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bioRxiv2021

A scalable analytical approach from bacterial genomes to epidemiology

Recent years have seen a remarkable increase in the practicality of sequencing whole genomes from large numbers of bacterial isolates. The availability of this data has huge potential to deliver new insights into the evolution and epidemiology of bacterial pathogens, but the scalability of the analytical methodology has been lagging behind that of the sequencing technology. Here we present a step-by-step approach for such large-scale genomic epidemiology analyses, from bacterial genomes to epidemiological interpretations. A central component of this approach is the dated phylogeny, which is a phylogenetic tree with branch lengths measured in units of time. The construction of dated phylogenies from bacterial genomic data needs to account for the disruptive effect of recombination on phylogenetic relationships, and we describe how this can be achieved. Dated phylogenies can then be used to perform fine-scale or large-scale epidemiological analyses, depending on the proportion of cases for which genomes are available. A key feature of this approach is computational scalability, and in particular the ability to process hundreds or thousands of genomes within a matter of hours. This is a clear advantage of the step-by-step approach described here. We discuss other advantages and disadvantages of the approach, as well as potential improvements and avenues for future research.

microbiology↗

bioRxiv2021

Genomic epidemiological models describe pathogen evolution across fitness valleys

Genomics is fundamentally changing epidemiological research. However, systematically exploring hypotheses in pathogen evolution requires new modeling tools. Models intertwining pathogen epidemiology and genomic evolution can help understand processes such as the emergence of novel pathogen genotypes with higher transmissibility or resistance to treatment. In this work, we present Opqua, a flexible simulation framework that explicitly links epidemiology to sequence evolution and selection. We use Opqua to study determinants of evolution across fitness valleys. We confirm that competition can limit evolution in high transmission environments and find that low transmission, host mobility, and complex pathogen life cycles facilitate reaching new adaptive peaks through population bottlenecks and decoupling of selective pressures. The results show the potential of genomic epidemiological modeling as a tool in infectious disease research.

evolutionary biology↗

bioRxiv2022

Is it the same strain? Defining genomic epidemiology thresholds tailored to individual outbreaks

BackgroundEpidemiological surveillance relies on microbial strain typing, which defines genomic relatedness among isolates to identify case clusters and their potential sources. No consensus exists on the choice of thresholds of genomic relatedness to define clusters. While a priori defined thresholds are often applied, outbreak-specific features such as pathogen mutation rate and duration of source contamination should be considered. MethodsWe developed a forward model of bacterial evolution to simulate mutation within a population diversifying at a specific mutation rate, with specific outbreak duration and sample isolation dates. Based on the resulting expected distribution of genetic distances we define a threshold beyond which isolates are considered as not part of the outbreak. We additionally embedded the model into a Markov Chain Monte Carlo inference framework to estimate, from data including sampling dates or isolates genetic variation, the most credible mutation rate or time since source contamination. FindingsA simulation study validated the model over realistic durations and mutation rates. When applied to 16 published datasets describing foodborne outbreaks, our framework consistently identified outliers. Appropriate thresholds for grouping cases were obtained for 14 outbreaks. For the remaining two outbreaks, re-estimation of the duration of outbreak lead to updated threshold values and was more likely, given our model, to result in the observed genetic distances. InterpretationWe propose an evolutionary approach to the single strain conundrum by defining the genetic threshold based on individual outbreak properties. The framework provides an informed estimation of the likelihood of a cluster given the samples epidemiological and microbiological context. This forward model, applicable to foodborne or environmental-source single point case clusters or outbreaks, will be useful for epidemiological surveillance and to guide control measures. FundingThis work was supported financially by the MedVetKlebs project, a component of European Joint Programme One Health EJP, which has received funding from the European Unions Horizon 2020 research and innovation programme under Grant Agreement No 773830. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Research in contextO_ST_ABSEvidence before this studyC_ST_ABSWe searched PubMed for studies published between database inception and April 3, 2021, with the term (threshold OR cut-off OR genetic relatedness) AND (outbreak) AND (cgMLST OR wgMLST OR SNPs) AND (microbial OR bacteria OR bacterial OR pathogen). We found 222 related articles. Most studies define a fixed SNP threshold that relate outbreak strains based on previous observations. One original study identifies outbreak clusters based on transmission events. However, it relies on strong assumptions about molecular clock and transmission processes. Added value of this studyOur study describes a new method based on a forward Wright-Fisher model to find the most credible genetic distance threshold. This method is fast and simple to use with only few assumptions, informed by outbreak duration and pathogen mutation rate. By using SNP or cgMLST pairwise distances and sample collection dates of the outbreak of interest, the algorithm provides context-based guidance to separate outbreak strains from outliers. Implications of all the available evidenceThe fast and easy method developed here enables to move away from a priori defined thresholds. Defining clusters more accurately based on the specific features of outbreaks, and the ability to estimate outbreak duration, will provide the needed precision for epidemiological surveillance and should contribute to leverage molecular epidemiology data more efficiently for the purpose of uncovering contamination sources. Data Availability StatementAll data and code used for this manuscript is available online at https://gitlab.pasteur.fr/BEBP.

