Modeling the impact of potential vaccines on epidemics of sexually transmitted chlamydia trachomatis infection

Background. We investigated the likely impact of vaccines on the prevalence of and morbidity due to Chlamydia trachomatis (chlamydia) infections in heterosexual populations. Methods.An individual‐based mathematical model of chlamydia transmission was developed and linked to the infection course in chlamydia‐infected individuals. The model describes the impact of a vaccine through its effect on the chlamydial load required to infect susceptible individuals (the “critical load”), the load in infected individuals, and their subsequent infectiousness. The model was calibrated using behavioral, biological, and clinical data. Results.A fully protective chlamydia vaccine administered before sexual debut can theoretically eliminate chlamydia epidemics within 20 years. Partially effective vaccines can still greatly reduce the incidence of chlamydia infection. Vaccines should aim primarily to increase the critical load in susceptible individuals and secondarily to decrease the peak load and/or the duration of infection in vaccinated individuals who become infected. Vaccinating both sexes has a beneficial impact on chlamydia‐related morbidity, but targeting women is more effective than targeting men. Conclusions.Our findings can be used in laboratory settings to evaluate vaccine candidates in animal models, by regulatory bodies in the promotion of candidates for clinical trials, and by public health authorities in deciding on optimal intervention strategies.

The new epidemics

In developed countries we once thought that the scourge of infectious diseases was tamed. Antibiotics were controlling infection in individual patients, vaccines were preventing illness and great faith was placed in the capacity of science to confound the most cunning organism. However, things have changed and in the new millennium we are confronting a host of challenges to public health from infectious diseases. Epidemics mean an excess of cases in the community from that normally expected or the appearance of a new infection (Webber ####, 22) Chapter 11 outlined the background to infectious diseases and the individual strategies directed towards the control and management of infectious diseases. The aim of this chapter is to outline the impact that infectious diseases have on population health, to identify the risks of major outbreaks and to identify the strategies required to reduce the risk and to manage any possible outbreak.

Synchrony of planting and proportions of susceptible varieties affect rice tungro disease epidemics in the Philippines.

Surveys were conducted in the Philippines from 1995 to 1997 to examine relationships between production environment variables (agroecosystem, synchrony of planting, and varieties planted) and the occurrence of rice tungro disease epidemics using correspondence analyses. The sites covered were Isabela, Nueva Ecija, North Cotabato, and Bohol provinces as well as Bicol region. Tungro disease incidence in farmers’ fields was assessed visually based on typical symptoms. In addition, leaf samples were collected from each field and indexed serologically by enzyme-linked immunosorbent assay for the presence of Rice tungro bacilliform (RTBV) and Rice tungro spherical (RTSV) viruses. Thus, relationships between the production environment variables and four disease variables — visual incidence and double RTBV and RTSV, single RTSV, and single RTBV infections — were examined. A higher association was observed between site and varieties planted as well as site and synchrony of planting than between site and agroecosystem or site and disease variables (visual incidence, double RTBV and RTSV and single RTSV infections). Disease variables depended on both varieties planted and synchrony of planting and correspondence analysis revealed that the low disease incidence in Nueva Ecija was associated with synchronous planting while the high disease incidence in Isabela was associated with the planting of susceptible varieties and asynchronous planting. Such findings suggest that the relationship between the last two factors at a given site is critical to predicting tungro occurrence. Moreover, correspondence analysis of the relationship among disease variables revealed that tungro incidence is associated with not only double RTBV and RTSV infections but also single RTSV infections. Implications of these results on tungro epidemiology and management are discussed.

Duty in the time of epidemics : what China and Zimbabwe teach us

In November 2002, a man with ‘atypical pneumonia’ treated in Foshan hospital, Guangdong Province, in the People's Republic of China, was the first known case of Severe Acute Respiratory Syndrome (SARS). However, it was not until April 2003 that the Chinese government admitted to the full scale of ‘atypical pneumonia’ cases infected with SARS, two months after the disease had rapidly spread across the world with initial infections in Hong Kong and Vietnam sourced to Guangdong. In 2008, Zimbabwe experienced one of the biggest outbreaks of cholera ever recorded. By February 2009, the disease had spread across all of Zimbabwe's 10 provinces and to neighbouring countries—Botswana, South Africa, Zambia and Mozambique—causing thousands of infections amongst their populations. This article seeks to examine what duties the Chinese and Zimbabwe states had to protect their citizens and the international community from these outbreaks. The article refers to the findings of the International Law Commission's study into the role of states and international organisations in protecting persons in the event of a disaster to consider whether there is an international duty to protect persons from epidemics. The article concludes that both cases reveal a growing concept of protection that entails an international duty to assist individuals when an affected state proves unwilling or unable to assist its own population in the event of a disease outbreak.

