In an epidemic, individuals can widely differ in the way they spread the infection depending on their age or on the number of days they have been infected for. In the absence of pharmaceutical ...interventions such as a vaccine or treatment, non-pharmaceutical interventions (e.g. physical or social distancing) are essential to mitigate the pandemic. We develop an original approach to identify the optimal age-stratified control strategy to implement as a function of the time since the onset of the epidemic. This is based on a model with a double continuous structure in terms of host age and time since infection. By applying optimal control theory to this model, we identify a solution that minimizes deaths and costs associated with the implementation of the control strategy itself. We also implement this strategy for three countries with contrasted age distributions (Burkina-Faso, France, and Vietnam). Overall, the optimal strategy varies throughout the epidemic, with a more intense control early on, and depending on host age, with a stronger control for the older population, except in the scenario where the cost associated with the control is low. In the latter scenario, we find strong differences across countries because the control extends to the younger population for France and Vietnam 2 to 3 months after the onset of the epidemic, but not for Burkina Faso. Finally, we show that the optimal control strategy strongly outperforms a constant uniform control exerted over the whole population or over its younger fraction. This improved understanding of the effect of age-based control interventions opens new perspectives for the field, especially for age-based contact tracing.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
•We produce novel human contact network analytics for the COVID-19 pandemic.•We use these analytics for time series models of French hospital incidence.•National-level predictions are greatly ...improved by adding these novel analytics.•Subnational analyses reveal spatial correlations of incidence.
Background COVID-19 was first detected in Wuhan, China, in 2019 and spread worldwide within a few weeks. The COVID-19 epidemic started to gain traction in France in March 2020. Subnational hospital admissions and deaths were then recorded daily and served as the main policy indicators. Concurrently, mobile phone positioning data have been curated to determine the frequency of users being colocalized within a given distance. Contrarily to individual tracking data, these can be a proxy for human contact networks between subnational administrative units.
Methods Motivated by numerous studies correlating human mobility data and disease incidence, we developed predictive time series models of hospital incidence between July 2020 and April 2021. We added human contact network analytics, such as clustering coefficients, contact network strength, null links or curvature, as regressors.
Findings We found that predictions can be improved substantially (by more than 50%) at both the national level and the subnational level for up to 2 weeks. Our subnational analysis also revealed the importance of spatial structure, as incidence in colocalized administrative units improved predictions. This original application of network analytics from colocalization data to epidemic spread opens new perspectives for epidemic forecasting and public health.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Theory predicts that selection for pathogen virulence and horizontal transmission is highest at the onset of an epidemic but decreases thereafter, as the epidemic depletes the pool of susceptible ...hosts. We tested this prediction by tracking the competition between the latent bacteriophage λ and its virulent mutant λcI857 throughout experimental epidemics taking place in continuous cultures of Escherichia coli. As expected, the virulent λcI857 is strongly favored in the early stage of the epidemic, but loses competition with the latent virus as prevalence increases. We show that the observed transient selection for virulence and horizontal transmission can be fully explained within the framework of evolutionary epidemiology theory. This experimental validation of our predictions is a key step towards a predictive theory for the evolution of virulence in emerging infectious diseases.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Serologic studies are crucial for clarifying dynamics of the coronavirus disease pandemic. Past work on serologic studies (e.g., during influenza pandemics) has made relevant contributions, but ...specific conditions of the current situation require adaptation. Although detection of antibodies to measure exposure, immunity, or both seems straightforward conceptually, numerous challenges exist in terms of sample collection, what the presence of antibodies actually means, and appropriate analysis and interpretation to account for test accuracy and sampling biases. Successful deployment of serologic studies depends on type and performance of serologic tests, population studied, use of adequate study designs, and appropriate analysis and interpretation of data. We highlight key questions that serologic studies can help answer at different times, review strengths and limitations of different assay types and study designs, and discuss methods for rapid sharing and analysis of serologic data to determine global transmission of severe acute respiratory syndrome coronavirus 2.
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DOBA, IZUM, KILJ, NUK, ODKLJ, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Much of the world experiences influenza in yearly recurring seasons, particularly in temperate areas. These patterns can be considered repeatable if they occur predictably and consistently at the ...same time of year. In tropical areas, including southeast Asia, timing of influenza epidemics is less consistent, leading to a lack of consensus regarding whether influenza is repeatable. This study aimed to assess repeatability of influenza in Vietnam, with repeatability defined as seasonality that occurs at a consistent time of year with low variation. We developed a mathematical model incorporating parameters to represent periods of increased transmission and then fitted the model to data collected from sentinel hospitals throughout Vietnam as well as four temperate locations. We fitted the model for individual (sub)types of influenza as well as all combined influenza throughout northern, central, and southern Vietnam. Repeatability was evaluated through the variance of the timings of peak transmission. Model fits from Vietnam show high variance (sd = 64-179 days) in peak transmission timing, with peaks occurring at irregular intervals and throughout different times of year. Fits from temperate locations showed regular, annual epidemics in winter months, with low variance in peak timings (sd = 32-57 days). This suggests that influenza patterns are not repeatable or seasonal in Vietnam. Influenza prevention in Vietnam therefore cannot rely on anticipation of regularly occurring outbreaks.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
The relationship between age and seroprevalence can be used to estimate the annual attack rate of an infectious disease. For pathogens with multiple serologically distinct strains, there is a need to ...describe composite exposure to an antigenically variable group of pathogens. In this study, we assay 24,402 general-population serum samples, collected in Vietnam between 2009 to 2015, for antibodies to eleven human influenza A strains. We report that a principal components decomposition of antibody titer data gives the first principal component as an appropriate surrogate for seroprevalence; this results in annual attack rate estimates of 25.6% (95% CI: 24.1% - 27.1%) for subtype H3 and 16.0% (95% CI: 14.7% - 17.3%) for subtype H1. The remaining principal components separate the strains by serological similarity and associate birth cohorts with their particular influenza histories. Our work shows that dimensionality reduction can be used on human antibody profiles to construct an age-seroprevalence relationship for antigenically variable pathogens.
