Biased seroprevalence estimates can occur using serological assays optimized with validation sets unrepresentative of disease spectrum in the general population. Correct interpretation of serosurveys for severe acute respiratory syndrome coronavirus 2 requires quantifying variations in sensitivity with disease severity and over time.

One of the challenges faced by global disease surveillance efforts is the lack of comparability across systems. Reporting commonly focuses on overall incidence, despite differences in surveillance quality between and within countries. For most immunizing infections, the age distribution of incident cases provides a more robust picture of trends in transmission. We present a framework to estimate transmission intensity for dengue virus from age-specific incidence data, and apply it to 359 administrative units in Thailand, Colombia, Brazil and Mexico. Our estimates correlate well with those derived from seroprevalence data (the gold standard), capture the expected spatial heterogeneity in risk, and correlate with known environmental drivers of transmission. We show how this approach could be used to guide the implementation of control strategies such as vaccination. Since age-specific counts are routinely collected by masany surveillance systems, they represent a unique opportunity to further our understanding of disease burden and risk for many diseases.

Background

The 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.

Methods

We 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.

Results

The 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.

Conclusions

As 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.

Background

Discrepancies between information in conference abstracts and full publications describing the same randomized controlled trial have been reported. The association between author conflicts of interest and the publication of randomized controlled trials is unclear. The objective of this study was to use randomized controlled trials in ophthalmology to evaluate (1) the agreement in the reported main outcome results by comparing abstracts and corresponding publications and (2) the association between the author conflicts of interest and publication of the results presented in the abstracts.

Methods

We considered abstracts describing results of randomized controlled trials presented at the 2001-2004 Association for Research in Vision and Ophthalmology conferences as eligible for our study. Through electronic searching and by emailing abstract authors, we identified the earliest publication (journal article) containing results of each abstract's main outcome through November 2013. We categorized the discordance between the main outcome results in the abstract and its paired publication as qualitative (a difference in the direction of the estimated effect) or as quantitative. We used the Association for Research in Vision and Ophthalmology categories for conflicts of interest: financial interest, employee of business with interest, consultant to business with interest, inventor/developer with patent, and receiving ≥ 1 gift from industry in the past year. We calculated the relative risks (RRs) of publication associated with the categories of conflicts of interest for abstracts with results that were statistically significant, not statistically significant, or not reported.

Results

We included 513 abstracts, 230 (44.8 %) of which reached publication. Among the 86 pairs with the same main outcome domain at the same time point, 47 pairs (54.7 %) had discordant results: qualitative discordance in 7 pairs and quantitative discordance in 40 pairs. Quantitative discordance was indicated as < 10, 10-20, > 20 %, and unclear in 14, 5, 14, and 7 pairs, respectively. First authors reporting of one or more conflicts of interest was associated with a greater likelihood of publication (RR = 1.31; 95 % CI = 1.04 to 1.64) and a shorter time-to-publication (log-rank p = 0.026). First author conflicts of interests that were associated with publication were financial support (RR = 1.50; 95 % CI = 1.19 to 1.90) and one or more gifts (RR = 1.42; 95 % CI = 1.05 to 1.92). The association between conflicts of interest and publication remained, irrespective of the statistical significance of the results.

Conclusions

More than half the abstract/publication pairs exhibited some amount of discordance in the main outcome results, calling into question the dependability of conference abstracts. Regardless of the main outcome results, the conflicts of interests of the abstract's first author were associated with publication.

Dengue vaccine development efforts have focused on the development of tetravalent vaccines. However, a recent Phase IIb trial of a tetravalent vaccine indicates a protective effect against only 3 of the 4 serotypes. While vaccines effective against a subset of serotypes may reduce morbidity and mortality, particular profiles could result in an increased number of cases due to immune enhancement and other peculiarities of dengue epidemiology. Here, we use a compartmental transmission model to assess the impact of partially effective vaccines in a hyperendemic Thai population. Crucially, we evaluate the effects that certain serotype heterogeneities may have in the presence of mass-vaccination campaigns. In the majority of scenarios explored, partially effective vaccines lead to 50% or greater reductions in the number of cases. This is true even of vaccines that we would not expect to proceed to licensure due to poor or incomplete immune responses. Our results show that a partially effective vaccine can have significant impacts on serotype distribution and mean age of cases.