microbiology↗

bioRxiv2022

Mathematical bridge between epidemiological and molecular data on cancer and beyond

BackgroundAt least six different mathematical models of cancer and their count-less variations and combinations have been published to date in the scientific literature that reasonably explain epidemiological prediction of multi-step carcinogenesis. Each one deals with a particular set of problems at a given organizational level ranging from populations to genes. Any of the models adopted in those articles so far do not account for both epidemiological and molecular levels of carcinogenesis. MethodsWe have developed a mathematically rigorous system to derive those equations satisfying the basic assumptions of both epidemiology and molecular biology without incorporating arbitrary numerical coefficients or constants devoid of any causal explanation just to fit the empirical data. The dataset we have used encompasses 21 major categories of cancer, 124 selected populations, 108 cancer registries, 5 continents, and 14,067,894 individual cases. ResultsWe generalized all the epidemiological and molecular data using our derived equations through linear and non-linear regression and found all the necessary coefficients to explain the data. We also tested our equations against non-neoplastic conditions satisfying equivalent mathematical assumptions. ConclusionThe aim of this treatise is not only to provide some novel insight into the mathematical modeling of malignant transformation but also to revive the classical tools we already have at our disposal to pave the way towards novel insight into integrated approaches in cancer research.

cancer biology↗

bioRxiv2024

Convergence and global epidemiology of Klebsiella pneumoniae plasmids harbouring the iuc3 virulence locus.

BackgroundKlebsiella pneumoniae (Kp) is an important pathogen of humans and animals, and recent reports of convergent strains that carry both virulence and antimicrobial resistance genes (ARGs) have raised serious public health concern. The plasmid-borne iuc locus, encoding the siderophore aerobactin, is a key virulence factor in this species. The variant iuc3 is associated with porcine and human clinical isolates and is carried by mostly uncharacterised IncF plasmids. MethodsWe used a combination of short-read and long-read sequencing to characterise IncFIB(K)/IncFII iuc3-carrying plasmids harboured by 79 Kp isolates and one K. oxytoca isolate recovered as part of two large One-Health studies in Italy (SpARK) and Thailand (OH-DART). Adding data from public repositories gave a combined dataset of 517 iuc3 isolates, and the plasmids were analysed using both clustering and phylogenetic methods. FindingsWe note seven large, convergent, plasmids from Thailand that have emerged through the hybridisation of co-circulating plasmids harbouring iuc3 and antimicrobial resistance genes (ARGs) encoding extended-spectrum beta-lactamases (ESBLs). We were also able to identify putative parental plasmids which were mostly associated with two neighbouring meat markets, as were the hybrid plasmids. Clustering and global phylogenetic analyses resolved an iuc3 plasmid sub-group circulating throughout Asia, with occasional examples in Europe and elsewhere. This variant carries multiple ARGs and is commonly harboured by clinical isolates, thus warranting targeted plasmid surveillance. InterpretationOur study reveals that plasmid hybridisation leading to the convergence of resistance and virulence traits may be very common, even in non-clinical ( One-Health) settings. Population-scale plasmid genomics makes it possible to identify putative parental plasmids, which will help to identify plasmid types that are most likely to hybridise, and what the selective consequences may be for the plasmid and host. A distinct iuc3 plasmid sub-variant is associated with clinical isolates in Asia which requires close monitoring. Research In ContextMultiple reports of convergent clones of Klebsiella pneumoniae that combine both hypervirulence and multidrug resistance (MDR-hvKp) have been published recently; a PubMed search in November 2023 using the key words convergence Klebsiella pneumoniae returned 143 papers, 99 of which were published from 2020 onwards. Our study demonstrates that the hybridisation of plasmids carrying AMR and virulence genes is a frequent, ongoing, process in natural populations. The subsequent transfer of plasmids conferring both traits is thus likely to be a key driver behind the spread of convergent strains. Our study also provides an exemplar of how hybrid assemblies can facilitate large-scale global genomic plasmid epidemiology. Evidence before the studyAlthough multiple recent reports highlight the emergence and spread of convergent Kp strains, the confluence of resistance and virulence genes within the same plasmid has not been studied at a population level, and putative parental plasmids are rarely identified. Moreover, there have been few high-resolution genomic epidemiology studies on closely related plasmids using both long and short-read data on a global scale. Added valueWe more than double the number of complete sequences available for plasmids harbouring iuc3 from 58 to 139 and provide evidence on the host lineages most likely to harbour these plasmids (e.g., ST35), and epidemiological source (e.g., pig, wild animal, human). Our comparative analysis of phylogenetic and clustering approaches will help to inform future plasmid epidemiological studies. ImplicationsThe hybridisation of plasmids harbouring virulence and resistance genes occurs frequently in natural populations, even within One-Health settings. However, the selective drivers (if any) and evolutionary consequences of this phenomenon are unclear. There is clear utility in generating closed plasmid genomes on a population scale, and targeted plasmid surveillance on a clinical sub-variant of iuc3 plasmids is warranted.