Stochastic population dynamics simulations are essential for many ecological and epidemiological studies to generate time series and genealogies that capture the relatedness between individuals. Many ...software packages allow one to simulate phylogenetic trees but these tend to suffer from one or two major limitations. First, the underlying population dynamics model is often simplistic (e.g. constant population size or exponential growth). Second, the software packages are not appropriate to simulate a large number of trees.
We introduce TiPS, an R package to generate trajectories and phylogenetic trees associated with a compartmental model. Trajectories are simulated using Gillespie's exact or approximate stochastic simulation algorithm, or a newly proposed mixed version of the two. Phylogenetic trees are simulated from a trajectory under a backwards‐in‐time approach (i.e. coalescent). TiPS is based on the Rcpp package, allowing to combine the flexibility of R for model definition and the speed of C++ for simulations execution. The model is defined in R with a set of reactions, which allow capturing heterogeneity in life cycles or any sort of population structure. TiPS converts the model into C++ code and compiles it into a simulator that is interfaced in R via a function.
TiPS is flexible, easy‐to‐use and available on the CRAN at https://cran.r‐project.org/package=TiPS. Plus, benchmarking analyses show that TiPS is faster than existing packages.
This package is particularly well suited for population genetics and phylodynamics studies that need to generate a large number of phylogenies used for population dynamics studies.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Antimicrobials are included in commercial animal feed rations in many low- and middle-income countries (LMICs). We measured antimicrobial use (AMU) in commercial feed products consumed by 338 ...small-scale chicken flocks in the Mekong Delta of Vietnam, before a gradual nationwide ban on prophylactic use of antimicrobials (including in commercial feeds) to be introduced in the country over the coming five years. We inspected the labels of commercial feeds and calculated amounts of antimicrobial active ingredients (AAIs) given to flocks. We framed these results in the context of overall AMU in chicken production, and highlighted those products that did not comply with Government regulations. Thirty-five of 99 (35.3%) different antimicrobial-containing feed products included at least one AAI. Eight different AAIs (avilamycin, bacitracin, chlortetracycline, colistin, enramycin, flavomycin, oxytetracycline, virginamycin) belonging to five classes were identified. Brooding feeds contained antimicrobials the most (60.0%), followed by grower (40.9%) and finisher feeds (20.0%). Quantitatively, chlortetracycline was consumed most (42.2 mg/kg SEM ±0.34; 50.0% of total use), followed by enramycin (18.4 mg/kg SEM ±0.03, 21.8%), bacitracin (16.4 mg/kg SEM ±0.20, 19.4%) and colistin (6.40 mg/kg SEM ± 4.21;7.6%). Other antimicrobials consumed were virgianamycin, avilamycin, flavomycin and oxytetracycline (each ≤0.50 mg/kg). Antimicrobials in commercial feeds were more commonly given to flocks in the earlier part of the production cycle. A total of 10 (9.3%) products were not compliant with existing Vietnamese regulation (06/2016/TT-BNNPTNT) either because they included a non-authorised AAI (4), had AAIs over the permitted limits (4), or both (2). A number of commercial feed formulations examined included colistin (polymyxin E), a critically important antimicrobial of highest priority for human medicine. These results illustrate the challenges for effective implementation and enforcement of restrictions of antimicrobials in commercial feeds in LMICs. Results from this study should help encourage discussion about policies on medicated feeds in LMICs.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
The accurate assessment of antimicrobial use (AMU) requires relating quantities of active ingredients (AAIs) with population denominators. These data can be used to prioritize potential sources of ...selective pressure for antimicrobial resistance and to establish reduction targets. Here, we estimated AMU in Vietnam (human population 93.4 M in 2015), and compared it with European Union (EU) data (population 511.5 M in 2014). We extrapolated AMU data on each key animal species and humans from different published sources to calculate overall AMU (in tonnes) in Vietnam. We then compared these data with published statistics on AMU in the European Union (EU). A total of 3838 t of antimicrobials were used in Vietnam, of which 2751 (71.7%) corresponded to animal use, and the remainder (1086 t; 28.3%) to human AMU. This equates to 261.7 mg and 247.3 mg per kg of human and animal biomass, compared with 122.0 mg and 151.5 mg in the EU. The greatest quantities of antimicrobials (in decreasing order) were used in pigs (41.7% of total use), humans (28.3%), aquaculture (21.9%) and chickens (4.8%). Combined AMU in other species accounted for < 1.5%. These results are approximate and highlight the need to conduct targeted surveys to improve country-level estimates of AMU.
Theoretical studies of wildlife population dynamics have proved insightful for sustainable management, where the principal aim is to maximize short-term yield, without risking population extinction. ...Surprisingly, infectious diseases have not been accounted for in harvest models, which is a major oversight because the consequences of parasites for host population dynamics are well-established. Here, we present a simple general model for a host species subject to density dependent reproduction and seasonal demography. We assume this host species is subject to infection by a strongly immunizing, directly transmitted pathogen. In this context, we show that the interaction between density dependent effects and harvesting can substantially increase both disease prevalence and the absolute number of infectious individuals. This effect clearly increases the risk of cross-species disease transmission into domestic and livestock populations. In addition, if the disease is associated with a risk of mortality, then the synergistic interaction between hunting and disease-induced death can increase the probability of host population extinction.
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BFBNIB, NMLJ, NUK, PNG, SAZU, UL, UM, UPUK
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