BACKGROUND:Little is known about the historical and current risk of Zika virus infection in southeast Asia, where the mosquito vector is widespread and other arboviruses circulate endemically. Centralised Zika virus surveillance began in Thailand in January, 2016. We assessed the long-term circulation of Zika virus in Thailand. METHODS:In this observational study, we analysed data from individuals with suspected Zika virus infection who presented at hospitals throughout the country and had biological samples (serum, plasma, or urine) tested for confirmation with PCR at the National Institute of Health laboratories in Bangkok. We analysed the spatial and age distribution of cases, and constructed time-resolved phylogenetic trees using genomes from Thailand and elsewhere to estimate when Zika virus was first introduced. FINDINGS:Of the 3089 samples from 1717 symptomatic individuals tested between January, 2016, and December, 2017, 368 were confirmed to have Zika virus infection. Cases of Zika virus infection were reported throughout the year, and from 29 of the 76 Thai provinces. Individuals had 2·8 times (95% CI 2·3-3·6) the odds of testing positive for Zika virus infection if they came from the same district and were sick within the same year of a person with a confirmed infection relative to the odds of testing positive anywhere, consistent with focal transmission. The probability of cases being younger than 10 years was 0·99 times (0·72-1·30) the probability of being that age in the underlying population. This probability rose to 1·62 (1·33-1·92) among those aged 21-30 years and fell to 0·53 (0·40-0·66) for those older than 50 years. This age distribution is consistent with that observed in the Zika virus epidemic in Colombia. Phylogenetic reconstructions suggest persistent circulation within Thailand since at least 2002. INTERPRETATION:Our evidence shows that Zika virus has circulated at a low but sustained level for at least 16 years, suggesting that Zika virus can adapt to persistent endemic transmission. Health systems need to adapt to cope with regular occurrences of the severe complications associated with infection. FUNDING:European Research Council, National Science Foundation, and National Institutes of Health.

An essential step toward reconstructing pathogen transmission and answering epidemiologically relevant questions from genomic data is obtaining pairwise genetic distance between infections. For recombining organisms such as malaria parasites, relatedness measures quantifying recent shared ancestry would provide a meaningful distance, suggesting methods based on identity by descent (IBD). While the concept of relatedness and consequently an IBD approach is fairly straightforward for individual parasites, the distance between polyclonal infections, which are prevalent in malaria, presents specific challenges, and awaits a general solution that could be applied to infections of any clonality and accommodate multiallelic (e.g. microsatellite or microhaplotype) and biallelic [single nucleotide polymorphism (SNP)] data. Filling this methodological gap, we present Dcifer (Distance for complex infections: fast estimation of relatedness), a method for calculating genetic distance between polyclonal infections, which is designed for unphased data, explicitly accounts for population allele frequencies and complexity of infection, and provides reliable inference. Dcifer's IBD-based framework allows us to define model parameters that represent interhost relatedness and to propose corresponding estimators with attractive statistical properties. By using combinatorics to account for unobserved phased haplotypes, Dcifer is able to quickly process large datasets and estimate pairwise relatedness along with measures of uncertainty. We show that Dcifer delivers accurate and interpretable results and detects related infections with statistical power that is 2-4 times greater than that of approaches based on identity by state. Applications to real data indicate that relatedness structure aligns with geographic locations. Dcifer is implemented in a comprehensive publicly available software package.

Antibodies directed against malaria parasites are easy and inexpensive to measure but remain an underused surveillance tool because of a lack of consensus on what to measure and how to interpret results. High-throughput screening of antibodies from well-characterized cohorts offers a means to substantially improve existing assays by rationally choosing the most informative sets of responses and analytical methods. Recent data suggest that high-resolution information on malaria exposure can be obtained from a small number of samples by measuring a handful of properly chosen antibody responses. In this review, we discuss how standardized multi-antibody assays can be developed and efficiently integrated into existing surveillance activities, with potential to greatly augment the breadth and quality of information available to direct and monitor malaria control and elimination efforts.

This study uses US Immigration and Customs Enforcement (ICE) Health Service Corps data to describe incident cases and outbreaks of influenza, varicella, and mumps in 22 US ICE detention centers between 2017 and March 2020.