Using mathematical modelling to evaluate drivers and predict trajectories of HIV and STI epidemics in South East Asian and Australian populations

Objective To evaluate the potential impact of the current global economic crisis (GEC) on the spread of HIV. Design To evaluate the impact of the economic downturn we studied two distinct HIV epidemics in Southeast Asia: the generalized epidemic in Cambodia where incidence is declining and the epidemic in Papua New Guinea (PNG) which is in an expansion phase. Methods Major HIV-related risk factors that may change due to the GEC were identified and a dynamic mathematical transmission model was developed and used to forecast HIV prevalence, diagnoses, and incidence in Cambodia and PNG over the next 3 years. Results In Cambodia, the total numbers of HIV diagnoses are not expected to be largely affected. However, an estimated increase of up to 10% in incident cases of HIV, due to potential changes in behavior, may not be observed by the surveillance system. In PNG, HIV incidence and diagnoses could be more affected by the GEC, resulting in respective increases of up to 17% and 11% over the next 3 years. Decreases in VCT and education programs are the factors that may be of greatest concern in both settings. A reduction in the rollout of antiretroviral therapy could increase the number of AIDS-related deaths (by up to 7.5% after 3 years). Conclusions The GEC is likely to have a modest impact on HIV epidemics. However, there are plausible conditions under which the economic downturns can noticeably influence epidemic trends. This study highlights the high importance of maintaining funding for HIV programs.

Evaluation of the potential impact of the global economic crisis on HIV epidemics in Southeast Asia

Economic conditions around the world are likely to deteriorate in the short to medium term. The potential impact of this crisis on the spread of HIV is not clear. Government revenues and aid flows from international donors may face constraints, possibly leading to reductions in funding for HIV programs. Economic conditions (leading to increases in unemployment, for example) may also have an indirect impact on HIV epidemics by affecting the behaviour of individual people. Some behavioural changes may influence the rate of HIV transmission. This report presents findings from a study that investigates the potential impact of the economic crisis on HIV epidemics through the use of mathematical modelling. The potential epidemiological impacts of changes in the economy are explored for two distinctly characterised HIV epidemics: (i) a well-defined, established, and generalised HIV epidemic (specifically Cambodia, where incidence is declining); (ii) an HIV epidemic in its early expansion phase (specifically Papua New Guinea, where incidence has not yet peaked). Country-specific data are used for both settings and the models calibrated to accurately reflect the unique HIV epidemics in each population in terms of both incidence and prevalence. Models calibrated to describe the past and present epidemics are then used to forecast epidemic trajectories over the next few years under assumptions that behavioural or program conditions may change due to economic conditions. It should be noted that there are very limited solid data on how HIV/AIDS program funds may decrease or how social determinants related to HIV risk may change due to the economic crisis. Potential changes in key relevant factors were explored, along with sensitivity ranges around these assumptions, based on extensive discussions with in-country and international experts and stakeholders. As with all mathematical models, assumptions should be reviewed critically and results interpreted cautiously.

What impact might the economic crisis have on HIV epidemics in Southeast Asia?

Objective: To evaluate the potential impact of the current global economic crisis (GEC) on the spread of HIV. Design: To evaluate the impact of the economic downturn we studied two distinct HIV epidemics in Southeast Asia: the generalized epidemic in Cambodia where incidence is declining and the epidemic in Papua New Guinea (PNG) which is in an expansion phase. Methods: Major HIV-related risk factors that may change due to the GEC were identified and a dynamic mathematical transmission model was developed and used to forecast HIV prevalence, diagnoses, and incidence in Cambodia and PNG over the next 3 years. Results: In Cambodia, the total numbers of HIV diagnoses are not expected to be largely affected. However, an estimated increase of up to 10% in incident cases of HIV, due to potential changes in behavior, may not be observed by the surveillance system. In PNG, HIV incidence and diagnoses could be more affected by the GEC, resulting in respective increases of up to 17% and 11% over the next 3 years. Decreases in VCT and education programs are the factors that may be of greatest concern in both settings. A reduction in the rollout of antiretroviral therapy could increase the number of AIDS-related deaths (by up to 7.5% after 3 years). Conclusions: The GEC is likely to have a modest impact on HIV epidemics. However, there are plausible conditions under which the economic downturns can noticeably influence epidemic trends. This study highlights the high importance of maintaining funding for HIV programs.