genomics↗

bioRxiv2025

Determinants of variation in epidemiological parameters for African Swine Fever virus

African Swine Fever (ASF) is a highly infectious reportable disease of swine that can have devastating consequences for pork producers and consumers. ASF virus can persist in either domestic or wild swine through several epidemiological cycles. This has led to a wide variety of epidemiological traits, making it challenging to plan effective surveillance and mitigation strategies. Here, we compile and analyze data from experimental infections of ASF virus variants from genotype II that have been reported in peer-reviewed publications. We provide descriptive summaries of the distributions of epidemiological parameters such as incubation period, infectious period, mortality rate, and R0 and develop predictive models that explain the variation in these quantities based on detection assays and other experimental design features. Our results provide a comprehensive perspective of estimates of epidemiological parameters for ASFV, allowing for increased transparency in accounting for parameter uncertainty in ASF preparedness modeling. Our meta-analysis also provides insight on knowledge gaps and study design issues that could be addressed by future experimentation.

immunology↗

bioRxiv2025

Spatial transmission dynamics of African Swine Fever in wild pigs: Sensitivity to epidemiological traits of different viral strains

African Swine Fever virus (ASFv) is a rapidly spreading animal disease with impacts on global economy and food security. Since the first known case of ASFv in Kenya in 1921, the virus has undergone significant evolution resulting in the emergence of 25 distinct genotypes. These genotypes have a wide variety of epidemiological traits, leading to uncertainty about how a genotype or variant of a genotype might spread in a population. Understanding the impacts of different epidemiological traits on the spread of ASFv is important for developing effective surveillance systems and control strategies. We developed a spatial epidemiological model of ASFv transmission in wild pigs, which contributes to ASFv persistence in countries where wild pig populations are widespread. We evaluated the impacts of a realistic set of epidemiological traits including incubation period, infectious period, disease-induced mortality rate, and length of immunity on spatial transmission dynamics under different ecological conditions for the host population (i.e. host density). We analyze effects of these conditions on outbreak metrics using boosted regression models with response variables: peak incidence, rate of spatial spread, seroprevalence and area invaded after one year, and probability that an outbreak will occur. We found that the infectious period of living individuals is the most important predictor at all pig densities for peak incidence and the area affected at one year, followed closely by the incubation period of the virus. We discuss considerations for surveillance and control strategies for different genotypes of ASFv.

ecology↗

bioRxiv2018

Evolution of subgenomic RNA shapes dengue virus adaptation and epidemiological fitness

Genetic changes in the dengue virus (DENV) genome affects viral fitness both clinically and epidemiologically. Even in the 3 untranslated region (3UTR), mutations could impact the formation of subgenomic flaviviral RNA (sfRNA) and the specificity of sfRNA in inhibiting host proteins necessary for successful viral replication. Indeed, we have recently shown that mutations in the 3UTR of DENV2 affected its ability to inhibit TRIM25 E3 ligase activity to reduce interferon (IFN) expression, which potentially contributed to the emergence of a new viral clade during the 1994 dengue epidemic in Puerto Rico. However, whether differences in 3UTRs shaped DENV evolution on a larger scale remains incompletely understood. Herein, we combined RNA phylogeny with phylogenetics to gain insights on sfRNA evolution. We found that sfRNA structures are under purifying selection and highly conserved despite sequence divergence. Interestingly, only the second flaviviral Nuclease-resistant RNA (fNR2) structure of DENV-2 has undergone strong positive selection. Epidemiological reports also suggest that nucleotide substitutions in fNR2 may drive DENV-2 epidemiological fitness, possibly through sfRNA-protein interactions. Collectively, our findings indicate that 3UTRs are important determinants of DENV fitness in human-mosquito cycles.\n\nHighlightsO_LIDengue viruses (DENV) preserve RNA elements in their 3 untranslated region (UTR).\nC_LIO_LISite-specific quantification of natural selection revealed positive selection on DENV2 sfRNA.\nC_LIO_LIFlaviviral nuclease-resistant RNA (fNR) structures in DENV 3UTRs contribute to DENV speciation.\nC_LIO_LIA highly evolving fNR structure appears to increase DENV-2 epidemiological fitness.\nC_LI

microbiology↗

bioRxiv2018

Core Genome Multi Locus Sequence Typing and Single Nucleotide Polymorphism Analysis in the Epidemiology of Brucella melitensis Infections

