Variation in dengue virus plaque reduction neutralization testing: systematic review and pooled analysis.

BackgroundThe plaque reduction neutralization test (PRNT) remains the gold standard for the detection of serologic immune responses to dengue virus (DENV). While the basic concept of the PRNT remains constant, this test has evolved in multiple laboratories, introducing variation in materials and methods. Despite the importance of laboratory-to-laboratory comparability in DENV vaccine development, the effects of differing PRNT techniques on assay results, particularly the use of different dengue strains within a serotype, have not been fully characterized.MethodsWe conducted a systematic review and pooled analysis of published literature reporting individual-level PRNT titers to identify factors associated with heterogeneity in PRNT results and compared variation between strains within DENV serotypes and between articles using hierarchical models.ResultsThe literature search and selection criteria identified 8 vaccine trials and 25 natural exposure studies reporting 4,411 titers from 605 individuals using 4 different neutralization percentages, 3 cell lines, 12 virus concentrations and 51 strains. Of 1,057 titers from primary DENV exposure, titers to the exposure serotype were consistently higher than titers to non-exposure serotypes. In contrast, titers from secondary DENV exposures (n = 628) demonstrated high titers to exposure and non-exposure serotypes. Additionally, PRNT titers from different strains within a serotype varied substantially. A pooled analysis of 1,689 titers demonstrated strain choice accounted for 8.04% (90% credible interval [CrI]: 3.05%, 15.7%) of between-titer variation after adjusting for secondary exposure, time since DENV exposure, vaccination and neutralization percentage. Differences between articles (a proxy for inter-laboratory differences) accounted for 50.7% (90% CrI: 30.8%, 71.6%) of between-titer variance.ConclusionsAs promising vaccine candidates arise, the lack of standardized assays among diagnostic and research laboratories make unbiased inferences about vaccine-induced protection difficult. Clearly defined, widely accessible reference reagents, proficiency testing or algorithms to adjust for protocol differences would be a useful first step in improving dengue PRNT comparability and quality assurance

Measuring Spatial Dependence for Infectious Disease Epidemiology.

Global spatial clustering is the tendency of points, here cases of infectious disease, to occur closer together than expected by chance. The extent of global clustering can provide a window into the spatial scale of disease transmission, thereby providing insights into the mechanism of spread, and informing optimal surveillance and control. Here the authors present an interpretable measure of spatial clustering, τ, which can be understood as a measure of relative risk. When biological or temporal information can be used to identify sets of potentially linked and likely unlinked cases, this measure can be estimated without knowledge of the underlying population distribution. The greater our ability to distinguish closely related (i.e., separated by few generations of transmission) from more distantly related cases, the more closely τ will track the true scale of transmission. The authors illustrate this approach using examples from the analyses of HIV, dengue and measles, and provide an R package implementing the methods described. The statistic presented, and measures of global clustering in general, can be powerful tools for analysis of spatially resolved data on infectious diseases

Differential mobility and local variation in infection attack rate.

Infectious disease transmission is an inherently spatial process in which a host's home location and their social mixing patterns are important, with the mixing of infectious individuals often different to that of susceptible individuals. Although incidence data for humans have traditionally been aggregated into low-resolution data sets, modern representative surveillance systems such as electronic hospital records generate high volume case data with precise home locations. Here, we use a gridded spatial transmission model of arbitrary resolution to investigate the theoretical relationship between population density, differential population movement and local variability in incidence. We show analytically that a uniform local attack rate is typically only possible for individual pixels in the grid if susceptible and infectious individuals move in the same way. Using a population in Guangdong, China, for which a robust quantitative description of movement is available (a travel kernel), and a natural history consistent with pandemic influenza; we show that local cumulative incidence is positively correlated with population density when susceptible individuals are more connected in space than infectious individuals. Conversely, under the less intuitively likely scenario, when infectious individuals are more connected, local cumulative incidence is negatively correlated with population density. The strength and direction of correlation changes sign for other kernel parameter values. We show that simulation models in which it is assumed implicitly that only infectious individuals move are assuming a slightly unusual specific correlation between population density and attack rate. However, we also show that this potential structural bias can be corrected by using the appropriate non-isotropic kernel that maps infectious-only code onto the isotropic dual-mobility kernel. These results describe a precise relationship between the spatio-social mixing of infectious and susceptible individuals and local variability in attack rates. More generally, these results suggest a genuine risk that mechanistic models of high-resolution attack rate data may reach spurious conclusions if the precise implications of spatial force-of-infection assumptions are not first fully characterized, prior to models being fit to data

Viridot: An automated virus plaque (immunofocus) counter for the measurement of serological neutralizing responses with application to dengue virus.