Considerations for a social and geographical framework for agent-based epidemics

Understanding the dynamics of disease spread is of crucial importance, in contexts such as estimating load on medical services to risk assessment and intervention policies against large-scale epidemic outbreaks. However, most of the information is available after the spread itself, and preemptive assessment is far from trivial. Here, we investigate the use of agent-based simulations to model such outbreaks in a stylised urban environment. For most diseases, infection of a new individual may occur from casual contact in crowds as well as from repeated interactions with social partners such as work colleagues or family members. Our model therefore accounts for these two phenomena.Presented in this paper is the initial framework for such a model, detailing implementation of geographical features and generation of social structures. Preliminary results are a promising step towards large-scale simulations and evaluation of potential intervention policies.

Fusarium graminearum and Fusarium pseudograminearum caused the 2010 head blight epidemics in Australia

Wheat crops in southeast Queensland (Qld) and northern New South Wales (NSW) were infected with fusarium head blight (FHB)-like symptoms during the 201011 wheat growing season. Wheat crops in this region were surveyed at soft dough or early maturity stage to determine the distribution, severity, aetiology and toxigenicity of FHB. FHB was widespread on bread wheat and durum, and Fusarium graminearum and/or F.pseudograminearum were diagnosed from 42 of the 44 sites using species-specific PCR primers directly on spikelets or from monoconidial cultures obtained from spikelets. Stem base browning due to crown rot (CR) was also evident in some samples from both states. The overall FHB and CR severity was higher for NSW than Qld. Deoxynivalenol (DON) concentration of immature grains was more than 1 mg kg-1 in samples from 11 Qld and 14 NSW sites, but only 13 of 498 mature grain samples sourced from the affected areas had more than 1 mg kg-1 DON. DON concentration in straw also exceeded 1 mg kg-1 in eight Qld and all but one NSW sites but this was not linked to DON concentration of immature grains. The proportion of spikelets with positive diagnosis for F.graminearum and/or F.pseudograminearum and weather-related factors influenced DON levels in immature grains. The average monthly rainfall for AugustNovember during crop anthesis and maturation exceeded the long-term monthly average by 10150%. Weather played a critical role in FHB epidemics for Qld sites but this was not apparent for the NSW sites, as weather was generally favourable at all sites.

Stochastic analysis of epidemics on adaptive time varying networks

Many studies investigating the effect of human social connectivity structures (networks) and human behavioral adaptations on the spread of infectious diseases have assumed either a static connectivity structure or a network which adapts itself in response to the epidemic (adaptive networks). However, human social connections are inherently dynamic or time varying. Furthermore, the spread of many infectious diseases occur on a time scale comparable to the time scale of the evolving network structure. Here we aim to quantify the effect of human behavioral adaptations on the spread of asymptomatic infectious diseases on time varying networks. We perform a full stochastic analysis using a continuous time Markov chain approach for calculating the outbreak probability, mean epidemic duration, epidemic reemergence probability, etc. Additionally, we use mean-field theory for calculating epidemic thresholds. Theoretical predictions are verified using extensive simulations. Our studies have uncovered the existence of an ``adaptive threshold,'' i.e., when the ratio of susceptibility (or infectivity) rate to recovery rate is below the threshold value, adaptive behavior can prevent the epidemic. However, if it is above the threshold, no amount of behavioral adaptations can prevent the epidemic. Our analyses suggest that the interaction patterns of the infected population play a major role in sustaining the epidemic. Our results have implications on epidemic containment policies, as awareness campaigns and human behavioral responses can be effective only if the interaction levels of the infected populace are kept in check.

