Epidemics最新文献

{"title":"Serodynamics: A primer and synthetic review of methods for epidemiological inference using serological data","authors":"James A. Hay ,&nbsp;Isobel Routledge ,&nbsp;Saki Takahashi","doi":"10.1016/j.epidem.2024.100806","DOIUrl":"10.1016/j.epidem.2024.100806","url":null,"abstract":"<div><div>We present a review and primer of methods to understand epidemiological dynamics and identify past exposures from serological data, referred to as serodynamics. We discuss processing and interpreting serological data prior to fitting serodynamical models, and review approaches for estimating epidemiological trends and past exposures, ranging from serocatalytic models applied to binary serostatus data, to more complex models incorporating quantitative antibody measurements and immunological understanding. Although these methods are seemingly disparate, we demonstrate how they are derived within a common mathematical framework. Finally, we discuss key areas for methodological development to improve scientific discovery and public health insights in seroepidemiology.</div></div>","PeriodicalId":49206,"journal":{"name":"Epidemics","volume":"49 ","pages":"Article 100806"},"PeriodicalIF":3.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11649536/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142796246","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Real-time estimates of the emergence and dynamics of SARS-CoV-2 variants of concern: A modeling approach","authors":"Nicolò Gozzi ,&nbsp;Matteo Chinazzi ,&nbsp;Jessica T. Davis ,&nbsp;Kunpeng Mu ,&nbsp;Ana Pastore y Piontti ,&nbsp;Marco Ajelli ,&nbsp;Alessandro Vespignani ,&nbsp;Nicola Perra","doi":"10.1016/j.epidem.2024.100805","DOIUrl":"10.1016/j.epidem.2024.100805","url":null,"abstract":"<div><div>The emergence of SARS-CoV-2 variants of concern (VOCs) punctuated the dynamics of the COVID-19 pandemic in multiple occasions. The stages subsequent to their identification have been particularly challenging due to the hurdles associated with a prompt assessment of transmissibility and immune evasion characteristics of the newly emerged VOC. Here, we retrospectively analyze the performance of a modeling strategy developed to evaluate, in real-time, the risks posed by the Alpha and Omicron VOC soon after their emergence. Our approach utilized multi-strain, stochastic, compartmental models enriched with demographic information, age-specific contact patterns, the influence of non-pharmaceutical interventions, and the trajectory of vaccine distribution. The models’ preliminary assessment about Omicron’s transmissibility and immune evasion closely match later findings. Additionally, analyses based on data collected since our initial assessments demonstrate the retrospective accuracy of our real-time projections in capturing the emergence and subsequent dominance of the Alpha VOC in seven European countries and the Omicron VOC in South Africa. This study shows the value of relatively simple epidemic models in assessing the impact of emerging VOCs in real time, the importance of timely and accurate data, and the need for regular evaluation of these methodologies as we prepare for future global health crises.</div></div>","PeriodicalId":49206,"journal":{"name":"Epidemics","volume":"49 ","pages":"Article 100805"},"PeriodicalIF":3.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142792598","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Building in-house capabilities in health agencies and outsourcing to academia or industry: Considerations for effective infectious disease modelling","authors":"Rachael Pung,&nbsp;Adam J. Kucharski","doi":"10.1016/j.epidem.2024.100802","DOIUrl":"10.1016/j.epidem.2024.100802","url":null,"abstract":"<div><div>Infectious disease models provide a systematic way to estimate crucial features of epidemic dynamics and explore different transmission and control scenarios. Given the importance of model-based analysis in managing public health crises, there has been an increase in post-pandemic creation of both academia-driven modelling centres, hubs and consortiums and government-driven public health agencies with in-house modelling units or teams. However, in the past, the delineation of roles and responsibilities between government- and academia-led modelling groups has often been unclear. Who should perform which tasks and when? This ambiguity can increase the risk of duplicated work or unaddressed gaps in analysis. It also raises questions about the sustainability of modelling capacity for addressing routine operational analytical needs while also developing new approaches that can be tailored for emergencies. In the sections below, we discuss factors that could inform decisions about where to locate infectious disease modelling activity. Rather than giving a fixed set of rules, we outlined key considerations and trade-offs that could be taken into account to enable academic and government modelling activities to complement each other effectively, which can in turn be refined as new public health crises emerge in future.