Classification of Spatiotemporal Data for Epidemic Alert Systems: Monitoring Influenza-Like Illness in France.

Surveillance data used by epidemic alert systems are typically fully aggregated in space at the national level. However, epidemics may be spatially heterogeneous, undergoing distinct dynamics in distinct regions of the surveillance area. We unveiled this in retrospective analyses by classifying incidence time series. We used Pearson correlation to quantify the similarity between local time series and then classified them using modularity maximization. The surveillance area was thus divided into regions with different incidence patterns. We analyzed 31 years (1985-2016) of data on influenza-like illness from the French Sentinelles system and found spatial heterogeneity in 19 of 31 influenza seasons. However, distinct epidemic regions could be identified only 4-5 weeks after a nationwide alert. The impact of spatial heterogeneity on influenza epidemiology was complex. First, when a nationwide alert was triggered, 32%-41% of the administrative regions of France were experiencing an epidemic, while the others were not. Second, the nationwide alert was timely for the whole surveillance area, but subsequently regions experienced distinct epidemic dynamics. Third, the epidemic dynamics were homogeneous in space. Spatial heterogeneity analyses can provide information on the timing of the peak and end of the epidemic, in various regions, for use in tailoring disease monitoring and control.

Heterosexual risk of HIV transmission per sexual act under combined antiretroviral therapy: systematic review and bayesian modeling.

BACKGROUND: Although essential for patient counseling and quality of life of human immunodeficiency virus (HIV)-infected individuals, the risk of HIV transmission during 1 unprotected sex act with an HIV-infected person under combination antiretroviral therapy (cART) remains unknown. METHODS: We reviewed systematically the literature for studies on HIV transmission among heterosexual HIV-serodiscordant couples, where the infected partner was on cART, with regular virological monitoring, reporting on condom use and sexual activity. We used Bayesian statistics to combine data from selected studies, to investigate the per-act risk of HIV transmission through unprotected sex with an HIV-infected person on cART for >6 months. RESULTS: At most, 1 HIV transmission, over an estimated 113 480 sex acts, of which 17% were not condom protected, was reported within 1672 HIV-serodiscordant couples where the index partner had been treated for >6 months. Data were insufficient to determine whether the reported transmission occurred before or after 6 months of cART. We estimated the upper-bound per-act risk of HIV transmission at either 8.7 or 13:100 000, depending on whether the transmission occurred before or after 6 months of cART. These estimates applied whether or not index partners were virally suppressed. Estimating an upper-bound risk <1:100 000 would require observing no HIV transmission while collecting >12 times the available amount of data. CONCLUSIONS: Available data do not support zero risk of HIV transmission under cART. The per-act risk of HIV transmission through unprotected sex with HIV-infected individuals on cART in comprehensive care for >6 months (whether or not virally suppressed) is <13:100 000. Estimating a 10-fold lower upper-bound risk may be unfeasible due to high condom use among HIV-serodiscordant couples in most research studies.

Interhuman transmissibility of Middle East respiratory syndrome coronavirus: estimation of pandemic risk.

BACKGROUND: The new Middle East respiratory syndrome coronavirus (MERS-CoV) infection shares many clinical, epidemiological, and virological similarities with that of severe acute respiratory syndrome (SARS)-CoV. We aimed to estimate virus transmissibility and the epidemic potential of MERS-CoV, and to compare the results with similar findings obtained for prepandemic SARS. METHODS: We retrieved data for MERS-CoV clusters from the WHO summary and subsequent reports, and published descriptions of cases, and took into account 55 of the 64 laboratory-confirmed cases of MERS-CoV reported as of June 21, 2013, excluding cases notified in the previous 2 weeks. To assess the interhuman transmissibility of MERS-CoV, we used Bayesian analysis to estimate the basic reproduction number (R0) and compared it to that of prepandemic SARS. We considered two scenarios, depending on the interpretation of the MERS-CoV cluster-size data. RESULTS: With our most pessimistic scenario (scenario 2), we estimated MERS-CoV R0 to be 0·69 (95% CI 0·50-0·92); by contrast, the R0 for prepandemic SARS-CoV was 0·80 (0·54-1·13). Our optimistic scenario (scenario 1) yielded a MERS-CoV R0 of 0·60 (0·42-0·80). Because of recent implementation of effective contact tracing and isolation procedures, further MERS-CoV transmission data might no longer describe an entire cluster, but only secondary infections directly caused by the index patient. Hence, we calculated that, under scenario 2, eight or more secondary infections caused by the next index patient would translate into a 5% or higher chance that the revised MERS-CoV R0 would exceed 1--ie, that MERS-CoV might have pandemic potential. INTERPRETATION: Our analysis suggests that MERS-CoV does not yet have pandemic potential. We recommend enhanced surveillance, active contact tracing, and vigorous searches for the MERS-CoV animal hosts and transmission routes to human beings. FUNDING: Agence Nationale de la Recherche (Labex Integrative Biology of Emerging Infectious Diseases), and the European Community's Seventh Framework Programme project PREDEMICS.