The use of whole genome sequencing (WGS) using next generation sequencing (NGS) technology has become a widely accepted method for microbiology laboratories in the application of molecular typing for outbreak tracing and genomic epidemiology. Several studies demonstrated the usefulness of WGS data analysis through Single Nucleotide Polymorphism (SNP) calling from a reference sequence analysis for Brucella melitensis, whereas gene-by-gene comparison through core-genome Multilocus Sequence Typing (cgMLST) has not been explored so far. The current study developed an allele-based method cgMLST and compared its performance to the genome-wide SNP approach and the traditional MLVA on a defined sample collection. The dataset comprised of 37 epidemiologically linked animal cases of brucellosis as well as 71 epidemiologically unrelated human and animal isolates collected in Italy. The cgMLST scheme generated in this study contained 2,687 targets of the B. melitensis 16M reference genome (75.4% of the complete genome). We established the potential criteria necessary for inclusion of an isolate into a brucellosis outbreak cluster to be [≤]4 loci in the cgMLST and [≤]10 in WGS SNP analysis. CgMLST and SNP analysis provided much higher phylogenetic distance resolution than MLVA, particularly for strains belonging to the same lineage thus allowing diverse and unrelated genotypes to be identified with greater confidence. The application of this cgMLST scheme to the characterization of B. melitensis strains provided insights into the epidemiology of this pathogen and it is a candidate to be a benchmark tool for outbreak investigations in human and animal brucellosis.

microbiology↗

bioRxiv2018

Genotyping and epidemiological metadata provides new insights into population structure of Xanthomonas isolated from walnut trees

Xanthomonas arboricola pv. juglandis (Xaj) is the etiological agent of walnut diseases affecting leaves, fruits, branches and trunks. Although this phytopathogen is widely spread in walnut producing regions and has a considerable genetic diversity, there is still a poor understanding of its epidemic behaviour. To shed some light on the epidemiology of these bacteria, 131 Xanthomonas isolates obtained from 64 walnut trees were included in this study considering epidemiological metadata such as year of isolation, bioclimatic regions, walnut cultivars, production regimes, host walnut specimen and plant organs. Genetic diversity was assessed by multilocus sequence analysis (MLSA) and dot blot hybridization patterns obtained with nine Xaj-specific DNA markers (XAJ1 - XAJ9). The results showed that Xanthomonas isolates grouped in ten distinct MLSA clusters and in 18 hybridization patterns (HP). The majority of isolates (112 out of 131) were closely related with X. arboricola strains of pathovar juglandis as revealed by MLSA (clusters I to VI) and hybridize with more than five Xaj-specific markers. Nineteen isolates clustered in four MLSA groups (clusters VII to X) which do not include Xaj strains, and hybridize to less than five markers. Taking this data together, was possible to distinguish 17 lineages of Xaj, three lineages of X. arboricola and 11 lineages of Xanthomonas sp. Some Xaj lineages appeared to be widely distributed and prevalent across the different bioclimatic regions and apparently not constrained by the other features considered. Assessment of type III effector genes and pathogenicity tests revealed that representative lineages of MLSA clusters VII to X were nonpathogenic on walnut, with exception for strain CPBF 424, making this bacterium particularly appealing to address Xanthomonas pathoadaptations to walnut.\n\nIMPORTANCEXanthomonas arboricola pv. juglandis is one of the most serious threats of walnut trees. New disease epidemics caused by this phytopathogen has been a big concern causing high economic losses on walnut production worldwide. Using a comprehensive sampling methodology to disclose the diversity of walnut infective Xanthomonas, we were able to identify a genetic diversity higher than previously reported and generally independent of bioclimatic regions and the other epidemiological features studied. Furthermore, co-colonization of the same plant sample by distinct Xanthomonas strains were frequent and suggested a sympatric lifestyle. The extensive sampling carried out resulted in a set of non-arboricola Xanthomonas sp. strains, including a pathogenic strain, therefore diverging from the nonpathogenic phenotype that have been associated to these atypical strains, generally considered to be commensal. This new strain might be particularly informative to elucidate novel pathogenicity traits and unveil pathogenesis evolution within walnut infective xanthomonads. Beyond extending the present knowledge about walnut infective xanthomonads, this study might contribute to provide a methodological framework for phytopathogen epidemiological studies, still largely disregarded.

