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bioRxiv2018

Accelerometry data in health research: challenges and opportunities. Review and examples

Wearable accelerometers provide detailed, objective, and continu-ous measurements of physical activity (PA). Recent advances in technology and the decreasing cost of wearable devices led to an explosion in the popula-rity of wearable technology in health research. An ever increasing number of studies collect high-throughput, sub-second level raw acceleration data. In this paper we discuss problems related to the collection and analysis of raw acce-lerometry data and provide insights into potential solutions. In particular, we describe the size and complexity of the data, the within- and between-subject variability and the effects of sensor location on the body. We also provide a short tutorial for dealing with sampling frequency, device calibration, data labeling and multiple PA monitors synchronization. We illustrate these po-ints using the Developmental Epidemiological Cohort Study (DECOS), which collected raw accelerometry data on individuals both in a controlled and the free-living environment.

epidemiology↗

bioRxiv2018

Cohort-based Smoothing Methods for Age-specific Contact Rates

The use of social contact rates is widespread in infectious disease modelling, since it is known that they provide proxies of crucial determinants of epidemiological and disease transmission parameters. Information on social contact rates can, for example, be obtained from a population-based contact diary survey, such as the POLYMOD study. Estimation of age-specific contact rates from these studies is often done using bivariate smoothing techniques. Typically, smoothing is done in the dimensions of the respondents and contacts age. In this paper, we introduce a smoothing constrained approach - taking into account the reciprocal nature of contacts - where the contact rates are assumed smooth from a cohort perspective as well as from the age distribution of contacts. This is achieved by smoothing over the diagonal components (including all subdiagonals) of the social contact matrix. This approach is supported by the fact that people age with time and thus contact rates should vary smoothly by cohorts. Two approaches that allow for smoothing of social contact data over cohorts are proposed: (1) reordening of the diagonal components of the social contact rate matrix; and (2) reordening of the penalty matrix associated with the diagonal components. Parameter estimation is done using constrained penalized iterative reweighted least squares. A simulation study is presented to compare methods. The proposed methods are illustrated on the Belgian POLYMOD data of 2006.

epidemiology↗

bioRxiv2018

An examination of multivariable Mendelian randomization in the single sample and two-sample summary data settings.

BackgroundMendelian Randomisation (MR) is a powerful tool in epidemiology which can be used to estimate the causal effect of an exposure on an outcome in the presence of unobserved confounding, by utilising genetic variants that are instrumental variables (IVs) for the exposure. This has been extended to Multivariable MR (MVMR) to estimate the effect of two or more exposures on an outcome.\n\nMethods/ResultsWe use simulations and theory to clarify the interpretation of estimated effects in a MVMR analysis under a range of underlying scenarios, where a secondary exposure acts variously as a confounder, a mediator, a pleiotropic pathway and a collider. We then describe how instrument strength and validity can be assessed for an MVMR analysis in the single sample setting, and develop tests to assess these assumptions in the popular two-sample summary data setting. We illustrate our methods using data from UK biobank to estimate the effect of education and cognitive ability on body mass index.\n\nConclusionMVMR analysis consistently estimates the effect of an exposure, or exposures, of interest and provides a powerful tool for determining causal effects in a wide range of scenarios with either individual or summary level data.

epidemiology↗

bioRxiv2018

Population-level HIV incidence estimates using a combination of synthetic cohort and recency biomarker approaches in KwaZulu-Natal, South Africa