The niche reduction approach: an opportunity for optimal control of infectious diseases in low-income countries?

BACKGROUND: During the last century, WHO led public health interventions that resulted in spectacular achievements such as the worldwide eradication of smallpox and the elimination of malaria from the Western world. However, besides major successes achieved worldwide in infectious diseases control, most elimination/control programs remain frustrating in many tropical countries where specific biological and socio-economical features prevented implementation of disease control over broad spatial and temporal scales. Emblematic examples include malaria, yellow fever, measles and HIV. There is consequently an urgent need to develop affordable and sustainable disease control strategies that can target the core of infectious diseases transmission in highly endemic areas. DISCUSSION: Meanwhile, although most pathogens appear so difficult to eradicate, it is surprising to realize that human activities are major drivers of the current high rate of extinction among upper organisms through alteration of their ecology and evolution, i.e., their "niche". During the last decades, the accumulation of ecological and evolutionary studies focused on infectious diseases has shown that the niche of a pathogen holds more dimensions than just the immune system targeted by vaccination and treatment. Indeed, it is situated at various intra- and inter- host levels involved on very different spatial and temporal scales. After developing a precise definition of the niche of a pathogen, we detail how major advances in the field of ecology and evolutionary biology of infectious diseases can enlighten the planning and implementation of infectious diseases control in tropical countries with challenging economic constraints. SUMMARY: We develop how the approach could translate into applied cases, explore its expected benefits and constraints, and we conclude on the necessity of such approach for pathogen control in low-income countries.

Emergence failure of early epidemics: A mathematical modeling approach.

Epidemic or pathogen emergence is the phenomenon by which a poorly transmissible pathogen finds its evolutionary pathway to become a mutant that can cause an epidemic. Many mathematical models of pathogen emergence rely on branching processes. Here, we discuss pathogen emergence using Markov chains, for a more tractable analysis, generalizing previous work by Kendall and Bartlett about disease invasion. We discuss the probability of emergence failure for early epidemics, when the number of infected individuals is small and the number of the susceptible individuals is virtually unlimited. Our formalism addresses both directly transmitted and vector-borne diseases, in the cases where the original pathogen is 1) one step-mutation away from the epidemic strain, and 2) undergoing a long chain of neutral mutations that do not change the epidemiology. We obtain analytic results for the probabilities of emergence failure and two features transcending the transmission mechanism. First, the reproduction number of the original pathogen is determinant for the probability of pathogen emergence, more important than the mutation rate or the transmissibility of the emerged pathogen. Second, the probability of mutation within infected individuals must be sufficiently high for the pathogen undergoing neutral mutations to start an epidemic, the mutation threshold depending again on the basic reproduction number of the original pathogen. Finally, we discuss the parameterization of models of pathogen emergence, using SARS-CoV1 as an example of zoonotic emergence and HIV as an example for the emergence of drug resistance. We also discuss assumptions of our models and implications for epidemiology.

Role of environmental persistence in pathogen transmission: a mathematical modeling approach.

Although diseases such as influenza, tuberculosis and SARS are transmitted through an environmentally mediated mechanism, most modeling work on these topics is based on the concepts of infectious contact and direct transmission. In this paper we use a paradigm model to show that environmental transmission appears like direct transmission in the case where the pathogen persists little time in the environment. Furthermore, we formulate conditions for the validity of this modeling approximation and we illustrate them numerically for the cases of cholera and influenza. According to our results based on recently published parameter estimates, the direct transmission approximation fails for both cholera and influenza. While environmental transmission is typically chosen over direct transmission in modeling cholera, this is not the case for influenza.

