Household and community transmission of the Asian influenza A (H2N2) and influenza B viruses in 1957 and 1961.

This study analyzed the distribution of the number of cases in households of various sizes, reconsidering previous survey data from the Asian influenza A (H2N2) pandemic in 1957 and the influenza B epidemic in 1961. The final size distributions for the number of household cases were extracted from four different data sources (n = 547, 671, 92 and 263 households), and a probability model was applied to estimate the community probability of infection (CPI) and household secondary attack rate (SAR). For the 1957 Asian influenza pandemic, the CPI and household SAR were estimated to be 0.42 [95% confidence intervals (CI): 0.37, 0.47] and 7.06% (95% CI: 4.73, 9.44), respectively, using data from Tokyo. The figures for the same pandemic using data from Osaka were 0.21 (95% CI: 0.19, 0.22) and 9.07% (95% CI: 6.73, 11.53), respectively. Similarly, the CPI and household SAR for two different datasets of influenza B epidemics in Osaka in 1961 were estimated as 0.37 (95% CI: 0.30, 0.44) and 18.41% (95% CI: 11.37, 25.95) and 0.20 (95% CI: 0.13, 0.28) and 10.51% (95% CI: 8.01, 13.15), respectively. Community transmission was more frequent than household transmission, both for the Asian influenza pandemic and the influenza B epidemic, implying that community-based countermeasures (eg, area quarantine and social distancing) may play key roles in influenza interventions.

Analysis of a previous smallpox vaccination study: estimation of the time period required to acquire vaccine-induced immunity as assessed by revaccination.

The time interval required to develop immunity after vaccination, in the event of a bioterrorist attack using variola virus, is yet to be clarified. In this article, a historical vaccination study conducted in Japan in 1929 was re-examined. Forty-four previously vaccinated and 44 unvaccinated children were involved. After successful first round primary (or re-) vaccination, all children underwent revaccination at variable intervals. Absence of a major reaction (vaccine 'take') after revaccination was taken as a sign of immunity conferred by first round primary (or re-) vaccination. Univariate analysis was employed to examine the relationship between vaccine 'take' and the exposure variables. Maximum likelihood estimates of the time period required to develop immunity were obtained using a simple logit model. The interval between vaccinations was significantly associated with vaccine 'take' in both the previously unvaccinated (p < 0.01) and vaccinated (p < 0.01) groups, and the median interval required for immunity after vaccination was estimated to be 6.4 [95% Confidence Interval (CI): 5.8, 7.1] and 4.3 days (95 % CI: 4.1, 4.7), respectively. Obtained estimates were consistent with previous observations, and the logistic fits reasonably explained the discrepancy among previous suggestions. The findings suggest that it is necessary to vaccinate exposed susceptible individuals within 3 days after exposure to ensure disease protection, and within at least 5 days (for those previously unvaccinated) to provide a certain level of protection; the probability shows a dramatic decline hereafter.

Health inequalities in Thailand: geographic distribution of medical supplies in the provinces.

The purpose of this study was to analyze the regional characteristics and geographic distribution of the medical staffs (physicians and nurses) and the patient beds in relation to the population and average death rates in each of the provinces in Thailand, by using the Lorenz curve and Gini coefficients. Those data were obtained from surveys conducted by the Ministry of Public Health and the Office of the National Education Commission. It was demonstrated that there are certain clear uneven distributions in medical personnel, especially physicians (Gini index = 0.433), by province. For physicians, nurses, and patient beds, approximately 39.6%, 25.8% and 20.6% are concentrated in the Bangkok Metropolis. Specific ideas to solve those problems are discussed in order to overcome this health care crisis by the year 2025.

Predicting the future trend of drug-resistant tuberculosis in Thailand: assessing the impact of control strategies.

The purposes of this study are to predict the future trend of drug-sensitive and resistant tuberculosis (TB) in Thailand, and to assess the impact of different control strategies on the generation of drug resistant TB, through the use of mathematical analysis. We assume that the present status of TB and the emergence of drug-resistant TB in Thailand are the consequence of past epidemics. Control strategies in the model are defined by specifying the value of the effective treatment rate (baseline value = 0.74) and the relative treatment efficacy (baseline value = 0.84). It is predicted that the total number of new TB cases would continue to decrease at the current level of intervention. Although a dramatic decline in the incidence rate of drug-sensitive cases is expected, drug-resistant cases are predicted to increase gradually, so that more than half of the TB strains would not be drug-sensitive after 2020. The prediction is not greatly altered by improving the interventions. They could, however, delay the emergence of drug-resistant strains for a few years. Our study demonstrates it would be impossible to avoid the continued emergence of drug-resistant TB in the future. It is pointed out that there are urgent needs to ensure adequate supervision and monitoring, to insure treatment of 100% of the targeted population with Directly Observed Therapy.