Pub Date : 2024-11-06DOI: 10.1016/j.epidem.2024.100798
Margaret J. de Villiers , Edward de Villiers , Shevanthi Nayagam , Timothy B. Hallett
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.
{"title":"Direct and indirect effects of hepatitis B vaccination in four low- and middle-income countries","authors":"Margaret J. de Villiers , Edward de Villiers , Shevanthi Nayagam , 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}
Pub Date : 2024-11-04DOI: 10.1016/j.epidem.2024.100800
Christopher J. Banks , Ewan Colman , Anthony J. Wood , Thomas Doherty , Rowland R. Kao
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.
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.
{"title":"Modelling plausible scenarios for the Omicron SARS-CoV-2 variant from early-stage surveillance","authors":"Christopher J. Banks , Ewan Colman , Anthony J. Wood , Thomas Doherty , 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}
Pub Date : 2024-10-18DOI: 10.1016/j.epidem.2024.100795
Sophie Seidel, Tanja Stadler , Timothy G. Vaughan
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.
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.
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.
{"title":"Estimating pathogen spread using structured coalescent and birth–death models: A quantitative comparison","authors":"Sophie Seidel, Tanja Stadler , 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}
Pub Date : 2024-10-11DOI: 10.1016/j.epidem.2024.100799
Alexander Tulchinsky , Gary Lin , Alisa Hamilton , Nodar Kipshidze , Eili Klein
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.
{"title":"Quantifying the impact of prevalence-dependent adaptive behavior on COVID-19 transmission: A modeling case study in Maryland","authors":"Alexander Tulchinsky , Gary Lin , Alisa Hamilton , Nodar Kipshidze , 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}
Pub Date : 2024-10-10DOI: 10.1016/j.epidem.2024.100797
Yiu Chung Lau , Sukhyun Ryu , Zhanwei Du , Lin Wang , Peng Wu , Eric H.Y. Lau , Benjamin J. Cowling , Sheikh Taslim Ali
The public health and social measures (PHSMs) for mitigation/control of COVID-19 pandemic influenced the transmission dynamics of many other infectious diseases, including respiratory syncytial virus (RSV) infection, and hand, foot and mouth disease (HFMD) and their disease-burden. This study aimed to infer the transmission dynamics of these respiratory viruses and assess the impact of COVID-19 PHSMs on their community activity. We developed a compartmental framework to infer the transmission dynamics of RSV and HFMD in Hong Kong and South Korea from January 2014 to May 2024. We assessed the impact of PHSMs by comparing the change in virus transmissibility, reproduction number and population susceptibility before, during, and after the COVID-19 pandemic period. A significant reduction in RSV and HFMD activity was observed starting in January 2020, with a resurgence since late 2021. Transmissibility of both diseases decreased by 46 % - 95 % during the lull, while population susceptibility was estimated to increase by maximum of 19 %. On relaxation of the PHSMs, the transmissibility were recovered up to 70 % in Hong Kong and nearly 100 % in South Korea in 2023 with significant epidemics for these viruses. Strict implementation of COVID-19 PHSMs led to low RSV and HFMD activity, but the absence of community infection resulted in reductions in population immunity, and slightly larger epidemics when these diseases re-emerged following the COVID-19 pandemic.