Impact of voluntary testing on infectious disease epidemiology: A game theoretic approach.

The World Health Organization recommends test-and-treat interventions to curb and even eliminate epidemics of HIV, viral hepatitis, and sexually transmitted infections (e.g., chlamydia, gonorrhea, syphilis and trichomoniasis). Epidemic models show these goals are achievable, provided the participation of individuals in test-and-treat interventions is sufficiently high. We combine epidemic models and game theoretic models to describe individual's decisions to get tested for infectious diseases within certain epidemiological contexts, and, implicitly, their voluntary participation to test-and-treat interventions. We develop three hybrid models, to discuss interventions against HIV, HCV, and sexually transmitted infections, and the potential behavioral response from the target population. Our findings are similar across diseases. Particularly, individuals use three distinct behavioral patterns relative to testing, based on their perceived costs for testing, besides the payoff for discovering their disease status. Firstly, if the cost of testing is too high, then individuals refrain from voluntary testing and get tested only if they are symptomatic. Secondly, if the cost is moderate, some individuals will test voluntarily, starting treatment if needed. Hence, the spread of the disease declines and the disease epidemiology is mitigated. Thirdly, the most beneficial testing behavior takes place as individuals perceive a per-test payoff that surpasses a certain threshold, every time they get tested. Consequently, individuals achieve high voluntary testing rates, which may result in the elimination of the epidemic, albeit on temporary basis. Trials and studies have attained different levels of participation and testing rates. To increase testing rates, they should provide each eligible individual with a payoff, above a given threshold, each time the individual tests voluntarily.

Environmental transmission of low pathogenicity avian influenza viruses and its implications for pathogen invasion.

Understanding the transmission dynamics and persistence of avian influenza viruses (AIVs) in the wild is an important scientific and public health challenge because this system represents both a reservoir for recombination and a source of novel, potentially human-pathogenic strains. The current paradigm locates all important transmission events on the nearly direct fecal/oral bird-to-bird pathway. In this article, on the basis of overlooked evidence, we propose that an environmental virus reservoir gives rise to indirect transmission. This transmission mode could play an important epidemiological role. Using a stochastic model, we demonstrate how neglecting environmentally generated transmission chains could underestimate the explosiveness and duration of AIV epidemics. We show the important pathogen invasion implications of this phenomenon: the nonnegligible probability of outbreak even when direct transmission is absent, the long-term infectivity of locations of prior outbreaks, and the role of environmental heterogeneity in risk.

Can HIV epidemics among MSM be eliminated through participation in preexposure prophylaxis rollouts?

OBJECTIVE: To study the conditions under which preexposure prophylaxis (PrEP) coverage can eliminate HIV among MSM in the Paris region. DESIGN: Mathematical modeling. METHODS: We propose an innovative approach, combining a transmission model with a game-theoretic model, for decision-making about PrEP use. Individuals at high risk of HIV infection decide to use PrEP, depending on their perceived risk of infection and the relative cost of using PrEP versus antiretroviral treatment (ART), which includes monetary and/or nonmonetary aspects, such as price and access model of PrEP, consequences of being infected and lifelong ART. RESULTS: If individuals assessed correctly their infection risk, and the cost of using PrEP were sufficiently low, then the PrEP rollout could lead to elimination. Specifically, assuming 86% PrEP effectiveness, as observed in two clinical trials, a minimum PrEP coverage of 55% [95% confidence interval (CI) 43-64%] among high-risk MSM would achieve elimination in the Paris region. A complete condom drop by MSM using PrEP slightly increases the minimum PrEP coverage required for elimination, by ∼1%, whereas underestimation of their own HIV infection risk would require PrEP programs reduce the cost of using PrEP by a factor ∼2 to achieve elimination. CONCLUSION: Elimination conditions are not yet met in the Paris region, where at most 47% of high-risk MSM were using PrEP as of mid-2019. Further lowering the cost of PrEP and promoting a fair perception of HIV risk are required and should be maintained in the long-run, to maintain elimination status.