IntroductionThere is a notable absence of consensus on how to generate estimates ofpopulation-level incidence. Incidence is a considerably more sensitive and harder to estimate indicator of epidemiological trends than prevalence. We used a novel hybrid method to estimate HIV incidence by age and sex in a rural district of KwaZulu-Natal, South Africa.\n\nMethodsOur novel method uses an optimal weighting of estimates based on an implementation of a particular synthetic cohort approach (interpreting the age/time structure of prevalence, in conjunction with estimates of excess mortality) and biomarkers of recent infection (combining Lag-Avidity, Bio-Rad Avidity and viral load results to define recent infection, and adapting the method for age-specific incidence estimation). Data were obtained from a population-based cross-sectional HIV survey conducted in Mbongolwane and Eshowe health service areas in 2013.\n\nResultsUsing the combined method, we find that age-specific HIV incidence in females rose rapidly during adolescence, from 1.33 cases/100 person-years (95% CI:0.98,1.67) at age 15 to a peak of 5.01/100PY (4.14,5.87) at age 23. In males, incidence was lower, 0.34/100PY (0.00-0.74) at age 15, and rose later, peaking at 3.86/100PY(2.52-5.20) at age 30. Susceptible population-weighted average incidence in females aged 15-29 was estimated at 3.84/100PY (3.36-4.40), in males aged 15-29 at 1.28/100PY(0.68-1.50) and in all individuals aged 15-29 at 2.55/100PY (2.09-2.76). Using the conventional recency biomarker approach, we estimated HIV incidence among females aged 15-29 at 2.99/100PY (1.79-4.36), among males aged 15-29 at 0.87/100PY(0.22-1.60) and among all individuals aged 15-59 at 1.66/100PY (1.13-2.27).\n\nDiscussionHIV incidence was very high in women aged 15-30, peaking in the early 20s. Men had lower incidence, which peaked at age 30. The estimates obtained from the hybrid method are more informative than those produced by conventional analysis of biomarker data, and represents a more optimal use of available data than either the age-continuous biomarker or synthetic cohort methods alone. The method is mainly useful at younger ages, where excess mortality is low and uncertainty in the synthetic cohort estimates is reasonably small.\n\nConclusionApplication of this method to large-scale population-based HIV prevalence surveys is likely to result in improved incidence surveillance over methods currently in wide use. Reasonably accurate and precise age-specific estimates of incidence are important to target better prevention, diagnosis and care strategies.

epidemiology↗

bioRxiv2018

Measurement of infection efficiency of a major wheat pathogen using time-resolved imaging of disease progress

Infection efficiency is a key epidemiological parameter that determines the proportion of pathogen spores able to infect and cause lesions once they have landed on a susceptible plant tissue. In this study, we present an improved method to measure infection efficiency of Zymoseptoria tritici using a replicated greenhouse experiment. Z. tritici is a fungal pathogen that infects wheat leaves and causes Septoria tritici blotch (STB), a major disease of wheat worldwide.\n\nWe devised an original experimental setup, where we (i) attached living wheat leaves to metal plates allowing for time-resolved imaging of disease progress in planta. Since lesions were continuously appearing, expanding and merging during the period of up to three weeks, daily measurements were necessary for accurate counting of lesions. We also (ii) used reference membranes to characterize the density and the spatial distribution of inoculated spores on leaf surfaces. In this way, we captured the relationship between the number of lesions and the number of viable spores deposited on the leaves and estimated the infection efficiency of about 4 % from the slope of this relationship.\n\nOur study provides a proof of principle for an accurate and reliable measurement of infection efficiency of Z. tritici. The method opens opportunities for determining the genetic basis of the component of quantitative resistance that suppresses infection efficiency. This knowledge would improve breeding for quantitative resistance against STB, a control measure considered more durable than deployment of major resistance genes.

epidemiology↗

bioRxiv2018

Equivalence of the Erlang SEIR epidemic model and the renewal equation

Most compartmental epidemic models can be represented using the Euler-Lotka renewal equation (RE). The value of the RE is not widely appreciated in the epidemiological modelling community, perhaps because its equivalence to standard models has not been presented rigorously in non-trivial cases. Here, we provide analytical expressions for the intrinsic generation interval distribution that must be used in the RE in order to yield epidemic dynamics that are identical to those of the susceptible-exposed-infectious-recovered (SEIR) compartmental model with Erlang-distributed latent and infectious periods. This class of models includes the standard (exponentially-distributed) SIR and SEIR models as special cases.

epidemiology↗

bioRxiv2018

Interpreting Diagnostic Histories into HIV Infection Time Estimates: Framework and Online Tool