{"title":"Impact of COVID-19 control measures on respiratory syncytial virus and hand-foot-and-mouth disease transmission in Hong Kong and South Korea","authors":"Yiu Chung Lau , Sukhyun Ryu , Zhanwei Du , Lin Wang , Peng Wu , Eric H.Y. Lau , Benjamin J. Cowling , Sheikh Taslim Ali","doi":"10.1016/j.epidem.2024.100797","DOIUrl":"10.1016/j.epidem.2024.100797","url":null,"abstract":"<div><div>The public health and social measures (PHSMs) for mitigation/control of COVID-19 pandemic influenced the transmission dynamics of many other infectious diseases, including respiratory syncytial virus (RSV) infection, and hand, foot and mouth disease (HFMD) and their disease-burden. This study aimed to infer the transmission dynamics of these respiratory viruses and assess the impact of COVID-19 PHSMs on their community activity. We developed a compartmental framework to infer the transmission dynamics of RSV and HFMD in Hong Kong and South Korea from January 2014 to May 2024. We assessed the impact of PHSMs by comparing the change in virus transmissibility, reproduction number and population susceptibility before, during, and after the COVID-19 pandemic period. A significant reduction in RSV and HFMD activity was observed starting in January 2020, with a resurgence since late 2021. Transmissibility of both diseases decreased by 46 % - 95 % during the lull, while population susceptibility was estimated to increase by maximum of 19 %. On relaxation of the PHSMs, the transmissibility were recovered up to 70 % in Hong Kong and nearly 100 % in South Korea in 2023 with significant epidemics for these viruses. Strict implementation of COVID-19 PHSMs led to low RSV and HFMD activity, but the absence of community infection resulted in reductions in population immunity, and slightly larger epidemics when these diseases re-emerged following the COVID-19 pandemic.</div></div>","PeriodicalId":49206,"journal":{"name":"Epidemics","volume":"49 ","pages":"Article 100797"},"PeriodicalIF":3.0,"publicationDate":"2024-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142478826","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}
Pub Date : 2024-10-05DOI: 10.1016/j.epidem.2024.100796
Alex Viguerie , Chaitra Gopalappa , Cynthia M. Lyles , Paul G. Farnham
Background
The OraQuick In-Home HIV self-test represents a fast, inexpensive, and convenient method for users to assess their HIV status. If integrated thoughtfully into existing testing practices, accompanied by efficient pathways to formal diagnosis, self-testing could enhance both HIV awareness and reduce HIV incidence. However, currently available self-tests are less sensitive, particularly for recent infection, when compared to gold-standard laboratory tests. It is important to understand the impact if some portion of standard testing is replaced by self-tests. We used a compartmental model to evaluate the effects of self-testing in diverse scenarios among gay, bisexual and other men who have sex with men (MSM) in the United States for the period 2020–2030, and to understand which scenarios maximize the advantages of self-testing.
Methods
We introduced a novel 4-compartment model for HIV self-testing. We employed the model under different screening rates, self-test proportions, and delays to diagnosis for those identified through self-tests to determine the potential effects of self-testing on HIV incidence and awareness of status when applied to the US MSM population. We studied scenarios in which self-tests supplement laboratory-based tests, with no replacement, and scenarios in which some replacement occurs. We also examined how future improvements in self-test sensitivity may affect our results.
Results
When HIV self-tests are supplemental rather than substitutes for laboratory-based testing, self-testing can decrease HIV incidence among MSM in the US by up to 10 % and increase awareness of status among MSM from 85 % to 91 % over a 10-year period, provided linkage to care and formal diagnosis occur promptly following a positive self-test (90 days or less). As self-tests replace a higher percentage laboratory-based testing algorithms, increases in overall testing rates were necessary to ensure reductions in HIV incidence. However, such needed increases were relatively small (under 10 % for prompt engagement in care and moderate levels of replacement). Improvements in self-test sensitivity and/or decreases in the detection period may further reduce any necessary increases in overall testing by up to 40 %.
Conclusions
If properly utilized, self-testing can provide significant long-term reductions to HIV incidence and improve awareness of HIV status. Ensuring that self-testing increases overall testing and that formal diagnosis and engagement in care occur promptly following a positive self-test are necessary to maximize the benefits of self-testing. Future improvements in self-test sensitivity and reductions in the detection period would further reduce HIV incidence and the potential risks associated with replacing laboratory tests with self-tests.