A general multi-strain model with environmental transmission: invasion conditions for the disease-free and endemic states.

Although many infectious diseases of humans and wildlife are transmitted via an environmental reservoir, the theory of environmental transmission remains poorly elaborated. Here we introduce an SIR-type multi-strain disease transmission model with perfect cross immunity where environmental transmission is broadly defined by three axioms. We establish the conditions under which a multi-strain endemic state is invaded by another strain which is both directly and environmentally transmitted. We discuss explicit forms for environmental transmission terms and apply our newly derived invasion conditions to a two-strain system. Then, we consider the case of two strains with matching basic reproduction numbers (i.e., R(0)), one directly transmitted only and the other both directly and environmentally transmitted, invading each other's endemic state. We find that the strain which is only directly transmitted can invade the endemic state of the strain with mixed transmission. However, the endemic state of the first strain is neutrally stable to invasion by the second strain. Thus, our results suggest that environmental transmission makes the endemic state less resistant to invasion.

The role of environmental transmission in recurrent avian influenza epidemics.

Avian influenza virus (AIV) persists in North American wild waterfowl, exhibiting major outbreaks every 2-4 years. Attempts to explain the patterns of periodicity and persistence using simple direct transmission models are unsuccessful. Motivated by empirical evidence, we examine the contribution of an overlooked AIV transmission mode: environmental transmission. It is known that infectious birds shed large concentrations of virions in the environment, where virions may persist for a long time. We thus propose that, in addition to direct fecal/oral transmission, birds may become infected by ingesting virions that have long persisted in the environment. We design a new host-pathogen model that combines within-season transmission dynamics, between-season migration and reproduction, and environmental variation. Analysis of the model yields three major results. First, environmental transmission provides a persistence mechanism within small communities where epidemics cannot be sustained by direct transmission only (i.e., communities smaller than the critical community size). Second, environmental transmission offers a parsimonious explanation of the 2-4 year periodicity of avian influenza epidemics. Third, very low levels of environmental transmission (i.e., few cases per year) are sufficient for avian influenza to persist in populations where it would otherwise vanish.

Quantifying the treatment efficacy of reverse transcriptase inhibitors: new analyses of clinical data based on within-host modeling.

BACKGROUND: Current measures of the clinical efficacy of antiretroviral therapy (ART) in the treatment of HIV include the change in HIV RNA in the plasma and the gain in CD4 cells. METHODS: We propose new measures for evaluating the efficacy of treatment that is based upon combinations of non-nucleoside and nucleoside reverse transcriptase inhibitors. Our efficacy measures are: the CD4 gain per virion eliminated, the potential of CD4 count restoration and the viral reproduction number (R0). These efficacy measures are based upon a theoretical understanding of the impact of treatment on both viral dynamics and the immune reconstitution. Patient data were obtained from longitudinal HIV clinical cohorts. RESULTS: We found that the CD4 cell gain per virion eliminated ranged from 10(-2) to 600 CD4 cells/virion, the potential of CD4 count restoration ranged from 60 to 1520 CD4 cells/microl, and the basic reproduction number was reduced from an average of 5.1 before therapy to an average of 1.2 after one year of therapy. There was substantial heterogeneity in these efficacy measures among patients with detectable viral replication. We found that many patients who achieved viral suppression did not have high CD4 cell recovery profiles. Our efficacy measures also enabled us to identify a subgroup of patients who were not virally suppressed but had the potential to reach a high CD4 count and/or achieve viral suppression if they had been switched to a more potent regimen. CONCLUSION: We show that our new efficacy measures are useful for analyzing the long-term treatment efficacy of combination reverse transcriptase inhibitors and argue that achieving a low R0 does not imply achieving viral suppression.

Is there any evidence that syphilis epidemics cycle?