microbiology↗

bioRxiv2026

Anopheles stephensi bionomics and epidemiology in Ethiopia: A systematic review and meta-analysis with implications for urban malaria control

BackgroundAnopheles stephensi, an invasive malaria vector originally endemic to South Asia, has rapidly expanded across East Africa. Its emerging malaria threats in urban Ethiopia threaten the elimination efforts, especially in areas once deemed low risk. A systematic review was conducted to synthesize the evidence regarding its bionomics and epidemiological impact, highlighting implications for urban malaria control strategies. This systematic review provides the first Ethiopia-specific quantitative evidence synthesis, addressing a vital knowledge gap necessary for guiding national malaria elimination programmes. MethodsWe conducted a PRISMA 2020-compliant systematic review and meta-analysis registered with PROSPERO (CRD420251176953). Searches of PubMed, Scopus, Web of Science, and regional repositories (2016-February 2026) identified studies reporting An. stephensi bionomics and epidemiological role in Ethiopia. Eligible studies required [≥]50% quality score on JBI appraisal tools. Random-effects meta-analysis estimated pooled proportions of An. stephensi among total Anopheles, with subgroup analyses by geography, habitat, and behavioural traits. Publication bias was assessed using Eggers and Beggs tests. ResultsEighteen studies (9 epidemiological, 11 bionomical) met inclusion criteria. The pooled proportion of An. stephensi was 0.51 (95% CI: 0.28-0.75) in epidemiological studies and 0.46 (95% CI: 0.26-0.66) in bionomics studies, with extreme heterogeneity (I{superscript 2} > 99%). Geographic analysis indicated significant variation: south-eastern Ethiopia showed a dominance of 0.73 (95% CI: 0.28-1.18) and eastern Ethiopia 0.57 (95% CI: 0.32-0.82), while central Ethiopia remained lower at 0.13 (95% CI: 0.12-0.14). These findings demonstrate genuine ecological differences rather than methodological objects, with substantial implications for region-specific vector management strategies. Extreme heterogeneity reflected genuine ecological variation across Ethiopia. No evidence of publication bias was detected. ConclusionAn. stephensi has very rapidly emerged as a major malaria vector in Ethiopia, with pooled proportions increasing from <10% at first detection (2016) to 51-73% in recent surveys (2024-2025), suggesting ongoing vector displacement parallel to invasion patterns documented in Djibouti. Geographic stratification indicates an urgent need for region-specific urban vector management integrating larval source management, resistance monitoring, and community engagement, particularly in south-eastern Ethiopia, where near-complete vector replacement has occurred. Author SummaryMalaria is usually thought of as a rural disease, but a new mosquito species called An. stephensi is changing that picture in Ethiopia. Originally found in South Asia, this mosquito has spread quickly across East Africa and is now common in Ethiopian towns and cities. We reviewed and combined results from published studies to understand how this species behaves and how much it contributes to malaria transmission. Our analysis shows that An. stephensi has become one of the dominant malaria vectors in several regions of Ethiopia, especially in the east and south-east, where it has almost replaced other mosquito species. This rapid change means that malaria risk is increasing in urban areas that were previously considered low risk. These findings highlight the urgent need for new control strategies that focus on city environments, such as managing breeding sites, monitoring insecticide resistance, and involving communities in prevention efforts. By understanding how An. stephensi is spreading and adapting, we can better protect urban populations and support Ethiopias malaria elimination goals.

microbiology↗

bioRxiv2026

Observation-masked neural posterior estimation for heterogeneous epidemiological surveillance data

Disease surveillance data are often sparse, irregularly timed and heterogeneous across observational units, creating challenges for inference in mechanistic epidemiological models. We present observation-masked neural posterior estimation (OM-NPE), a simulation-based Bayesian inference framework for such settings. The approach represents observations on a common temporal grid and records observation availability through a binary mask, enabling heterogeneous surveillance records to be analysed using a single amortised neural posterior estimator. We demonstrate OM-NPE using two contrasting epidemiological systems. First, we fit an effective SEIR model of Zika virus transmission to weekly sentinel surveillance data from six French Polynesian archipelagos during the 2013-14 outbreak. Second, we fit a stochastic compartmental model of Xylella fastidiosa spread to annual disease-severity observations from 17 olive groves in Apulia, Italy, each surveyed only two or three times over seven years. In both applications, OM-NPE recovered epidemiological parameters consistent with the assumed epidemiological and observation models, appropriately represented uncertainty, and generated posterior distributions in well under one second without retraining or Markov chain Monte Carlo sampling. Observation masking extends amortised Bayesian inference to heterogeneous longitudinal surveillance systems and supports rapid evaluation of alternative monitoring schedules.