背景：OraQuick 居家 HIV 自我检测是一种快速、廉价、方便的方法，用户可以通过它来评估自己的 HIV 感染状况。如果能将其与现有的检测方法周到地结合起来，并辅以高效的正规诊断途径，那么自我检测既能提高人们对艾滋病的认识，又能降低艾滋病的发病率。然而，与黄金标准的实验室检测相比，目前可用的自我检测灵敏度较低，尤其是对近期感染的检测。了解由自我检测取代部分标准检测的影响非常重要。我们使用了一个分室模型来评估 2020-2030 年期间在美国男同性恋、双性恋和其他男男性行为者（MSM）中不同情况下自我检测的影响，并了解哪种情况能最大限度地发挥自我检测的优势：方法：我们为 HIV 自我检测引入了一个新颖的四室模型。我们在不同的筛查率、自我检测比例以及通过自我检测发现者的诊断延迟条件下使用了该模型，以确定自我检测在应用于美国男男性行为人群时对 HIV 感染率和感染状况认知度的潜在影响。我们研究了自我检测作为实验室检测的补充（不存在替代）和存在一定替代的两种情况。我们还研究了未来自我检测灵敏度的提高会如何影响我们的结果：结果：如果艾滋病毒自我检测是实验室检测的补充而非替代，那么自我检测可在 10 年内将美国男男性行为者中的艾滋病毒发病率降低 10%，并将男男性行为者对自身状况的认知度从 85% 提高到 91%，前提是在自我检测呈阳性后（90 天或更短）及时联系医疗机构并进行正式诊断。由于自我检测取代了较高比例的实验室检测算法，因此有必要提高总体检测率，以确保降低艾滋病毒发病率。然而，这种所需的提高幅度相对较小（对于及时参与护理和中等程度的替代来说，低于 10%）。自我检测灵敏度的提高和/或检测期的缩短可能会进一步减少总体检测率的必要增长，增幅可达 40%：如果使用得当，自我检测可显著降低艾滋病的长期发病率，并提高人们对艾滋病状况的认识。要使自我检测的益处最大化，就必须确保自我检测能提高总体检测率，并在自我检测呈阳性后及时进行正式诊断和参与护理。未来自我检测灵敏度的提高和检测周期的缩短将进一步降低艾滋病毒的发病率，并降低用自我检测取代实验室检测的潜在风险。
{"title":"The effects of HIV self-testing on HIV incidence and awareness of status among men who have sex with men in the United States: Insights from a novel compartmental model","authors":"Alex Viguerie , Chaitra Gopalappa , Cynthia M. Lyles , Paul G. Farnham","doi":"10.1016/j.epidem.2024.100796","DOIUrl":"10.1016/j.epidem.2024.100796","url":null,"abstract":"<div><h3>Background</h3><div>The OraQuick In-Home HIV self-test represents a fast, inexpensive, and convenient method for users to assess their HIV status. If integrated thoughtfully into existing testing practices, accompanied by efficient pathways to formal diagnosis, self-testing could enhance both HIV awareness and reduce HIV incidence. However, currently available self-tests are less sensitive, particularly for recent infection, when compared to gold-standard laboratory tests. It is important to understand the impact if some portion of standard testing is replaced by self-tests. We used a compartmental model to evaluate the effects of self-testing in diverse scenarios among gay, bisexual and other men who have sex with men (MSM) in the United States for the period 2020–2030, and to understand which scenarios maximize the advantages of self-testing.</div></div><div><h3>Methods</h3><div>We introduced a novel 4-compartment model for HIV self-testing. We employed the model under different screening rates, self-test proportions, and delays to diagnosis for those identified through self-tests to determine the potential effects of self-testing on HIV incidence and awareness of status when applied to the US MSM population. We studied scenarios in which self-tests supplement laboratory-based tests, with no replacement, and scenarios in which some replacement occurs. We also examined how future improvements in self-test sensitivity may affect our results.</div></div><div><h3>Results</h3><div>When HIV self-tests are supplemental rather than substitutes for laboratory-based testing, self-testing can decrease HIV incidence among MSM in the US by up to 10 % and increase awareness of status among MSM from 85 % to 91 % over a 10-year period, provided linkage to care and formal diagnosis occur promptly following a positive self-test (90 days or less). As self-tests replace a higher percentage laboratory-based testing algorithms, increases in overall testing rates were necessary to ensure reductions in HIV incidence. However, such needed increases were relatively small (under 10 % for prompt engagement in care and moderate levels of replacement). Improvements in self-test sensitivity and/or decreases in the detection period may further reduce any necessary increases in overall testing by up to 40 %.</div></div><div><h3>Conclusions</h3><div>If properly utilized, self-testing can provide significant long-term reductions to HIV incidence and improve awareness of HIV status. Ensuring that self-testing increases overall testing and that formal diagnosis and engagement in care occur promptly following a positive self-test are necessary to maximize the benefits of self-testing. Future improvements in self-test sensitivity and reductions in the detection period would further reduce HIV incidence and the potential risks associated with replacing laboratory tests with self-tests.</div></div>","PeriodicalId":49206,"journal":{"name":"Epidemics","volume":"49 ","pages":"Article 100796"},"PeriodicalIF":3.0,"publicationDate":"2024-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142382152","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}
Pub Date : 2024-09-26DOI: 10.1016/j.epidem.2024.100793
Chen Chen , Yunfan Wang , Gursharn Kaur , Aniruddha Adiga , Baltazar Espinoza , Srinivasan Venkatramanan , Andrew Warren , Bryan Lewis , Justin Crow , Rekha Singh , Alexandra Lorentz , Denise Toney , Madhav Marathe