We re-examine the evidence behind the controversial hypothesis that syphilis epidemics cycle. We used the same methods (spectral analysis) used by the proponents of this hypothesis to reanalyse a longitudinal dataset provided by the US Centers for Disease Control and Prevention (CDC). We also analysed a longitudinal CDC mortality dataset. To investigate the theoretical results generated by the transmission model that was used to support the hypothesis, we simulated the model and predicted the expected dynamics of syphilis epidemics. By contrast with previous findings, we found that neither of the CDC's datasets provides compelling evidence that syphilis epidemics cycle, and the transmission model (if more reasonable parameter values are used) does not predict cycling behaviour. We explain the possible reasons for the previous proposal that syphilis epidemics cycle. Our findings imply that it is quite possible that the CDC could be successful in eliminating syphilis within the next few decades.

Infectious syphilis in high-income settings in the 21st century.

In high-income countries after World War II, the widespread availability of effective antimicrobial therapy, combined with expanded screening, diagnosis, and treatment programmes, resulted in a substantial decline in the incidence of syphilis. However, by the turn of the 21st century, outbreaks of syphilis began to occur in different subpopulations, especially in communities of men who have sex with men. The reasons for these outbreaks include changing sexual and social norms, interactions with increasingly prevalent HIV infection, substance abuse, global travel and migration, and underinvestment in public-health services. Recently, it has been suggested that these outbreaks could be the result of an interaction of the pathogen with natural immunity, and that syphilis epidemics should be expected to intrinsically cycle. We discuss this hypothesis by examining long-term data sets of syphilis. Today, syphilis in western Europe and the USA is characterised by low-level endemicity with concentration among population subgroups with high rates of partner change, poor access to health services, social marginalisation, or low socioeconomic status.

Can influenza epidemics be prevented by voluntary vaccination?

Previous modeling studies have identified the vaccination coverage level necessary for preventing influenza epidemics, but have not shown whether this critical coverage can be reached. Here we use computational modeling to determine, for the first time, whether the critical coverage for influenza can be achieved by voluntary vaccination. We construct a novel individual-level model of human cognition and behavior; individuals are characterized by two biological attributes (memory and adaptability) that they use when making vaccination decisions. We couple this model with a population-level model of influenza that includes vaccination dynamics. The coupled models allow individual-level decisions to influence influenza epidemiology and, conversely, influenza epidemiology to influence individual-level decisions. By including the effects of adaptive decision-making within an epidemic model, we can reproduce two essential characteristics of influenza epidemiology: annual variation in epidemic severity and sporadic occurrence of severe epidemics. We suggest that individual-level adaptive decision-making may be an important (previously overlooked) causal factor in driving influenza epidemiology. We find that severe epidemics cannot be prevented unless vaccination programs offer incentives. Frequency of severe epidemics could be reduced if programs provide, as an incentive to be vaccinated, several years of free vaccines to individuals who pay for one year of vaccination. Magnitude of epidemic amelioration will be determined by the number of years of free vaccination, an individuals' adaptability in decision-making, and their memory. This type of incentive program could control epidemics if individuals are very adaptable and have long-term memories. However, incentive-based programs that provide free vaccination for families could increase the frequency of severe epidemics. We conclude that incentive-based vaccination programs are necessary to control influenza, but some may be detrimental. Surprisingly, we find that individuals' memories and flexibility in adaptive decision-making can be extremely important factors in determining the success of influenza vaccination programs. Finally, we discuss the implication of our results for controlling pandemics.

Brief Report: Per Sex-Act Risk of HIV Transmission Under Antiretroviral Treatment: A Data-Driven Approach.

BACKGROUND: Before the completion of HPTN 052, PARTNER, and Opposites Attract studies, data were lacking to directly estimate HIV transmission risk under effective combined antiretroviral treatment (cART). Rather, estimates were obtained by extrapolating a dose-response relationship between viral load and risk of HIV transmission, observed among untreated individuals, to treated individuals. Presently, data have accumulated from 9 clinical studies for a direct validation of this extrapolation. METHODS: Using estimates of per sex-act risk of HIV transmission on effective cART obtained by extrapolation, sexual behavior data, and a simple mathematical model, we estimated the number of seroconversions that should have been observed in HIV-serodiscordant couples where the HIV-positive partner was on cART across the 9 studies. We compared this with the number of seroconversions actually observed. Next, we directly estimated the risk of HIV transmission on effective cART, using Bayesian statistics to combine all available data. RESULTS: We found that at least 4.7 (uncertainty bounds: 1.7-12.6) and 35.1 (uncertainty bounds: 13.2-92.0) seroconversions should have been observed among, respectively, heterosexual and men who have sex with men (MSM) serodiscordant couples. This is not validated by observations across the studies, which reported at most 1 seroconversion among heterosexual couples and 0 for MSM. Combining all available data, we found that the maximum per sex-act risk of HIV transmission under effective cART is 3.9:100,000 for heterosexuals and 4.4:100,000 for MSM. CONCLUSIONS: Data have accumulated to render obsolete estimates of the risk of HIV transmission on cART obtained by extrapolation. Direct estimates are substantially lower and should be used in practice.

