Challenges in Real-Time Prediction of Infectious Disease: A Case Study of Dengue in Thailand.

Epidemics of communicable diseases place a huge burden on public health infrastructures across the world. Producing accurate and actionable forecasts of infectious disease incidence at short and long time scales will improve public health response to outbreaks. However, scientists and public health officials face many obstacles in trying to create such real-time forecasts of infectious disease incidence. Dengue is a mosquito-borne virus that annually infects over 400 million people worldwide. We developed a real-time forecasting model for dengue hemorrhagic fever in the 77 provinces of Thailand. We created a practical computational infrastructure that generated multi-step predictions of dengue incidence in Thai provinces every two weeks throughout 2014. These predictions show mixed performance across provinces, out-performing seasonal baseline models in over half of provinces at a 1.5 month horizon. Additionally, to assess the degree to which delays in case reporting make long-range prediction a challenging task, we compared the performance of our real-time predictions with predictions made with fully reported data. This paper provides valuable lessons for the implementation of real-time predictions in the context of public health decision making

Sympathovagal balance and 1-h postload plasma glucose in normoglucose tolerant hypertensive patients.

AIMS: Normoglucose tolerant (NGT) subjects with a 1-h postload plasma glucose (PLPG) value ≥155 mg/dL have an increased risk of type-2 diabetes and subclinical organ damage. Heart rate variability (HRV) reflects cardiac autonomic balance, frequently impaired in course of diabetes. At this time, no data support the association between 1-h PLPG and HRV; thus, we investigated the possible association between 1-h PLPG and HRV. METHODS: We enrolled 92 never-treated hypertensive subjects (56 women, 36 men), aged 55 ± 9.8 years. During OGTT, the patients underwent electrocardiographic recordings to evaluate HRV in the time domain (SDNN). Insulin sensitivity was assessed by Matsuda index. RESULTS: Among participants, 56 were NGT, 20 had impaired glucose tolerance (IGT), and 16 had type-2 diabetes. According to the 1-h PLPG cutoff point of 155 mg/dL, we divided NGT subjects into: NGT < 155 (n = 38) and NGT ≥ 155 (n = 18). Glucose tolerance status was associated with a significant (P < 0.0001) increase in PLPG and insulin and the reduction in Matsuda index. In all groups, the SDNN values significantly (P < 0.0001) decreased during the first hour of OGTT. A complete recovery in NGT groups was observed at the end of the second hour; in IGT and type-2 diabetes, SDNN remained significantly lower with respect to baseline values. At multiple regression analysis, Matsuda index resulted in the only determinant of SDNN modification, explaining the 12.3 % of its variability. CONCLUSIONS: Our data demonstrate that during OGTT, sympathovagal balance is acutely affected by both glucose and insulin modifications. Particularly, NGT ≥ 155 subjects behave in the same way of IGT and type-2 diabetes patients

Papillary carcinoma of the thyroid: methylation is not involved in the regulation of MET expression

Hypomethylation has been reported to be responsible for the activation of several oncogenes. The possibility that hypomethylation is involved in the regulation of MET transcription was investigated through the analysis of the methylation status of one CpG island containing 43 CpGs in six cases of papillary carcinoma, in the corresponding normal thyroid tissue, and in two cases of hyperplastic goitre. Evidence of methylation was not found in any of the analysed CpG. © 2004 Cancer Research UK

Cost-effectiveness of next-generation vaccines: The case of pertussis.

Despite steady vaccination coverage rates, pertussis incidence in the United States has continued to rise. This public health challenge has motivated calls for the development of a new vaccine with greater efficacy and duration of protection. Any next-generation vaccine would likely come at a higher cost, and must provide sufficient health benefits beyond those provided by the current vaccine in order to be deemed cost-effective. Using an age-structured transmission model of pertussis, we quantified the health and economic benefits of a next-generation vaccine that would enhance either the efficacy or duration of protection of the childhood series, the duration of the adult booster, or a combination. We developed a metric, the maximum cost-effective price increase (MCPI), to compare the potential value of such improvements. The MCPI estimates the per-dose price increase that would maintain the cost-effectiveness of pertussis vaccination. We evaluated the MCPI across a range of potential single and combined improvements to the pertussis vaccine. As an upper bound, we found that a next-generation vaccine which could achieve perfect efficacy for the childhood series would permit an MCPI of $18 per dose (95$12-$31). Pertussis vaccine improvements that extend the duration of protection to an average of 75 years would allow for an MCPI of$22 per dose for the childhood series (CI: $10-$33) or $12 for the adult booster (CI:$4-$18). Despite the short duration of the adult booster, improvements to the childhood series could be more valuable than improvements to the adult booster. Combining improvements in both efficacy and duration, a childhood series with perfect efficacy and average duration of 75 years would permit an MCPI of$39 per dose, the highest of any scenario evaluated. Our results highlight the utility of the MCPI metric in evaluating potential vaccines or other interventions when prices are unknown

