Capture-recapture methodology, originally developed for estimating demographic parameters of animal populations, has been applied to human populations. This tutorial reviews various closed capture-recapture models which are applicable to ascertainment data for estimating the size of a target population based on several incomplete lists of individuals. Most epidemiological approaches merging different lists and eliminating duplicate cases are likely to be biased downwards. That is, the final merged list misses those who are in the population but were not ascertained in any of the lists. If there are no matching errors, then the duplicate information collected from a capture-recapture experiment can be used to estimate the number of missed under proper assumptions. Three approaches and their associated estimation procedures are introduced: ecological models; log-linear models, and the sample coverage approach. Each approach has its unique way of incorporating two types of source dependencies: local (list) dependence and dependence due to heterogeneity. An interactive program, CARE (for capture-recapture) developed by the authors is demonstrated using four real data sets. One set of data deals with infection by the acute hepatitis A virus in an outbreak in Taiwan; the other three sets are ascertainment data on diabetes, spina bifida and infants' congenital anomaly discussed in the literature. These data sets provide examples to show the usefulness of the capture-recapture method in correcting for under-ascertainment. The limitations of the methodology and some cautionary remarks are also discussed.

Studies of the pathogenesis of dengue hemorrhagic fever (DHF), a potentially life-threatening disease, have revealed the importance of initial high levels of virus replication. However, the possible involvement of virus during the transition from fever to defervescence, a critical stage in determining the severity of disease, has not been appreciated. Using quantitative reverse transcription-polymerase chain reaction, we examined the levels of plasma dengue viral load during both fever and defervescence periods in patients from a DEN-3 outbreak in southern Taiwan in 1998. Higher levels of plasma dengue viral RNA were found in DHF patients than in DF patients. During defervescence, while the level of plasma dengue viral RNA was undetectable in most DF patients, it remains high in all DHF patients. Using a modified immunoprecipitation assay, we demonstrated for the first time that the plasma dengue viruses persisting during defervescence were in the immune complexes for most DHF patients. These findings suggest that continued active viral replication or delay in the clearance of viremia contributes to the pathogenesis of DHF. Moreover, high levels of plasma dengue viral RNA during defervescence may serve as a disease marker for DHF.

BackgroundDespite dengue dynamics being driven by complex interactions between human hosts, mosquito vectors and viruses that are influenced by climate factors, an operational model that will enable health authorities to anticipate the outbreak risk in a dengue non-endemic area has not been developed. The objectives of this study were to evaluate the temporal relationship between meteorological variables, entomological surveillance indices and confirmed dengue cases; and to establish the threshold for entomological surveillance indices including three mosquito larval indices [Breteau (BI), Container (CI) and House indices (HI)] and one adult index (AI) as an early warning tool for dengue epidemic.Methodology/Principal FindingsEpidemiological, entomological and meteorological data were analyzed from 2005 to 2012 in Kaohsiung City, Taiwan. The successive waves of dengue outbreaks with different magnitudes were recorded in Kaohsiung City, and involved a dominant serotype during each epidemic. The annual indigenous dengue cases usually started from May to June and reached a peak in October to November. Vector data from 2005–2012 showed that the peak of the adult mosquito population was followed by a peak in the corresponding dengue activity with a lag period of 1–2 months. Therefore, we focused the analysis on the data from May to December and the high risk district, where the inspection of the immature and mature mosquitoes was carried out on a weekly basis and about 97.9% dengue cases occurred. The two-stage model was utilized here to estimate the risk and time-lag effect of annual dengue outbreaks in Taiwan. First, Poisson regression was used to select the optimal subset of variables and time-lags for predicting the number of dengue cases, and the final results of the multivariate analysis were selected based on the smallest AIC value. Next, each vector index models with selected variables were subjected to multiple logistic regression models to examine the accuracy of predicting the occurrence of dengue cases. The results suggested that Model-AI, BI, CI and HI predicted the occurrence of dengue cases with 83.8, 87.8, 88.3 and 88.4% accuracy, respectively. The predicting threshold based on individual Model-AI, BI, CI and HI was 0.97, 1.16, 1.79 and 0.997, respectively.Conclusion/SignificanceThere was little evidence of quantifiable association among vector indices, meteorological factors and dengue transmission that could reliably be used for outbreak prediction. Our study here provided the proof-of-concept of how to search for the optimal model and determine the threshold for dengue epidemics. Since those factors used for prediction varied, depending on the ecology and herd immunity level under different geological areas, different thresholds may be developed for different countries using a similar structure of the two-stage model.

The introduction and the widespread use of the varicella vaccine in Taiwan has led to a 75-80% decrease in the incidence of varicella in children. However the vaccine's long-term impact on the incidence of herpes zoster (HZ) has attracted attention. By controlling gender, underlying diseases, and age effects, a Poisson regression was applied on the 2000-2008 chart records of 240 000 randomly selected residents who enrolled in the Universal National Health Insurance. The results show that, as the vaccine coverage in children increases, the incidence of varicella decreases. However, the incidence of HZ increased even before the implementation of the free varicella vaccination programme in 2004, particularly in females. The increase in the incidence of HZ cannot be entirely and directly attributed to the widespread vaccination of children. Continuous monitoring is needed to understand the secular trends in HZ before and after varicella vaccination in Taiwan and in other countries.

Noroviruses (NoVs) and sapoviruses (SaVs) of the family Caliciviridae are emerging enteric pathogens in humans and animals. Recent detection of genogroup II norovirus (GII NoV) RNA from swine raises public health concerns about zoonotic transmission of porcine NoVs to humans. However, few papers reported genotype distributions and epidemiological features in swine farms and their genetic relationship to human strains, which was the objective of our study. This study investigated the epidemiological features and genotypes of caliciviruses in swine farms using 533 pig faecal samples from six farms in central and southern Taiwan, tested for viral RNA using RT-PCR targeting the conserved polymerase gene. NoVs and SaVs were detected with a positive rate of 7.1% and 0.6%, respectively. To confirm the positive rate of NoVs, 255 pig faecal samples from two farms in central Taiwan were tested with primer pairs targeting the partial capsid gene of GII, and 32.3% of the positive rate was found. Furthermore, the results from the capsid region suggested a higher positive rate of 41.7% in winter than 26.4% in summer with statistical significance (P < 0.05). Sequence analysis showed 29 strains belonging to GII.4 (human) and nine strains belonging to GII.11 (swine) identified based on the partial polymerase gene. Additional genotypes clustered with GII.2 (human) and GII.18 (swine) were also characterized based on the partial capsid gene. SaVs detected in porcine faecal samples belonged to genogroup III (GIII), which clustered with the PEC-Cowden strain. Our study demonstrated the presence of multiple genotypes of both human and porcine NoVs infecting swine of various ages asymptomatically. Although the zoonotic potential of detected human NoVs in swine was not conclusive owing to the lack of local human faecal samples, our study revealed the importance of monitoring emerging strains in swine to mitigate the potential impact of recombinant NoVs infecting the human population.