</div></div>","PeriodicalId":49206,"journal":{"name":"Epidemics","volume":"49 ","pages":"Article 100802"},"PeriodicalIF":3.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142683156","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Hospital population density and risk of respiratory infection: Is close contact density dependent?","authors":"George Shirreff ,&nbsp;Anne C.M. Thiébaut ,&nbsp;Bich-Tram Huynh ,&nbsp;NODS-Cov2 Investigation Group ,&nbsp;Guillaume Chelius ,&nbsp;Antoine Fraboulet ,&nbsp;Didier Guillemot ,&nbsp;Lulla Opatowski ,&nbsp;Laura Temime","doi":"10.1016/j.epidem.2024.100807","DOIUrl":"10.1016/j.epidem.2024.100807","url":null,"abstract":"<div><div>Respiratory infections acquired in hospital depend on close contact, which may be affected by hospital population density. Models of infectious disease transmission typically assume that contact rates are independent of density (frequency dependence) or proportional to it (linear density dependence), without justification. We evaluate these assumptions by measuring contact rates in hospitals under different population densities. We analysed data from a study in 15 wards in which staff, patients and visitors carried wearable sensors which detected close contacts. We proposed a general model, non-linear density dependence, and fit this to data on several types of interactions. Finally, we projected the fitted models to predict the effect of increasing population density on epidemic risk. We identified considerable heterogeneity in density dependence between wards, even those with the same medical specialty. Interactions between all persons present usually depended little on the population density. However, increasing patient density was associated with higher rates of patient contact for staff and for other patients. Simulations suggested that a 10 % increase in patient population density would carry a markedly increased risk in many wards. This study highlights the variance in density dependent dynamics and the complexity of predicting contact rates.</div></div>","PeriodicalId":49206,"journal":{"name":"Epidemics","volume":"49 ","pages":"Article 100807"},"PeriodicalIF":3.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142796175","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Forecasting SARS-CoV-2 epidemic dynamic in Poland with the pDyn agent-based model","authors":"Karol Niedzielewski ,&nbsp;Rafał P. Bartczuk ,&nbsp;Natalia Bielczyk ,&nbsp;Dominik Bogucki ,&nbsp;Filip Dreger ,&nbsp;Grzegorz Dudziuk ,&nbsp;Łukasz Górski ,&nbsp;Magdalena Gruziel-Słomka ,&nbsp;Jędrzej Haman ,&nbsp;Artur Kaczorek ,&nbsp;Jan Kisielewski ,&nbsp;Bartosz Krupa ,&nbsp;Antoni Moszyński ,&nbsp;Jędrzej M. Nowosielski ,&nbsp;Maciej Radwan ,&nbsp;Marcin Semeniuk ,&nbsp;Urszula Tymoszuk ,&nbsp;Jakub Zieliński ,&nbsp;Franciszek Rakowski","doi":"10.1016/j.epidem.2024.100801","DOIUrl":"10.1016/j.epidem.2024.100801","url":null,"abstract":"<div><div>We employ pDyn (derived from “pandemics dynamics”), an agent-based epidemiological model, to forecast the fourth wave of the SARS-CoV-2 epidemic, primarily driven by the Delta variant, in Polish society. The model captures spatiotemporal dynamics of the epidemic spread, predicting disease-related states based on pathogen properties and behavioral factors. We assess pDyn’s validity, encompassing pathogen variant succession, immunization level, and the proportion of vaccinated among confirmed cases. We evaluate its predictive capacity for pandemic dynamics, including wave peak timing, magnitude, and duration for confirmed cases, hospitalizations, ICU admissions, and deaths, nationally and regionally in Poland. Validation involves comparing pDyn’s estimates with real-world data (excluding data used for calibration) to evaluate whether pDyn accurately reproduced the epidemic dynamics up to the simulation time. To assess the accuracy of pDyn’s predictions, we compared simulation results with real-world data acquired after the simulation date. The findings affirm pDyn’s accuracy in forecasting and enhancing our understanding of epidemic mechanisms.</div></div>","PeriodicalId":49206,"journal":{"name":"Epidemics","volume":"49 ","pages":"Article 100801"},"PeriodicalIF":3.0,"publicationDate":"2024-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142649434","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimizing spatial distribution of wastewater-based epidemiology to advance health equity","authors":"Maria L. Daza-Torres ,&nbsp;J. Cricelio Montesinos-López ,&nbsp;César Herrera ,&nbsp;Yury E. García ,&nbsp;Colleen C. Naughton ,&nbsp;Heather N. Bischel ,&nbsp;Miriam Nuño","doi":"10.1016/j.epidem.2024.100804","DOIUrl":"10.1016/j.epidem.2024.100804","url":null,"abstract":"<div><div>In 2022, the US Centers for Disease Control and Prevention commissioned the National Academies of Sciences, Engineering, and Medicine to assess the role of community-level wastewater-based epidemiology (WBE) beyond COVID-19. WBE is recognized as a promising mechanism for promptly identifying infectious diseases, including COVID-19 and other novel pathogens. An important conclusion from this initiative is the critical importance of maintaining equity and expanding access to fully realize the benefits of wastewater surveillance for marginalized communities. To address this need, we propose an optimization framework that strategically allocates wastewater monitoring resources at the wastewater treatment plant (WWTP) level, ensuring more effective and equitable distribution of surveillance efforts to serve underserved populations.