The gold-standard method for quantifying neutralizing antibody responses to many viruses, including dengue virus (DENV), is the plaque reduction neutralization test (PRNT, also called the immunofocus reduction neutralization test). The PRNT conducted on 96-well plates is high-throughput and requires a smaller volume of antiserum than on 6- or 24-well plates, but manual plaque counting is challenging and existing automated plaque counters are expensive or difficult to optimize. We have developed Viridot (Viridot package), a program for R with a user interface in shiny, that counts viral plaques of a variety of phenotypes, estimates neutralizing antibody titers, and performs other calculations of use to virologists. The Viridot plaque counter includes an automatic parameter identification mode (misses <10 plaques/well for 87% of diverse DENV strains [n = 1521]) and a mode that allows the user to fine-tune the parameters used for counting plaques. We compared standardized manual and Viridot plaque counting methods applied to the same wells by two analyses and found that Viridot plaque counts were as similar to the same analyst's manual count (Lin's concordance correlation coefficient, ρc = 0.99 [95% confidence interval: 0.99-1.00]) as manual counts between analysts (ρc = 0.99 [95% CI: 0.98-0.99]). The average ratio of neutralizing antibody titers based on manual counted plaques to Viridot counted plaques was 1.05 (95% CI: 0.98-1.14), similar to the average ratio of antibody titers based on manual plaque counts by the two analysts (1.06 [95% CI: 0.84-1.34]). Across diverse DENV and ZIKV strains (n = 14), manual and Viridot plaque counts were mostly consistent (range of ρc = 0.74 to 1.00) and the average ratio of antibody titers based on manual and Viridot counted plaques was close to 1 (0.94 [0.86-1.02]). Thus, Viridot can be used for plaque counting and neutralizing antibody titer estimation of diverse DENV strains and potentially other viruses on 96-well plates as well as for formalization of plaque-counting rules for standardization across experiments and analysts

Assessing the global threat from Zika virus.

First discovered in 1947, Zika virus (ZIKV) infection remained a little-known tropical disease until 2015, when its apparent association with a considerable increase in the incidence of microcephaly in Brazil raised alarms worldwide. There is limited information on the key factors that determine the extent of the global threat from ZIKV infection and resulting complications. Here, we review what is known about the epidemiology, natural history, and public health effects of ZIKV infection, the empirical basis for this knowledge, and the critical knowledge gaps that need to be filled

Reconstruction of antibody dynamics and infection histories to evaluate dengue risk.

As with many pathogens, most dengue infections are subclinical and therefore unobserved 1 . Coupled with limited understanding of the dynamic behaviour of potential serological markers of infection, this observational problem has wide-ranging implications, including hampering our understanding of individual- and population-level correlates of infection and disease risk and how these change over time, between assay interpretations and with cohort design. Here we develop a framework that simultaneously characterizes antibody dynamics and identifies subclinical infections via Bayesian augmentation from detailed cohort data (3,451 individuals with blood draws every 91 days, 143,548 haemagglutination inhibition assay titre measurements)2,3. We identify 1,149 infections (95% confidence interval, 1,135-1,163) that were not detected by active surveillance and estimate that 65% of infections are subclinical. After infection, individuals develop a stable set point antibody load after one year that places them within or outside a risk window. Individuals with pre-existing titres of ≤1:40 develop haemorrhagic fever 7.4 (95% confidence interval, 2.5-8.2) times more often than naive individuals compared to 0.0 times for individuals with titres >1:40 (95% confidence interval: 0.0-1.3). Plaque reduction neutralization test titres ≤1:100 were similarly associated with severe disease. Across the population, variability in the size of epidemics results in large-scale temporal changes in infection and disease risk that correlate poorly with age

Reconstructing unseen transmission events to infer dengue dynamics from viral sequences.

For most pathogens, transmission is driven by interactions between the behaviours of infectious individuals, the behaviours of the wider population, the local environment, and immunity. Phylogeographic approaches are currently unable to disentangle the relative effects of these competing factors. We develop a spatiotemporally structured phylogenetic framework that addresses these limitations by considering individual transmission events, reconstructed across spatial scales. We apply it to geocoded dengue virus sequences from Thailand (N = 726 over 18 years). We find infected individuals spend 96% of their time in their home community compared to 76% for the susceptible population (mainly children) and 42% for adults. Dynamic pockets of local immunity make transmission more likely in places with high heterotypic immunity and less likely where high homotypic immunity exists. Age-dependent mixing of individuals and vector distributions are not important in determining spread. This approach provides previously unknown insights into one of the most complex disease systems known and will be applicable to other pathogens

Preschool-Aged Household Contacts as a Risk Factor for Viral Respiratory Infections in Healthcare Personnel