The pandemic of COVID-19 has imposed tremendous pressure on public health systems and social economic ecosystems over the past years. To alleviate its social impact, it is important to proactively track the prevalence of COVID-19 within communities. The traditional way to estimate the disease prevalence is to estimate from reported clinical test data or surveys. However, the coverage of clinical tests is often limited and the tests can be labor-intensive, requires reliable and timely results, and consistent diagnostic and reporting criteria. Recent studies revealed that patients who are diagnosed with COVID-19 often undergo fecal shedding of SARS-CoV-2 virus into wastewater, which makes wastewater-based epidemiology for COVID-19 surveillance a promising approach to complement traditional clinical testing. In this paper, we survey the existing literature regarding wastewater-based epidemiology for COVID-19 surveillance and summarize the current advances in the area. Specifically, we have covered the key aspects of wastewater sampling, sample testing, and presented a comprehensive and organized summary of wastewater data analytical methods. Finally, we provide the open challenges on current wastewater-based COVID-19 surveillance studies, aiming to encourage new ideas to advance the development of effective wastewater-based surveillance systems for general infectious diseases.
{"title":"Wastewater-based epidemiology for COVID-19 surveillance and beyond: A survey","authors":"Chen Chen , Yunfan Wang , Gursharn Kaur , Aniruddha Adiga , Baltazar Espinoza , Srinivasan Venkatramanan , Andrew Warren , Bryan Lewis , Justin Crow , Rekha Singh , Alexandra Lorentz , Denise Toney , Madhav Marathe","doi":"10.1016/j.epidem.2024.100793","DOIUrl":"10.1016/j.epidem.2024.100793","url":null,"abstract":"<div><div>The pandemic of COVID-19 has imposed tremendous pressure on public health systems and social economic ecosystems over the past years. To alleviate its social impact, it is important to proactively track the prevalence of COVID-19 within communities. The traditional way to estimate the disease prevalence is to estimate from reported clinical test data or surveys. However, the coverage of clinical tests is often limited and the tests can be labor-intensive, requires reliable and timely results, and consistent diagnostic and reporting criteria. Recent studies revealed that patients who are diagnosed with COVID-19 often undergo fecal shedding of SARS-CoV-2 virus into wastewater, which makes wastewater-based epidemiology for COVID-19 surveillance a promising approach to complement traditional clinical testing. In this paper, we survey the existing literature regarding wastewater-based epidemiology for COVID-19 surveillance and summarize the current advances in the area. Specifically, we have covered the key aspects of wastewater sampling, sample testing, and presented a comprehensive and organized summary of wastewater data analytical methods. Finally, we provide the open challenges on current wastewater-based COVID-19 surveillance studies, aiming to encourage new ideas to advance the development of effective wastewater-based surveillance systems for general infectious diseases.</div></div>","PeriodicalId":49206,"journal":{"name":"Epidemics","volume":"49 ","pages":"Article 100793"},"PeriodicalIF":3.0,"publicationDate":"2024-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142367150","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}
Pub Date : 2024-09-21DOI: 10.1016/j.epidem.2024.100794
Hélène Duault , Benoit Durand , Laetitia Canini
In a multi-host system, understanding host-species contribution to transmission is key to appropriately targeting control and preventive measures. Outbreak reconstruction methods aiming to identify who-infected-whom by combining epidemiological and genetic data could contribute to achieving this goal. However, the majority of these methods remain untested on realistic simulated multi-host data. Mycobacterium bovis is a slowly evolving multi-host pathogen and previous studies on outbreaks involving both cattle and wildlife have identified observation biases. Indeed, contrary to cattle, sampling wildlife is difficult. The aim of our study was to evaluate and compare the performances of three existing outbreak reconstruction methods (seqTrack, outbreaker2 and TransPhylo) on M. bovis multi-host data simulated with and without biases. Extending an existing transmission model, we simulated 30 bTB outbreaks involving cattle, badgers and wild boars and defined six sampling schemes mimicking observation biases. We estimated general and specific to multi-host systems epidemiological indicators. We