BackgroundIt is frequently of epidemiological and/or clinical interest to estimate the date of HIV infection or time-since-infection of individuals. Yet, for over 15 years, the only widely-referenced infection dating algorithm that utilises diagnostic testing data to estimate time-since-infection has been the Fiebig staging system. This defines a number of stages of early HIV infection through various standard combinations of contemporaneous discordant diagnostic results, using tests of different sensitivity.\n\nObjectiveTo develop a new, more nuanced infection dating algorithm, we generalised the Fiebig approach to accommodate positive and negative diagnostic results generated on the same or different dates, and arbitrary current or future tests - as long as the test sensitivity is known. For this purpose, test sensitivity is conceptualised as the probability that a specimen will produce a positive result, expressed as a function of time since infection. This can be summarised as a median diagnostic delay parameter, together with a measure of inter-subject variability.\n\nMethodsThe present work outlines the analytical framework for infection date estimation using subject-level diagnostic testing histories, and data on test sensitivity. We introduce a publicly-available online HIV infection dating tool that implements this estimation method, bringing together 1) curatorship of HIV test performance data, and 2) infection date estimation functionality, to calculate plausible intervals within which infection likely became detectable for each individual. The midpoints of these intervals are interpreted as infection time point estimates and referred to as Estimated Dates of Detectable Infection (EDDIs).\n\nResultsIn many settings, including most research studies, detailed diagnostic testing data are routinely recorded, and can provide reasonably precise estimates of the timing of HIV infection. We present a simple logic to the interpretation of diagnostic testing histories into infection time estimates, either as a point estimate (EDDI) or an interval (earliest plausible to latest plausible dates of detectable infection), along with a publicly-accessible online tool that supports wide application of this logic.\n\nConclusionsThis tool, available at https://tools.incidence-estimation.org/idt/, is readily updatable as test technology evolves, given the simple architecture of the system and its nature as an open source project.

epidemiology↗

bioRxiv2018

Diagnostic algorithms to study post-concussion syndrome using electronic health records: validating a method to capture an important patient population

IntroductionPost-concussion syndrome (PCS) is characterized by persistent cognitive, somatic, and emotional symptoms after a mild traumatic brain injury (mTBI). Genetic and other biological variables may contribute to PCS etiology, and the emergence of biobanks linked to electronic health records (EHR) offers new opportunities for research on PCS. We sought to validate the use of EHR data of PCS patients by comparing two diagnostic algorithms.\n\nMethodsVanderbilt University Medical Center curates a de-identified database of 2.8 million patient EHR. We developed two EHR-based algorithmic approaches that identified individuals with PCS by: (i) natural language processing (NLP) of narrative text in the EHR combined with structured demographic, diagnostic, and encounter data; or (ii) coded billing and procedure data. The predictive value of each algorithm was assessed, and cases and controls identified by each approach were compared on demographic and medical characteristics.\n\nResultsFirst, the NLP algorithm identified 507 cases and 10,857 controls. The positive predictive value (PPV) in the cases was 82% and the negative predictive value in the controls was 78%. Second, the coded algorithm identified 1,142 patients with two or more PCS billing codes and had a PPV of 76%. Comparisons of PCS controls to both case groups recovered known epidemiology of PCS: cases were more likely than controls to be female and to have pre-morbid diagnoses of anxiety, migraine, and PTSD. In contrast, controls and cases were equally likely to have ADHD and learning disabilities, in accordance with the findings of recent systematic reviews of PCS risk factors.\n\nConclusionsEHR are a valuable research tool for PCS. Ascertainment based on coded data alone had a predictive value comparable to an NLP algorithm, recovered known PCS risk factors, and maximized the number of included patients.

epidemiology↗

bioRxiv2018

Enterobacter cloacae complex ST171 Isolates Expressing KPC-4 Carbapenemase Recovered from Canine Patients in Ohio, USA