</div><div>The purpose of the framework is to obtain a balanced spatial distribution, inclusive population coverage, and efficient representation of disadvantaged groups in the allocation of resources for WBE. Furthermore, the framework concentrates on areas with high population density and gives priority to vulnerable regions, as well as identifying signals that display significant variations from other monitored sources. The optimization objective is to maximize a weighted combination of these critical factors. This problem is formulated as an integer optimization problem and solved using simulated annealing. We evaluate various scenarios, considering different weighting factors, to optimize the allocation of WWTPs with monitoring systems. This optimization framework provides an opportunity to enhance WBE by providing customized monitoring strategies created to address specific priorities and situations, thus enhancing the decision-making processes in public health responses.</div></div>","PeriodicalId":49206,"journal":{"name":"Epidemics","volume":"49 ","pages":"Article 100804"},"PeriodicalIF":3.0,"publicationDate":"2024-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142644710","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Direct and indirect effects of hepatitis B vaccination in four low- and middle-income countries","authors":"Margaret J. de Villiers ,&nbsp;Edward de Villiers ,&nbsp;Shevanthi Nayagam ,&nbsp;Timothy B. Hallett","doi":"10.1016/j.epidem.2024.100798","DOIUrl":"10.1016/j.epidem.2024.100798","url":null,"abstract":"<div><div>Population-level vaccination effects of the hepatitis B vaccine were investigated in four low- and middle-income countries with different levels of vertical and horizontal transmission. Indirect vaccination effects constitute a large proportion of overall vaccination effects of the vaccination programmes in all four countries (over 70% by 2030 in all four countries). However, countries with higher levels of vertical transmission benefit less from indirect vaccination effects from the infant hepatitis B vaccine series during the first decades of the vaccination programme, making the birth dose vaccine more important in these countries. Vaccination, even at levels that do not fully control transmission, has a great effect on the development of disease as it also increases the average age of infection, thereby causing a decrease in the number of chronic infections relative to the number of acute infections.</div></div>","PeriodicalId":49206,"journal":{"name":"Epidemics","volume":"49 ","pages":"Article 100798"},"PeriodicalIF":3.0,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142631155","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modelling plausible scenarios for the Omicron SARS-CoV-2 variant from early-stage surveillance","authors":"Christopher J. Banks ,&nbsp;Ewan Colman ,&nbsp;Anthony J. Wood ,&nbsp;Thomas Doherty ,&nbsp;Rowland R. Kao","doi":"10.1016/j.epidem.2024.100800","DOIUrl":"10.1016/j.epidem.2024.100800","url":null,"abstract":"<div><div>We used a spatially explicit agent-based model of SARS-CoV-2 transmission combined with spatially fine-grained COVID-19 observation data from Public Health Scotland to investigate the initial rise of the Omicron (BA.1) variant of concern. We evaluated plausible scenarios for transmission rate advantage and vaccine immune escape relative to the Delta variant based on the data that would have been available at that time. We also explored possible outcomes of different levels of imposed non-pharmaceutical intervention. The initial results of these scenarios were used to inform the Scottish Government in the early outbreak stages of the Omicron variant.</div><div>Using the model with parameters fit over the Delta variant epidemic, some initial assumptions about Omicron transmission rate advantage and vaccine escape, and a simple growth rate fitting procedure, we were able to capture the initial outbreak dynamics for Omicron. We found that the modelled dynamics hold up to retrospective scrutiny. The modelled imposition of extra non-pharmaceutical interventions planned by the Scottish Government at the time would likely have little effect in light of the transmission rate advantage held by the Omicron variant and the fact that the planned interventions would have occurred too late in the outbreak’s trajectory. Finally, we found that any assumptions made about the projected distribution of vaccines in the model population had little bearing on the outcome, in terms of outbreak size and timing. Instead, it was the landscape of prior immunity that was most important.