tested four alternative transmission scenarios changing the mutation rate or the composition of the epidemiological system. The reconstruction of who-infected-whom was sensitive to the mutation rate and seqTrack reconstructed prolific super-spreaders. TransPhylo and outbreaker2 poorly estimated the contribution of each host-species and could not reconstruct the presence of a dead-end epidemiological host. However, the host-species of cattle (but not badger) index cases was correctly reconstructed by seqTrack and outbreaker2. These two specific indicators improved when considering an observation bias. We found an overall poor performance for the three methods on simulated biased and unbiased bTB data. This seemed partly attributable to the low evolutionary rate characteristic of M. bovis leading to insufficient genetic information, but also to the complexity of the simulated multi-host system. This study highlights the importance of an integrated approach and the need to develop new outbreak reconstruction methods adapted to complex epidemiological systems and tested on realistic multi-host data.
{"title":"Outbreak reconstruction with a slowly evolving multi-host pathogen: A comparative study of three existing methods on Mycobacterium bovis outbreaks","authors":"Hélène Duault , Benoit Durand , Laetitia Canini","doi":"10.1016/j.epidem.2024.100794","DOIUrl":"10.1016/j.epidem.2024.100794","url":null,"abstract":"<div><div>In a multi-host system, understanding host-species contribution to transmission is key to appropriately targeting control and preventive measures. Outbreak reconstruction methods aiming to identify who-infected-whom by combining epidemiological and genetic data could contribute to achieving this goal. However, the majority of these methods remain untested on realistic simulated multi-host data. <em>Mycobacterium bovis</em> is a slowly evolving multi-host pathogen and previous studies on outbreaks involving both cattle and wildlife have identified observation biases. Indeed, contrary to cattle, sampling wildlife is difficult. The aim of our study was to evaluate and compare the performances of three existing outbreak reconstruction methods (<em>seqTrack</em>, <em>outbreaker2</em> and <em>TransPhylo</em>) on <em>M. bovis</em> multi-host data simulated with and without biases. Extending an existing transmission model, we simulated 30 bTB outbreaks involving cattle, badgers and wild boars and defined six sampling schemes mimicking observation biases. We estimated general and specific to multi-host systems epidemiological indicators. We tested four alternative transmission scenarios changing the mutation rate or the composition of the epidemiological system. The reconstruction of who-infected-whom was sensitive to the mutation rate and <em>seqTrack</em> reconstructed prolific super-spreaders. <em>TransPhylo</em> and <em>outbreaker2</em> poorly estimated the contribution of each host-species and could not reconstruct the presence of a dead-end epidemiological host. However, the host-species of cattle (but not badger) index cases was correctly reconstructed by <em>seqTrack</em> and <em>outbreaker2</em>. These two specific indicators improved when considering an observation bias. We found an overall poor performance for the three methods on simulated biased and unbiased bTB data. This seemed partly attributable to the low evolutionary rate characteristic of <em>M. bovis</em> leading to insufficient genetic information, but also to the complexity of the simulated multi-host system. This study highlights the importance of an integrated approach and the need to develop new outbreak reconstruction methods adapted to complex epidemiological systems and tested on realistic multi-host data.</div></div>","PeriodicalId":49206,"journal":{"name":"Epidemics","volume":"49 ","pages":"Article 100794"},"PeriodicalIF":3.0,"publicationDate":"2024-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142319703","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}
Pub Date : 2024-09-11DOI: 10.1016/j.epidem.2024.100790
Isaac Osei , Emmanuel Mendy , Kevin van Zandvoort , Olimatou Jobe , Golam Sarwar , Baleng Mahama Wutor , Stefan Flasche , Nuredin I. Mohammed , Jane Bruce , Brian Greenwood , Grant A. Mackenzie
Introduction
School-aged children play a major role in the transmission of many respiratory pathogens due to high rate of close contacts in schools. The validity and accuracy of proxy-reported contact data may be limited, particularly for children when attending school. We observed social contacts within schools and assessed the accuracy of proxy-reported versus observed physical contact data among students in rural Gambia.