Role of parametric resonance in virological failure during HIV treatment interruption therapy.

We present a novel hypothesis that could explain virological failure to structured treatment interruptions (STI). We analysed a classic mathematical model of HIV within-host viral dynamics and found that non-linear parametric resonance occurs when STI are added to the model; resonance is observed as virological failure. We simulated clinical trial data and calculated patient-specific resonant spectra. We gained two important insights. First, within an STI trial, patients who begin with similar viral loads can be expected to show very different virological responses as a result of resonance. Second, and more importantly, virological failure is not simply due to STI or patients' characteristics; instead it is the result of complex interaction between STI and the patient's viral dynamics. Hence, our analyses show that no universal regimen with periodic interruptions will be effective for all patients.

Mean-field analysis of an inductive reasoning game: application to influenza vaccination.

Recently we have introduced an inductive reasoning game of voluntary yearly vaccination to establish whether or not a population of individuals acting in their own self-interest would be able to prevent influenza epidemics. Here, we analyze our model to describe the dynamics of the collective yearly vaccination uptake. We discuss the mean-field equations of our model and first order effects of fluctuations. We explain why our model predicts that severe epidemics are periodically expected even without the introduction of pandemic strains. We find that fluctuations in the collective yearly vaccination uptake induce severe epidemics with an expected periodicity that depends on the number of independent decision makers in the population. The mean-field dynamics also reveal that there are conditions for which the dynamics become robust to the fluctuations. However, the transition between fluctuation-sensitive and fluctuation-robust dynamics occurs for biologically implausible parameters. We also analyze our model when incentive-based vaccination programs are offered. When a family-based incentive is offered, the expected periodicity of severe epidemics is increased. This results from the fact that the number of independent decision makers is reduced, increasing the effect of the fluctuations. However, incentives based on the number of years of prepayment of vaccination may yield fluctuation-robust dynamics where severe epidemics are prevented. In this case, depending on prepayment, the transition between fluctuation-sensitive and fluctuation-robust dynamics may occur for biologically plausible parameters. Our analysis provides a practical method for identifying how many years of free vaccination should be provided in order to successfully ameliorate influenza epidemics.

Prevention of treatable infectious diseases: A game-theoretic approach.

We model outcomes of voluntary prevention using an imperfect vaccine, which confers protection only to a fraction of vaccinees for a limited duration. Our mathematical model combines a single-player game for the individual-level decision to get vaccinated, and a compartmental model for the epidemic dynamics. Mathematical analysis yields a characterization for the effective vaccination coverage, as a function of the relative cost of prevention versus treatment; note that cost may involve monetary as well as non-monetary aspects. Three behaviors are possible. First, the relative cost may be too high, so individuals do not get vaccinated. Second, the relative cost may be moderate, such that some individuals get vaccinated and voluntary vaccination alleviates the epidemic. In this case, the vaccination coverage grows steadily with decreasing relative cost of vaccination versus treatment. Unlike previous studies, we find a third case where relative cost is sufficiently low so epidemics may be averted through the use of prevention, even for an imperfect vaccine. However, we also found that disease elimination is only temporary-as no equilibrium exists for the individual strategy in this third case-and, with increasing perceived cost of vaccination versus treatment, the situation may be reversed toward the epidemic edge, where the effective reproductive number is 1. Thus, maintaining relative cost sufficiently low will be the main challenge to maintain disease elimination. Furthermore, our model offers insight on vaccine parameters, which are otherwise difficult to estimate. We apply our findings to the epidemiology of measles.