Carbapenem resistant Enterobacteriaceae (CRE) have emerged as a critical public health threat. Organisms expressing the Klebsiella pneumoniae carbapenemase (KPC) were first recognized in the US in the late 1990s and continue to be the predominant CRE genotype reported in clinical isolates. Strains harboring blaKPC alleles have been observed in multiple species of Enterobacteriaceae, including the Enterobacter cloacae complex. A major E. cloacae clone, Enterobacter xiangfangensis ST171, has emerged as an important cause of hospital associated infections (HAI) and has been shown to carry different alleles of KPC in the context of Tn4401, residing on plasmids of multiple incompatibility groups. While CRE are commonly isolated from infected humans, their recovery from animals has been rare, particularly from companion animals. In the US, only six CRE have been reported from companion animals, and one from livestock, none of which were blaKPC. This report describes two E. xiangfangensis sequence type ST171 isolates each with a large IncHI2 plasmid bearing blaKPC-4 recovered from dogs with infections at the Ohio State University Veterinary Medical Center. Our phylogenetic comparison of these canine isolates with available sequences from clinical human isolates of KPC-4 identified in ST171 suggest an epidemiologically significant clonal strain.

epidemiology↗

bioRxiv2018

Spatial analysis of the cure rate for tuberculosis in primary health care in the municipality of Rio de Janeiro between 2012 and 2014

BackgroundTuberculosis (TB) has a high disease burden and the World Health Organization (WHO) states it is a global emergency. TB is the most important cause of death from infectious disease in adults. It is directly related to access to health services and socioeconomic factors. Primary health care (PHC) provides greater linkage of people to health services and greater medication adherence in some chronic diseases. It also provides supervised treatment and more effective search for contactants. The PHC Reform started in 2009 in Rio de Janeiro, increasing coverage from 7% to 46.16% in 2015.\n\nMethodology/Principal findingsThis paper aims to evaluate the spatial distribution of new TB cases closed with a cure outcome in dwellers of Rio de Janeiro in the period 2012-2014, according to PHC coverage, controlling socioeconomic, demographic and epidemiological factors. Variables were obtained from the Notifiable Diseases Information System for Tuberculosis (SINAN-TB) and the socioeconomic variables from the 2010 national census at census tract level. The socioeconomic variables were selected from multivariate analysis using main factors analysis technique. The generalized additive model (GAM) was used for the spatial analysis. Association was found between TB cure and variables education, alcoholism, contacts search, HIV serology and elderly. People with family health coverage between 35 and 41 months were 1.64 more likely of cure when compared to people without coverage (95% CI 1.07-2.51). Spatial analysis identified areas with less probability of cure for tuberculosis in the municipality of Rio de Janeiro.\n\nAuthor SummaryTuberculosis is associated to social and demographic conditions. Lack of access to healthcare contributes to delay in diagnosis and in the beginning of the treatment. Primary health care improve access and adherence to treatment. This study can be useful as a public health policy, since it is possible to prioritize the region in the map to improve TB cure. We found association between tuberculosis cure and the duration of implantation of the primary health care teams. This finding corroborates the importance of treating tuberculosis in this level of care. The spatial analysis of cases of tuberculosis cure showed a significant spatial association with the cure of tuberculosis. The results of this study can contribute reinforcing the policy makers for developing primary health care to improve the access to health services and to reach better TB cure rates. Spatial analysis may be an useful tool for identifying the areas where to prioritize efforts for reaching better results.

epidemiology↗

bioRxiv2018

Longitudinal changes in the prevalence and intensity of soil-transmitted helminth infection following expanded community-wide mass drug administration in the delta region of Myanmar

Mass drug administration (MDA), targeted at school-aged children is the method recommended by the World Health Organization for the control of morbidity induced by soil-transmitted helminth (STH) infection in endemic countries. However, MDA does not prevent reinfection between treatment rounds. In countries with endemic infection, such as Myanmar, the MDA coverage, who is targeted, and rates of reinfection in given environmental and social settings will determine how effective mass drug treatment is in suppressing transmission in the long-term. In this paper, data from an epidemiology study on STH, conducted between June 2015 and June 2016 in the delta region of Myanmar, are analysed to determine the risks of STH infection in the whole community over a year which included two MDA rounds. Risk ratios (RRs) for the four-month reinfection period were below one, whereas RRs for the six-month reinfection period were above one, indicating that more people were infected after six months of exposure post-MDA. Evidence of predisposition, as measured by the Kendall Tau-b statistic, was found for all STH species and across all age groups. This study demonstrates that a six-month gap between MDA in these communities is enough time for STH infection to return to pre-MDA levels and that the same individuals are being consistently infected between MDA rounds.\n\nAuthor summaryMass drug administration (MDA), treating either whole communities or targeted groups without a prior diagnosis, is used as a control strategy for many neglected tropical diseases, including soil-transmitted helminth (STH) infection. MDA takes place at set intervals, aiming to reduce morbidity caused by the target disease and potentially interrupt transmission. In this study we measure STH infection in two villages in the delta region of Myanmar over the course of a year, both before and after MDA rounds, to quantify the effect of treatment on infection and to identify groups with persistent infections. We found that whilst overall prevalence of STH infection decreased over the year, intensity of infection, measured by eggs per gram of faeces, did not significantly decrease. We also found evidence to suggest that particular people are predisposed to STH infection. This is possibly due to non-compliance to MDA, or behavioural and social factors. The findings presented here will provide evidence to support continuing Myanmars MDA programme for STH control and using accurate diagnostics to identify and target \"predisposed\" people for sustained treatment.

