be negatively associated with HIV prevalence, but the epidemiological impacts of other forms of gender-asymmetric concurrency have not been formally explored. Here we investigate how gender asymmetry in concurrency, including polygyny, can affect the disease dynamics. We use a model for a dynamic network where individuals may have concurrent partners. The maximum possible number of simultaneous partnerships can differ for men and women, e.g. in the case of polygyny. We control for mean partnership duration, mean lifetime number of partners, mean degree, and sexually active lifespan. We assess the effects of gender asymmetry in concurrency on two epidemic phase quantities (R0 and the contribution of the acute HIV stage to R0) and on the endemic HIV prevalence. We find that gender asymmetry in concurrent partnerships is associated with lower levels of all three epidemiological quantities, especially in the polygynous case. This effect on disease transmission can be attributed to changes in network structure, where increasing asymmetry leads to decreasing network connectivity.

Dangerous connections: on binding site models of infectious disease dynamics.

We formulate models for the spread of infection on networks that are amenable to analysis in the large population limit. We distinguish three different levels: (1) binding sites, (2) individuals, and (3) the population. In the tradition of physiologically structured population models, the formulation starts on the individual level. Influences from the 'outside world' on an individual are captured by environmental variables. These environmental variables are population level quantities. A key characteristic of the network models is that individuals can be decomposed into a number of conditionally independent components: each individual has a fixed number of 'binding sites' for partners. The Markov chain dynamics of binding sites are described by only a few equations. In particular, individual-level probabilities are obtained from binding-site-level probabilities by combinatorics while population-level quantities are obtained by averaging over individuals in the population. Thus we are able to characterize population-level epidemiological quantities, such as [Formula: see text], r, the final size, and the endemic equilibrium, in terms of the corresponding variables.