</div></div>","PeriodicalId":49206,"journal":{"name":"Epidemics","volume":"49 ","pages":"Article 100800"},"PeriodicalIF":3.0,"publicationDate":"2024-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142689487","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Estimating pathogen spread using structured coalescent and birth–death models: A quantitative comparison","authors":"Sophie Seidel,&nbsp;Tanja Stadler ,&nbsp;Timothy G. Vaughan","doi":"10.1016/j.epidem.2024.100795","DOIUrl":"10.1016/j.epidem.2024.100795","url":null,"abstract":"<div><div>Elucidating disease spread between subpopulations is crucial in guiding effective disease control efforts. Genomic epidemiology and phylodynamics have emerged as key principles to estimate such spread from pathogen phylogenies derived from molecular data. Two well-established structured phylodynamic methodologies – based on the coalescent and the birth–death model – are frequently employed to estimate viral spread between populations. Nonetheless, these methodologies operate under distinct assumptions whose impact on the accuracy of migration rate inference is yet to be thoroughly investigated.</div><div>In this manuscript, we present a simulation study, contrasting the inferential outcomes of the structured coalescent model with constant population size and the multitype birth–death model with a constant rate. We explore this comparison across a range of migration rates in endemic diseases and epidemic outbreaks. The results of the epidemic outbreak analysis revealed that the birth–death model exhibits a superior ability to retrieve accurate migration rates compared to the coalescent model, regardless of the actual migration rate. Thus, to estimate accurate migration rates, the population dynamics have to be accounted for. On the other hand, for the endemic disease scenario, our investigation demonstrates that both models produce comparable coverage and accuracy of the migration rates, with the coalescent model generating more precise estimates. Regardless of the specific scenario, both models similarly estimated the source location of the disease.</div><div>This research offers tangible modelling advice for infectious disease analysts, suggesting the use of either model for endemic diseases. For epidemic outbreaks, or scenarios with varying population size, structured phylodynamic models relying on the Kingman coalescent with constant population size should be avoided as they can lead to inaccurate estimates of the migration rate. Instead, coalescent models accounting for varying population size or birth–death models should be favoured. Importantly, our study emphasises the value of directly capturing exponential growth dynamics which could be a useful enhancement for structured coalescent models.</div></div>","PeriodicalId":49206,"journal":{"name":"Epidemics","volume":"49 ","pages":"Article 100795"},"PeriodicalIF":3.0,"publicationDate":"2024-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142511437","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Quantifying the impact of prevalence-dependent adaptive behavior on COVID-19 transmission: A modeling case study in Maryland","authors":"Alexander Tulchinsky ,&nbsp;Gary Lin ,&nbsp;Alisa Hamilton ,&nbsp;Nodar Kipshidze ,&nbsp;Eili Klein","doi":"10.1016/j.epidem.2024.100799","DOIUrl":"10.1016/j.epidem.2024.100799","url":null,"abstract":"<div><div>The COVID-19 pandemic highlighted the need for robust epidemic forecasts, projecting health burden over short- and medium-term time horizons. Many COVID-19 forecasting models incorporate information on infection transmission, disease progression, and the effects of interventions, but few combine information on how individuals change their behavior based on altruism, fear, risk perception, or personal economic circumstances. Moreover, early models of COVID-19 produced under- and over-estimates, failing to consider the complexity of human responses to disease threat and prevention measures. In this study, we modeled adaptive behavior during the first year of the COVID-19 pandemic in Maryland, USA. The adapted compartmental model incorporates time-varying transmissibility informed on data of environmental factors (e.g., absolute humidity) and behavioral factors (aggregate mobility and perceived risk). We show that humidity and mobility alone did little to explain transmissibility after the first 100 days. Including adaptive behavior in the form of perceived risk as a function of hospitalizations more effectively explained inferred transmissibility and improved out-of-sample fit, demonstrating the model’s potential in real-time forecasting. These results demonstrate the importance of incorporating endogenous behavior in models, particularly during a pandemic, to produce more accurate projections, which could lead to more impactful and efficient decision making and resource allocation.</div></div>","PeriodicalId":49206,"journal":{"name":"Epidemics","volume":"49 ","pages":"Article 100799"},"PeriodicalIF":3.0,"publicationDate":"2024-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142445877","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}