Methods
We enrolled school children who had also been recruited to a survey of Streptococcus pneumoniae carriage and social contacts. We visited participants at school and observed their contact patterns within and outside the classroom for two hours. We recorded the contact type, gender and approximate age of the contactee, and class size. We calculated age-stratified contact matrices to determine in-school contact patterns. We compared proxy-reported estimated physical contacts for the subset of participants (18 %) randomised to be observed on the same day for which the parent or caregiver reported the school contacts.
Results
We recorded 3822 contacts for 219 participants from 114 schools. The median number of contacts was 15 (IQR: 11–20). Contact patterns were strongly age-assortative, and mainly involved physical touch (67.5 %). Those aged 5–9 years had the highest mean number of contacts [19.0 (95 %CI: 16.7–21.3)] while the ≥ 15-year age group had fewer contacts [12.8 (95 %CI: 10.9–14.7)]. Forty (18 %) participants had their school-observed contact data collected on the same day as their caregiver reported their estimated physical contacts at school; only 22.5 % had agreement within ±2 contacts between the observed and reported contacts. Fifty-eight percent of proxy-reported contacts were under-estimates.
Conclusions
Social contact rates observed among pupils at schools in rural Gambia were high, strongly age-assortative, and physical. Reporting of school contacts by proxies may underestimate the effect of school-age children in modelling studies of transmission of infections. New approaches are needed to quantify contacts within schools.
{"title":"Directly observed social contact patterns among school children in rural Gambia","authors":"Isaac Osei , Emmanuel Mendy , Kevin van Zandvoort , Olimatou Jobe , Golam Sarwar , Baleng Mahama Wutor , Stefan Flasche , Nuredin I. Mohammed , Jane Bruce , Brian Greenwood , Grant A. Mackenzie","doi":"10.1016/j.epidem.2024.100790","DOIUrl":"10.1016/j.epidem.2024.100790","url":null,"abstract":"<div><h3>Introduction</h3><p>School-aged children play a major role in the transmission of many respiratory pathogens due to high rate of close contacts in schools. The validity and accuracy of proxy-reported contact data may be limited, particularly for children when attending school. We observed social contacts within schools and assessed the accuracy of proxy-reported versus observed physical contact data among students in rural Gambia.</p></div><div><h3>Methods</h3><p>We enrolled school children who had also been recruited to a survey of <em>Streptococcus pneumoniae</em> carriage and social contacts. We visited participants at school and observed their contact patterns within and outside the classroom for two hours. We recorded the contact type, gender and approximate age of the contactee, and class size. We calculated age-stratified contact matrices to determine in-school contact patterns. We compared proxy-reported estimated physical contacts for the subset of participants (18 %) randomised to be observed on the same day for which the parent or caregiver reported the school contacts.</p></div><div><h3>Results</h3><p>We recorded 3822 contacts for 219 participants from 114 schools. The median number of contacts was 15 (IQR: 11–20). Contact patterns were strongly age-assortative, and mainly involved physical touch (67.5 %). Those aged 5–9 years had the highest mean number of contacts [19.0 (95 %CI: 16.7–21.3)] while the ≥ 15-year age group had fewer contacts [12.8 (95 %CI: 10.9–14.7)]. Forty (18 %) participants had their school-observed contact data collected on the same day as their caregiver reported their estimated physical contacts at school; only 22.5 % had agreement within ±2 contacts between the observed and reported contacts. Fifty-eight percent of proxy-reported contacts were under-estimates.</p></div><div><h3>Conclusions</h3><p>Social contact rates observed among pupils at schools in rural Gambia were high, strongly age-assortative, and physical. Reporting of school contacts by proxies may underestimate the effect of school-age children in modelling studies of transmission of infections. New approaches are needed to quantify contacts within schools.</p></div>","PeriodicalId":49206,"journal":{"name":"Epidemics","volume":"49 ","pages":"Article 100790"},"PeriodicalIF":3.0,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1755436524000513/pdfft?md5=2ccba6450d1e00d97d1ad0d607a86a19&pid=1-s2.0-S1755436524000513-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142172930","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}