epidemiology↗

bioRxiv2018

Worldwide survey reveals lower susceptibility of African Aedes aegypti mosquitoes to diverse strains of Zika virus

Zika virus (ZIKV) is a flavivirus mainly transmitted to humans through the bite of infected Aedes aegypti mosquitoes. First isolated in Uganda in 1947, ZIKV was shown to circulate in enzootic sylvatic cycles in Africa and Asia for at least half a century before the first reported human epidemic occurred in 2007 on the Pacific island of Yap, Micronesia. Subsequently, larger ZIKV outbreaks were recorded in French Polynesia and other South Pacific islands during 2013-2014. In 2015, ZIKV reached Brazil from where it rapidly spread across the Americas and the Caribbean, causing hundreds of thousands of human cases. The factors that have fueled the explosiveness and magnitude of ZIKV emergence in the Pacific and the Americas are poorly understood. Reciprocally, the lack of major human epidemics of ZIKV in regions with seemingly favorable conditions, such as Africa or Asia, remains largely unexplained. To evaluate the potential contribution of vector population diversity to ZIKV epidemiological patterns, we established dose-response curves for eight field-derived Ae. aegypti populations representing the global range of the species, following experimental exposure to six low-passage ZIKV strains spanning the current viral genetic diversity. Our results reveal that African Ae. aegypti are significantly less susceptible than non-African Ae. aegypti across all ZIKV strains tested. We suggest that low susceptibility of vector populations may have contributed to prevent large-scale human transmission of ZIKV in Africa.

epidemiology↗

bioRxiv2018

Mixing patterns of HIV transmission among men who have sex with men in the United Kingdom

BackgroundNear 60% of new HIV infections in the United Kingdom are estimated to occur in men who have sex with men (MSM). Patterns of mixing between different risk groups of MSM have been suggested to spread the HIV epidemics through age-disassortative partnerships and to contribute to ethnic disparities in infection rates. Understanding these mixing patterns in transmission can help to determine which groups are at a greater risk and guide prevention.\n\nMethodsWe analyzed combined epidemiologic data and viral sequences from MSM diagnosed with HIV as of mid-2015 at the national level. We applied a phylodynamic source attribution model to infer patterns of transmission between groups of patients by age, ethnicity and region.\n\nResultsFrom pair probabilities of transmission between 19 847 MSM patients, we found that potential transmitters of HIV subtype B were on average 5 months older than recipients. We also found a moderate overall assortativity of transmission by ethnic group and a stronger assortativity by region.\n\nConclusionsOur findings suggest that there is only a modest net flow of transmissions from older to young MSM in subtype B epidemics and that young MSM, both for Black or White groups, are more likely to be infected by one another than expected in a sexual network with random mixing.

epidemiology↗

bioRxiv2018

Bigger and Better? Representativeness of the Influenza A surveillance using one consolidated clinical microbiology laboratory data set as compared to the Belgian Sentinel Network of Laboratories