How to run a campaign: Optimal control of SIS and SIR information epidemics

Information spreading in a population can be modeled as an epidemic. Campaigners (e.g., election campaign managers, companies marketing products or movies) are interested in spreading a message by a given deadline, using limited resources. In this paper, we formulate the above situation as an optimal control problem and the solution (using Pontryagin's Maximum Principle) prescribes an optimal resource allocation over the time of the campaign. We consider two different scenarios-in the first, the campaigner can adjust a direct control (over time) which allows her to recruit individuals from the population (at some cost) to act as spreaders for the Susceptible-Infected-Susceptible (SIS) epidemic model. In the second case, we allow the campaigner to adjust the effective spreading rate by incentivizing the infected in the Susceptible-Infected-Recovered (SIR) model, in addition to the direct recruitment. We consider time varying information spreading rate in our formulation to model the changing interest level of individuals in the campaign, as the deadline is reached. In both the cases, we show the existence of a solution and its uniqueness for sufficiently small campaign deadlines. For the fixed spreading rate, we show the effectiveness of the optimal control strategy against the constant control strategy, a heuristic control strategy and no control. We show the sensitivity of the optimal control to the spreading rate profile when it is time varying. (C) 2014 Elsevier Inc. All rights reserved.

Optimal control of information epidemics modeled as Maki Thompson rumors

We model the spread of information in a homogeneously mixed population using the Maki Thompson rumor model. We formulate an optimal control problem, from the perspective of single campaigner, to maximize the spread of information when the campaign budget is fixed. Control signals, such as advertising in the mass media, attempt to convert ignorants and stiflers into spreaders. We show the existence of a solution to the optimal control problem when the campaigning incurs non-linear costs under the isoperimetric budget constraint. The solution employs Pontryagin's Minimum Principle and a modified version of forward backward sweep technique for numerical computation to accommodate the isoperimetric budget constraint. The techniques developed in this paper are general and can be applied to similar optimal control problems in other areas. We have allowed the spreading rate of the information epidemic to vary over the campaign duration to model practical situations when the interest level of the population in the subject of the campaign changes with time. The shape of the optimal control signal is studied for different model parameters and spreading rate profiles. We have also studied the variation of the optimal campaigning costs with respect to various model parameters. Results indicate that, for some model parameters, significant improvements can be achieved by the optimal strategy compared to the static control strategy. The static strategy respects the same budget constraint as the optimal strategy and has a constant value throughout the campaign horizon. This work finds application in election and social awareness campaigns, product advertising, movie promotion and crowdfunding campaigns. (C) 2014 Elsevier B.V. All rights reserved.

Dynamics of history-dependent epidemics in temporal networks

The structural properties of temporal networks often influence the dynamical processes that occur on these networks, e.g., bursty interaction patterns have been shown to slow down epidemics. In this paper, we investigate the effect of link lifetimes on the spread of history-dependent epidemics. We formulate an analytically tractable activity-driven temporal network model that explicitly incorporates link lifetimes. For Markovian link lifetimes, we use mean-field analysis for computing the epidemic threshold, while the effect of non-Markovian link lifetimes is studied using simulations. Furthermore, we also study the effect of negative correlation between the number of links spawned by an individual and the lifetimes of those links. Such negative correlations may arise due to the finite cognitive capacity of the individuals. Our investigations reveal that heavy-tailed link lifetimes slow down the epidemic, while negative correlations can reduce epidemic prevalence. We believe that our results help shed light on the role of link lifetimes in modulating diffusion processes on temporal networks.

Campaigning in Heterogeneous Social Networks: Optimal Control of SI Information Epidemics

We study the optimal control problem of maximizing the spread of an information epidemic on a social network. Information propagation is modeled as a susceptible-infected (SI) process, and the campaign budget is fixed. Direct recruitment and word-of-mouth incentives are the two strategies to accelerate information spreading (controls). We allow for multiple controls depending on the degree of the nodes/individuals. The solution optimally allocates the scarce resource over the campaign duration and the degree class groups. We study the impact of the degree distribution of the network on the controls and present results for Erdos-Renyi and scale-free networks. Results show that more resource is allocated to high-degree nodes in the case of scale-free networks, but medium-degree nodes in the case of Erdos-Renyi networks. We study the effects of various model parameters on the optimal strategy and quantify the improvement offered by the optimal strategy over the static and bang-bang control strategies. The effect of the time-varying spreading rate on the controls is explored as the interest level of the population in the subject of the campaign may change over time. We show the existence of a solution to the formulated optimal control problem, which has nonlinear isoperimetric constraints, using novel techniques that is general and can be used in other similar optimal control problems. This work may be of interest to political, social awareness, or crowdfunding campaigners and product marketing managers, and with some modifications may be used for mitigating biological epidemics.