systems biology↗

bioRxiv2018

Sample size calculation for estimating key epidemiological parameters using serological data and mathematical modelling

BackgroundOur work was motivated by the need to, given serum availability and/or financial resources, decide on which samples to test for different pathogens in a serum bank. Simulation-based sample size calculations were performed to determine the age-based sampling structures and optimal allocation of a given number of samples for testing across various age groups best suited to estimate key epidemiological parameters (e.g., seroprevalence or force of infection) with acceptable precision levels in a cross-sectional seroprevalence survey.\n\nMethodsStatistical and mathematical models and three age-based sampling structures (survey-based structure, population-based structure, uniform structure) were used. Our calculations are based on Belgian serological survey data collected in 2002 where testing was done, amongst others, for the presence of IgG antibodies against measles, mumps, and rubella, for which a national mass immunisation programme was introduced in 1985 in Belgium, and against varicella-zoster virus and parvovirus B19 for which the endemic equilibrium assumption is tenable in Belgium.\n\nResultsThe optimal age-based sampling structure to use in the sampling of a serological survey as well as the optimal allocation distribution varied depending on the epidemiological parameter of interest for a given infection and between infections.\n\nConclusionsWhen estimating key epidemiological parameters with acceptable levels of precision within the context of a single cross-sectional serological survey, attention should be given to the age-based sampling structure. Simulation-based sample size calculations in combination with mathematical modelling can be utilised for choosing the optimal allocation of a given number of samples over various age groups.

epidemiology↗

bioRxiv2018

Estimating the current burden of Chagas disease in Mexico: a systematic review of epidemiological surveys from 2006 to 2017

BackgroundIn Mexico, estimates of Chagas disease prevalence and burden vary widely. Updating surveillance data is therefore an important priority to ensure that Chagas disease does not remain a barrier to the development of Mexicos most vulnerable populations.\n\nMethodology/Principal FindingsThe aim of this systematic review was to analyze the literature on epidemiological surveys to estimate Chagas disease prevalence and burden in Mexico, during the period 2006 to 2017. A total of 2,764 articles were screened and 38 were retained for the final analysis. Epidemiological surveys have been performed in most of Mexico, but with variable geographic coverage. Based on studies reporting confirmed cases, i.e. using at least 2 serological tests, the national seroprevalence of Trypanosoma cruzi infection was 2.26% [95% Confidence Interval (CI) 2.12-2.41], suggesting that there are 2.71 million cases in Mexico. Studies focused on pregnant women, which may transmit the parasite to their newborn during pregnancy, reported a seroprevalence of 1.00% [95% CI 0.87-1.14], suggesting that there are 22,930 births from T. cruzi infected pregnant women per year, and 1,445 cases of congenitally infected newborns per year. Children under 18 years had a seropositivity rate of 1.49% [95% CI 1.20-1.85], which indicate ongoing transmission. Finally, cases of T. cruzi infection in blood donors have also been reported in most states, with a national seroprevalence of 0.51% [95% CI 0.49-0.53].\n\nConclusions/SignificanceOur analysis suggests a disease burden for T. cruzi infection higher than previously recognized, highlighting the urgency of establishing Chagas disease surveillance and control as a key national public health priority in Mexico, to ensure that it does not remain a major barrier to the economic and social development of the countrys most vulnerable populations.\n\nAuthor summaryIn Mexico, estimates of Chagas disease prevalence and burden vary widely due to the ecology and epidemiology of this disease resulting of many geographical, ecological, biological, and social interactions. Better data are thus urgently needed to help develop appropriate public health programs for disease control and patient care. In this study we analyzed published data on T. cruzi seroprevalence infection in Mexico between 2006 and 2017. This systematic review shows a national seroprevalence of T. cruzi infection of 2.26% [95%CI 2.12-2.41], with over 2.71 million cases in Mexico, which is higher than previously recognized. The presence of T. cruzi infection in specific subpopulations such as pregnant women, children and blood donors also informs on specific risks of infection and call for the implementation of well-established control interventions. This work confirms the place of Mexico as the country with the largest number of cases, highlighting the urgency of establishing Chagas disease control as a key national public health priority.

epidemiology↗

bioRxiv2019

Epidemic foci of hemorrhagic fever with renal syndrome in Shandong Province, China, based on patients, rodents and molecular epidemiology characteristics, 2012-2015