Infectious diseases remain a serious public health concern globally, while the need for reliable and representative surveillance systems remains as acute as ever. The public health surveillance of infectious diseases uses reported positive results from sentinel clinical laboratories or laboratory networks, to survey the presence of specific microbial agents known to constitute a threat to public health in a given population. This monitoring activity is commonly based on a representative fraction of the microbiology laboratories nationally reporting to a single central reference point. However in recent years a number of clinical microbiology laboratories (CML) have undergone a process of consolidation involving a shift towards laboratory amalgamation and closer real-time informational linkage. This report aims to investigate whether such merging activities might have a potential impact on infectious diseases surveillance. Influenza data was used from Belgian public health surveillance 2014-2017, to evaluate whether national infection trends could be estimated equally as effectively from only just one centralised CML serving the wider Brussels area (LHUB-ULB). The overall comparison reveals that there is a close correlation and representativeness of the LHUB-ULB data to the national and international data for the same time periods, both on epidemiological and molecular grounds. Notably, the effectiveness of the LHUB-ULB surveillance remains partially subject to local regional variations. These results illustrate that centralised CML-derived data are not only credible but also advantageous to use for future surveillance and prediction purposes, especially for automatic detection systems that might include multiple layers of information and timely implementation of control strategies.

epidemiology↗

bioRxiv2018

The impact of news exposure on collective attention in the United States during the 2016 Zika epidemic

In recent years, many studies have drawn attention to the important role of collective awareness and human behaviour during epidemic outbreaks. A number of modelling efforts have investigated the interaction between the disease transmission dynamics and human behaviour change mediated by news coverage and by information spreading in the population. Yet, given the scarcity of data on public awareness during an epidemic, few studies have relied on empirical data. Here, we use fine-grained, geo-referenced data from three online sources - Wikipedia, the GDELT Project and the Internet Archive - to quantify population-scale information seeking about the 2016 Zika virus epidemic in the U.S., explicitly linking such behavioural signal to epidemiological data. Geolocalized Wikipedia pageview data reveal that visiting patterns of Zika-related pages in Wikipedia were highly synchronized across the United States and largely explained by exposure to national television broadcast. Contrary to the assumption of some theoretical models, news volume and Wikipedia visiting patterns were not significantly correlated with the magnitude or the extent of the epidemic. Attention to Zika, in terms of Zika-related Wikipedia pageviews, was high at the beginning of the outbreak, when public health agencies raised an international alert and triggered media coverage, but subsequently exhibited an activity profile that suggests nonlinear dependencies and memory effects in the relation between information seeking, media pressure, and disease dynamics. This calls for a new and more general modelling framework to describe the interaction between media exposure, public awareness and disease dynamics during epidemic outbreaks.

epidemiology↗

bioRxiv2018

Spatial-temporal clustering analysis of yaws on Lihir Island, Papua New Guinea to enhance planning and implementation of eradication programs

BackgroundIn the global program for the eradication of yaws, assessments of the prevalence of the disease are used to decide where to initiate mass treatment. However, the smallest administrative unit which should be used as the basis for making decisions is not clear. We investigated spatial and temporal clustering of yaws to help inform the choice of implementation unit.\n\nMethodology/Principal findingsWe analyzed 11 years of passive surveillance data on incident yaws cases (n = 1448) from Lihir Island, Papua New Guinea. After adjusting for age, sex, and trends in health-seeking, we detected three non-overlapping spatiotemporal clusters (p < 1 x 10-17, p = 1.4 x 10-14, p = 1.4 x 10-8). These lasted from 28 to 47 months in duration and each encompassed between 4 and 6 villages. We also assessed spatial clustering of prevalent yaws cases (n = 532) that had been detected in 7 biannual active case finding surveys beginning in 2013. We identified 1 statistically significant cluster in each survey. We considered the possibility that schools that serve multiple villages might be loci of transmission, but we found no evidence that incident cases of yaws among 8- to 14-year-olds clustered within primary school attendance areas (p = 0.684).\n\nConclusions/SignificanceThese clusters likely reflect transmission of yaws across village boundaries; villages may be epidemiologically linked to a degree such that mass drug administration may be more effectively implemented at a spatial scale larger than the individual village.\n\nAuthor SummaryThe World Health Organization aims to eradicate yaws using mass drug administration (MDA), which consists of treating everyone in an administrative unit with antibiotics. The administrative unit in a country which is used as the basis for making decisions about implementing MDA is called the implementation unit. Prevalence assessments are used to identify endemic communities for mass treatment programs, but the spatial scale (e.g. village, sub-district, district, or province) at which mass treatment should be implemented is currently unclear. The choice of implementation unit depends on many factors; one of these is the underlying transmission patterns of the disease. Using data from Lihir Island, Papua New Guinea, we found that geographic clusters of yaws often spanned multiple villages. These clusters likely reflect transmission of the infectious disease across village boundaries and suggest that it may be best to implement MDA at a spatial scale larger than the individual village, for example at sub-district level.