Pub Date : 2024-09-06DOI: 10.1016/j.epidem.2024.100791
Subekshya Bidari , Wan Yang
Households play an important role in the transmission of infectious diseases due to the close contact therein. Previous modeling studies on disease transmission with household-level mixing have explored the relationship between household size distribution and epidemic characteristics such as final epidemic sizes and the basic reproduction number but have not considered the epidemic impact of declining household sizes caused by demographic shifts. Here, we use a disease transmission model that incorporates demographic changes in household sizes to study the long-term transmission dynamics of measles in communities with varying household size distributions. We explore the impact of incorporating both household- and age-structured mixing on the dynamic properties of the transmission model and compare these dynamics across different household size distributions. Our analysis, based on the household- and age-structured model, shows that communities with larger household sizes require higher vaccination thresholds and bear a greater burden of infections. However, simulations show the apparent impact of changing household sizes is the combined result of changing birth rates and household mixing, and that changing birth rates likely play a larger role than changes in household mixing in shaping measles transmission dynamics (n.b, life-long immunity makes replenishment of population susceptibility from births a crucial transmission driver for measles). In addition, simulations of endemic transmission of measles within a hypothetical population formulated using aggregated world demographic data suggest the decline in household size (driven by changing fertility rates of the population), in addition to increasing vaccination coverage, could have had a significant impact on the incidence of measles over time.
{"title":"The impact of household size on measles transmission: A long-term perspective","authors":"Subekshya Bidari , Wan Yang","doi":"10.1016/j.epidem.2024.100791","DOIUrl":"10.1016/j.epidem.2024.100791","url":null,"abstract":"<div><p>Households play an important role in the transmission of infectious diseases due to the close contact therein. Previous modeling studies on disease transmission with household-level mixing have explored the relationship between household size distribution and epidemic characteristics such as final epidemic sizes and the basic reproduction number but have not considered the epidemic impact of declining household sizes caused by demographic shifts. Here, we use a disease transmission model that incorporates demographic changes in household sizes to study the long-term transmission dynamics of measles in communities with varying household size distributions. We explore the impact of incorporating both household- and age-structured mixing on the dynamic properties of the transmission model and compare these dynamics across different household size distributions. Our analysis, based on the household- and age-structured model, shows that communities with larger household sizes require higher vaccination thresholds and bear a greater burden of infections. However, simulations show the apparent impact of changing household sizes is the combined result of changing birth rates and household mixing, and that changing birth rates likely play a larger role than changes in household mixing in shaping measles transmission dynamics (<em>n.b</em>, life-long immunity makes replenishment of population susceptibility from births a crucial transmission driver for measles). In addition, simulations of endemic transmission of measles within a hypothetical population formulated using aggregated world demographic data suggest the decline in household size (driven by changing fertility rates of the population), in addition to increasing vaccination coverage, could have had a significant impact on the incidence of measles over time.</p></div>","PeriodicalId":49206,"journal":{"name":"Epidemics","volume":"49 ","pages":"Article 100791"},"PeriodicalIF":3.0,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1755436524000525/pdfft?md5=06402016900ab2293e62ef84e9728b1b&pid=1-s2.0-S1755436524000525-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142230112","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}
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