BackgroundHemorrhagic fever with renal syndrome (HFRS), an infectious disease caused by hantaviruses, is endemic in China and remains a serious public health problem. Historically, Shandong Province has had the largest HFRS burden in China. However, we do not have a comprehensive and clear understanding of the current epidemic foci of HFRS in Shandong Province.\n\nMethodology/Principal FindingsThe incidence and mortality rates were calculated, and a phylogenetic analysis was performed after laboratory testing of the virus in rodents. Spatial epidemiology analysis was applied to investigate the epidemic foci, including their sources. A total of 6,206 HFRS cases and 59 related deaths were reported in Shandong Province. The virus carriage rates of the rodents Rattus norvegicus, Apodemus agrarius and Mus musculus were 10.24%, 6.31% and 0.27%, respectively. The phylogenetic analysis indicated that two novel viruses isolated from R. norvegicus in Anqiu City and Qingzhou City were dissimilar to the other isolated strains, but closely related to strains previously isolated in northeastern China. Three epidemic foci were defined, two of which were derived from the Jining and Linyi epidemic foci, respectively, while the other was the residue of the Jining epidemic focus.\n\nConclusions/SignificanceThe southeastern and central Shandong Province are current key HFRS epidemic foci dominated by A. agrarius and R. norvegicus, respectively. Our study could help local departments to strengthen prevention and control measures in key areas to reduce the hazards of HFRS.\n\nAuthor summaryHemorrhagic fever with renal syndrome (HFRS) is a global infectious disease, which is still a serious public health threat in China today. The reported HFRS cases in Shandong Province accounted for approximate one third of total cases in the whole country. HFRS is a zoonosis mainly caused by Hantaan virus (HTNV) and Seoul virus (SEOV), which natural rodent hosts are A. agrarius and R. norvegicus, respectively. To explore the current HFRS epidemic foci based on patients, rodents and molecular epidemiology characteristics in Shandong Province, we collected the records of HFRS cases from whole province and the rodents captured in 14 surveillance sites. We found that the epidemic situation of HFRS is quiet different in temporal and spatial distribution. Three epidemic foci were defined based on patients, rodents and molecular epidemiology characteristics. The situation of HFRS epidemic foci in Shandong Province was clear. Our study provides a reference for relevant departments to develop key prevention strategies.

epidemiology↗

bioRxiv2019

The use of mixture-density networks in the emulation of complex epidemiological individual-based models

Complex, highly computational, individual-based models are abundant in epidemiology. For epidemics such as macro-parasitic diseases, detailed modelling of human behaviour and pathogen life-cycle are required in order to produce accurate results. This can often lead to models that are computationally-expensive to analyse and perform model fitting, and often require many simulation runs in order to build up sufficient statistics. Emulation can provide a more computationally-efficient output of the individual-based model, by approximating it using a statistical model. Previous work has used Gaussian processes in order to achieve this, but these can not deal with multi-modal, heavy-tailed, or discrete distributions. Here, we introduce the concept of a mixture density network (MDN) in its application in the emulation of epidemiological models. MDNs incorporate both a mixture model and a neural network to provide a flexible tool for emulating a variety of models and outputs. We develop an MDN emulation methodology and demonstrate its use on a number of simple models incorporating both normal, gamma and beta distribution outputs. We then explore its use on the stochastic SIR model to predict the final size distribution and infection dynamics. MDNs have the potential to faithfully reproduce multiple outputs of an individual-based model and allow for rapid analysis from a range of users. As such, an open-access library of the method has been released alongside this manuscript. Author summaryInfectious disease modellers have a growing need to expose their models to a variety of stakeholders in interactive, engaging ways that allow them to explore different scenarios. This approach can come with a considerable computational cost that motivates providing a simpler representation of the complex model. We propose the use of mixture density networks as a solution to this problem. These are highly flexible, deep neural network-based models that can emulate a variety of data, including counts and over-dispersion. We explore their use firstly through emulating a negative-binomial distribution, which arises in many places in ecology and parasite epidemiology. We then explore the approach using a stochastic SIR model. We also provide an accompanying Python library with code for all examples given in the manuscript. We believe that the use of emulation will provide a method to package an infectious disease model such that it can be disseminated to the widest audience possible.

epidemiology↗

bioRxiv2019

Analysis on epidemiological characteristics of 4 species natural-focal diseases in Shandong Province, China in 2009-2017: a descriptive analysis