Optimizing Provider Recruitment for Influenza Surveillance Networks

The increasingly complex and rapid transmission dynamics of many infectious diseases necessitates the use of new, more advanced methods for surveillance, early detection, and decision-making. Here, we demonstrate that a new method for optimizing surveillance networks can improve the quality of epidemiological information produced by typical provider-based networks. Using past surveillance and Internet search data, it determines the precise locations where providers should be enrolled. When applied to redesigning the provider-based, influenza-like-illness surveillance network (ILINet) for the state of Texas, the method identifies networks that are expected to significantly outperform the existing network with far fewer providers. This optimized network avoids informational redundancies and is thereby more effective than networks designed by conventional methods and a recently published algorithm based on maximizing population coverage. We show further that Google Flu Trends data, when incorporated into a network as a virtual provider, can enhance but not replace traditional surveillance methods

Using combined diagnostic test results to hindcast trends of infection from cross-sectional data

Infectious disease surveillance is key to limiting the consequences from infectious pathogens and maintaining animal and public health. Following the detection of a disease outbreak, a response in proportion to the severity of the outbreak is required. It is thus critical to obtain accurate information concerning the origin of the outbreak and its forward trajectory. However, there is often a lack of situational awareness that may lead to over- or under-reaction. There is a widening range of tests available for detecting pathogens, with typically different temporal characteristics, e.g. in terms of when peak test response occurs relative to time of exposure. We have developed a statistical framework that combines response level data from multiple diagnostic tests and is able to ‘hindcast’ (infer the historical trend of) an infectious disease epidemic. Assuming diagnostic test data from a cross-sectional sample of individuals infected with a pathogen during an outbreak, we use a Bayesian Markov Chain Monte Carlo (MCMC) approach to estimate time of exposure, and the overall epidemic trend in the population prior to the time of sampling. We evaluate the performance of this statistical framework on simulated data from epidemic trend curves and show that we can recover the parameter values of those trends. We also apply the framework to epidemic trend curves taken from two historical outbreaks: a bluetongue outbreak in cattle, and a whooping cough outbreak in humans. Together, these results show that hindcasting can estimate the time since infection for individuals and provide accurate estimates of epidemic trends, and can be used to distinguish whether an outbreak is increasing or past its peak. We conclude that if temporal characteristics of diagnostics are known, it is possible to recover epidemic trends of both human and animal pathogens from cross-sectional data collected at a single point in time

Activated Leukocyte Cell Adhesion Molecule Expression and Shedding in Thyroid Tumors

Activated leukocyte cell adhesion molecule (ALCAM, CD166) is expressed in various tissues, cancers, and cancer-initiating cells. Alterations in expression of ALCAM have been reported in several human tumors, and cell adhesion functions have been proposed to explain its association with cancer. Here we documented high levels of ALCAM expression in human thyroid tumors and cell lines. Through proteomic characterization of ALCAM expression in the human papillary thyroid carcinoma cell line TPC-1, we identified the presence of a full-length membrane-associated isoform in cell lysate and of soluble ALCAM isoforms in conditioned medium. This finding is consistent with proteolytically shed ALCAM ectodomains. Nonspecific agents, such as phorbol myristate acetate (PMA) or ionomycin, provoked increased ectodomain shedding. Epidermal growth factor receptor stimulation also enhanced ALCAM secretion through an ADAM17/TACE-dependent pathway. ADAM17/TACE was expressed in the TPC-1 cell line, and ADAM17/TACE silencing by specific small interfering RNAs reduced ALCAM shedding. In addition, the CGS27023A inhibitor of ADAM17/TACE function reduced ALCAM release in a dose-dependent manner and inhibited cell migration in a wound-healing assay. We also provide evidence for the existence of novel O-glycosylated forms and of a novel 60-kDa soluble form of ALCAM, which is particularly abundant following cell stimulation by PMA. ALCAM expression in papillary and medullary thyroid cancer specimens and in the surrounding non-tumoral component was studied by western blot and immunohistochemistry, with results demonstrating that tumor cells overexpress ALCAM. These findings strongly suggest the possibility that ALCAM may have an important role in thyroid tumor biology

Simultaneous detection of lung fusions using a multiplex RT-PCR next generation sequencing-based approach:A multi-institutional research study

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