BACKGROUND: Viral respiratory infections (VRIs) are common and are occupational risks for healthcare personnel (HCP). VRIs can also be acquired at home and other settings among HCPs. We sought to determine if preschool-aged household contacts are a risk factor for VRIs among HCPs working in outpatient settings. METHODS: We conducted a secondary analysis of data from a cluster randomized trial at 7 medical centers in the United States over 4 influenza seasons from 2011-2012 to 2014-2015. Adult HCPs who routinely came within 6 feet of patients with respiratory infections were included. Participants were tested for respiratory viruses whenever symptomatic and at 2 random times each season when asymptomatic. The exposure of interest was the number of household contacts 0-5 years old (preschool-aged) at the beginning of each HCP-season. The primary outcome was the rate of polymerase chain reaction-detected VRIs, regardless of symptoms. The VRI incidence rate ratio (IRR) was calculated using a mixed-effects Poisson regression model that accounted for clustering at the clinic level. RESULTS: Among the 4476 HCP-seasons, most HCPs were female (85.4%) and between 30 and 49 years of age (54.6%). The overall VRI rate was 2.04 per 100 person-weeks. In the adjusted analysis, HCPs having 1 (IRR, 1.22 [95% confidence interval {CI}, 1.05-1.43]) and ≥2 (IRR, 1.35 [95% CI, 1.09-1.67]) preschool-aged household contacts had higher VRI rates than those with zero preschool-aged household contacts. CONCLUSIONS: Preschool-aged household contacts are a risk factor for developing VRIs among HCPs working in outpatient settings

Modelling distributions of Aedes aegypti and Aedes albopictus using climate, host density and interspecies competition.

Florida faces the challenge of repeated introduction and autochthonous transmission of arboviruses transmitted by Aedes aegypti and Aedes albopictus. Empirically-based predictive models of the spatial distribution of these species would aid surveillance and vector control efforts. To predict the occurrence and abundance of these species, we fit a mixed-effects zero-inflated negative binomial regression to a mosquito surveillance dataset with records from more than 200,000 trap days, representative of 53% of the land area and ranging from 2004 to 2018 in Florida. We found an asymmetrical competitive interaction between adult populations of Aedes aegypti and Aedes albopictus for the sampled sites. Wind speed was negatively associated with the occurrence and abundance of both vectors. Our model predictions show high accuracy (72.9% to 94.5%) in validation tests leaving out a random 10% subset of sites and data since 2017, suggesting a potential for predicting the distribution of the two Aedes vectors

Effectiveness of CoronaVac, ChAdOx1 nCoV-19, BNT162b2, and Ad26.COV2.S among individuals with previous SARS-CoV-2 infection in Brazil: a test-negative, case-control study.

BACKGROUND: COVID-19 vaccines have proven highly effective among individuals without a previous SARS-CoV-2 infection, but their effectiveness in preventing symptomatic infection and severe outcomes among individuals with previous infection is less clear. We aimed to estimate the effectiveness of four COVID-19 vaccines against symptomatic infection, hospitalisation, and death for individuals with laboratory-confirmed previous SARS-CoV-2 infection. METHODS: Using national COVID-19 notification, hospitalisation, and vaccination datasets from Brazil, we did a test-negative, case-control study to assess the effectiveness of four vaccines (CoronaVac [Sinovac], ChAdOx1 nCoV-19 [AstraZeneca], Ad26.COV2.S [Janssen], and BNT162b2 [Pfizer-BioNtech]) for individuals with laboratory-confirmed previous SARS-CoV-2 infection. We matched cases with RT-PCR positive, symptomatic COVID-19 with up to ten controls with negative RT-PCR tests who presented with symptomatic illnesses, restricting both groups to tests done at least 90 days after an initial infection. We used multivariable conditional logistic regression to compare the odds of test positivity and the odds of hospitalisation or death due to COVID-19, according to vaccination status and time since first or second dose of vaccines. FINDINGS: Between Feb 24, 2020, and Nov 11, 2021, we identified 213 457 individuals who had a subsequent, symptomatic illness with RT-PCR testing done at least 90 days after their initial SARS-CoV-2 infection and after the vaccination programme started. Among these, 30 910 (14·5%) had a positive RT-PCR test consistent with reinfection, and we matched 22 566 of these cases with 145 055 negative RT-PCR tests from 68 426 individuals as controls. Among individuals with previous SARS-CoV-2 infection, vaccine effectiveness against symptomatic infection 14 or more days from vaccine series completion was 39·4% (95% CI 36·1-42·6) for CoronaVac, 56·0% (51·4-60·2) for ChAdOx1 nCoV-19, 44·0% (31·5-54·2) for Ad26.COV2.S, and 64·8% (54·9-72·4) for BNT162b2. For the two-dose vaccine series (CoronaVac, ChAdOx1 nCoV-19, and BNT162b2), effectiveness against symptomatic infection was significantly greater after the second dose than after the first dose. Effectiveness against hospitalisation or death 14 or more days from vaccine series completion was 81·3% (75·3-85·8) for CoronaVac, 89·9% (83·5-93·8) for ChAdOx1 nCoV-19, 57·7% (-2·6 to 82·5) for Ad26.COV2.S, and 89·7% (54·3-97·7) for BNT162b2. INTERPRETATION: All four vaccines conferred additional protection against symptomatic infections and severe outcomes among individuals with previous SARS-CoV-2 infection. The provision of a full vaccine series to individuals after recovery from COVID-19 might reduce morbidity and mortality. FUNDING: Brazilian National Research Council, Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro, Oswaldo Cruz Foundation, JBS, Instituto de Salud Carlos III, Spanish Ministry of Science and Innovation, and Generalitat de Catalunya