BackgroundNatural-focal diseases have always been a kind of serious disease that endangers human health. It threatens about 100 million people in Shandong Province, and causes illness in thousands of people each year. However, information on the epidemiological characteristics of natural-focal diseases in Shandong Province has been limited. The purpose of the study is to describe and analyze the epidemiological characteristics of natural-focal diseases in Shandong Province, 2009-2017. MethodsWe describe the incidence and distribution of 4 species natural-focal diseases in Shandong Province using surveillance data from 2009-2017. ResultsFrom 2009-2017, 11123 cases of 4 species natural-focal diseases including 257 deaths were reported in Shandong Province, China. The 4 species natural-focal diseases were severe fever with thrombocytopenia syndrome (SFTS), human granulocytic anaplasmosis (HGA), typhus and scrub typhus respectively. The high-risk groups of the 4 species diseases all were farmers and the elderly. The incidence rate of scrub typhus was significantly higher in females, however, this difference was not seen in the other 3 diseases. The 4 species diseases were mainly clustered in middle-southern part of Shandong (Mount Yimeng) and Shandong Peninsula (Laoshan Mountain). The annual incidence of SFTS and scrub typhus had increased in the mass, typhus had been relatively stable, and HGA had declined. However, the popular range of SFTS had been expanding, HGA had been shrinking, and typhus and scrub typhus were unchanged. The epidemic period of SFTS and HGA was from May to October, typhus was from October to November, scrub typhus was from September to November in Shandong Province. The fatality rates of SFTS, typhus, scrub typhus, HGA were 9.19%, 0%, 0.01%, 2.24%, respectively. ConclusionsOur study described and analyzed the prevalence of natural-focal diseases in Shandong, and confirmed that age was closely related to the SFTS fatality rate. This study may be applicable to an improved understanding of the prevalence of natural-focal diseases in Shandong Province in recent years and the better development of the accurate prevention and control strategies for natural-focal diseases in Shandong Province. Author SummaryNatural-focal diseases are a serious public health problem in Shandong Province, China. It threatens about 100 million people in Shandong Province, and causes illness in thousands of people each year. This study used the monitoring data from Shandong Province for 2009-2017 to describe and analyze the epidemiological characteristics of the 4 species natural-focal diseases. The results showed that the risk population of natural-focal diseases in Shandong Province was farmers and the elderly, the epidemic season was mainly in summer and autumn, the middle-southern part of Shandong Province and Shandong Peninsula were more seriously affected compared with other regions. In addition, the epidemic area of SFTS was expanded, with a fatality rate of 9.19%. These findings indicated that public awareness of natural-focal diseases should be raised in the epidemic focus, especially for farmers, and further efforts should be strengthen specially in high-risk areas and during the epidemic season.

epidemiology↗

bioRxiv2019

Epidemiological consequences of enduring strain-specific immunity requiring repeated episodes of infection

Group A Streptococcus (GAS) skin infections are caused by a diverse array of strain types and are highly prevalent in Indigenous and other disadvantaged populations. The role of strain-specific immunity in preventing GAS infections is poorly understood, representing a critical knowledge gap in vaccine development. A recent GAS murine challenge study showed evidence that sterilising strain-specific and enduring immunity required two skin infections by the same GAS strain within three weeks. This mechanism of developing enduring immunity may be a significant impediment to the accumulation of immunity in populations.\n\nWe used a mathematical model of GAS transmission to investigate the epidemiological consequences of enduring strain-specific immunity developing only after two infections with the same strain within a specified interval. Accounting for uncertainty when correlating murine timeframes to humans, we varied this maximum inter-infection interval from 3 to 420 weeks to assess its impact on prevalence and strain diversity. Model outputs were compared with longitudinal GAS surveillance observations from northern Australia, a region with endemic infection. We also assessed the likely impact of a targeted strain-specific multivalent vaccine in this context.\n\nOur model produced patterns of transmission consistent with observations when the maximum inter-infection interval for developing enduring immunity was 19 weeks. Our vaccine analysis suggests that the leading multivalent GAS vaccine may have limited impact on the prevalence of GAS in populations in northern Australia if strain-specific immunity requires repeated episodes of infection.\n\nOur results suggest that observed GAS epidemiology from disease endemic settings is consistent with enduring strain-specific immunity being dependent on repeated infections with the same strain, and provide additional motivation for relevant human studies to confirm the human immune response to GAS skin infection.\n\nAuthor summaryGroup A Streptococcus (GAS) is a ubiquitous bacterial pathogen that exists in many distinct strains, and is a major cause of death and disability globally. Vaccines against GAS are under development, but their effective use will require better understanding of how immunity develops following infection. Evidence from an animal model of skin infection suggests that the generation of enduring strain-specific immunity requires two infections by the same strain within a short time frame. It is not clear if this mechanism of immune development operates in humans, nor how it would contribute to the persistence of GAS in populations and affect vaccine impact. We used a mathematical model of GAS transmission, calibrated to data collected in an Indigenous Australian community, to assess whether this mechanism of immune development is consistent with epidemiological observations, and to explore its implications for the impact of a vaccine. We found that it is plausible that repeat infections are required for the development of immunity in humans, and illustrate the difficulties associated with achieving sustained reductions in disease prevalence with a vaccine.

epidemiology↗