Forty Years of Dengue Surveillance at a Tertiary Pediatric Hospital in Bangkok, Thailand, 1973-2012.

Long-term observational studies can provide valuable insights into overall dengue epidemiology. Here, we present analysis of dengue cases at a pediatric hospital in Bangkok, Thailand, during a 40-year period from 1973 to 2012. Data were analyzed from 25,715 hospitalized patients with laboratory-confirmed dengue virus (DENV) infection. Several long-term trends in dengue disease were identified including an increase in mean age of hospitalized cases from an average of 7-8 years, an increase after 1990 in the proportion of post-primary cases for DENV-1 and DENV-3, and a decrease in the proportion of dengue hemorrhagic fever and dengue shock syndrome cases in primary and post-primary cases over time. Exploratory mechanistic analysis of these observed trends considered changes in diagnostic methods, demography, force of infection, and Japanese encephalitis vaccination as possible explanations. Thailand is an important setting for studying DENV transmission as it has a "mature" dengue epidemiology with a strong surveillance system in place since the early 1970s. We characterized changes in dengue epidemiology over four decades, and possible impact of demographic and other changes in the human population. These results may inform other countries where similar changes in transmission and population demographics may now or may soon be occurring.

The impact of the demographic transition on dengue in Thailand: insights from a statistical analysis and mathematical modeling.

BACKGROUND: An increase in the average age of dengue hemorrhagic fever (DHF) cases has been reported in Thailand. The cause of this increase is not known. Possible explanations include a reduction in transmission due to declining mosquito populations, declining contact between human and mosquito, and changes in reporting. We propose that a demographic shift toward lower birth and death rates has reduced dengue transmission and lengthened the interval between large epidemics. METHODS AND FINDINGS: Using data from each of the 72 provinces of Thailand, we looked for associations between force of infection (a measure of hazard, defined as the rate per capita at which susceptible individuals become infected) and demographic and climactic variables. We estimated the force of infection from the age distribution of cases from 1985 to 2005. We find that the force of infection has declined by 2% each year since a peak in the late 1970s and early 1980s. Contrary to recent findings suggesting that the incidence of DHF has increased in Thailand, we find a small but statistically significant decline in DHF incidence since 1985 in a majority of provinces. The strongest predictor of the change in force of infection and the mean force of infection is the median age of the population. Using mathematical simulations of dengue transmission we show that a reduced birth rate and a shift in the population's age structure can explain the shift in the age distribution of cases, reduction of the force of infection, and increase in the periodicity of multiannual oscillations of DHF incidence in the absence of other changes. CONCLUSIONS: Lower birth and death rates decrease the flow of susceptible individuals into the population and increase the longevity of immune individuals. The increase in the proportion of the population that is immune increases the likelihood that an infectious mosquito will feed on an immune individual, reducing the force of infection. Though the force of infection has decreased by half, we find that the critical vaccination fraction has not changed significantly, declining from an average of 85% to 80%. Clinical guidelines should consider the impact of continued increases in the age of dengue cases in Thailand. Countries in the region lagging behind Thailand in the demographic transition may experience the same increase as their population ages. The impact of demographic changes on the force of infection has been hypothesized for other diseases, but, to our knowledge, this is the first observation of this phenomenon. Please see later in the article for the Editors' Summary.

Variation in season of birth in singleton and multiple births concordant for autism spectrum disorders.

Patterns of seasonal variation in births in some neuropsychiatric conditions have been found in previous research; however, no study to date has examined these disorders for seasonal variation in singletons and multiple births separately. This study aimed to determine whether the birth date distribution for individuals with autism spectrum disorders (ASD), including singletons and multiple births, differed from the general population. Two ASD case groups were studied: 907 singletons and 161 multiple births concordant for ASD. Two control groups were obtained from registered births of singletons and multiples. Results of the non-parametric time-series analyses, where day of birth was used, suggested there were three peaks in ASD singletons and ASD concordant multiple births. Roughly, the peaks were in April, June and October for singletons and about 2-4 weeks earlier in multiples. Results from multivariable Poisson regression, where month of birth was used, indicated that ASD concordant multiple births in males tended to be higher than expected in March, May and September (with borderline statistical significance), but were 87% less in December (P < 0.05), as compared with January. Overall, the patterns of relative risk estimates from Poisson regression are similar to findings from the non-parametric time-series approach, but are not exactly congruent. It is important to note that indications of seasonality may be sensitive to the selection of time cut-points and therefore an arbitrary binning of time can either mask existing trends or falsely indicate the presence of a trend. The presence of seasonal trends in ASD singletons and concordant multiple births suggests a role for non-heritable factors operating during the pre- or perinatal period, even among cases with a genetic susceptibility.