epidemiology↗

bioRxiv2018

Within-host infectious disease models accommodating cellular coinfection, with an application to influenza

Within-host models are useful tools for understanding the processes regulating viral load dynamics. While existing models have considered a wide range of within-host processes, at their core these models have shown remarkable structural similarity. Specifically, the structure of these models generally consider target cells to be either uninfected or infected, with the possibility of accommodating further resolution (for example, cells that are refractory to infection and cells that are in an eclipse phase). Recent findings, however, indicate that cellular coinfection is the norm rather than the exception for many viral infectious diseases, and that cells with high multiplicity of infection are present over at least some duration of an infection. The reality of these cellular coinfection dynamics is not accommodated in current within-host models although it may be critical for understanding within-host dynamics. This is particularly the case if multiplicity of infection impacts infected cell phenotypes such as their death rate and their viral production rates. Here, we present a new class of within-host disease models that allow for cellular coinfection in a scalable manner by retaining the low-dimensionality that is a desirable feature of many current within-host models. The models we propose adopt the general structure of epidemiological macroparasite models that allow hosts to be variably infected by parasites such as nematodes and host phenotypes to flexibly depend on parasite burden. Specifically, our within-host models consider target cells as hosts and viral particles as macroparasites, and allow viral output and infected cell lifespans, among other phenotypes, to depend on a cells multiplicity of infection. We show with an application to influenza that these models can be statistically fit to viral load and other within-host data, that they can reproduce notable features of within-host viral dynamics, and that important in vivo quantities such as the mean multiplicity of cellular infection can be easily quantified with these models once parameterized. The within-host model structure we develop here provides an alternative approach for modeling within-host viral load dynamics and allows for a new class of questions to be addressed that consider the effects of cellular coinfection, collective viral interactions, and viral complementation in within-host viral dynamics and evolution.

epidemiology↗

bioRxiv2018

Model-based assessment of public health impact and cost-effectiveness of dengue vaccination following screening for prior exposure

The tetravalent dengue vaccine CYD-TDV (Dengvaxia(R)) is the first licensed vaccine against dengue, but recent findings indicate an elevated risk of severe disease among vaccinees without prior dengue virus (DENV) exposure. The World Health Organization currently recommends CYD-TDV only for individuals with serological confirmation of past DENV exposure. Our objective was to evaluate the potential impact and cost-effectiveness of vaccination following serological screening. To do so, we used an agent-based model to simulate DENV transmission with and without vaccination over a 30-year timeframe. Under a range of values for the proportion of vaccinees with prior DENV exposure, we projected the proportion of symptomatic and hospitalized cases averted as a function of the sensitivity and specificity of serological screening. Scenarios about the cost-effectiveness of screening and vaccination were chosen to be representative of Brazil and the Philippines. We found that public health impact depended primarily on the sensitivity of serological screening in high-transmission settings and on a combination of sensitivity and specificity in low-transmission settings. Reducing risk from an individual perspective required high specificity, no less than 0.8. Cost-effectiveness could be achievable from the perspective of a public payer provided that screening sensitivity for prior DENV exposure and the value of a disability-adjusted life-year were both high. Cost-effectiveness was also achievable from an individual perspective, particularly with high screening specificity and low coverage. Whereas the results of this analysis offer general guidelines about CYD-TDV vaccination, decisions in specific contexts would benefit from additional, more context-specific modeling analyses. In conclusion, vaccination with CYD-TDV following serological screening could have a positive impact in certain epidemiological settings, provided that screening is highly specific, at least moderately sensitive, and inexpensive.

epidemiology↗